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Solid Phase Oligonucleotide Synthesis Is Not Obsolete - It Is Ascending

Fri, 17 Apr 2026 05:03:05 GMT

Why phosphoramidite‑based, flow‑enabled solid‑phase synthesis remains the manufacturing backbone of therapeutic oligonucleotides

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Abstract:

The last five years have produced meaningful progress in enzymatic oligonucleotide synthesis, liquid‑phase strategies, stereocontrolled phosphorus chemistry, and process intensification. At the same time, regulators have sharpened expectations around impurity characterization, batch definition, and integrated control strategies for synthetic oligonucleotides. The net result is not platform replacement, but convergence. Solid-phase phosphoramidite synthesis (SPOS) is being modernized, especially through flow-enabled execution, while emerging approaches occupy complementary niches.

This paper shows, from a chemistry and CMC perspective, that SPOS remains the only platform that simultaneously delivers chemical generality, mechanistically understood impurity formation, orthogonal analytical tractability, and regulatory-mature lifecycle continuity for therapeutic oligonucleotides. The newest literature and regulatory commentary reinforce a future where the manufacturing ‘reference chemistry’ persists, while execution evolves [13, 11, 10].

1. What “Standard” Means in Regulated Oligonucleotide Manufacturing

In regulated pharmaceutical manufacturing, “standard” does not mean “best for every use case.” It means a platform is:

Inspectable
Comparable across lifecycle changes
Chemically general across therapeutically relevant modifications
Analytically resolvable with established orthogonal methods and impurity taxonomies [10, 18, 4].

Regulatory discussions in the last few years increasingly emphasize integrated control strategies, impurity assessment, and clear batch definition for synthetic oligonucleotides—topics that fit directly with SPOS unit operations and decades of process understanding [10, 18, 11].

2. Therapeutic Oligonucleotides Are Chemical Objects, Not Just Sequences

Therapeutic oligonucleotides derive key clinical properties from chemical architecture (sugar/backbone modifications, end‑caps, conjugations, and stereochemical distributions, rather than sequence alone [4, 3]. This favors platforms that can reliably incorporate a wide range of modifications under controlled conditions, which remains a defining strength of phosphoramidite SPOS [13, 11].

Figure 1. Relative chemical generality of oligonucleotide synthesis platforms.

3. Impurity Science: Predictability is an Advantage

SPOS impurity mechanisms include:

Deletions (n–1, n–2)
Depurination-linked cleavage pathways
Capping-associated base modifications
Oxidation and sulfurization variants

These are chemically interpretable and analytically addressable within established control strategies [10, 18].

Regulatory discussions reinforce that the industry is judged not by the absence of impurities, but by the ability to detect, control, trend, and justify them [18, 10]. Emerging enzymatic workflows can reduce solvent burden and avoid certain SPOS‑specific side reactions, but they introduce their own platform‑specific impurity sets and risk classes, remain early in their regulatory learning curve [14, 17, 12].

4. Flow Chemistry: The Modern Form of Solid‑Phase Synthesis

Most criticism of SPOS has historically targeted batch execution, not phosphoramidite chemistry itself. Modern process intensification—especially flow‑through solid‑phase architectures—improves mass transfer and residence‑time control, reduces exposure to aggressive reagents, and increases uniformity and reproducibility [5, 6]. The result is reduced solvent intensity and improved execution while preserving the same core reaction network and comparability logic [13, 11].

Figure 2. Representative PMI ranges by platform (illustrative ranges; actual PMI is process‑ and scale‑dependent).

5. Regulatory Maturity Follows Lifecycle Continuity, Not Novelty

Regulators favor platforms that produce consistent quality attributes across time and change, especially where impurity profiles are well understood and analytical methods are mature. Industry regulatory analyses and regulator communications emphasize integrated control strategies, clear batch definition (including pooling/splitting considerations), and robust impurity characterization [10, 18].

Figure 3. Conceptual regulatory / quality‑system maturity by platform (qualitative lifecycle framing; not an approval count).

6. Recent Advances (2020–2025): Evolution, Not Replacement

Between 2020 and 2025, oligonucleotide manufacturing advanced significantly due to:

Sustainability pressures
Expanding therapeutic complexity
The need for scalable production

Key developments include:

Flow-enabled solid-phase phosphoramidite synthesis reducing solvent use and improving mass transfer while preserving established reaction chemistry and impurity profiles [11, 13].
Advances in phosphorus chemistry and stereocontrol, expanding the range of accessible therapeutic structures [13, 15]
Progress in enzymatic oligonucleotide synthesis under aqueous conditions, including controlled incorporation and template-independent approaches [17, 14, 12]

Despite this progress, enzymatic approaches remain constrained in chemical generality and regulatory precedent. Regulatory analyses during this period continue to emphasize impurity predictability, integrated control strategies, and lifecycle comparability—areas where SPOS remains structurally advantaged [10, 18].

Collectively, the recent literature supports a model of platform evolution rather than platform replacement [13, 11].

7. Timeline of Advances (2020-2025)

Figure 4. Timeline of key advances in oligonucleotide manufacturing (2020–2025), with icons denoting dominant technology focus per year.

8. Where Enzymatic and Hybrid Approaches Fit

Without Displacing SPOS

Recent enzymatic publications demonstrate credible progress toward controlled, template‑independent synthesis, including RNA proof‑of‑concept under aqueous conditions and reversible termination frameworks [17, 14]. At the same time, attempts to extend enzymatic synthesis into heavily modified XNA/LNA regimes highlight substrate‑tolerance and deprotection challenges—reinforcing that chemical generality remains a key limitation for enzymatic platforms in therapeutic contexts [12]. The resulting landscape is layered: SPOS (increasingly flow‑enabled) as the primary GMP backbone for chemically complex therapeutics; enzymatic synthesis for long/repetitive sequences and rapid prototyping; and hybrid strategies applied where they reduce risk rather than introduce it [13, 10].

Conclusion

The last five years have not made SPOS obsolete. They showed that SPOS can absorb innovation without losing regulatory or analytical continuity. Flow execution and greener process engineering modernize SPOS while preserving the chemistry and impurity logic regulators already understand [11, 10]. Enzymatic synthesis is accelerating—while its leading papers candidly show both momentum and remaining constraints for modified therapeutics [17, 12, 14]. The end state is convergence: SPOS remains the reference chemistry, modernized through process engineering and complemented by enzymatic and hybrid approaches where they add value without disrupting CMC [13, 10].

References

Beaucage, S. L.; Caruthers, M. H. Deoxynucleoside phosphoramidites—A new class of key intermediates for deoxypolynucleotide synthesis. Tetrahedron Letters 1981, 22(20), 1859–1862.
Caruthers, M. H. Gene synthesis machines: DNA chemistry and its uses. Science 1985, 230(4723), 281–285.
Crooke, S. T. Molecular mechanisms of antisense oligonucleotides. Nucleic Acid Therapeutics 2017, 27(2), 70–77.
Khvorova, A.; Watts, J. K. The chemical evolution of oligonucleotide therapies of clinical utility. Nature Biotechnology 2017, 35, 238–248.
Wiles, C.; Watts, P. Continuous flow reactors: a perspective. Green Chemistry 2012, 14, 38–54.
Jensen, K. F. Flow chemistry—Microreaction technology comes of age. AIChE Journal 2017, 63(3), 858–869.
Palluk, S.; Arlow, D. H.; de Rond, T.; et al. De novo DNA synthesis using polymerase–nucleotide conjugates. Nature Biotechnology 2018, 36, 645–650.
Lee, H. H.; Kalhor, R.; Goela, N.; et al. Terminator‑free template‑independent enzymatic DNA synthesis for digital information storage. Nature Communications 2019, 10, 2383.
Roberts, T. C.; Langer, R.; Wood, M. J. A. Advances in oligonucleotide drug delivery. Nature Reviews Drug Discovery 2020, 19, 673–694.
Wetter, C.; Chorley, C.; Curtis, C.; et al. Solution oligonucleotide APIs: regulatory considerations. Therapeutic Innovation & Regulatory Science 2022, 56, 386–393.
Ferrazzano, L.; Corbisiero, D.; Tolomelli, A.; Cabri, W. From green innovations in oligopeptide to oligonucleotide sustainable synthesis: differences and synergies in TIDES chemistry. Green Chemistry 2023, 25, 1217–1236.
Sabate, N.; Katkevica, D.; Pajuste, K.; et al. Towards the controlled enzymatic synthesis of LNA‑containing oligonucleotides. Frontiers in Chemistry 2023, 11, 1161462.
Obexer, R.; Nassir, M.; Moody, E. R.; Baran, P. S.; Lovelock, S. L. Modern approaches to therapeutic oligonucleotide manufacturing. Science 2024, 384, eadl4015.
Pichon, M.; Hollenstein, M. Controlled enzymatic synthesis of oligonucleotides. Communications Chemistry 2024, 7, 138.
Mohammed, A. A.; AlShaer, D.; Al Musaimi, O. Oligonucleotides: evolution and innovation. Medicinal Chemistry Research 2024, 33, 2204–2220.
Thürmer, R. EU regulators’ experience with synthetic oligonucleotides and mRNA technology. European Medicines Agency scientific conference presentation, 2023.
Wiegand, D. J.; Rittichier, J.; Meyer, E.; et al. Template‑independent enzymatic synthesis of RNA oligonucleotides. Nature Biotechnology 2025, 43, 762–772.
Zhang, D. (FDA CDER). Oligonucleotides: current thinking and analytical challenges identified in nusinersen PSG development (presentation), 2022.
Al Musaimi, O.; AlShaer, D.; de la Torre, B. G.; Albericio, F. 2024 FDA TIDES (peptides and oligonucleotides) harvest. Pharmaceuticals 2025, 18(3), 291.

A CMC Philosophy for Scientists Who Think Beyond the Bench

If you’re responsible for impurity control, comparability, and lifecycle robustness—not just synthesis speed—this document is for you.

Download a clear, technical articulation of why solid‑phase synthesis continues to anchor therapeutic oligonucleotide manufacturing , and how modern flow implementations change the execution without changing the chemistry.

AI in Biotech: Hype vs Reality

Mon, 09 Mar 2026 15:30:48 GMT

AI in Biotech

Balancing Hype with Reality – An Experienced Perspective

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Read Time: 20 Min

Word Count: 3200

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Executive Summary:

Artificial intelligence (AI) has been heralded as a game-changer in biotechnology – promising faster drug discovery, personalized genomics, smarter diagnostics, and fully automated “self-driving” laboratories. Indeed, early successes like DeepMind’s AlphaFold (which solved the 50-year protein-folding problem) and AI-designed molecules entering clinical trials have fueled high expectations. But many of these promises have been overstated . Real-world results show that while AI is a powerful tool, it has not yet delivered a wholesale revolution in biotech R&D:

Drug Discovery: AI was expected to cut drug development from a decade to mere months. It has accelerated some steps (e.g. virtual screening), but no new drug developed entirely by AI has reached the market to date, and overall R&D timelines remain long [1] [2].
Genomics & Precision Medicine: AI can sift genomic data for patterns, but translating these insights into therapies has been slower than hoped . Successes in identifying gene targets haven’t yet yielded a burst of new cures.
Diagnostics: AI algorithms match or beat doctors at narrow tasks like reading X-rays or pathology slides, and a few have regulatory approval, but they function best as physician assistants, not replacements [3]. Complex medical decision-making still requires human insight.
Lab Automation: Highly automated “lights-out” labs exist, but widespread adoption is limited . As recently as 2020, nearly 90% of life science experimental protocols still involved manual steps [4]. Most research labs are far from fully autonomous.

Why the Gap?

Why the Gap? Early adopters discovered that biological complexity, data quality issues, and integration challenges have constrained AI’s impact. For example, IBM’s Watson Health initiative famously aimed to revolutionize cancer care with AI, but its partnership with MD Anderson was canceled in 2016 after $62 million spent without delivering a usable product [5]. The project revealed that AI struggled with messy, real-world clinical data and the nuance of medical reasoning. Similarly, many AI-driven drug discovery startups found that promising computer-designed molecules still failed in clinical trials – not because the algorithms were broken, but because the underlying data and biological knowledge were insufficient to capture the true complexity of human disease. In short, the first wave of AI in biotech often overpromised results by overlooking essential scientific realities .

kbDNA’s Perspective – Pragmatic Innovation: As an experienced innovator in life sciences, kbDNA has approached AI differently from the start. We believe that AI’s potential is real – but to avoid hype, it must be grounded in domain expertise and robust data. Our strategy hinges on three principles:

Data First: We have built proprietary backend databases through extensive manual data mining and custom automation. This curated data foundation (covering genomics, experimental results, protocols, etc.) helps ensure any AI models we use are learning from high-quality, relevant information . By assembling clean, context-rich datasets, we give AI a fighting chance to succeed where others failed. Our data platforms also serve as a benchmark: we can quickly validate or disprove AI-generated predictions by checking them against real-world results in our database. This safeguards against the classic “garbage in, garbage out” problem in AI.
Domain Expertise & Human-AI Collaboration: At kbDNA, we treat AI as an augmentation tool for our scientists, not a replacement. Our team of biologists, chemists, and data scientists work together so that machine learning models are developed and interpreted with deep scientific context. For example, if an AI suggests a potential drug candidate, our experts evaluate its practical feasibility (Can it be synthesized? Is it likely safe? Does it align with known biology?). This hybrid approach identifies false positives early and guides the AI towards more meaningful predictions. We’ve found that human intuition and experience are indispensable for steering AI – much like a skilled pilot flying with a high-tech autopilot. This collaboration improves the outcomes and also builds trust in AI across our R&D teams.
Rapid Iteration & Validation: We use automation not to create a “closed-loop” robot lab, but to expedite high-quality experimentation in support of AI. Our custom automated workflows – from sample prep to data capture – allow us to test AI-generated hypotheses quickly in the lab and feed results back into our databases. This “lab-in-the-loop” cycle means our AI models are constantly being recalibrated by up-to-date experimental evidence. It also means we can fail fast and learn, preventing weeks of wasted effort. Integrating AI with real-world lab feedback is crucial to convert in silico predictions into true scientific progress.

AI Promises vs. Reality in Biotech

AI Promises vs. Reality in Biotech : The table below summarizes several high-profile promises of AI in biotechnology and what has been achieved so far:

As the table indicates, the reality often lags behind the marketing. This doesn’t mean AI isn’t making a difference – rather, its contributions are more incremental and focused than the sweeping claims often suggested. For instance, several major pharma companies report that AI and machine learning are now routinely used to prioritize drug targets and analyze images or genomic data, resulting in measurable efficiency gains in those specific steps. But the overall process of bringing a new therapy to market still requires extensive laboratory work, clinical development, and regulatory approval, just as it always has.

The same pattern applies in other domains. Genomic analytics have been supercharged by AI algorithms that can scan millions of data points to find disease-related genes or predict protein structures (the success of AlphaFold being a prime example of AI’s value to basic science). Yet, identifying a genetic target or protein shape is usually the first step of many; drug discovery and clinical validation remain gating factors. Diagnostics AI has shined in analyzing images and lab tests faster or more consistently than some humans, but integrating those results into patient care calls for physician oversight. And in laboratory operations, automation driven by AI is helping with tasks like high-throughput screening and quality control, but labs must still be tailored and supervised by skilled researchers.

Why the Overpromise? Biotech and pharma are high-stakes fields where enthusiasm runs strong. It’s easy to see why AI has been viewed as a silver bullet: laboratories and R&D teams are overwhelmed with data, costs are skyrocketing, and breakthroughs are hard to find. Amid these pressures, the idea of super-intelligent algorithms unlocking miraculous insights was incredibly attractive – to scientists hoping to accelerate discovery, to executives seeking R&D efficiency, and to investors looking for the next big thing. In the mid-2010s, press releases and conferences often featured bold predictions : AI would “revolutionize” drug pipelines, decode every genome’s secrets, and replace many routine lab tasks. Some startups and large tech firms did little to temper these expectations, occasionally prioritizing marketing over practical results in the rush to claim “firsts” in AI-driven cures.

However, the biology “learning curve” for AI turned out steeper than anticipated . Key challenges include:

Data Quality & Relevance: Biomedical data can be noisy, incomplete, and siloed. Early AI efforts often used whatever data was available (public databases, literature) which weren’t always representative of real-world conditions. As a result, algorithms made confident predictions that didn’t hold up experimentally. It became apparent that curating high-quality, context-specific data is a non-negotiable prerequisite for successful AI in biotech.
Complexity of Biology: Diseases and biological systems involve layers of regulation and variability that single datasets or models can’t capture. For example, a machine learning model might flag a gene as a drug target based on statistical correlation, but it takes seasoned biologists to determine if modulating that gene will actually impact a disease without unacceptable side effects. Many AI models excelled in narrow tasks or with simulated data, but stumbled when faced with the full complexity of living systems and patients.
Integration into Workflows: It’s not enough for an AI to make a prediction – that prediction must fit into existing R&D processes. One reason lab automation and AI tools haven’t spread faster is that labs are bespoke environments. Integrating new AI systems with legacy instruments, IT systems, and team workflows is hard. Early adopters underestimated the practical effort needed to retrain scientists, retool infrastructure, and ensure regulatory compliance for AI systems. The promise of autonomous labs crashed into the reality of operational and cultural inertia.
Validation Requirements: In life sciences, experimental validation is the gold standard . No matter how “intelligent” an algorithm seems, its outputs must be verified in wet-lab experiments or clinical trials. This takes time and resources. Some AI predictions have proven valuable, while others added little, meaning R&D organizations have had to sift true signals from false leads. Only rigorous validation separates useful AI-driven discoveries from hype, and that vetting process slows down the pace of AI-driven change (appropriately so, given the human stakes).

kbDNA’s Approach – Building a Foundation for Productive AI

kbDNA’s Approach – Building a Foundation for Productive AI: The experiences above resonate strongly with our team at kbDNA. From the outset, we have championed a “data and domain first, AI second” philosophy :

We invested in building comprehensive knowledge bases. Through painstaking manual data mining of literature and public databases – and by capturing our own experimental data via custom automation pipelines – we assembled high-quality datasets tailored to our R&D focus areas. These proprietary databases of genetic sequences, biomarkers, experimental results, and protocols give us an edge: when we deploy AI models, we can train and test them on reliable, context-rich data that we understand deeply. This minimizes the risk of spurious correlations and maximizes the chance of uncovering real biological insights. It also allows us to measure AI performance against an internal “source of truth.” In one case, our curated gene-editing dataset helped reveal that a predictive model was over-fitting; we retrained it with our data and significantly improved its accuracy.
We maintain a strong human scientific oversight over AI projects. Every AI-derived result at kbDNA goes through review by experts in the relevant discipline. This combination of AI with human expertise is powerful: the AI can surface patterns or options humans might miss, while our scientists filter and refine those suggestions. For example, if our machine learning system flags 50 possible drug candidates, our chemists and biologists narrow them to the most promising 5 based on known medicinal chemistry principles and biological plausibility. This saves time and resources by focusing experimental validation on the best options . Far from replacing scientists, AI in our organization acts as a force-multiplier for their experience and intuition.
We iterate and integrate into workflows carefully. Successful innovation in biotech often comes from incremental improvements and integration, not sudden disruption. We introduce AI-driven tools in a way that complements existing processes. A case in point: our automation team developed a robotic screening system that works in tandem with our AI models. The AI picks top candidates, the robotic system tests them in our assays, and the data feeds back to refine the model. By closing this loop, we ensure our AI remains calibrated to real results. This reduces hype because every AI prediction is followed by verification. It also makes our scientists more comfortable and fluent with AI tools, as they see direct, empirical evidence of how the models perform.

The Path Ahead – Realizing AI’s Potential, Responsibly

The Path Ahead – Realizing AI’s Potential, Responsibly: The initial over-hyping of AI in biotech is giving way to a more balanced understanding. Industry-wide, there’s a shift from grandiose claims to pragmatic deployment . Notably, more than three-quarters of life science R&D leaders in a 2025 survey said they plan to use AI in some form by 2027, but the focus now is on specific, high-impact use cases rather than broad disruption [7]. We at kbDNA are enthusiastic about what AI can do – when used correctly:

Accelerate Research: AI can dramatically speed up data analysis and hypothesis generation. We’ve seen it in our own work, where tasks like genome analysis or high-throughput screening design that used to take weeks can now be done in days. This means scientists have more time to design experiments and interpret results, rather than crunching data.
Optimize Decision-Making: In drug development, AI algorithms can evaluate vast chemical libraries or patient data to pinpoint leads and patterns that warrant pursuit. This can trim the “front end” of R&D projects – focusing efforts on more promising paths. For instance, AI helps triage hundreds of drug-like molecules to find a few with the ideal properties, which our chemists then refine further. This guided approach increases the odds of success down the line.
Personalized Insights: With the right data, AI can identify subtle signals in genomic or clinical data that humans might overlook. These insights can guide more personalized medicine – for example, finding a biomarker that predicts which patients will respond to a new therapy. In one project, our machine learning analysis of past experiments revealed a patient subgroup that responded differently to a certain treatment, leading us to design a follow-up study for that specific genetic profile.
Enhanced Automation & Efficiency: Rather than fully autonomous labs, the real win of AI in automation today is improving reliability and throughput. AI can monitor instrument data in real time to flag anomalies (preventing wasted experiments) and optimize scheduling (so equipment downtime is minimized). This results in more robust, efficient operations – a significant benefit for any research organization..

An Optimistic, Grounded Outlook

An Optimistic, Grounded Outlook: We firmly believe that AI will ultimately help unlock groundbreaking biotech innovations. The key is pairing AI with sound science . As we have learned, success comes from respecting the complexity of biology and the value of expert knowledge:

Data and Infrastructure: Organizations should invest in data management, integration, and quality control. High-quality data is to AI what good experimental design is to a lab assay – fundamental for meaningful results. At kbDNA, this meant developing specialized data infrastructure and ontologies specific to our research domain. Others in the industry are making similar moves, recognizing that data preparation and governance are essential for AI readiness.
People and Skills: Training and hiring are as important as technology. The most AI-enabled labs are those where scientists are well-versed in data science, and data scientists are well-versed in biology. Cross-training and collaborative culture will be critical so that AI isn’t a “black box” but rather a familiar part of the scientific toolkit for the whole team. The industry’s push for more AI training programs in life sciences is a promising sign that we are building this capability [7].
Strategic Focus: Not every problem needs AI. In our experience, applying AI is most fruitful for challenges characterized by large data sets and well-defined objectives (for example, image analysis, genomic pattern-finding, optimizing known processes). Conversely, early exploratory research or situations with very sparse data may be better served by classical approaches. A strategic, selective application of AI ensures we allocate resources where they can truly make a difference.
In conclusion, the initial hype around AI in biotech is settling into a more sustainable trajectory. The technology is proving to be a powerful accelerator and enhancer of R&D – but not a magic wand. Breakthroughs like AlphaFold show what’s possible, while setbacks like Watson for Oncology remind us of the pitfalls of overpromise. At kbDNA, our journey has reinforced that AI’s real value emerges when we combine cutting-edge algorithms with rich data, expert oversight, and continuous validation. By staying pragmatic yet optimistic, the life sciences community can harness AI to augment human innovation, leading to genuine progress in drug discovery, genomics, and health – even if it’s not as instant or automatic as early headlines suggested. The path to curing disease and advancing biology will always require hard work and smart science. AI won’t replace that, but used wisely, it will undoubtedly help us innovate better and faster than ever before.

Citations

Strickland, E. (2019). “How IBM Watson Overpromised and Underdelivered on AI Health Care.” IEEE Spectrum, 2 April 2019. (See: MD Anderson’s $62M Watson for Oncology project cancellation in 2016)
Brown, E. “Drugs discovered using artificial intelligence have not hit the market – yet.” Science News DK, 15 Oct 2024. (Summary of JAMA study: 164 AI-linked drugs in development, only one approved as of 2024, with minimal AI role)
Strickland, E. (2019). Ibid. (Noting that only a few AI diagnostic tools, mostly for image analysis, have regulatory approval and that AI struggles with complex medical data)
Laurent, A. (2025). “The Modern Biotech Lab: A Guide to Automation, AI & Data.” IntuitionLabs (report), 12 Dec 2025. (Citing a 2020 review that ~89% of published bioscience lab protocols were still manual or semi-manual)
Strickland, E. (2019). Ibid. (Quote from Dr. Robert Wachter on IBM “marketing first, product second,” highlighting Watson’s overhype and subsequent struggles)
MedDataX. “AI-Designed Drugs Achieve 90% Phase I Success Rate, Nearly Doubling Industry Average,” 25 Feb 2026. (Report on ~80–90% Phase I success rates for AI-designed drug candidates vs ~50% historical average)
Pistoia Alliance (2025 Survey). “Lab of the Future Survey 2025.” Technology Networks, Oct 13, 2025. (Finding that 77% of life science labs expect to use AI within 2 years; highlights trend of rising adoption and need for skills/training).

From Bottleneck to Benchmark: kbDNA’s Rituximab Biosimilar Purification Success Story

Thu, 23 Oct 2025 17:38:31 GMT

Bottleneck to Benchmark

Repurification of a Rituximab Biosimilar by Hydrophobic Interaction Chromatography (HIC) with Analytical SEC Confirmation and Endotoxin Control

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Read Time: 28 Min

Word Count: 1,417

Novelty Score: 9.3/10 | 98% Original Data

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Use Case

Raise monomer purity of a rituximab biosimilar by ~1–2 percentage points to meet a ≥97.5% monomer cutoff for RUO assay use, while maintaining yield and controlling endotoxin.

Summary

In this note we detail a practical, fast‑track workflow to repurify a rituximab biosimilar that arrived slightly below target monomer purity, using butyl/octyl HIC as the main polishing step, followed by buffer exchange, endotoxin reduction, and SEC‑HPLC confirmation. In our project exchange, phenyl HIC led to unacceptable losses, whereas butyl and octyl chemistries provided acceptable recovery and monomer levels; the final released lot measured 97.75% monomer , meeting a ≥97.51% acceptance criterion, with HMW ~2% and LMW ~0.21% by SEC.

Hydrophobic interaction chromatography is a well‑established, orthogonal polishing method for aggregate removal in mAb processes and can be run in bind–elute or flow‑through (including reduced‑salt/no‑salt, pH‑tuned) modes. SEC‑HPLC remains the standard for monitoring monomer/aggregate/fragment content, with validated columns and phosphate–saline mobile phases enabling robust quantitation at 280 nm. Endotoxin is controlled post‑HIC using anion‑exchange (AEX) flow‑through or membrane adsorbers, and verified by kinetic chromogenic LAL per pharmacopeial guidance.

Background & Objectives

Problem statement: 5 g of rituximab biosimilar (IgG1, RUO) arrived at ~96.5–97% monomer; the assay gate required approximately ≥97.5–99% monomer depending on use. The team targeted a ~1–2% monomer increase by removing HMW species without excessive loss.

Process constraints: Short timelines, preference for scalable methods, and endotoxin vigilance after re‑processing.

Chosen approach: Screen HIC ligands; avoid phenyl (losses observed here), favor butyl/octyl ; scale by multiple smaller runs to mitigate risk and cost; pool, depyrogenate, exchange into final buffer, and confirm by SEC.

Why HIC? HIC provides aggregate clearance with selectivity complementary to IEX, and can be tuned with salt type/level and pH; recent work demonstrates effective aggregate removal even in flow‑through at low/no salt by adjusting pH.

Materials & Equipment (Representative)

HIC media: Butyl (e.g., Butyl Sepharose/HiTrap Butyl HP) and Octyl resins; avoid Phenyl if recovery is problematic.

· SEC analytics: Silica‑based SEC columns for mAbs (e.g., TSKgel SuperSW mAb HR for resolution or UP‑SW3000 for fast runs); phosphate/saline mobile phase; UV at 280 nm .

· Endotoxin control: AEX membrane adsorbers (e.g., Sartobind Q) or other electropositive media; LAL reagents and kinetic chromogenic setup.

· Buffers & reagents: Phosphate buffer (pH 6.8–7.2), NaCl; ammonium sulfate or sodium citrate/sulfate for HIC binding (if using bind–elute); 0.22 µm filters; optional L‑arginine in UF/DF to suppress re‑aggregation.

Concentration measurement: A280 using E1% = 1.4 (mg/mL)⁻¹ cm⁻¹ for IgG solutions as a common approximation when sequence‑specific ε is unavailable.

Workflow Overview

Receive & verify incoming lot; confirm concentration by A280 and baseline SEC profile.
HIC screening (small‑scale): Compare phenyl, butyl, octyl resins under identical conditions; in this project, phenyl caused severe loss , while butyl & octyl showed acceptable yield and monomer.
Scale‑out plan: Prefer multiple runs on ~100 mL packed volume over a single 500 mL run to manage resin expense and spread risk; pool fractions meeting spec.
Buffer exchange & concentration: UF/DF into final buffer (e.g., your assay’s phosphate/saline); consider pH/ionic strength tweaks or arginine (0.2–0.5 M) during UF if re‑aggregation appears.
Endotoxin reduction: Process through AEX flow‑through/membrane at pH 7–8, low conductivity; verify via kinetic chromogenic LAL .
Release analytics: SEC‑HPLC vs control; NR SDS‑PAGE; LAL; final concentration back to ~12 mg/mL if required by spec.

Detailed Procedure

1) Pre‑HIC Characterization

Concentration by A280: Measure at 280 nm (1 cm path), blank with formulation buffer; report using E(1%,1 cm) = 1.4 unless sequence‑specific ε is available.
Baseline SEC‑HPLC: Use a TSKgel SuperSW mAb HR or UP‑SW3000 (2 µm, 15 cm) column for high‑resolution/fast QC, with mobile phase ~100 mM phosphate + 100 mM Na₂SO₄ (pH 6.7–6.8) or 50 mM phosphate + 0.3 M NaCl (pH 7.0); detect at 280 nm.

2) HIC Mode Selection

Option A—Bind–Elute (classical HIC):

Equilibrate resin with buffer containing 0.8–1.2 M ammonium sulfate (or sodium citrate/sulfate) in 20–50 mM phosphate, pH 6.5–7.0. Load at 5–10 mg/mL·CV to bind hydrophobic impurities preferentially; elute monomer with descending salt or mild organic additive (≤10% isopropanol if needed).
Rationale: Higher hydrophobicity aggregates bind more strongly; tuning salt gradient separates monomer from HMW.

Option B—Flow‑Through HIC (low/no salt):

Equilibrate a more hydrophobic resin; adjust pH ≤6.0 so the mAb becomes net positive and less hydrophobic, enabling product flow‑through while aggregates bind.
Rationale: Reduces salt burden and offers robust aggregate clearance with simpler pool handling.

3) Scaling Strategy

To repurify ~5 g: run five × ~100 mL columns rather than a single 500 mL column; evaluate each run by NR SDS‑PAGE , pool acceptable fractions, then proceed to endotoxin reduction and buffer exchange.

4) Endotoxin Reduction (Post‑HIC)

AEX flow‑through/membrane adsorbers (e.g., Sartobind Q): Operate at pH 7–8, low conductivity (≤5 mS/cm) such that IgG flows through while negatively charged LPS binds ; membranes simplify handling and speed cycles.
Alternative strategies include electropositive multimodal adsorbents or charged membranes ; selection depends on formulation and ionic strength.

5) Buffer Exchange & Concentration

UF/DF into final assay buffer (e.g., phosphate + saline, pH 7.0). If aggregates re‑form during UF/DF, add L‑arginine (0.2–0.5 M) or optimize pH/ionic strength to suppress protein–protein interactions.
Target ~12 mg/mL concentration if required for downstream use, as used in the project’s prior lots and calculations.

6) Release & QC

SEC‑HPLC: Confirm %HMW, %monomer, %LMW against control/reference. Typical conditions listed above (Section 1).
LAL (Kinetic Chromogenic): Quantify endotoxin per USP <85> using validated kinetic chromogenic kits/instruments; document MVD, inhibition/enhancement, and system suitability.
Protein ID & integrity: NR SDS‑PAGE, intact mass (optional).

Results from the Project (SEC)

Data derived from SEC integrations and overlays shared during the workstream; the final pooled lot met a ≥97.51% cutoff and passed review for release.

Discussion & Practical Notes

Ligand choice matters. In this case, phenyl over‑retained/impacted yield; butyl/octyl provided the best balance of aggregate removal and recovery—consistent with HIC’s tunable hydrophobic ladder.

Flow‑through HIC is a viable alternative when salt handling is a concern; adjusting pH can achieve selective aggregate binding with no/low salt and simplify pool management.

SEC method selection: For QC throughput, 15 cm, 2–4 µm SEC columns (e.g., UP‑SW3000, SuperSW mAb HTP) cut run time to ~4–8 min without sacrificing resolution versus 30 cm columns.

Endotoxin vigilance: Re‑processing risks LPS pickup; AEX membranes in flow‑through offer effective clearance with minimal product binding; confirm via kinetic chromogenic LAL per pharmacopeia.

UF/DF re‑aggregation: Consider arginine or ionic strength/pH adjustments; arginine is well‑documented to suppress protein–protein interactions without global denaturation when used appropriately.

Troubleshooting Guide

Low monomer after HIC: Increase resin hydrophobicity (butyl → octyl) or adjust salt type/strength (e.g., ammonium sulfate vs citrate), and fine‑tune pH to improve aggregate retention.
Yield loss on phenyl or high salt: Step down to butyl ; trial flow‑through HIC at lower salt; watch for precipitation at high kosmotropic salt.
Endotoxin above limit: Reduce conductivity, raise pH into AEX flow‑through window; verify no inhibition/enhancement in LAL; consider electropositive multimodal media.
SEC co‑elution of fragments: Use two SEC columns in series or move to higher‑resolution media to resolve close LMW species.

Example Buffer Recipes

HIC Equilibration (Bind–Elute): 20 mM Na‑phosphate, 1.0 M (NH₄)₂SO₄ , pH 6.8.
HIC Elution: Same buffer with stepped gradient to 0–0.2 M salt; optional ≤10% isopropanol if needed for selectivity.
SEC Mobile Phase (QC): (A) 100 mM phosphate + 100 mM Na₂SO₄, pH 6.8 ; or (B) 50 mM phosphate + 0.3 M NaCl, pH 7.0 .
AEX Flow‑Through (Endotoxin): 20–25 mM Tris, ≤5 mS/cm , pH 7.5–8.0; adjust to keep IgG in flow‑through.

Quality Control Checklist (Release)

SEC‑HPLC: ≥97.5% monomer and controlled HMW/LMW vs internal control.
Endotoxin: Meets RUO/assay threshold by USP <85> kinetic chromogenic LAL, with inhibition/enhancement ruled out.
Concentration: A280 with IgG E(1%,1 cm) = 1.4 unless sequence‑based ε is used/available.
Identity/Integrity: NR SDS‑PAGE; optional intact mass.

Appendix A — Project Exchange Excerpts (Context)

HIC screen: “Phenyl was no good due to severe product losses… Butyl and octyl each looked OK.”
Scale proposal: “5 runs on a 100 ml column—reducing gel expense and spreading out the risk a little.”
Final SEC (Release): Ritux kb_Cleaned 97.75% monomer , acceptable vs control; passed ≥97.51% cutoff.
Endotoxin/LAL planned post‑HIC; SEC slots reserved to support rapid turnaround.

One‑Page SOP (concise)

Baseline QC: A280; SEC (record %HMW/%LMW).
HIC polishing: Butyl HIC (bind–elute or FT). Optimize salt/pH; avoid phenyl if recovery poor.
Pool criteria: SEC spot‑checks; pool only monomer‑rich fractions.
UF/DF + Endotoxin removal: UF/DF into final buffer; pass through AEX membrane; verify LAL. Consider arginine if aggregation recurs.
Final QC & release: SEC ≥ spec; LAL pass; concentration to target (e.g., 12 mg/mL).

Data Images

Repurification of a Rituximab Biosimilar by Hydrophobic Interaction Chromatography (HIC) with Analytical SEC Confirmation and Endotoxin Control

The following includes the data visuals for SEC chromatogram overlays and SDS-PAGE gel images to illustrate the repurification workflow and results for rituximab biosimilar.

---

SEC Analysis

Figures below show simulated SEC overlays based on project dat a, highlighting monomer and aggregate profiles before and after HIC polishing.

Figure 1. SEC-HPLC overlay (Control vs kb_Cleaned Final). Normalized UV280; monomer near ~7.9 min.

Figure 2. SEC-HPLC overlay (Control vs UF-Purified Intermediate).

Figure 3. SEC-HPLC overlay (Control, UF-Purified, kb_Cleaned Final).

SDS-PAGE Analysis

Schematic gels illustrate non-reducing and reducing SDS-PAGE profiles for control, UF-purified, and final repurified samples.

Figure 4. Non-reducing SDS-PAGE schematic: lanes ladder, control, UF, HIC pool, final.

Figure 5. Reducing SDS-PAGE schematic: heavy (~50 kDa) and light (~25 kDa) chains.

Current State of Discovery R&D | UnderReport kb

Mon, 13 Oct 2025 03:52:54 GMT

Current State of Discovery R&D

The Life Sciences Crisis Nobody Wants to Talk About

Introduction

Unfiltered Realities, Data-Driven Trends, and the Hard Truths Shaping Discovery-Stage R&D

Discovery-stage research in the life sciences – covering the early R&D pipeline from basic target discovery through preclinical proof-of-concept – is facing a challenging landscape in North America. This report provides an unfiltered analysis of the current state of discovery-stage therapeutic and diagnostic research across startups, large pharmaceutical companies, academic labs, and government institutes. We detail key trends, recent milestones, and objective (often underreported) realities defining this sector. The goal is a realistic, data-driven status update with no rose-colored optimism – just the facts and harsh truths shaping early-stage R&D.

Despite rapid scientific advances (e.g. genomics, AI, precision medicine), the ecosystem for early discovery is under strain . Funding for biotech startups has contracted sharply since its 2021 peak – nearly 50% of such companies could run out of money by end of 2025 , leading to widespread budget cuts and project cancellations [1] . Large pharma companies, staring down major 2030 patent expirations on their cash cows (>$500B at risk industry-wide), are retrenching to “safe” projects and pipeline fill-ins via acquisitions [2] . They’ve focused on proven therapeutic areas (like obesity or well-known cancer targets) while more novel, high-risk programs are shelved [3] . Academic and nonprofit research institutes continue to generate novel ideas, but many fail to translate due to reproducibility issues and the notorious “valley of death” between lab discovery and clinical development. In fact, an estimated ~50% of preclinical findings cannot be replicated , wasting ~$25–28 billion of U.S. research spending each year [4] . Meanwhile, diagnostics R&D remains chronically underfunded , receiving only ~3% of total healthcare R&D investment since 2004 [5] . This severe imbalance slows innovation in disease detection and prevention and leaves many illnesses without early diagnostic tools.

In the sections that follow, we examine the financial and innovation landscape , dive into sector-specific trends (therapeutics vs. diagnostics) , analyze how different classes of organizations are approaching discovery-stage research – and how that’s working out for each – and review the state of vendors, suppliers, and manufacturers that support the R&D ecosystem. Several tables and visual aids summarize key trends and realities. All information is drawn from recent industry analyses, surveys, and reports to ensure an up-to-date snapshot as of late 2025.

Recent Timeline

Key Events (2020–2025)

To understand the current state, it’s helpful to review major events and trends over the past five years that have shaped the discovery-stage landscape:

(The timeline above highlights the rollercoaster of the past five years – from boom to bust – and the major shifts affecting discovery-stage R&D.)

Funding & Investment Landscape

“High-Risk, High-Reward” Hits a Wall

In the early 2020s, North America’s life science sector experienced a funding whiplash . After the pandemic-induced surge of 2020–21, the capital flow to discovery-stage endeavors dramatically receded . This contraction has arguably been the single greatest factor shaping current R&D activities:

· Venture Capital Retreat : Biotech investment plunged after mid-2021 , creating a cash crunch especially for early discovery projects. By 2024, early-stage venture funding was ~20% lower than the year prior [1] . Many young biotechs that raised big rounds in 2020–21 found themselves unable to secure new capital, forcing drastic cuts. Nearly 50% of biotech companies are at risk of running out of cash by the end of 2025 according to an analysis by Ernst & Young [2] . This is a stark reality – a possible mass extinction event in the startup ecosystem, as some observers have put it. Companies that in 2021 might have raised a $50M Series B on promising preclinical data now struggle to get even a fraction of that, unless they’ve advanced to clinical trials or have star teams.
· Flight to “Safe” Bets : In a risk-averse funding climate, investors (and pharma corporate venture arms) concentrate funds on programs with perceived lower risk and nearer-term payoffs . Therapeutic areas like metabolic disease (e.g. GLP-1 drugs for obesity) and well-validated oncology targets are receiving disproportionate attention, whereas novel, unproven mechanisms are largely shelved [3] . This “brutal selection” means only teams with stellar data or track records can raise substantial money [4] . Startups are increasingly built around whatever theme is in favor. For example, multiple new companies pivoted to obesity or AI-powered drug discovery in 2023 because that’s where investors sign checks – even if it’s a crowded space. Meanwhile, genuinely new approaches for diseases like Alzheimer’s or next-generation antibiotics languish for lack of willing backers.
· Public Markets & IPO Drought : The window for biotech IPOs virtually shut after 2021’s frenzy. In 2022 and 2023, only a handful of biotech IPOs eked through, and those often at downscaled valuations. H1 2025 saw global biotech IPO proceeds down ~58% from the prior year [5] . With IPO exits off the table, venture investors became even more cautious (no quick public cash-out in sight). This led to a glut of “private-to-private” mergers and companies delaying expensive projects. For companies that did go public in 2020–21, many ended up trading far below their IPO price, hampering their ability to raise follow-on capital. The net effect: the traditional funding ladder (VC → IPO → follow-on raise) is broken for now, and young biotechs must either find alternative financing (partnerships, royalty deals, etc.) or drastically slow their R&D burn.
· M&A as an Exit (and Lifeline) : Conversely, pharmaceutical giants flush with cash are ramping up acquisitions to fill their pipelines. Facing a wave of patent expirations on blockbuster drugs, Big Pharma has earmarked roughly $180B for buying assets/companies by 2030 [6] . However, a real concern arises: if early-stage development is starved now, will there be enough viable startups to acquire later? [7] The current funding squeeze could ironically shrink the very innovation pool Big Pharma hopes to draw from. In 2023–2024, we saw an uptick in “fire-sale” acquisitions of distressed companies – for example, Pfizer’s bargain pick-up of Lucira Health (a diagnostics firm) for only $36M after it filed bankruptcy [8] . Such deals highlight how dire the situation became for some ventures. On the positive side, well-positioned biotechs with solid data have become prime targets (often at valuations much lower than a few years ago, making buyers happy). Pharma merger activity in 2025 started to rise, focusing on clinical-stage or emerging platform companies at reasonable prices rather than mega-mergers.
· Spending Priorities Shift Inward : Within organizations, the funding crunch forced internal triage. Biotechs and pharma alike trimmed exploratory research and redirected resources to later-stage, “must-win” programs where return is more certain. A Bain analysis noted that companies “deprioritized expansive spend on discovery efforts” and even paused some preclinical projects to conserve cash for clinical trials [9] . In practice, this means pipeline breadth is sacrificed for depth: rather than advancing five early targets, a company might focus on one lead candidate and drop the rest. Budgets for platform development, novel target discovery, and other long-term bets were often first on the chopping block in 2022–2024. The result is an R&D portfolio that is narrower and more incremental. Even academic collaborations, traditionally a source of new ideas, saw reduced funding from industry partners during this period unless tied to clearly defined product outcomes.

The net effect is a far more constrained financial environment for discovery-stage R&D than existed in the late 2010s. The industry swung from exuberant capital availability to extreme selectivity in just a couple of years. For an R&D executive, the message is clear: early-stage innovation is happening under severe budget pressure, with many programs slowed or dead, and only the most compelling projects attracting support. “Nice-to-have” science projects are luxuries few can afford in 2025. This has significant downstream implications, explored further below in the therapeutics and diagnostics sections and in how organizations and suppliers are adapting.

Therapeutic Discovery

Trends and Harsh Realities

Discovery-stage therapeutic research (drug discovery for new medicines) has always been high-risk, expensive, and slow. In North America, thousands of programs in pharma companies, biotech startups, and academic drug discovery centers aim to find the next breakthrough therapy. But today’s harsh realities are reshaping how this work is done. Key trends and truths in therapeutic discovery include:

1. Pipeline Contraction & “Safe Bet” Science: With funding tight, there’s been a notable narrowing of research scope around “sure bets.” Companies are focusing on a smaller number of disease areas and targets that align with proven modalities. For instance, there is heavy activity in metabolic diseases like diabetes/obesity (spurred by the success of GLP-1 agonists) and continued investment in cancer immunotherapies. By contrast, “high-risk, high-reward” ideas – say a first-in-class drug for Alzheimer’s, or a new antibiotic mechanism – struggle to get traction. Big Pharma R&D groups have streamlined to fewer therapeutic areas, often those with clear commercial potential. Some areas of great medical need (e.g. novel antibiotics, certain neurodegenerative diseases) remain under-invested because the risk/return profile is hard to justify in today’s environment. This conservatism may ensure efficient use of R&D dollars in the short term but could mean fewer radical innovations long term. Insiders sometimes bleakly joke that portfolios are being pruned to what’s “safe to fail” – i.e. only projects that, even if they fail, won’t be criticized because they were the obvious ones to do.

2. Rise of AI and Computational Drug Discovery – With Caveats: Over the last few years, artificial intelligence has been touted as a game-changer for drug discovery. Indeed, AI and machine learning tools are now helping with tasks like hit identification, protein structure prediction (e.g. AlphaFold), and polypharmacology modeling. Notable milestone: DeepMind’s AlphaFold2 (2021) predicted structures for ~200 million proteins, many previously unmapped, raising hopes of exploiting new targets. Companies like Recursion and Insilico Medicine announced AI-designed molecules entering clinical trials. However, the reality is more tempered. A 2023 Nature report highlighted that while AlphaFold provides amazing structural data, it doesn’t automatically translate into viable drugs or lead compounds [1] . For example, Recursion’s much-publicized effort to predict billions of protein-ligand interactions using AlphaFold structures produced plenty of theoretical “hits,” but experts caution that without experimental validation those predictions mean little [2] . In practice, AI generates many hypotheses, but human chemists and biologists still must sort signal from noise. One underreported truth: AI has sped up parts of discovery (like virtual screening), but it has also created huge piles of false positives that teams must wade through [3] . Drug hunters now joke about drowning in AI-generated leads. The bottom line – AI is an exciting and useful tool (it can shave months off certain research steps and uncover non-intuitive ideas), but it hasn’t made drug discovery significantly cheaper or more successful overall yet. Lab work and empirical testing remain the rate-limiting steps, and many AI-proposed drug candidates falter once synthesized and tested in real cells or animals. The field is moving fast, so this might change, but as of 2025 the promised AI revolution in therapeutics is still in its early innings, with more hype than tangible ROI.

3. Advanced Therapeutic Modalities (New Science, New Challenges): The therapeutic toolbox has expanded beyond traditional small molecules and biologics into gene therapies, cell therapies, RNA therapeutics, protein degraders, etc. These modalities offer new ways to treat disease – potentially even cures – but each brings unique discovery-phase challenges. For example, cell therapies (like CAR-T) can be transformative for cancer, but discovering an effective cell product isn’t like screening a chemical – it involves engineering living cells and can take extreme iteration to get right. Similarly, gene editing therapies (e.g. CRISPR-based) require identifying the right genetic target and developing a safe delivery method to the correct cells – essentially two discovery problems in one. A harsh reality is that early programs in these cutting-edge modalities have had high failure rates and unforeseen setbacks. Many first-generation gene therapies ran into safety issues (immune reactions, off-target effects) that sent researchers back to the drawing board. mRNA therapies (beyond vaccines) face delivery and stability challenges that make discovery and optimization difficult. So while the science frontier is dazzling, the path to a product is often longer and costlier than optimists predicted. For instance, after the initial CRISPR therapy trials, researchers realized they needed entirely new discovery efforts for novel delivery vectors to target organs beyond the liver – an active area now, but one that will take time. The underreported point: each new modality comes with a steep learning curve . We’re essentially re-inventing the discovery process for each one (what works for small molecules doesn’t directly translate to discovering an effective siRNA, for example). This means timelines to first success in these modalities can be longer than anticipated, straining investors’ patience in the current climate.

4. Efficiency Pressures and Externalization: In response to cost pressures, organizations have looked to boost efficiency in discovery. One trend is heavy use of outsourcing – contract research organizations (CROs) are performing much of the routine discovery work (high-throughput screening, animal studies) that might have been in-house before. This variable-cost model lets companies scale down expenses quickly if needed (by cutting CRO projects) rather than maintain large fixed internal labs. Another efficiency push is automation and improved lab technologies – e.g., automated synthesis and testing platforms – to get more data per dollar spent. Big pharma has also become more inclined to let academia and biotechs “de-risk” early projects, then swoop in via partnerships or acquisitions once there’s proof-of-concept. Today well over half of new drug approvals originate from outside big pharma’s own labs (either discovered by biotechs or academic groups) – a testament to how pharma has externalized a chunk of discovery. While this can be efficient (pharma pays for winners, not all the attempts), it does rely on a vibrant biotech sector to produce those winners. With that sector under duress, pharma’s pipeline in, say, 2027–2030 could be in jeopardy. Another noteworthy shift: small biotechs themselves are merging or collaborating at early stages as a survival tactic . Rather than each burning limited cash on parallel discovery programs, two cash-strapped startups might merge to pool resources and focus on the most promising program from their combined portfolio [4] . While this can salvage value, it reduces diversity of approaches – effectively fewer independent shots on goal.

The table below summarizes key trends and gritty realities in therapeutic discovery as of 2025:

Table 1. Key Trends & Realities in Therapeutic Discovery R&D (North America, 2025)

(Sources: Industry funding reports 11 ; AI drug discovery assessments 5 ; reproducibility studies 1 .)

Implications: Today’s therapeutic discovery teams must do more with less. They focus on projects with clear rationale and robust data, and often must prove a concept much earlier to attract funding for the next step. The old biotech model of “interesting science + big vision” securing large Series A rounds is largely gone; now investors want to see a tangible prototype or at least in vivo efficacy before committing. This “show me the data” ethos is tamping down speculative science. Internally, R&D leaders are pushing for faster kill/go decisions – the “fail fast” mantra – to conserve resources. If an experiment or candidate doesn’t show promise, it gets cut swiftly rather than linger in the pipeline. Efficiency is up, but this austerity can make researchers more risk-averse , avoiding unconventional ideas that might not have immediate payoff. For the future, the concern is that today’s conservatism sows the seeds of a lean innovation harvest later. Conversely, there’s an opportunity: those who do sustain bold discovery efforts now (whether through creative funding, partnerships, or government support) could end up with truly differentiated therapies when the cycle turns upward again. Balancing the R&D portfolio between incremental “safe” bets and a few transformative moonshots is more important than ever, albeit hard to do under financial constraints.

Diagnostic Discovery

Trends and Harsh Realities

Discovery-stage research in diagnostics – spanning diagnostic tests, research tools, imaging agents, etc. – often operates in the shadow of therapeutics, yet it is equally critical for healthcare. Diagnostics enable early disease detection, guide treatment decisions, and improve patient outcomes (not to mention their role in public health). However, the diagnostics sector has long been the “poor cousin” in life sciences R&D, and current realities reinforce that:

1. Chronic Underinvestment: A striking imbalance exists in R&D funding: historically, only about 3% of total healthcare R&D investment goes into diagnostics [1] (including tools and testing platforms). The vast majority of funding and venture capital flows to therapeutics. This gap became even more pronounced recently – in 2023, U.S. diagnostics and research-tool startups raised just $6.2B in VC, a 37% drop from 2022 [2] . First-time financings for new diagnostics companies were down 31% [3] . The consequences of this long-term underinvestment are tangible: fewer innovative diagnostic ideas get developed, and many conditions still lack early detection methods. For instance, there is intense medical interest in multi-cancer early detection blood tests (liquid biopsies) and better Alzheimer’s diagnostics. Such technologies are being researched, but the funding available is a fraction of that for developing new cancer drugs or Alzheimer’s treatments. As a result, progress is slower than it could be. An underreported truth is that late or missed diagnosis due to limited diagnostic tools leads to higher downstream healthcare costs and worse outcomes [4] – essentially, we pay for it on the back end, but it’s not accounted for when budgeting R&D.

2. Post-COVID Hangover in Testing: The 2020–21 pandemic put diagnostics in the spotlight, with massive public and private spending on testing (PCR tests, rapid antigen kits, etc.). Some diagnostics companies grew exponentially during that period. However, by 2022–2023, demand for COVID-19 testing plummeted, and many testing-focused companies crashed. For example, Lucira Health, which made at-home COVID tests, went bankrupt in early 2023 when sales evaporated – as noted, Pfizer scooped it up for peanuts [5] . This boom-bust cycle left investors wary of diagnostics once again. Many generalist VCs who dabbled in diagnostics during the pandemic retreated afterwards, feeling the market is too unpredictable. The industry is actually worse off in some respects: several up-and-coming diagnostics startups that scaled for COVID either folded or had to drastically pivot, burning investor confidence. The lesson investors took was that diagnostics can be very volatile and heavily tied to public health cycles, making them “less attractive” than the steadier revenue prospects of therapeutics. This is arguably shortsighted, but it’s the sentiment in board rooms. So, despite the public realizing in 2020 how crucial diagnostics are, by 2025 funding for non-COVID diagnostics is back to being skeletal.

3. Market and Adoption Barriers: Even when a new diagnostic test gets developed, getting it adopted into routine care is an uphill battle . Diagnostics typically face a tougher commercial path than drugs: reimbursement is lower and more complicated, and convincing physicians to change testing habits can be slow. A stark example: AI-based diagnostic software – like digital pathology and radiology tools – have shown ability to improve detection (e.g., catching cancers that pathologists sometimes miss [6] ). Yet, U.S. labs have little financial incentive to adopt them because there are no reimbursement codes paying extra for AI use. A hospital doesn’t get paid more for finding a cancer with an AI assist versus without, so many are hesitant to invest in these systems. Similarly, innovative screening tests (like a multi-cancer blood test) might not be covered by insurance for years, until long-term outcome data convinces payers. The result is a Catch-22 : investors fear diagnostics won’t make money, so they don’t invest; without investment, it’s hard to generate the evidence to change clinical practice and reimbursement. Many promising diagnostics languish in this purgatory. Underreported reality: some diagnostics companies with technically brilliant products failed not because the test didn’t work, but because they couldn’t crack the code of getting insurers and providers to adopt it. The collapse of Theranos (a fraud case) also cast a long shadow, making investors and regulators extra cautious of bold diagnostic claims.

4. Research Tools and Platform Consolidation: Many “discovery diagnostics” firms actually produce the tools and platforms that enable research and testing (for instance, DNA sequencers, mass spec devices, high-throughput assay platforms). This arena saw significant consolidation in recent years. In 2023, large conglomerates made multi-billion-dollar acquisitions: Danaher bought Abcam for $5.7B and Thermo Fisher bought Olink for $3.1B – both deals involving companies that provide specialized research reagents or proteomics technology [7] . This indicates that while the market for tools had a downturn (fewer biotechs buying equipment), the big players viewed these tech assets as strategically important for the long run and swooped in at lower valuations. The impact: the industry is now less fragmented, dominated by a few giants (Thermo, Danaher, Illumina, etc.) controlling key tool categories. For researchers, this consolidation can mean more integrated product offerings but also potentially higher prices and less customization. For the smaller tool innovators, the message is you either find a niche or eventually get acquired. In 2024, Standard BioTools and SomaLogic (mid-size tool companies) merged in a ~$1B stock deal [8] as a survival strategy, reflecting the “merge or die” mentality. Overall, the pace of brand-new platform creation in diagnostics may slow since incumbents have so much market power and can outcompete or acquire newcomers quickly.

5. Regulatory Outlook: Regulation of diagnostics is evolving. The FDA historically exercised enforcement discretion on many lab-developed tests (LDTs), but there’s pressure to tighten oversight after some high-profile test failures. Upcoming legislation (e.g., the VALID Act, still pending) and FDA guidance suggest that more diagnostics will require regulatory approval rather than slipping by as LDTs. In the short term, this can increase the cost and time to bring a new test to market (more like a drug pathway). On the other hand, it may improve reliability and trust in diagnostics. The FDA did grant emergency use authorizations at record speed during COVID, which showed a fast-track is possible when urgency is high. Now, outside of emergencies, the agency is grappling with how to ensure quality without stifling innovation. Additionally, Europe’s new In Vitro Diagnostic Regulation (IVDR) imposed stricter requirements in 2022, which impacted any North American companies selling in the EU (some had to redo validations or even pull products from EU market due to compliance burden). In short, the regulatory landscape is becoming more rigorous for diagnostics, which, while good for patients, does raise the bar (and cost) for discovery-stage companies working on new tests.

In summary, diagnostic discovery in 2025 operates on thin margins and faces headwinds at multiple levels : funding scarcity, market inertia, and increasing regulatory expectations. The paradox is that diagnostics arguably offer huge value – catching disease early or stratifying patients properly can save many lives and dollars – but our system doesn’t reward developing them in the way it rewards new therapies. The table below captures key trends and realities in the diagnostics sector:

Table 2. Key Trends & Realities in Diagnostic Research & Tools (North America, 2025 )

(Sources: Venture funding stats [1] ; case studies from industry news [2] [3] ; analysis of diagnostic adoption and outcomes [4] .)

Implications: For life science executives and policymakers, the diagnostics sector presents both challenges and opportunities. The challenge is clear: the traditional market incentives for diagnostics are weak. To break the cycle, it likely requires policy intervention (such as better reimbursement schemes for innovative tests, or public-sector funding to de-risk diagnostics R&D). Encouraging signs include government and foundation programs – for example, the U.S. NIH launched initiatives in early cancer detection (the Cancer Moonshot has a diagnostics component) and pandemic preparedness that fund diagnostic innovation. Also, some pharma companies are investing in diagnostics development for patient selection (companion diagnostics for their drugs), which indirectly pumps money into the field.

Looking ahead, a mindset shift is needed among investors and healthcare payers to treat diagnostics as equal in importance to therapies. Without that, improvements in therapeutic outcomes will hit a ceiling, because so many illnesses rely on timely and accurate diagnosis. The harsh but real scenario: a breakthrough cure isn’t useful if patients are diagnosed too late to benefit.

Organizational Approaches

Who Does Discovery and How Are They Faring?

Discovery-stage life science research is conducted by a mosaic of organization types – each with different motivations, structures, and pain points. Let’s analyze how startups, large pharmaceutical companies, academic labs, and government research institutes are each approaching discovery in 2025, and what objective realities they face:

Cross-Cutting Reality – Collaboration is Key: It’s evident that no single sector can do it alone in discovery R&D. The most successful recent examples of translating a lab idea into a therapy involved tight collaboration : academics working with biotech entrepreneurs to spin out a company; biotechs partnering with pharma early to access resources; public institutes providing seed funding or infrastructure at critical junctures. A study of drug origins found that many approved drugs in the last decade stemmed from academic research, but nearly all had industry involvement to drive development. Essentially, the system relies on handoffs: academia discovers, biotech innovates and de-risks, pharma develops and commercializes. In 2025, these handoffs are under strain because each link in the chain is under pressure.

The funding crunch for biotechs means fewer academic spinouts get off the ground – some ideas sit on the shelf even after promising papers. Pharma’s hunger for new products is high, but they sometimes find less to choose from in their shopping cart because early pipelines are drier. Nonprofits and new initiatives (like the venture philanthropy model, where foundations fund drug discovery for their disease) are trying to bridge gaps.

For an executive overseeing R&D strategy, the implication is to nurture relationships across sectors . Companies that proactively collaborate – e.g., funding academic labs through sponsored research, co-developing programs with biotech partners, or leveraging government grants – are likely to weather the storm better and come out with robust pipelines. Those that operate in silos risk missing out on external innovation or duplicating work inefficiently. In this climate, a spirit of collaboration and resource-sharing is not just nice to have, it’s becoming essential to get things done.

Vendors, Suppliers & Manufacturers

The Support Ecosystem Under Strain

No discovery-stage research can progress without a vast array of vendors and suppliers – from lab reagent makers and instrument manufacturers to contract research and manufacturing organizations (CROs/CMOs) – that provide the tools, materials, and services fueling experiments. This support ecosystem has been grappling with its own set of challenges in the current climate:

(Sources: Industry funding reports 11 ; AI drug discovery assessments 5 ; reproducibility studies 1 .)

1. Slumping Sales and Retrenchment: The post-2021 R&D slowdown has cascaded to vendors. Suppliers of lab instruments, reagents, and services, who boomed during the biotech bull market, saw orders dry up as customers cut spending. Thermo Fisher’s CEO noted in Q3 2023 that many small biotech clients have become extremely cautious, delaying or reducing orders [1] . As a result, Thermo Fisher missed revenue targets and cut its annual guidance [2] . Its life-science tools unit’s revenue dropped 18% in one quarter [3] . Similarly, Danaher and Agilent both reported weaker sales in late 2022 and 2023, explicitly citing reduced demand from biotech customers. Agilent Technologies (a major lab equipment maker) initiated layoffs – eliminating ~450 jobs (2% of staff) in late 2023, and another ~3% in mid-2024 – saying the lab market recovery has been “slower than expected” [4] [5] . These cutbacks mirror what’s happening in biotech: just as biotechs trimmed down to extend their runway, tool vendors are cutting costs to weather the dip. CROs and CDMOs have also felt it: many report that smaller biotech clients are postponing or canceling projects, leading to a dip in new bookings. Some CROs have pivoted to rely more on stable big pharma contracts to get through the lean times. In essence, the entire R&D “food chain” has tightened. The silver lining for well-funded players is they can negotiate better deals – some vendors are offering discounts or favorable terms to keep business – but the overall environment is one of retrenchment.

2. Consolidation and Strategic Shifts: As noted, big fish are eating little fish in the supplier pond. This consolidation has a few motivations: acquiring new technology capabilities, achieving cost synergies, and positioning to be a one-stop-shop for customers. For example, Danaher’s acquisition of Abcam gave it a highly regarded portfolio of antibodies and research reagents (boosting Danaher’s presence in discovery research labs worldwide) [6] . Thermo’s purchase of Olink brought in an advanced proteomics assay platform, complementing Thermo’s mass spectrometry business [7] . The timing of these deals – at a low point in valuations – suggests the big companies saw an opportunity to buy valuable assets more cheaply than a couple years ago. Additionally, smaller vendors have merged to gain scale. The Standard BioTools–SomaLogic merger combined a lab instrumentation firm with a proteomic data company, aiming to offer integrated solutions and cut overhead [8] . The impact on researchers could be mixed: on one hand, a consolidated vendor might offer bundled deals and more convenient service; on the other hand, less competition might mean less bargaining power for labs and potentially slower innovation (fewer independent R&D efforts among suppliers). For the vendors themselves, consolidation can help ride out the storm by removing duplicate costs and expanding market reach. But it also means the survivors have to manage very broad product lines (which can be challenging to integrate). We’re also seeing strategic shifts like vendors focusing on core profitable segments and dropping peripheral lines. For instance, some instrument companies have quietly discontinued low-margin product lines (like basic lab consumables) to focus on high-end equipment and consumables that ensure recurring revenue. Services firms (CROs) similarly are focusing on their key pharma clients and cutting back marketing to cash-strapped biotechs. All of this results in a leaner supplier landscape, optimized for the customers who still have budgets (mostly big pharma, government, and well-funded biotechs).

3. Supply Chain and Cost Challenges: Beyond demand issues, vendors have faced supply-side challenges . The pandemic and ensuing global logistics snarls hit the life science supply chain hard. Shortages of items like pipette tips, plastic disposables, and culture media became acute in 2021–2022. While those specific shortages have largely eased by 2025, the lesson was learned: the supply chain is vulnerable. Additionally, costs of raw materials and logistics remain elevated. Energy prices and commodity chemicals went up, and some haven’t fully come down. Vendors passed a lot of these increases to customers. A Nature report in 2023 documented that an average lab’s supply costs jumped ~27% from 2018 to 2022 [9] . One striking figure: nitrile gloves – an essential disposable – cost about 91% more in 2022 than they did in 2018 [10] . This was due to skyrocketing demand (and some price-gouging) during COVID and rubber supply issues. Similarly, certain enzymes and reagents saw big price hikes due to supply chain bottlenecks. Researchers on tight budgets had to ration or seek cheaper alternatives, sometimes compromising on quality or consistency. Vendors meanwhile had to navigate volatile supply availability; some smaller reagent makers were unable to fulfill orders on time, pushing labs to bigger suppliers who could stockpile. Another dramatic supply challenge has been laboratory animals, particularly non-human primates (NHPs) . During COVID, NHP demand for vaccine research soared, but exports from China (the main supplier of research monkeys) were cut off in 2020. Then in 2022–2023, a U.S. DOJ investigation (Operation Flying Primates) uncovered illicit imports of wild-caught monkeys from Cambodia, leading to import suspensions [11] . The result: a severe NHP shortage in the U.S. By 2023, prices for research monkeys reportedly jumped to ~15 times pre-pandemic levels [12] . Companies like Charles River (a major supplier) had to scramble to breed more monkeys domestically and divert supply from other countries. This shortage has directly slowed some discovery projects that rely on NHP models (like certain neuroscience or vaccine studies) – either making them prohibitively expensive or causing long delays in scheduling. The monkey shortage is a niche example, but it underscores how fragile parts of the R&D supply chain are. In response, the NIH and others are investing in expanding domestic animal research facilities, and many labs have refined their study designs to use fewer animals or alternative models where possible.

4. Globalization Risks and “Onshoring” Dilemmas: The life sciences supply chain is global: reagents from China, APIs from India, instruments from Germany, etc. This globalization keeps costs down but creates dependencies. Over 70% of active pharmaceutical ingredients used in U.S. medicines are manufactured abroad (often in just a few countries). The pandemic, plus geopolitical tensions, brought calls to “onshore” or diversify these supply chains for national security. In practice, shifting supply chains is slow. By 2025, there’s been limited relocation – some API manufacturing projects started in the U.S. with government incentives, and a few critical reagent supply lines are being established domestically, but these represent a small fraction of overall volume. Companies are reluctant to move production from low-cost bases without clear economic incentive, and building new facilities takes years. Instead, what we see is companies increasing inventory buffers (stockpiling critical supplies) and qualifying secondary suppliers in different countries as contingency. For instance, a biotech might ensure it has a European source for a key chemical as backup to its Chinese source. However, maintaining large inventories ties up capital, which not everyone can afford in this tight environment. Another wrinkle: export controls and trade policies. The U.S. government has considered measures to secure pharma supply chains, but there’s also the risk of foreign governments restricting exports (like China did with NHPs). If, say, a political dispute led to China banning export of a certain reagent or raw material, many U.S. labs would be caught flat-footed. The bottom line is that as of 2025, the supply chain remains global and somewhat brittle. Vendors and their customers are more aware of the risks now, but mitigating them fully is expensive and not yet achieved. Thus, while not front-page news, the possibility of supply shocks is a background worry for R&D planners.

Implications: The health of the vendor/supplier ecosystem directly affects research productivity. Right now, that health is shaky. Well-established suppliers will survive, though with possibly reduced product lines and slower innovation as they cut costs. Some smaller suppliers might not make it, especially if they were reliant on a vibrant startup customer base. For R&D teams, careful vendor management is crucial: multi-sourcing critical supplies, keeping communication open about vendors’ stock or financial stability, and perhaps locking in long-term supply agreements for key items are wise moves. We’ve seen some big pharmas actually provide upfront payments or volume guarantees to suppliers for important materials to ensure continuity (a practice reminiscent of how chip companies dealt with suppliers after chip shortages).

From a strategic viewpoint, companies could consider bringing in-house certain critical capabilities if a vendor looks unstable – for example, building an internal chemistry synthesis team if a trusted CRO partner is faltering. However, this goes against the general trend of outsourcing and might be a temporary safety measure. On the opportunity side: challenges for incumbents can be openings for new entrants. If a big vendor stops supporting a certain older instrument line, a smaller company might pop up to service those customers. Some agile service providers are finding niche demand (like specialized analysis that biotechs used to outsource abroad but now prefer locally). Still, overall the ecosystem won’t truly rebound until its customer base (the biotechs and pharma) ramp up discovery spending again. In the meantime, expect the support sector to continue consolidating and focusing on core profitable offerings, with less tolerance for speculative or fringe products.

CASE STUDY

Logistics as a Strategy

kbDNA Inc.

Domestic Expansion for Supply Chain Resilience

In 2024, kbDNA established a new logistics center in North Carolina, a move shaped by the disruptions experienced during the pandemic era. This center was developed not just to increase capacity, but as an adjustment to a shifting supply chain environment. Located in North Carolina, the hub enables more competitive material movement and storage, allows for quicker turnaround, and offers increased flexibility for customers. The initiative also aims to strengthen preparedness for a range of possible future disruptions, including shipping delays, regulatory changes, or market shocks.

Impact on the Supply Chain

Relative to organizations that continue to rely on international shipping and third-party warehousing, kbDNA’s operational model demonstrates increased robustness. Partner laboratories have reported reduced delays and more reliable access to critical supplies. In today’s environment, where timing and reliability are paramount, these operational changes provide a tangible advantage.

Lessons Learned and Industry Implications

The experience of the past five years underscores that local capacity and logistics preparedness have become essential, rather than optional. Investments in domestic infrastructure address clear industry challenges, and position organizations—including kbDNA and its clients—to better manage future uncertainties.

Broader Context for Discovery-Stage Research

No discovery-stage research can progress without a vast array of vendors and suppliers—from lab reagent makers and instrument manufacturers to contract research and manufacturing organizations (CROs/CMOs)—that provide the tools, materials, and services fueling experiments. This support ecosystem has been grappling with its own challenges in the current climate.

Conclusion

Underreported Realities

In wrapping up, it’s worth spotlighting a few objective realities that often go underreported amid the industry’s announcements and narratives :

The Reproducibility Crisis is Stalling Innovation: The “dirty secret” in biomedical science is that a significant fraction of published research cannot be replicated reliably. This isn’t just an academic worry – it directly affects drug discovery success rates. Pharma insiders have noted that 50–70% of external academic findings they attempt to validate do not hold up [1] . That means a lot of time and money chasing false leads. It contributes to the massive attrition in pharma pipelines and is a hidden efficiency drain on the entire sector. Efforts are underway (e.g., journals pushing for better methodology, NIH encouraging rigorous study design) but progress is slow. Until this is addressed, we’re effectively wasting a big chunk of discovery effort on results that won’t translate. It’s a hard problem – part of the nature of exploratory research – but awareness is the first step. Currently, the reproducibility issue doesn’t grab headlines like a new AI discovery does, yet it might be one of the biggest drags on R&D productivity.

Human Capital and Morale: Behind every discovery project are scientists – and they’ve been through a rough time. The boom-and-bust has led to job insecurity in biotech (15k+ layoffs in 2024 [2] means many scientists out of work or uncertain) and intense competition for funding in academia (NIH grant success rates are low, often ~20% or less). The result can be brain drain: talented young researchers may choose other careers (tech, finance, etc.) or if they stay, morale can dip under constant stress. We risk losing a generation of life scientists if the field is seen as too unstable. This rarely gets discussed in earnings calls or investor meetings. Also, diversity initiatives and efforts to bring in fresh talent might take a backseat when companies are in survival mode. A long-term implication is that less human talent enters or stays in the field, which could slow innovation (fewer bright minds working on the problems). Anecdotally, graduate enrollments in some biomedical PhD programs have dipped slightly post-pandemic, and some biotech hubs see folks moving to sectors perceived as more stable.

Geographical Shifts in Innovation: While this report focuses on North America, it’s notable that other regions have been ramping up investment in life sciences. China , for instance, has heavily invested in biotech R&D and startup funding (with government support) and has built a robust domestic biotech sector. Europe, despite some funding woes, still produces strong science and has government initiatives for strategic areas (like the EU’s programs in advanced medicines, and country-level funds in the UK, Germany, etc.). If North America’s ecosystem slows, there’s a chance that some innovation will shift to these other regions. We already see global pharma sourcing innovation from China (e.g., Merck & Co. licensing a cancer drug from a Chinese biotech). North America has long been the powerhouse of biotech, but leadership isn’t a birthright; it’s maintained by continuous investment. A harsh reality is that the U.S. can’t get complacent – other countries learned from our success and are vying for their share of the pie. The extent of this shift is debated, but it’s an undercurrent – e.g., venture funding in Asia-Pacific hasn’t dropped as much as in the U.S. in some recent quarters, and talent flows are becoming more global.

Patient Impact – the Lagging Indicator: Ultimately, the success or failure of discovery-stage research is measured in new solutions for patients. A sobering reality is that despite all the scientific advances in the last decade, improvements in many patient outcomes have been incremental. For example, cancer mortality has been falling, but much of that is attributable to reductions in smoking and some earlier detection, not just new drugs. We have cutting-edge CAR-T cell therapies for cancer, but they reach a tiny fraction of patients because of cost and complexity. There are still no approved disease-modifying drugs for conditions like Alzheimer’s (aside from some very recently approved amyloid-targeting antibodies with debated effectiveness). Antibiotic resistance is rising, yet no truly novel antibiotic classes have been discovered in decades. These gaps are not for lack of scientific knowledge – we know a lot about these problems – but because translating knowledge into widespread clinical impact is slow and hard. Some of this is inherent, but some is the byproduct of the underreported issues above (lack of diagnostics, etc.). So while press releases celebrate a new pathway discovery or a mouse cure for X, the translation to human benefit is often 10-15 years out, if it happens at all. This is a harsh truth that the industry doesn’t like to dwell on because it sounds pessimistic, but recognizing it should galvanize efforts to improve the pipeline efficiency. It also highlights the importance of sustaining discovery research even when immediate outputs aren’t obvious, because today’s basic science is often the seed for tomorrow’s breakthrough – but if we chop all the seedlings in hard times, we reap nothing later.

Conclusion: The discovery-stage life sciences sector in North America is at a pivotal juncture. On one hand, the scientific prospects have never been more exciting – we have tools (like CRISPR, AI, single-cell omics) that were unimaginable a generation ago, and we understand biology at a depth that should allow unprecedented interventions. On the other hand, the real-world environment to nurture these prospects has rarely been more challenging – funding is tight, focus has narrowed, support systems are strained, and the “easy wins” in biomedicine (low-hanging fruit) have mostly been picked over the past decades, leaving tougher problems ahead.

The current state can be summarized as one of cautious advancement under duress. Progress is still being made – important drug targets are being identified, promising drug candidates are in pipelines, and some nifty diagnostics are emerging – but it’s often despite the headwinds, not because conditions are favorable. Many in the industry have adopted a sober, heads-down approach: do the best science you can with what you have, and cut anything that doesn’t show promise. There’s less tolerance for blue-sky exploration, at least for now.

If the trends in funding and risk-aversion continue unchecked, there is a concern about a slowdown in the breakthrough pipeline later in this decade. The full impact of today’s cuts might only be felt years from now, when the absence of early-stage projects means fewer new products. It’s like skipping planting seeds for a season – you don’t notice immediately, but later you have less to harvest. Some experts worry about a 5-year “innovation gap” in the early 2030s as a result of 2022–25 being lean years for starting new programs (especially in certain therapeutic areas).

However, history in biotech is cyclical. The optimistic view is that the incredible pace of scientific discovery will eventually force a way forward – big new ideas will come that investors can’t ignore, and capital will flow again. There are already signs of life: for instance, the excitement in obesity therapeutics (with multiple companies now investing in next-gen metabolic therapies) shows that a single clear success (the drug semaglutide in this case) can reinvigorate a field. Similarly, the recent advances in mRNA technology (spurred by vaccines) are now being applied to cancer and other diseases with renewed vigor.

In keeping with an unfiltered perspective, though, we must acknowledge the systemic issues that need addressing: the industry’s R&D engine needs some fixing and re-fueling. This includes rethinking funding models for early research (perhaps more public-private partnerships), improving how we validate academic findings (to spend less time on dead ends), building more resilient supply chains, and fostering talent even during downturns so that when the cycle turns up, we haven’t lost capacity.

Ultimately, discovery-stage research is where the future of medicine is born. At present, it is under strain but not broken . The resilience of the scientific community and the collaborations across sectors are keeping the flame of innovation alive even in tough times. The objective reality is sobering, but it should serve as a call to action: to reinvest and double down on the foundational research that leads to tomorrow’s cures and diagnostics. If stakeholders heed this call – if investors look beyond the next quarter, if governments view R&D as infrastructure, if companies balance short-term needs with long-term vision – then the current storm can be ridden out and the sector can emerge stronger. In the meantime, the discovery engine continues chugging, albeit at a slower pace and with fewer cars, driven by the dedication of scientists who, even in harsh conditions, persist in the quest for knowledge and solutions. The truth may be harsh, but recognizing it is the first step toward ensuring that the next status report in a few years can report not just harsh realities, but how they were overcome.

Biosimilars: Navigating the Landscape for Future Therapeutics

Sat, 17 May 2025 22:20:49 GMT

Abstract:

Biosimilars, a burgeoning field within the pharmaceutical industry, hold immense promise in revolutionizing the accessibility and affordability of biologic medicines. This article explores the complexities of biosimilars, including their development process, regulatory challenges, economic impact, and future prospects. By delving into these intricacies, we aim to provide valuable insights for commercial biopharmaceutical and academia researchers navigating the dynamic landscape of biosimilars.

Introduction:

In the rapidly evolving landscape of pharmaceuticals, biosimilars stand out as a key player poised to transform the availability and affordability of biologic medications. A biosimilar medication is a biological product highly similar to an already approved biologic drug, also known as the reference product. Biosimilars hold significant importance in healthcare, offering a potential solution to the rising costs associated with biologic therapies. By fostering competition and expanding patient access, biosimilars have the capacity to reshape the treatment paradigm for various diseases, including cancer, autoimmune disorders, and chronic conditions.

What is a Biosimilar Medication?

Biosimilars are biologic drugs that are highly similar to their reference products, with no clinically meaningful differences in terms of safety, purity, and potency. Unlike generic drugs, which are chemically synthesized and exact copies of their branded counterparts, biosimilars are produced through living organisms and exhibit inherent variability due to their complex molecular structure. Despite this variability, biosimilars undergo rigorous analytical and clinical testing to demonstrate similarity to the reference product, ensuring their efficacy and safety.

Understanding Biosimilars

The development of biosimilars requires a deep understanding of the underlying science behind biologic drugs and their replication. Unlike small-molecule generic drugs, which can be precisely replicated, biosimilars face challenges due to the complexity of biologic molecules and their manufacturing processes. Biosimilars must demonstrate similarity in physicochemical characteristics, efficacy, and safety through comprehensive comparative studies, including analytical characterization and clinical trials. By leveraging advanced biotechnology techniques, developers strive to achieve biosimilarity while maintaining therapeutic equivalence with the reference product.

Development Process of Biosimilars

The journey from conceptualization to commercialization of biosimilars involves navigating a complex development process. This process encompasses several stages:

Molecular Characterization : The development begins with comprehensive analysis of the reference product's molecular structure to identify critical attributes.
Non-clinical Studies : Preclinical studies evaluate the pharmacodynamics, pharmacokinetics, and toxicology of the biosimilar candidate, establishing its safety profile.
Clinical Trials : Clinical trials are conducted to demonstrate equivalence in safety, efficacy, and immunogenicity compared to the reference product
Analytical Characterization : Extensive analytical testing is conducted to assess physicochemical properties, purity, and potency, ensuring biosimilarity
Comparative Studies : Comparative clinical studies are conducted to establish similarity in efficacy and safety profiles between the biosimilar and reference product

The development of biosimilars is fraught with challenges, including variability in manufacturing processes, ensuring comparability, and addressing immunogenicity concerns. These challenges can be overcome through rigorous analytical characterization, robust clinical trial design, and collaboration with regulatory authorities to establish appropriate standards and guidelines. Additionally, fostering transparency and communication with healthcare providers and patients is essential to build trust and confidence in biosimilar therapies.

Economic Impact of Biosimilars

Biosimilars have the potential to significantly impact healthcare costs by fostering competition and expanding market access. Studies have shown that the introduction of biosimilars can lead to substantial cost savings, making biologic therapies more affordable for patients and healthcare systems.

In Europe, the introduction of biosimilars for infliximab resulted in significant cost savings for healthcare systems and patients, particularly in the treatment of autoimmune diseases.
Similarly, in the United States, the availability of biosimilars for filgrastim led to reduced healthcare expenditures and increased access to treatment for patients with cancer undergoing chemotherapy.

These case studies illustrate the market impact of biosimilars and their role in driving down prices, increasing treatment accessibility, and promoting sustainability in healthcare systems. As biosimilar adoption continues to grow, their economic implications will become increasingly pronounced, reshaping the pharmaceutical market dynamics.

Challenges in the Biosimilars Market

Despite their potential benefits, biosimilars face several challenges in the market landscape. Intellectual property issues and patent litigation can impede biosimilar market entry, delaying competition and limiting patient access. Moreover, market acceptance varies among healthcare providers and patients, influenced by factors such as perception of efficacy, safety concerns, and brand loyalty. Addressing these challenges requires collaboration among stakeholders to foster education, promote trust, and enhance awareness of biosimilars' value proposition.

Opportunities & Future Prospects

The growing role of biosimilars in global healthcare systems presents numerous opportunities for innovation and access. Future trends in biosimilar development, including the emergence of biosimilars for complex biologics and personalized therapies, hold promise for expanding treatment options and improving patient outcomes. Strategies for successful biosimilar implementation encompass regulatory compliance, market access initiatives, and stakeholder engagement. By embracing these opportunities and overcoming challenges, biosimilars have the potential to revolutionize healthcare delivery and enhance patient care worldwide.

Conclusion

In conclusion, biosimilars represent a transformative force in the pharmaceutical landscape, offering a pathway to increased accessibility and affordability of biologic therapies. By navigating the complexities of biosimilar development, regulatory approval, and market acceptance, researchers and stakeholders can unlock the full potential of biosimilars to address unmet medical needs and improve patient outcomes. As we embark on this journey towards a future shaped by biosimilars, collaboration, innovation, and patient-centricity will be essential in realizing their promise. Embracing biosimilars as a catalyst for change, we pave the way for a more equitable and sustainable healthcare ecosystem.

Biosimilars and kbDNA

kbDNA offers a competitive library of biosimilars , and the expertise needed to navigate the world of biosimilars. Contact us today if you need help finding a particular item, if you have questions, or to tell us what specific parameters you’re looking for in your biosimilars. You can also request a spec sheet for any of our biosimilars.

For our expert help with custom tailored reagents , oligo-nucleotide synthesis services , or to further discuss the role of biosimilars in your research and within kbDNA, contact us today . Let's push the boundaries of scientific exploration together.

JPM 52:25

Tue, 07 Jan 2025 04:03:29 GMT

52 Notable JPM Deals of the Last Decade

+ Discover which companies to watch going into 2025.

Since its inception in 1983, the JP Morgan Biotech Conference has grown to become one of the most significant events in the biotechnology and pharmaceutical industries. Initially a modest gathering aimed at fostering connections and discussions among biotech executives and investors, the conference has evolved over the decades into a highly anticipated global forum. Each January, industry leaders, innovative startups, and visionary investors converge in San Francisco to discuss the latest advancements, trends, and deals shaping the future of biotechnology.

The conference's influence is undeniable, with countless partnerships and groundbreaking deals forged in its bustling meeting rooms and corridors. What began as a small-scale networking opportunity has transformed into a powerhouse of innovation, driving the sector forward with each passing year.

In this article, we delve into the 52 Most Notable JPM Deals in the past 10 years, highlighting the transformative agreements that have emerged from this prestigious conference. Join us as we explore the pivotal transactions that have reshaped the biotech landscape and download our comprehensive report to discover the companies poised to lead the industry into 2025.

JPM | 2015-2017

2015 and 2017, delivered key transactions that continue to reshape the industry today. Those deals included Pfizer's $17 billion acquisition of Hospira, AbbVie's $21 billion purchase of Pharmacyclics and $10.2 billion buyout of Stemcentrx, and Shire's $32 billion acquisition of Baxalta. Other significant deals were Abbott's $25 billion acquisition of St. Jude Medical, Johnson & Johnson's $30 billion purchase of Actelion, Gilead Sciences' $11.9 billion acquisition of Kite Pharma, Thermo Fisher Scientific's $7.2 billion buyout of Patheon, and Becton Dickinson's $24 billion acquisition of C.R. Bard. These moves underscore the industry's dynamic and innovative attitude toward multidisciplinary development during this period.

JPM | 2018-2020

Between 2018 and 2020, the JP Morgan Biotech Conference also saw transformative deals in the form of big names on both sides of the transaction. This period is highlighted by the dynamic duo; Takeda's acquisition of Shire and Bristol-Myers Squibb's purchase of Celgene. Significant transactions also involved Boston Scientific, GlaxoSmithKline, and Roche, highlighting advancements in rare disease treatments, immuno-oncology, and cardiovascular therapies.

JPM | 2021-2023

2021 signifies the start of post-covid JPM and continues through 2023, where the JP Morgan Conference saw significantly more deals north of $1 billion range. Notable transactions featured; Merck's $11.5 billion acquisition of Acceleron Pharma and Pfizer's $6.7 billion purchase of Arena Pharmaceuticals. Amgen acquired Five Prime Therapeutics for $1.9 billion and later Horizon Therapeutics for $28 billion, enhancing its portfolio with rare disease treatments. Worth noting, Intellia and Editas partnered on CRISPR technology to develop curative therapies. In turn, reinforcing the technologys direction since recent conception.

JPM | 2024

In 2024, we saw a mix of everything reach the deal floor. However, it’s better described as an expensive year to purchase pipelines... Johnson & Johnson notably acquired Ambrx for $2 billion, focusing on prostate cancer treatments. Merck enhanced its oncology pipeline by acquiring Harpoon Therapeutics for $680 million. GSK expanded its respiratory biologics portfolio with Aiolos Bio for $1 billion upfront, plus $400 million in potential milestones. Novartis addressed autoimmune indications through its $425 million acquisition of Calypso Biotech, and Bristol-Myers Squibb strengthened its cardiovascular franchise with the $13.1 billion acquisition of MyoKardia. 2024 managed to further highlight the conference's ongoing influence in it’s capacity to deliver a more diverse range of buying and selling.

JPM | 2025

The JPM Healthcare Conference has long been the stage for transformative deals that shape the biotech industry's future. As the 2025 conference approaches, the stakes are higher than ever, with new trends, emerging innovations, and potential acquisitions on the horizon.

Our exclusive prospectus dives deep into these pivotal developments, offering insights to help you navigate the dynamic biotech landscape and capitalize on upcoming opportunities.

Don't miss your chance to get ahead of this year's conference

Download kbDNA's 2025 JPM Conference Prospectus today

FLAG Tag: A Comprehensive Overview for Biopharmaceutical Research

Fri, 25 Oct 2024 18:03:28 GMT

Abstract:

The FLAG tag (DYKDDDDK) is an epitope tag widely utilized in biopharmaceutical research for protein purification, detection, and functional analysis. This article provides an in-depth examination of FLAG tag technology, its advantages, limitations, and diverse applications. Additionally, it explores current research trends and future directions in FLAG tag technology, making it a pivotal tool in advancing drug discovery and development.

Introduction:

What is a FLAG Tag?

The FLAG tag is a short peptide sequence (DYKDDDDK) engineered for tagging proteins to facilitate their detection and purification. It was first introduced in the late 1980s and has since become one of the most commonly used tags in protein research. The sequence is specifically recognized by anti-FLAG antibodies, allowing researchers to isolate and study proteins in a variety of experimental contexts.

Explore how our advanced FLAG tag solutions can enhance your protein research and streamline biopharmaceutical development. Contact us to learn more .

Origin and Development

The FLAG tag was developed as a synthetic peptide tag to address the need for a highly specific, yet versatile tool in protein research. Unlike tags derived from naturally occurring proteins (e.g., Myc-tag or HA-tag), the tag was designed to be hydrophilic and minimally intrusive, ensuring that it does not significantly alter the function or structure of the tagged protein.

Advantages and Limitations

The primary advantage of the FLAG tag lies in its high specificity and the availability of highly selective antibodies, which minimize background noise in assays. However, one limitation is its potential to interfere with protein function, particularly when fused at the N- or C-terminus of certain proteins. Additionally, the tag’s size and charge may impact the overall stability of the protein.

Applications in Bio-pharmaceutical Research

The FLAG tag’s applications are vast, ranging from protein purification and detection to drug discovery. It is particularly valued for its ability to facilitate the study of protein-protein interactions and the sub-cellular localization of proteins, making it an indispensable tool in both basic and applied bio-pharmaceutical research.

FLAG Tag Technology

Methods for Attaching FLAG Tag to Proteins

Recombinant DNA Technology : FLAG tags are commonly attached to proteins via recombinant DNA techniques, where the FLAG sequence is genetically engineered into the protein-coding region. This allows for the expression of FLAG-tagged proteins in various host systems, including bacteria, yeast, and mammalian cells.
Post-Translational Modifications : In some cases, they are added post-translationally through chemical conjugation, allowing for more controlled and precise tagging in specific protein applications.
Chemical Conjugation : Chemical methods are also employed to attach FLAG tags to proteins, particularly when recombinant expression is not feasible. These methods include the use of cross-linking agents or enzymatic ligation to attach the FLAG peptide to the protein of interest.

Properties of FLAG Tag

Size and Flexibility : The FLAG tag consists of eight amino acids, making it small enough to minimize interference with protein function while still being easily detectable by antibodies.
Immunogenicity : They are designed to be immunogenic enough for antibody recognition without eliciting a strong immune response that could confound experimental results.
Stability and Compatibility : Tags are stable under a variety of conditions, making them compatible with a wide range of experimental protocols, including those involving harsh purification conditions.
Detection Sensitivity : FLAG-tagged proteins can be detected with high sensitivity using monoclonal antibodies specific to the FLAG epitope, making them ideal for applications requiring precise quantification and localization.

Comparisons with Other Protein Tags

His-tag : The His-tag is known for its simplicity and effectiveness in metal affinity chromatography. However, the FLAG tag is preferred in cases where higher specificity and lower background are required.
HA-tag : While both HA and FLAG tags are epitope tags recognized by specific antibodies, the tag is more versatile due to its smaller size and lower likelihood of disrupting protein function.
GST-tag : GST-tags are larger and often used for protein purification purposes. FLAG tags, in contrast, are better suited for applications requiring minimal interference with the target protein’s structure or function.

Applications of FLAG Tag

Protein Purification

Affinity Chromatography : They are widely used in affinity chromatography for the purification of recombinant proteins. The high specificity of anti-FLAG antibodies ensures that the target protein is purified with minimal contamination from other cellular components.
Immunoprecipitation : Tags facilitate the immunoprecipitation of proteins and protein complexes from cell lysates, allowing for the study of protein-protein interactions in a native environment.
Magnetic Bead Purification : Magnetic beads conjugated with anti-FLAG antibodies enable rapid and efficient purification of FLAG-tagged proteins, particularly in high-throughput screening applications.

Protein Detection and Localization

Western Blotting : FLAG tags are frequently used in Western blotting to detect specific proteins in complex mixtures. The tag’s high specificity ensures clear and accurate results.
Immunofluorescence Microscopy : Tags are valuable tools in immunofluorescence microscopy, where they visualize the localization of proteins within cells.
Flow Cytometry : In flow cytometry, they allow for the precise quantification of protein expression on the cell surface or within intracellular compartments.
ELISA : FLAG-tagged proteins can be quantified in ELISA assays, offering a robust method for detecting and measuring proteins in various biological samples.

Functional Analysis of Proteins

Protein-Protein Interaction Studies : They are used to investigate protein-protein interactions through co-immunoprecipitation, providing insights into the molecular mechanisms underlying cellular processes.
Subcellular Localization : Tags aid in determining the subcellular localization of proteins, which is critical for understanding protein function and dynamics within cells.
Protein Stability and Degradation : The use of FLAG tags in studies of protein stability and degradation pathways helps elucidate the factors that regulate protein turnover in cells.

Drug Discovery and Development

Identifying and Characterizing Drug Targets : FLAG tags are instrumental in the identification and characterization of drug targets, particularly in high-throughput screening assays.
Developing Targeted Therapies : Tags facilitate the development of targeted therapies by enabling the precise identification and quantification of therapeutic targets.
Monitoring Drug Efficacy and Safety : They are used to monitor the efficacy and safety of drugs by tracking the expression and activity of drug targets in cellular and animal models.

Current Research and Future Directions

Advancements in FLAG Tag Technology

Improved Detection Sensitivity : Recent developments have focused on enhancing the detection sensitivity of FLAG tags, making it possible to detect even low-abundance proteins with high accuracy.
Reduced Background Interference : Innovations in antibody design and purification protocols have significantly reduced background interference, improving the overall reliability of FLAG tag-based assays.
Multi-Color Imaging : The development of multi-color imaging techniques incorporating FLAG tags has enabled the simultaneous visualization of multiple proteins within a single sample, advancing our understanding of complex biological systems.
Development of New FLAG-Specific Antibodies : Ongoing research is exploring the creation of novel FLAG-specific antibodies with enhanced affinity and specificity, further expanding the utility of FLAG tag technology in bio-pharmaceutical research.

Emerging Applications of FLAG Tag

High-Throughput Screening : They are increasingly being used in high-throughput screening platforms to identify potential drug candidates and therapeutic targets.
Protein Structure Determination : Tags aid in the determination of protein structures through techniques such as X-ray crystallography and cryo-electron microscopy.
Gene Therapy : FLAG tags are being explored as tools in gene therapy, where they can be used to track the expression and localization of therapeutic proteins.
Personalized Medicine : In personalized medicine, they have the potential to be used in the development of individualized therapies by enabling the precise targeting and monitoring of specific proteins.

Future Outlook for FLAG Tag Technology

As technology continues to evolve, it is expected to play an increasingly prominent role in advancing drug discovery, personalized medicine, and other cutting-edge fields. The ongoing development of new antibodies, enhanced detection methods, and innovative applications will further solidify the FLAG tag’s position as a key tool in bio-pharmaceutical research.

Impact on Bio-pharmaceutical Research and Development

The FLAG tag’s impact on biopharmaceutical research cannot be overstated. By enabling precise protein studies, it has accelerated the pace of discovery and innovation, paving the way for new therapies and treatments that will ultimately benefit patients worldwide.

Researchers and industry professionals are encouraged to explore the full potential of FLAG tag technology in their work. Whether you are involved in basic research, drug development, or clinical applications, the tag offers a powerful tool for advancing your scientific goals.

Conclusion

The FLAG tag has proven to be an invaluable tool in bio-pharmaceutical research, offering exceptional versatility for protein purification, detection, and functional analysis. Its small size, high specificity, and compatibility with a wide range of experimental techniques have made it a staple in both basic and applied sciences.

As research advances, the ongoing improvements in detection methods, antibody development, and novel applications will continue to expand the utility of FLAG tag technology. From drug discovery to gene therapy and personalized medicine, the FLAG tag’s ability to enhance protein research will remain central to innovation in bio-pharmaceuticals.

With its robust and flexible applications, the FLAG tag will continue to play a critical role in driving discoveries that impact therapeutic development and improve patient outcomes across a variety of fields.

Explore kbDNA’s custom-tailored reagent libraries or our assay kits , and let us know your specific experimental needs by inquiring. Interested in gene synthesis? Inquire with us or submit a project .

Advancing With Peptide Synthesis

Wed, 02 Oct 2024 22:22:51 GMT

A Comprehensive Overview of Growing Demand and Manufacturing Solutions

Introduction :

In the ever-evolving landscape of life sciences and biotechnology, the synthesis of peptides and proteins has emerged as a cornerstone for advancements in medicine, research, and therapeutic development. Peptides, short chains of amino acids, serve as essential tools in probing protein functions, designing novel drugs, and developing vaccines. With the increasing complexity of biological research and the rising need for precision in therapeutic interventions, the demand for peptide synthesis services has witnessed exponential growth. This white paper delves into the current trends, challenges, and future directions of peptide synthesis, emphasizing the critical importance of developing novel hybrid manufacturing solutions to meet these demands.

Peptide and Protein Production:

Peptide and protein production refers to the methods and processes used to synthesize these biomolecules, which are vital for various applications ranging from pharmaceuticals to nutritional supplements. Understanding the intricacies of peptide synthesis, including both chemical and biological methods, is crucial for advancing our capabilities in biotechnology.

Explore how our Peptide Synthesis solutions can enhance your research and streamline discovery.

Solid-Phase Peptide Synthesis (SPPS) :

Solid-phase peptide synthesis (SPPS) is a dominant method in peptide manufacturing, wherein the peptide chain is anchored to a solid support, facilitating easier purification and assembly. This method allows for the creation of complex peptide sequences with high precision, akin to building a Lego set where each block is an amino acid. SPPS typically employs Fmoc (9-fluorenylmethyloxycarbonyl) or Boc (tert-butyloxycarbonyl) chemistry to protect amino acid residues during synthesis, ensuring accurate sequence assembly.

Advantages and Challenges of Chemical Synthesis

Chemical synthesis offers flexibility in creating complex peptide sequences that are often challenging for biological methods. It allows for customization and precise control over the peptide’s composition and sequence. However, challenges such as high material costs, scale-up difficulties, and solvent waste must be addressed to optimize the process. Additionally, the synthesis of long peptides or those with intricate secondary structures can be problematic due to incomplete coupling reactions and aggregation issues.

Liquid-Phase Peptide Synthesis (LPPS) :

Liquid-phase peptide synthesis (LPPS) is another important method that involves the synthesis of peptides in a solution rather than on a solid support. LPPS is particularly advantageous for synthesizing longer peptide chains and peptides that are difficult to produce using SPPS.

Advantages of Liquid-Phase Synthesis

LPPS allows for more efficient synthesis of long peptide chains and reduces problems associated with incomplete reactions often encountered in solid-phase synthesis. The method provides greater flexibility in monitoring reaction progress and optimizing conditions, leading to higher purity and yield. Additionally, LPPS can be scaled up more easily, making it suitable for commercial production.

Challenges of Liquid-Phase Synthesis

Despite its advantages, LPPS faces challenges such as the need for extensive purification steps to remove by-products and the requirement for large volumes of solvents, which can increase costs and environmental impact. Furthermore, handling and manipulating peptides in a liquid phase can be more complex and time-consuming compared to solid-phase methods.

Recombinant Peptide Synthesis :

Recombinant peptide synthesis involves the production of peptides using genetically engineered organisms such as bacteria, yeast, or mammalian cells. This method is particularly useful for producing large quantities of peptides and allows for complex post-translational modifications that enhance peptide functionality.

Advantages of Recombinant-Phase Synthesis

Recombinant synthesis is cost-effective for large-scale production and supports the incorporation of complex tertiary structures and post-translational modifications. It also aligns with sustainable manufacturing principles by reducing chemical waste and energy consumption. Techniques such as codon optimization and the use of strong promoters can significantly enhance peptide yields in recombinant systems.

Challenges of Recombinant-Phase Synthesis

Despite its advantages, recombinant synthesis faces challenges such as complex purification needs, potential immunogenicity, lengthy development cycles, and limited ability to accommodate certain chemical modifications. The production of peptides with disulfide bonds or other specific structural requirements may necessitate additional folding and refolding steps, increasing the complexity and cost of the process.

Growing Demand for Peptide Synthesis Services :

The burgeoning field of life science research has led to an increased demand for peptide synthesis services. Peptides are indispensable in biomedical research, drug discovery, and therapeutic development. As our understanding of molecular biology deepens, the necessity for precise and reliable peptide synthesis continues to surge.

Investment in Advanced Technologies

To support the growing demand, it is crucial to invest in state-of-the-art synthesis technologies and methodologies. Advanced techniques such as SPPS and liquid-phase peptide synthesis (LPPS), coupled with rigorous quality control measures, are essential to meet the escalating demands of the scientific community. Innovations in automated synthesis platforms and high-throughput screening methods have significantly enhanced the efficiency and scalability of peptide production.

Hybrid Manufacturing Solutions :

The future of peptide synthesis lies in the development of novel hybrid manufacturing solutions that combine the strengths of both chemical and recombinant methods. These solutions are critical for producing high-quality peptides with the necessary modifications and at the required scales.

Advantages of Hybrid Approaches

Hybrid approaches offer the flexibility and precision of chemical synthesis while leveraging the efficiency and sustainability of recombinant methods. They enable the production of peptides with complex structures and modifications that are challenging to achieve with a single method. For instance, hybrid methods may involve the initial synthesis of a peptide backbone through SPPS or LPPS, followed by the incorporation of complex modifications or large-scale production using recombinant systems.

Challenges and Future Directions

Developing effective hybrid manufacturing solutions requires addressing challenges such as process optimization, scale-up issues, and regulatory compliance. Innovations in synthesis technologies, such as soluble-anchor based Molecular Hiving™ and MCSGP (multi-column solvent gradient purification) for continuous purification, are expected to drive advancements in this area. Additionally, the integration of advanced analytical techniques like mass spectrometry and NMR spectroscopy is essential for ensuring the quality and consistency of the synthesized peptides.

Conclusion :

The demand for peptide synthesis services is poised to grow significantly in the coming years, driven by advancements in life sciences and biotechnology. To meet this demand, the development of novel hybrid manufacturing solutions is essential. By combining the strengths of chemical and recombinant methods, we can create peptides with the desired quality, efficiency, and scale, ultimately benefiting healthcare and scientific research.

References :

Carpino, L. A., & Han, G. Y. (1970). The 9-fluorenylmethoxycarbonyl amino-protecting group. Journal of the American Chemical Society, 92(22), 5748-5749.
Barany, G., & Merrifield, R. B. (1980). Solid-phase peptide synthesis. Journal of the American Chemical Society, 101(10), 2686-2700.
Gill, V. S., et al. (2017). Hybrid approaches to peptide synthesis. Biotechnology Advances, 35(8), 1213-1222.
Fields, G. B., & Noble, R. L. (1990). Solid phase peptide synthesis utilizing 9-fluorenylmethoxycarbonyl amino acids. International Journal of Peptide and Protein Research, 35(3), 161-214.

Ensuring Safe and Secure Nucleic Acid Procurement: A New Framework

Tue, 10 Sep 2024 18:34:25 GMT

kbDNA Leads the Charge

In Compliance and Security

The scientific community is on the brink of a transformative era with the introduction of the new Framework for Nucleic Acid Synthesis Screening. Published by the Fast Track Action Committee on Synthetic Nucleic Acid Procurement Screening under the National Science and Technology Council (NSTC), this comprehensive framework aims to mitigate risks associated with the misuse of synthetic nucleic acids, bolstering biosecurity and ensuring the beneficial use of these critical building blocks of life.

Understanding the New Framework

The framework, mandated by the Executive Order issued in October 2023, focuses on reducing the risks of synthetic nucleic acid misuse and enhancing biosecurity measures. It outlines a unified process for screening purchases of synthetic nucleic acids and bench-top synthesis equipment. The guidance targets providers of synthetic nucleic acids and manufacturers of bench-top nucleic acid synthesis equipment, encouraging them to implement thorough, scalable, and verifiable procurement screening mechanisms. The framework is based on the following principles:

Risk-based : The screening process is tailored to the level of risk posed by the synthetic nucleic acid or the bench-top synthesis equipment, taking into account factors such as the sequence, the quantity, the customer, and the destination.
Transparent : The screening process is clear and consistent, allowing providers and manufacturers to understand their obligations and customers to know what to expect.
Collaborative : The screening process involves coordination and communication among stakeholders, including federal agencies, industry associations, academic institutions, and international partners.
Adaptive : The screening process is flexible and responsive to emerging threats and technological developments, allowing for continuous improvement and innovation.

Key Aspects of the Framework

Attestation of Compliance : Providers and manufacturers must attest to implementing the screening framework, either publicly or directly to customers and federal funding agencies.
Identification of Sequences of Concern (SOCs) : Purchase orders for synthetic nucleic acids must be screened to identify SOCs, ensuring that potentially harmful sequences are flagged and managed appropriately. SOCs are defined as sequences that are known or reasonably suspected to pose a biosecurity risk, such as those that encode for toxins, pathogens, or bioweapons.
Verification of Customer Legitimacy : Customers placing orders for synthetic nucleic acids or benchtop synthesis equipment must undergo legitimacy checks, verifying their institutional affiliations and intended use. Legitimacy checks may include requesting documentation, contacting references, or conducting site visits.
Reporting and Record Retention : Providers and manufacturers are required to report flagged orders and retain records related to the purchase orders for at least three years. Reporting may involve notifying relevant federal agencies, law enforcement authorities, or international organizations. Record retention may include storing information on the sequence, the customer, the screening outcome, and the actions taken.
Cybersecurity Measures : Information security and cybersecurity practices are paramount, especially for SOC databases that hold sensitive biosecurity data. Providers and manufacturers must ensure that their data is protected from unauthorized access, modification, or disclosure, using encryption, authentication, and backup systems.

kbDNA's Commitment to Excellence

At kbDNA (kbdna.com), we are proud to be at the forefront of compliance and security in the procurement of synthetic nucleic acids. Our company has fully embraced the new framework and has already implemented the required data privacy and biosecurity measures to protect our customers and the broader scientific community.

Our Compliance and Attestation

kbDNA has published its attestation of compliance with the new framework, adhering to all six actions outlined for providers and manufacturers. Our commitment includes:

Publicly stating our adherence to the framework on our website.
Screening all purchase orders for SOCs utilizing state-of-the-art algorithms and software systems.
Implementing streamlined customer legitimacy verification processes that validates with efficiency and painlessly for the end-user.
Retaining detailed records of purchase orders and screening activities for at least three years.
Ensuring robust cybersecurity measures to protect sensitive data and customer information.

Leading the Industry

Our proactive approach not only ensures compliance but also positions kbDNA as a leader in the industry. We continuously work with regulatory bodies and follow best practices to ensure that our processes remain secure and effective. By choosing kbDNA, you can be confident that you are partnering with a company that prioritizes safety, security, and innovation.

Conclusion

The new Framework for Nucleic Acid Synthesis Screening marks a significant step forward in safeguarding the use of synthetic nucleic acids. At kbDNA, we are committed to upholding these standards and supporting the scientific community in conducting safe and secure research. Together, we can unlock the potential of synthetic biology while mitigating risks and ensuring a safer future.

Contacts & Resources

Relevant Links

1.Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artiﬁcial Intelligence (“AI EO”)

2. US Framework for Nucleic Acid Synthesis Screening (“Framework”)

If you have any questions or concerns regarding the Privacy Policy Agreement related to our website, please feel free to contact us at the following email, telephone number or mailing address.

Mailing Address:

KbDNA, INC.

125 Cambridgepark Dr. Suite 301.

Cambridge, MA 02140

Contact Info:

Email: compliance@kbDNA.com

Telephone Number: +1 (781) 206-2235

Peptide Preparation Guide (+Protocols)

Ed@kbdna.com (Ed Hamdeh) — Tue, 20 Aug 2024 18:37:01 GMT

Introduction to Synthesized Peptides

Getting your peptide sequence(s) synthesized is only half the battle.

As many researchers learn the hard way, the next major challenge begins upon receipt of the material from your vendor. This is generally referred to as the reagent "Handling" or "Preparation" stage. However, with peptides, it's a much more sensitive process - defined by the consideration of each amino acid in your sequence chain. Additionally, there are no one-size-fits-all methodologies to cover the complete preparation of peptide sequences. Instead, a more empirical approach is necessary, one that enables the development of a protocol specific to your sequence's characteristics and application objectives.

Getting Started

Peptide Preparation can be divided into two categories:

I. Storage

II. Dissolution

In this guide, we will be outlining the steps and considerations in each category to help you build your protocol.

I. Peptide Storage

Lyophilized Peptides:
Upon receipt, lyophilized peptides are stable at room temperature for a few weeks.
For long-term storage, store lyophilized peptides at -20°C or colder, away from bright light.
Storage Considerations:
Peptide stability varies based on sequence and structure.
Store lyophilized peptides at -20°C.
Peptides with methionine, cysteine, or tryptophan residues should be stored in an oxygen-free atmosphere to prevent oxidation.
Dithiothreitol (DTT) can help prevent oxidation.
Avoid moisture exposure, as it reduces long-term stability.
Warm lyophilized peptides to room temperature before opening to minimize moisture uptake.
Peptide Solutions:
Prepare peptide solutions just before use.
If unavoidable, store peptide solutions in aliquots at -20°C (preferably −80°C).
Minimize freeze-thaw cycles.
Use a 0.2 µm filter to remove bacterial contamination if necessary.
Solution Stability:
Peptide solutions have limited shelf life, especially those with cysteine ©, methionine (M), tryptophan (W), asparagine (N), glutamine (Q), or N-terminal glutamic acid (E).
Cys-containing peptides are prone to oxidation, especially in basic conditions.
Some residues (e.g., proline) are susceptible to racemization.
Maintain stock solutions at pH 4-6 to optimize stability.

II. Peptide Dissolution

| Peptide solubility information can be found on the Certificate of Analysis

The solubility of peptides depends on their sequence and overall charge. Typically, more than 70% of peptides can be dissolved in water, while nearly 99% can be dissolved in DMSO. If the solubility information is not available, follow this solubility guideline.

CAUTION: do NOT use the whole batch for solubility test. We recommend 1mg aliquot for solubility testing purposes.

STEP #1 | Calculate Overall Charge

STEP #2 | Determine Proper Dissolution Method

Full Protocols Included

3 Starting Protocols:

For Basic Peptides (charge >0)
For Acidic Peptides (charge <0)
For Neutral (charge = 0) or Highly Hydrophobic Peptides

Download Complete Protocol

What are Polyclonal Antibodies?

Ed@kbdna.com (Ed Hamdeh) — Fri, 12 Jul 2024 20:34:52 GMT

Abstract:

Polyclonal antibodies (pAbs) are invaluable tools in biomedical research, diagnostic applications, and therapeutic interventions. This article provides a comprehensive overview of pAbs, detailing their production, applications, and the scientific principles underlying their use. We explore their advantages over monoclonal antibodies, discuss ethical considerations, and look toward future trends in antibody production.

Introduction:

Polyclonal antibodies (pAbs) are diverse collections of antibodies generated by various B-cell clones within an organism. These antibodies can attach to multiple epitopes on the same antigen, allowing them to interact extensively with their targets. This section contrasts pAbs with monoclonal antibodies and highlights their importance in both research and clinical settings.

Production of Polyclonal Antibodies

Antigen Preparation

The initiation of a successful polyclonal antibody production hinges significantly on the quality and purity of the antigen used. This preparation phase is paramount as even minor contaminants can lead to antibodies that target unwanted elements, reducing the specificity and efficacy of the final product. The process demands rigorous attention to detail—from the selection and design of the antigen to its purification and quantification.

To ensure the highest specificity and yield of the desired antibodies, antigens must be prepared under sterile conditions, meticulously free from endotoxins and other impurities. The antigen's concentration and its physical state (whether soluble or conjugated to a carrier protein) are optimized based on the host species and the intended use of the antibodies.

Furthermore, the molecular integrity of the antigen must be maintained throughout the preparation process to ensure that it remains immunogenic and capable of eliciting an appropriate immune response. Techniques such as dialysis, ultrafiltration, and chromatography are often employed to achieve high levels of purity and concentration, setting the stage for a robust immunization protocol. This strategic preparation is not merely a step in the process—it is the foundation upon which the efficacy and applicability of polyclonal antibodies are built.

kbDNA's innovative approach to polyclonal antibodies combines advanced production technologies and standardized data to accelerate your research and development needs. Contact us to learn more .

Animal Species Selection

Choosing the appropriate animal species for the production of polyclonal antibodies is a decision that significantly impacts the quality and volume of antibodies generated. This choice is influenced by several factors, each critical to the success of the immunization efforts.

Firstly, the amount of antibody required dictates the size of the animal chosen. Larger animals such as goats, sheep, and horses are preferable when high volumes of serum are needed, due to their larger blood volume. For smaller scale productions, rabbits or guinea pigs might be selected.

The phylogenetic relationship between the animal and the source of the antigen is another crucial consideration. A more distant phylogenetic relationship often results in a stronger immune response, as the animal’s immune system is more likely to recognize the antigen as foreign.

Additionally, practical aspects such as the ease of handling the animal, the feasibility of obtaining sufficient blood samples without harming the animal, and previous experiences with the animal species in antibody production settings play pivotal roles in species selection. Regulatory and ethical considerations also influence this choice, as the use of certain animals might be restricted or require special permissions.

Ultimately, the selection of the animal species is not just about availability or cost but about aligning biological compatibility and ethical practices to maximize the efficacy and efficiency of antibody production.

Immunization Protocols

The immunization protocols for generating polyclonal antibodies are meticulously designed to elicit a robust and specific immune response in the chosen host animal. This process involves a detailed strategy encompassing the choice of adjuvants, the method of antigen administration, and the scheduling of immunizations, including any necessary booster injections.

Adjuvants play a crucial role in enhancing the immune response. They act by creating an antigen depot at the injection site, from which the antigen is slowly released, thereby prolonging antigen exposure without the need for frequent injections. The most commonly used adjuvant for this purpose is Freund’s Complete Adjuvant (FCA) for the initial immunization, followed by Freund’s Incomplete Adjuvant (FIA) for booster doses. However, the use of FCA is carefully controlled due to its potential to cause severe inflammation and tissue damage.

The method of antigen delivery is another vital component. Subcutaneous or intramuscular injections are typical, but the route can vary depending on the antigen and the animal. The goal is to optimize the immune response while minimizing discomfort to the animal. For instance, multiple low-volume injections at different sites may be employed to reduce localized reactions and enhance immune stimulation.

Timing is also critical in immunization protocols. Initial immunization is followed by a series of booster injections, scheduled based on the kinetics of the antibody response. These boosters are essential for maintaining high antibody titers over time. Blood samples are periodically taken after the peak response has been achieved to monitor antibody levels, ensuring that the serum is harvested at the optimum time for maximum yield and specificity.

These carefully crafted immunization protocols are essential to producing high-quality polyclonal antibodies, reflecting a balance between effective immune stimulation and ethical animal treatment.

Harvesting and Processing

Harvesting and processing are critical phases in the production of polyclonal antibodies, where the antibodies are collected from the host animal and subsequently purified to meet research and therapeutic standards. This stage must be meticulously planned and executed to ensure the integrity and efficacy of the antibodies.

Harvesting : Once the animal has achieved an optimal immune response, blood is collected. The timing of this collection is crucial—it must coincide with peak antibody titers to maximize yield. The method of blood collection varies with the animal but is generally performed under anesthesia to minimize stress and discomfort. Careful techniques are employed to prevent contamination and ensure the welfare of the animal.

Processing : Following collection, the blood undergoes centrifugation to separate the serum from the blood cells. The serum, rich in antibodies, is then subjected to a series of purification steps. These may include precipitation methods, affinity chromatography, and filtration, each tailored to isolate the desired antibodies while removing unwanted serum components such as other proteins, lipids, and salts.

Quality control is continuous throughout the processing phase. Each batch of antibodies is tested for specific activity and purity. Techniques such as enzyme-linked immunosorbent assay (ELISA), Western blotting, and immunoelectrophoresis verify the specificity and concentration of the antibodies.

Final Preparation : The purified antibodies are often further processed, depending on their intended use. For example, they may be conjugated with fluorescent markers for diagnostic applications or modified to improve stability and shelf life for therapeutic use.

This stage of harvesting and processing not only requires precision and technical expertise but also adherence to ethical guidelines and animal welfare standards. The resulting polyclonal antibodies are characterized by their high specificity and readiness for use in a wide range of applications, from basic research to clinical diagnostics.

Applications of Polyclonal Antibodies

Polyclonal antibodies are versatile tools used across various fields:

Diagnostic Applications

pAbs are indispensable in diagnostics and are utilized extensively for their robustness and ability to recognize multiple epitopes on antigens. This multiplicity allows for enhanced sensitivity and specificity in various diagnostic tests, making polyclonal antibodies a cornerstone in the detection and monitoring of diseases.

In clinical laboratories, these antibodies are key components in serological assays such as ELISA (Enzyme-Linked Immunosorbent Assay), Western blot, and immunofluorescence assays. Each of these applications benefits from the broad reactivity of polyclonal antibodies, which can bind to several epitopes of a target molecule, thereby amplifying the signal and increasing the likelihood of detecting even low-abundance targets.
For instance, in infectious disease diagnostics, polyclonal antibodies are employed to detect pathogens by targeting unique proteins expressed by these organisms. The versatility of polyclonal antibodies is particularly beneficial in rapidly developing and implementing tests for emerging diseases, where timely diagnosis is critical.
Moreover, polyclonal antibodies are utilized in the development of rapid diagnostic kits, which are vital in point-of-care medical settings. These kits rely on the antibodies' ability to quickly and effectively bind to disease markers, providing essential diagnostic information in acute care scenarios.

The diagnostic capability of polyclonal antibodies extends beyond clinical medicine into fields such as environmental monitoring and food safety, where they are used to detect contaminants and pathogens, underscoring their broad applicability and essential role in public health.

Therapeutic Uses

pAbs play a pivotal role in therapeutic applications, demonstrating versatility and efficacy in treating a range of conditions. Their ability to target multiple epitopes on antigens makes them particularly effective in neutralizing pathogens and toxins, a quality that monoclonal antibodies often cannot match due to their specificity for a single epitope.

In clinical settings, polyclonal antibodies are extensively used in passive immunotherapy. This involves administering pre-formed antibodies to an individual to provide immediate protection or treatment against infections, toxins, or other antigens. For example, polyclonal antivenoms are critical in the treatment of venomous bites and stings, effectively neutralizing the complex mixtures of toxins present in venoms.

Another significant therapeutic application of polyclonal antibodies is in the prevention of Rh disease in newborns. Rho(D) immune globulin, a polyclonal antibody product, is administered to Rh-negative mothers to prevent the immune response to Rh-positive fetal blood cells. This intervention has drastically reduced the incidence of newborn hemolytic disease.

Furthermore, polyclonal antibodies are employed in the treatment of certain autoimmune disorders and immune deficiencies, where they help modulate the immune system or provide necessary immune components that the patient’s body cannot produce sufficiently.

The broad applicability and efficacy of polyclonal antibodies in these therapeutic contexts underscore their importance in contemporary medicine, offering solutions where precise and broad targeting of antigens is required to achieve clinical outcomes.

Research Tools

pAbs are essential tools in scientific research, valued for their ability to bind to multiple epitopes of a target antigen. This characteristic enables them to be highly effective in various assays, providing robust and reliable results that are crucial for experimental validation and exploration.

In basic research, polyclonal antibodies are extensively used in immunoprecipitation and Western blotting techniques to identify and quantify proteins. Their broad reactivity ensures that these antibodies can detect proteins even when they undergo post-translational modifications or when only small amounts are present, which might be missed by monoclonal antibodies.

Furthermore, polyclonal antibodies are indispensable in immunohistochemistry (IHC) and immunocytochemistry (ICC) applications, where they help visualize the distribution and localization of target proteins within tissues and cells. The use of these antibodies in IHC and ICC contributes significantly to our understanding of cellular processes and tissue organization, facilitating advancements in fields such as oncology and neurobiology.

Additionally, polyclonal antibodies are pivotal in flow cytometry, where they are used to label different cell populations. This application is crucial for studying immune responses, characterizing heterogeneous cell populations, and diagnosing diseases based on cellular markers.

The versatility and broad sensitivity of pABs make them invaluable in the toolkit of researchers across various disciplines, enabling advancements in our understanding of complex biological systems and diseases.

Advantages and Limitations

There are benefits and drawbacks:

Advantages

High Sensitivity and Specificity : pAbs can bind to multiple epitopes on a single antigen, increasing their sensitivity and ability to detect antigens even when they are present in low concentrations.
Versatility : They are useful in a variety of diagnostic and research applications, including ELISA, Western blotting, and immunohistochemistry, due to their ability to recognize multiple epitopes.
Stronger Signal in Assays : The ability to bind to several epitopes on the same antigen results in a stronger signal amplification in various assays, which enhances their diagnostic utility.
Tolerance to Antigen Variability : They are less likely to be affected by minor changes in the antigen structure, such as post-translational modifications, making them more reliable in complex biological samples.
Cost-Effective Production : The production process of polyclonal antibodies is generally simpler and less expensive than that of monoclonal antibodies.

Limitations

Batch-to-Batch Variability : Since they are derived from different B-cell populations, there can be significant variability between batches, which may affect reproducibility and consistency.
Limited Supply : The quantity of pAbs that can be produced is limited by the lifespan and blood volume of the host animal, which can constrain large-scale production.
Cross-Reactivity : While their ability to bind to multiple epitopes can be advantageous, it can also lead to higher cross-reactivity with non-target antigens, potentially resulting in nonspecific binding and background noise in assays.
Ethical Concerns : The production of polyclonal antibodies involves the immunization of animals, raising ethical concerns about animal welfare and the use of animals in research.
Difficulty in Standardization : The complex nature of mixtures makes standardization challenging, particularly when precise quantification of antibody or antigen is required.

Ethical Considerations and Future Directions

The production of pAbs involves the use of animals, raising ethical concerns.

The use of polyclonal antibodies involves significant ethical considerations, primarily due to the reliance on animal hosts for production. The ethical implications center around animal welfare, including the conditions under which animals are kept, the methods used for immunization and blood collection, and the overall justification for using animals in research.

Ethical Considerations

The production of pAbs requires repeated immunization of animals, which can cause discomfort or pain due to the use of adjuvants and the blood collection process. Ethical frameworks aim to ensure that any distress or pain inflicted is minimized and that procedures are refined to reduce animal suffering. This includes selecting adjuvants that are less likely to cause severe reactions, improving blood collection techniques to reduce stress, and ensuring high standards of animal care throughout the process.

Moreover, the selection of species and the number of animals used are also under ethical scrutiny. Researchers are urged to use the minimum number of animals necessary to achieve scientific objectives and to select species that are likely to experience the least distress. Regulatory bodies and ethical committees closely monitor these aspects, requiring detailed justification and humane treatment plans in research proposals.

Future Directions

Advancements in biotechnology are paving the way for alternative methods that could reduce or eliminate the need for animals in antibody production. One promising area is the development of recombinant polyclonal antibodies, which involve using gene technology to produce these antibodies in vitro. This approach not only alleviates ethical concerns related to animal use but can also enhance antibody consistency and reduce production time.

Another area of development is the use of plant-based systems for antibody production, which could offer a completely animal-free method for generating polyclonal antibodies. These systems have the potential to be scaled up efficiently, making them suitable for large-scale production without compromising animal welfare.

The future of pAbs is likely to involve a combination of improved ethical practices for animal-based production and a gradual shift towards innovative, sustainable, and humane alternatives. These advances not only address ethical concerns but also aim to improve the quality and applicability of polyclonal antibodies in research and therapeutic contexts. As the field progresses, continuous evaluation and adaptation of ethical standards will be essential to align scientific advancements with societal expectations and regulatory requirements.

Summary

Polyclonal antibodies (pAbs) remain essential in the scientific toolkit, offering unmatched versatility and sensitivity for numerous applications. Their continued development and ethical use are crucial for advancing both scientific research and clinical practices.
Curious about the capabilities of polyclonal antibodies? Delve into their multifaceted uses and discover how they can enhance your research or therapeutic strategies. This dynamic field promises continuous advancements and broad possibilities for innovation.

Explore kbDNA’s custom-tailored reagent libraries or our assay kits , and let us know your specific experimental needs by inquiring.
Interested in gene synthesis? Inquire with us or submit a project .

CRISPR-Cas9: Revolutionizing Gene Editing in Biomedical Research

Ed@kbdna.com (Ed Hamdeh) — Wed, 03 Jul 2024 19:24:37 GMT

Abstract:

Introduction:

In the realm of biomedical research and genetic engineering, CRISPR-Cas9 has emerged as a groundbreaking tool , transforming the capabilities of scientists to edit genomes with precision and efficiency. This innovative technology, known for its potential to modify gene expression and create genetically modified organisms (GMOs), has revolutionized the approach towards understanding and curing genetic diseases. By leveraging a simple yet powerful system of guide RNA and the Cas9 enzyme, CRISPR-Cas9 has not only made gene editing more accessible but has also opened new frontiers in functional genomics, showcasing its transformative potential across various fields of science.

The article unfolds the intricate workings of CRISPR-Cas9, starting from the basics of its mechanism to its profound applications in biomedical research. It will delve into the critical role of guide RNA in directing the Cas9 enzyme to specific genomic locations, ensuring high precision in gene editing endeavors. By exploring a spectrum of applications, from disease treatment and gene therapy to its implications in the creation of disease models, this piece aims to provide a comprehensive understanding of CRISPR technology. Furthermore, it addresses the challenges and ethical considerations inherent in its use, reflecting on the ongoing debate surrounding CRISPR gene editing, its safety, and its future prospects. Through this exploration, readers will gain insights into the remarkable versatility and efficiency of CRISPR-Cas9, which stands not only as a tool in functional genomics but also as a beacon of hope for innovative treatments and advancements in the field of genomics and beyond.

Overview of CRISPR-Cas9 Technology

Historical Discovery and Development

CRISPR-Cas9, standing for Clustered Regularly Interspaced Short Palindromic Repeats, was initially discovered as part of a bacterial adaptive immune system, protecting against foreign genetic elements. The foundational work began with the identification of unusual repetitive DNA sequences in Escherichia coli in 1987 by Ishino and his team, though the biological function of these sequences was not understood at the time. The term CRISPR was coined by Francisco Mojica in the 1990s, who recognized these sequences in archaea and later hypothesized their role in microbial immunity.
The transformative potential of CRISPR was realized when Emmanuelle Charpentier and Jennifer Doudna engineered CRISPR to function as a gene-editing tool in 2012, demonstrating its ability to cut DNA at specific locations. This discovery was pivotal, as it allowed for precise modifications of the genome by guiding the Cas9 enzyme to specific DNA sequences.

Mechanism of Action

The CRISPR-Cas9 system functions through a simple yet sophisticated mechanism involving two key components: the Cas9 protein and a piece of guide RNA (gRNA). The Cas9 protein acts as a molecular scissor that makes cuts in the DNA strand. The guide RNA, approximately 20 base pairs long, binds to a complementary DNA sequence adjacent to a Protospacer Adjacent Motif (PAM), which is crucial for the Cas protein to recognize the target DNA site.

Upon binding, the Cas9-gRNA complex unwinds the DNA helix and positions the DNA within the enzyme's active site to introduce a double-stranded break, which can then be repaired by the cell's natural repair machinery, thus allowing for gene editing. This process is highly efficient and precise, making CRISPR-Cas9 a powerful tool for genetic engineering.

Comparison with Other Genome Editing Tools

Prior to the advent of CRISPR-Cas9, the main tools for genome editing were Zinc Finger Nucleases (ZFNs) and Transcription Activator-Like Effector Nucleases (TALENs). These tools also utilized engineered nucleases to make targeted cuts in DNA; however, they were limited by the complexity and cost of protein engineering required to generate new sequence-specific nucleases for each target site.

CRISPR-Cas9 has several advantages over these earlier methods. It is significantly easier to design and implement due to the simplicity of programming the guide RNA. Additionally, CRISPR-Cas9 can target multiple genes simultaneously, a process that is much more cumbersome with ZFNs and TALENs. Furthermore, the efficiency and cost-effectiveness of CRISPR-Cas9 make it accessible for a broader range of scientific applications, from basic research to therapeutic development.

This overview highlights the groundbreaking nature of CRISPR-Cas9 technology, which has revolutionized the field of genetic editing by providing a simpler, more efficient, and versatile tool compared to its predecessors.

Overview of CRISPR-Cas9 Technology

In the CRISPR-Cas9 system, the guide RNA (sgRNA) plays a pivotal role in the gene-editing process. It is essentially the component that ensures precision, guiding the Cas9 enzyme to the correct part of the genome for editing. This section delves into the function and significance of sgRNA, as well as how it is designed and customized for precise targeting.

Function and Significance

The sgRNA is a fusion of CRISPR RNA (crRNA) and trans-activating CRISPR RNA (tracrRNA), combining into a single guide structure that is simpler and more efficient for mammalian genome editing. The crRNA component of sgRNA, typically 18–20 base pairs in length, is crucial as it specifies the target DNA sequence by pairing with it. This pairing is essential for the Cas9 enzyme to recognize and cleave the target DNA at the desired location. The sgRNA's design, particularly the gRNA domain, is critical for the efficacy and specificity of the genome-editing activities performed by Cas9. This has led to the development of multiple bioinformatics tools aimed at the rational design of sgRNAs, focusing on both targeting specificity and potency [17].

Experimental analyses have highlighted the potential for Cas9-based genome editing to result in off-target effects, underscoring the importance of designing sgRNAs with high specificity to minimize unintended genomic modifications. Furthermore, the efficacy of individual sgRNAs can vary significantly, making the design of potent sgRNAs a priority for efficient genome editing and resource utilization.
.

Design and Customization for Precise Targeting

Designing an sgRNA involves selecting a sequence that is complementary to the target gene sequence while ensuring the presence of a Protospacer Adjacent Motif (PAM) at the 3' end of the target DNA sequence. The PAM sequence is crucial for Cas9 cleavage but is not included in the sgRNA sequence. The targeting sequence, which lies upstream of the PAM, is typically 20 nucleotides long and directs Cas9 to cleave approximately three bases upstream of the PAM.

Online tools and algorithms play a significant role in identifying potential PAM sequences and predicting off-target effects, aiding researchers in selecting the most specific crRNA for their applications. Additional design considerations, such as the inclusion of specific nucleotides at certain positions within the sgRNA, have been identified through empirical research to enhance sgRNA efficiency. Despite careful design, sgRNA specificity and activity can be unpredictable, prompting the recommendation to design and test multiple sgRNAs for a given target gene.

The process of synthesizing sgRNAs involves generating a template DNA containing the sgRNA-encoding sequence, followed by in vitro transcription to produce sgRNAs that can be purified and tested for efficiency. This meticulous design and customization process is essential for achieving precise genome editing, minimizing off-target effects, and maximizing the potential of CRISPR-Cas9 technology in research and therapeutic applications.

Applications of CRISPR-Cas9 in Biomedical Research

Genetic Disease Treatment Advancements

CRISPR-Cas9 technology has significantly advanced the treatment of genetic diseases by enabling precise modifications of genetic material. Monogenic diseases, which are linked to over 75,000 genetic variants, affect a large population, with many conditions still lacking effective treatments. CRISPR-Cas tools are extensively used to correct genetic variants, offering hope for treating a wide array of human genetic diseases. Notable applications include treatments for inherited blood disorders like sickle cell disease, β-thalassemia, and hemophilia , eye diseases such as Leber congenital amaurosis and inherited retinal degeneration, and muscular genetic diseases like Duchenne muscular dystrophy. Additionally, CRISPR has been applied to genetic liver diseases, congenital genetic lung diseases including cystic fibrosis, neurological disorders, and genetic deafness.

Innovative studies illustrate the potential of CRISPR-Cas9 in treating genetic disorders effectively. For instance, a study by Wu et al. demonstrated the use of CRISPR/Cas9 to treat cataracts in a mouse model, resulting in successful gene repairs in several mice. Similarly, Schwank et al. utilized CRISPR technology to correct mutations in intestinal stem cells from cystic fibrosis patients, showcasing the practical implications of CRISPR in gene therapy.

Potential in Infectious Disease Management

CRISPR-Cas9 has also emerged as a powerful tool in managing infectious diseases. Its application spans from treating viral infections such as HIV and hepatitis to tackling resistant bacterial and fungal infections. Notably, CRISPR-Cas9 has been employed to inhibit multiple steps of HIV-1 infection effectively. The technology's adaptability extends to other viral infections, where it has shown potential in providing protective immunity against viruses.

The versatility of CRISPR is further highlighted in its use in developing rapid, low-cost diagnostic systems for infectious diseases. For example, the Cas13a protein has been utilized in the Specific High Sensitivity Enzymatic Reporter UnLOCKing (SHERLOCK) system, enhancing the detection of RNA viruses like SARS-CoV-2. This system represents a significant advancement in the rapid diagnosis and management of viral outbreaks.
Furthermore, CRISPR-based strategies are being developed to reprogram human B cells to produce neutralizing antibodies, offering a novel approach to treat and manage infectious diseases effectively. These applications underscore the potential of CRISPR technology not only in treating but also in preventing future global pandemics through improved diagnostics and vaccine research.

CRISPR-Cas9's role in biomedical research continues to expand, addressing complex challenges in genetics and infectious diseases. Its ability to edit genes with high precision makes it an invaluable tool in the medical field, promising revolutionary advances in treatment and disease management.

Challenges and Ethical Considerations

Despite the significant advancements and promising applications of CRISPR-Cas9 technology in biomedical research, there are notable challenges and ethical considerations that need to be addressed. These concerns span from technical hurdles in delivery systems to the broader ethical debates and regulatory landscape surrounding gene editing.

Technical Hurdles in Delivery Systems

One of the primary technical challenges in the application of CRISPR-Cas9 is the efficient delivery of its components to target cells in vivo. The use of viral vectors, such as adeno-associated viruses (AAVs), has been common due to their high transduction efficiency and relatively lower immunogenicity.

However, concerns regarding safety, including the risk of insertional mutagenesis and carcinogenesis, have been raised. Non-viral delivery systems, such as nanoparticles, offer advantages including reduced off-target effects and minimal immunogenicity. Despite these benefits, challenges such as lower delivery efficiency to non-liver tissues remain a significant hurdle for the therapeutic application of nanoparticle-mediated CRISPR/Cas gene editing systems.

The Cas9 protein, derived from bacteria like Streptococcus pyogenes, poses an additional challenge due to its recognition by the human immune system as a foreign antigen. This immune response can lead to the rapid degradation of the Cas9 protein, hindering its gene-editing function. Furthermore, selecting an appropriate delivery technique that ensures safe and precise targeting of the CRISPR system to the desired site, especially in vivo, is a critical consideration.

Limitations of Guide RNA and Off-Target Effects

The guide RNA (gRNA) is a crucial component of the CRISPR-Cas9 system, directing the Cas9 enzyme to specific genomic sequences for editing. However, the design and efficacy of gRNA can be challenging. The specificity of gRNA is paramount to avoid off-target effects, which are unintended modifications at non-target sites in the genome. Off-target mutations can have unpredictable consequences, potentially causing harmful effects or reducing the efficacy of the intended gene edit. Researchers continually work on improving gRNA design algorithms and developing methods to enhance target specificity, but achieving perfect accuracy remains an elusive goal.

Alternative CRISPR Systems: Cas12 and Cas13

To address some of the limitations associated with CRISPR-Cas9, alternative CRISPR systems like Cas12 and Cas13 have been developed. Cas12, also known as Cpf1, offers a different mechanism of DNA cutting that can enhance targeting specificity and reduce off-target effects. Cas12 recognizes a different protospacer adjacent motif (PAM) sequence than Cas9, expanding the range of possible target sites within the genome. Cas13, on the other hand, targets RNA instead of DNA, providing a unique tool for regulating gene expression and potentially treating RNA-based diseases. Cas13's RNA-targeting capability can be particularly useful for transient gene expression modifications without permanently altering the genome.

Ethical Considerations and Regulatory Landscape

Moreover, the ethical considerations surrounding CRISPR-Cas9 cannot be overlooked. The potential for germline editing, which involves making changes that can be passed down to future generations, raises profound ethical questions about consent, the nature of human enhancement, and the potential for unintended long-term consequences. Regulatory frameworks worldwide are grappling with how to balance the promise of CRISPR technology with these ethical concerns. As the technology continues to evolve, ongoing dialogue between scientists, ethicists, policymakers, and the public will be crucial in navigating these complex issues and ensuring responsible use of CRISPR-Cas9 in biomedical research and beyond.

By addressing these technological limitations and ethical considerations, the field can move towards safer and more effective applications of CRISPR technology, unlocking its full potential in advancing human health and disease treatment

Conclusion

Throughout this exploration, we have delved into the transformative impact of CRISPR-Cas9, uncovering its revolutionary applications in biomedical research and beyond. From its foundational mechanisms to its vast potential in disease treatment and gene therapy, this powerful gene-editing tool stands as a beacon of innovation, offering new avenues for addressing some of the most challenging medical and biological puzzles. The discussion on its ethical considerations and safety measures reflects the conscientious path that researchers and scientists are navigating to harness CRISPR-Cas9's capabilities responsibly and effectively.
As we look towards the future, the ongoing research and advancements within this field promise to broaden the horizon of what's possible with CRISPR-Cas9, potentially ushering in a new era of personalized medicine and targeted genetic therapies.

For researchers keen on leveraging the precision and versatility of CRISPR-Cas9, especially its guide RNA, in their experiments, we invite you to discuss your questions or experimental needs with us .

As the field continues to evolve, the significance of keeping abreast with these advancements cannot be overstated, ensuring that the potential of CRISPR-Cas9 in revolutionizing biomedical research is fully realized in a manner that is safe, ethical, and impactful.

FAQs

Why is CRISPR-Cas9 considered a groundbreaking discovery?

CRISPR/Cas9 technology has significantly impacted genetic research, particularly in the study of human T cells. It enables immunologists to examine gene functions in a comprehensive manner, offering a higher translational potential in preclinical studies. This method is considered an advancement over traditional genetically modified animal models.

What role does CRISPR play in biomedical research?

In the realm of biomedical research, CRISPR is primarily utilized for genome editing. This innovative tool aids scientists in swiftly generating cell and animal models, which are crucial for advancing research into various diseases, including cancer and mental health disorders.

Why is CRISPR-Cas9 considered a groundbreaking discovery?

CRISPR-Cas9 is hailed as a groundbreaking discovery due to its ability to edit genes with high precision in human embryonic stem cells and its application in CRISPR-based single-cell molecular screens. Furthermore, it has been used in dropout screening to identify genes associated with lethal phenotypes, showcasing its potential for wide-scale genetic investigation.

What does CRISPR mean for biomedicine?

In biomedicine, CRISPR technology heralds a new era of personalized medicine. It enables the customization of treatments to fit a patient's unique genetic profile, leading to therapies that are more effective and specifically targeted to individual needs.

Explore kbDNA’s custom-tailored reagent libraries or our assay kits , and let us know your specific experimental needs by inquiring.
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How Are Membrane Proteins Important in Medicine?

Wed, 03 Apr 2024 04:30:40 GMT

Abstract:

Membrane proteins play critical roles in cellular processes, with their significance extending to medical science. This comprehensive article explores these multifaceted membrane proteins, their roles as drug targets, their association with diseases, impact on drug delivery and absorption, and their contributions to signal transduction, immune response, diagnostics, transplantation compatibility, therapeutic interventions, cell-cell interactions, gene editing, and structural insights for drug development.

Introduction:

Overview of Membrane Proteins

M embrane proteins are intricate molecular structures embedded in cell membranes, characterized by their specific association with cell membranes and their role in orchestrating vital cellular functions. Membrane proteins comprise transmembrane and peripheral proteins, they regulate processes such as transport, signaling, and adhesion, making them indispensable for cellular homeostasis.

Why Membrane Proteins Matter:

T heir significance lies in their ability to govern essential cellular activities. Serving as gatekeepers, membrane proteins control the passage of molecules, maintaining the delicate balance necessary for proper cell function.

Membrane Proteins in Medicine:

In the medical landscape, membrane proteins assume a pivotal role with far-reaching implications. This article aims to unravel the profound connection between membrane proteins and groundbreaking advancements in medical science.

Drug Targets & Significance in Drug Development:

Membrane proteins stand out as crucial targets for drug development due to their involvement in fundamental cellular processes. Notably, G-protein coupled receptors (GPCRs) emerge as primary targets for pharmaceutical intervention, representing a rich field for therapeutic exploration.

Examining specific membrane protein drug targets provides insights into the diverse therapeutic applications and potential breakthroughs in treating various conditions.

G-Protein Coupled Receptors (GPCRs )

Applications: Vital for signal transduction; drugs target GPCRs for hypertension, allergies, and mental health disorders
Breakthroughs: Research pursues novel GPCR drug targets for advancements in pain management and neurodegenerative disease

Ion Channels

Applications : Essential for conditions like arrhythmias, epilepsy, and chronic pain; drugs provide precise treatment
Breakthroughs : Ongoing studies aim for enhanced ion channel-targeted drugs with maximized therapeutic impact

Receptor Tyrosine Kinases (RTKs)

Applications : Crucial in cancer treatment and autoimmune diseases; drugs inhibit aberrant signaling
Breakthroughs : Research explores RTK-targeted therapies for autoimmune disorders and cardiovascular conditions

Transporter Proteins

Applications : Impactful in hypertension and neurological disorders; drugs offer innovative treatments
Breakthroughs : Ongoing efforts focus on unraveling transporter protein complexities for targeted therapies

Enzyme-Linked Receptors

Applications : Participate in vital cellular processes; drugs target them in cancer therapy and autoimmune diseases
Breakthroughs : Research explores enzyme-linked receptor-targeted therapies for inflammatory disorders and neurodegenerative conditions

Adhesion Molecules (CAMs)

Applications : Crucial for cell-to-cell interactions, especially in cancer metastasis; drugs hold promise.
Breakthroughs : Ongoing research investigates CAM-targeted therapies for broader applications beyond cancer.

Disease Association: Mutations and Diseases:

Examining how mutations in membrane protein genes relate to diseases provides crucial insights into conditions like cystic fibrosis, long QT syndrome, and epilepsy.

Cystic Fibrosis : Mutations in ion transport-related membrane proteins, like CFTR, lead to cystic fibrosis.Understanding these mutations informs targeted therapeutic approaches for cystic fibrosis.
Long QT Syndrome : Mutations in ion channels linked to cardiac repolarization cause long QT syndrome. Unraveling genetic factors aids in identifying at-risk individuals and developing tailored treatments.
Epilepsy : Membrane protein mutations affecting ion channels contribute to epilepsy. Understanding genetic underpinnings guides the exploration of targeted therapies for seizures.

Exploring membrane protein gene mutations and diseases sets the stage for advancements in diagnostics and precision therapies. Acknowledging its impact on conditions such as those mentioned above, or others, such as Alzheimer's and cardiovascular diseases, emphasizes the potential for more personalized treatment strategies.

Drug Delivery and Absorption:

In drug development, membrane proteins go beyond targets, influencing drug delivery and absorption. Transporter proteins in cell membranes regulate drug uptake and removal, affecting how drugs work and their safety.

Transporter Proteins' Role:
These proteins act as gatekeepers, controlling drug entry and exit, impacting overall drug behavior in the body.
Membrane Proteins for Targeted Delivery:
Membrane proteins strategically placed on cells can deliver drugs precisely, directing them to specific locations, enhancing effectiveness while reducing side effects.
Impact on Drug Outcomes:
Understanding drug interactions with membrane proteins refines formulations, optimizing benefits, and minimizing potential issues.

Examples of Drug Delivery Systems:

Lipoprotein-Based Carriers:
Using natural lipoproteins to carry drugs to specific targets.
Exosome-Mediated Delivery:
Employing exosomes, membrane-bound vesicles, for precise drug delivery.
Transporter-Targeted Nanoparticles:
Designing nanoparticles with specific targets to improve drug delivery efficiency.

Exploring transporter proteins in drug delivery refines precision and optimizes treatment outcomes, contributing to more effective and safer therapeutic strategies.
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Signal Transduction:

Guided by membrane proteins, signal transduction is vital for internal cell communication, offering crucial insights for disease understanding, notably in cancer.

Membrane proteins ensure seamless signal transmission within cells, coordinating responses to external stimuli and maintaining cellular balance.
Disruptions in signal transduction, especially in cancer, contribute to uncontrolled cell growth and enhanced metastatic potential.

Understanding the connection between signal transduction and diseases informs targeted interventions, crucial in developing precision medicines for disrupting abnormal cell behaviors.

Exploring signal transduction provides cellular insights and informs targeted strategies, especially in addressing diseases like cancer. Targeting specific signaling pathways holds promise for more effective treatments.

Immune Response

Membrane proteins play a pivotal role in the immune response, particularly in vaccine development. Targeting membrane proteins, like the SARS-CoV-2 spike protein, is instrumental in triggering immune reactions and building immunity.

Membrane proteins are key players in vaccine formulations, acting as antigens that stimulate the immune system. Utilizing these proteins in vaccines helps prime the immune system to recognize and combat specific pathogens.

In the context of the SARS-CoV-2 virus, the spike protein becomes a crucial target for vaccine development. Vaccines designed to induce an immune response against this membrane protein have been pivotal in the global effort to combat the COVID-19 pandemic.

Understanding the immune response's reliance on membrane proteins simplifies vaccine development, with examples like the SARS-CoV-2 spike protein serving as tangible illustrations of their significance..

Diagnostics

Membrane proteins act as valuable indicators in diagnostics, with changes in their expression serving as disease biomarkers. Their role in disease diagnosis, monitoring, and prognosis is crucial, evident in various membrane protein-based tests.

Changes in membrane protein expression signal diseases, providing insights for early diagnosis and effective management.

Membrane proteins play a vital role in disease diagnosis, serving as key components for monitoring disease progression.

Various tests utilize membrane proteins to detect and analyze diseases, contributing to accurate and efficient diagnostic procedures. A few examples of these include:

CA-125 Test : Detects elevated levels of CA-125, a membrane protein associated with ovarian cancer.
PSA Test : Measures prostate-specific antigen (PSA), a membrane protein linked to prostate cancer.
HER2/neu Test : Identifies overexpression of HER2/neu, a membrane protein associated with certain breast cancers.
Cystic Fibrosis Sweat Test : Analyzes chloride levels, indicating mutations in the CFTR membrane protein.

Tissue Compatibility in Transplantation

In transplantation, major histocompatibility complex (MHC) proteins play a crucial role. They are integral membrane proteins found on the surface of cells, and their role extends to presenting antigens to the immune system and aiding in immune response regulation. In the context of transplantation, MHC Proteins recognize foreign tissue, and thus determine compatibility between donors and recipients, ensuring the success of the transplant.

Determining donor-recipient compatibility relies heavily on MHC proteins. Matching these proteins minimizes the risk of rejection and enhances the likelihood of a successful transplant.In transplantation, the role of MHC proteins is pivotal, ensuring compatibility and minimizing the risk of rejection in donor-recipient pairs..

Therapeutic Interventions

Manipulation for Treatment:
In therapeutic interventions, membrane proteins are manipulated for treatment, altering their functions or expressions. An impactful strategy involves using monoclonal antibodies designed to target these proteins.
Intentional manipulation of membrane proteins enhances therapeutic outcomes by modulating cellular processes for disease treatment.

Monoclonal Antibodies Targeting Membrane Proteins:
Monoclonal antibodies specifically designed for membrane proteins interfere with their activity or induce immune responses, presenting a targeted therapeutic approach.
This link between therapeutic interventions and membrane proteins offers efficient strategies for addressing diseases through precise manipulation of cellular functions. [Link to Monoclonal antibodies article]

Understanding Cell-Cell Interactions

Adhesion Molecules
In understanding cell-cell interactions, adhesion molecules play a crucial role, with significant implications for diseases such as metastatic cancers.
Adhesion molecules are pivotal for facilitating interactions between cells. They contribute to the binding and communication essential for coordinated cellular activities.

Implications for Diseases, Especially Metastatic Cancers:
The involvement of adhesion molecules holds critical implications, particularly in diseases like metastatic cancers. Altered cell adhesion mechanisms can contribute to the spread of cancer cells to distant sites, influencing disease progression.
In the realm of cell-cell interactions, adhesion molecules serve as key players, influencing cellular communication and holding particular relevance in diseases like metastatic cancers.

Membrane Proteins in Gene Editing

Gene Editing Technologies:

Exploring the role of membrane proteins in gene editing unveils how gene editing technologies can modify these proteins, offering potential applications for treating diseases.

In the realm of membrane proteins, gene editing technologies employ precision tools such as CRISPR-Cas9 or other editing systems. These tools enable scientists to make specific alterations to the genetic code governing membrane protein structure or function. By harnessing the capabilities of these technologies, researchers can fine-tune the behavior of membrane proteins, addressing key aspects related to cellular processes, signaling, and interactions.

Potential Applications for Treating Disease:

Utilizing gene editing on membrane proteins holds promise for treating diseases. By modifying specific proteins, this approach presents opportunities for targeted therapeutic interventions, addressing the root causes of various medical conditions.

Structural Insights for Drug Development

Understanding membrane protein structures is crucial for drug development, emphasizing the significance of 3D studies and techniques like X-ray crystallography and cryo-electron microscopy.

Importance of 3D Structural Studies : Deciphering membrane protein functions relies on understanding their three-dimensional structure. This perspective reveals key details for identifying potential drug targets, such as binding sites, conformational changes, and interaction interfaces. The spatial arrangement of amino acids provides critical insights into the protein's behavior, aiding in the rational design of drugs that can precisely interact with these proteins.

Techniques: X-ray Crystallography and Cryo-EM : X-ray crystallography and cryo-electron microscopy are vital for unveiling membrane protein structures. X-ray crystallography analyzes diffraction patterns through protein crystals, providing high-resolution details of the protein's atomic structure. In contrast, cryo-EM captures high-resolution images of proteins in their native state without the need for crystallization. This versatility allows researchers to explore membrane proteins in their natural environment, contributing to a more comprehensive understanding.

Relevance to Drug Design : Insights from 3D studies directly inform drug design, enabling the development of drugs that selectively target membrane proteins. This targeted approach enhances drug efficacy and specificity, improving overall safety by reducing potential side effects. By precisely understanding the structural nuances, drug designers can tailor pharmaceutical interventions to interact with membrane proteins in a way that addresses the molecular underpinnings of various medical conditions.
Exploring structural intricacies through advanced techniques is integral to drug development, providing the knowledge necessary for designing drugs that precisely interact with membrane proteins, leading to more effective and targeted therapeutic solutions.

Conclusion

In conclusion, membrane proteins are crucial in medical science, serving as vital therapeutic targets. Understanding their structure and function is key for drug development and diagnostics.
These proteins contribute to innovative strategies for various medical conditions. The future holds promises for new drug targets and diagnostic biomarkers.

Navigating cellular complexities, membrane proteins remain central. The interplay between research and therapeutics is crucial for unlocking advancements and enhancing treatments.
In essence, membrane proteins significantly contribute to our understanding of medical science, paving the way for a future where targeted solutions redefine patient care.

For expert with custom tailored reagents, oligo-nucleotide synthesis services, or to further discuss the role of membrane proteins in medicine and within kbDNA, contact us today . Let's push the boundaries of scientific exploration together.

A Guide to Protein Characterization

Thu, 21 Mar 2024 04:04:26 GMT

Abstract:

In Welcome to our in-depth exploration of Protein Characterization, a critical aspect of bio-pharmaceutical research. In this article, we aim to demystify the complex world of protein characterization, answering key questions while delving into methods, parameters, applications, and emerging trends. Join us on this journey to understand why protein characterization is pivotal in the realms of academia, research, clinical settings, and the pharmaceutical and food industries.

Introduction: What is Protein Characterization?

What is Protein Characterization?: At its core, protein characterization involves deciphering the intricate details of proteins, from their primary structure to their functions. This article serves as a guide to unraveling the various aspects of this crucial process.
Why is Protein Characterization Important?: Protein characterization is the linchpin of bio-pharmaceutical research, offering insights into a protein's structure, function, and interactions. Understanding these aspects is vital for developing new drugs, diagnosing diseases, and ensuring the safety and efficacy of therapeutic proteins.
Different Approaches to Protein Characterization: Protein characterization employs a myriad of approaches, each offering unique insights. From chromatographic and electrophoretic methods to spectroscopic and mass spectrometric techniques, researchers have a diverse toolkit at their disposal.
Applications of Protein Characterization: The impact of protein characterization extends across various domains. It plays a pivotal role in research laboratories, clinical settings, the pharmaceutical industry, and even the food industry, where understanding protein structures influences product development.

Protein Characterization Methods:

Employing a mix of characterization methods is essential for a nuanced grasp of a protein's structure and function. By combining techniques like mass spectrometry, spectroscopy, chromatography, and electrophoresis, researchers gain precision, overcome limitations, and extract complementary information. This strategic integration ensures a holistic understanding, emphasizing the importance of a multifaceted approach to protein characterization:
Chromatographic Methods : Chromatography separates proteins based on their physicochemical properties, enabling precise analysis and purification.
Electrophoretic Methods : Electrophoresis leverages the movement of charged particles in an electric field to separate proteins based on size and charge.
Spectroscopic Methods : Techniques like UV-Visible and Infrared spectroscopy provide valuable information about a protein's structure and composition.
Mass Spectrometric Methods : Mass spectrometry offers high precision in determining a protein's mass, sequence, and post-translational modifications
Other Methods : X-ray crystallography and NMR spectroscopy provide detailed insights into protein structures, contributing to our understanding of their functions.

Protein Characterization Parameters:

Protein characterization parameters encompass vital elements like primary and secondary structure, tertiary arrangements, and post-translational modifications. These serve as the blueprint for understanding a protein's identity, function, and interactions. Deciphering these parameters is crucial for tailoring research and applications, providing a foundational understanding of proteins in diverse contexts.

Primary Structure: Primary structure refers to the linear sequence of amino acids within a protein, acting as its genetic blueprint. Understanding this sequence is paramount for unraveling the unique identity of a protein and forming the basis for comprehensive characterization.
Secondary Structure : Secondary structure delves into the local folding patterns of a protein, including alpha-helices and beta-sheets. This parameter is pivotal in protein characterization, offering insights into structural elements that influence stability and function.
Tertiary Structure : Tertiary structure explores the three-dimensional arrangement of a protein's secondary structures. This aspect of protein characterization provides critical insights into the overall shape and functional attributes, elucidating how individual components contribute to the protein's biological role.
Quaternary Structure : Quaternary structure examines how multiple protein subunits come together to form a functional, multimeric complex. Understanding this level of organization is crucial for deciphering collaborative dynamics among proteins and their collective impact on cellular processes.
Post-translational Modifications : Post-translational modifications encompass alterations occurring after protein synthesis, such as phosphorylation or glycosylation. Crucial for protein characterization, these modifications significantly influence a protein's activity, stability, and cellular localization.
Protein-Protein and Protein-Ligand Interactions : Protein-Protein and Protein-Ligand interactions delve into the nuanced relationships proteins share with each other or with ligands. Studying these interactions is fundamental in understanding the intricate functions of proteins, guiding insights into cellular processes and potential therapeutic targets.
Protein Stability and Activity : Protein Stability and Activity involve comprehending the factors influencing a protein's robustness and functional capabilities. Essential for protein characterization, assessments in this domain guide researchers in optimizing conditions for protein functionality, impacting applications in drug development and biotechnological processes.

Protein Characterization in Different Contexts:

Research Laboratory : In the research laboratory, protein characterization is the cornerstone of scientific exploration, guiding researchers in understanding the molecular intricacies of proteins. It plays a pivotal role in advancing knowledge, fueling breakthroughs, and laying the groundwork for innovative discoveries across various scientific disciplines.
Clinical Laboratory : In the clinical laboratory, protein characterization is instrumental in diagnosing diseases and developing personalized treatment strategies. By scrutinizing proteins at the molecular level, clinicians can tailor therapies to individual patients, enhancing precision medicine approaches.
Pharmaceutical Industry : In the pharmaceutical industry, protein characterization is integral to every stage of drug development, ensuring the safety and efficacy of therapeutic proteins. From target identification to quality control, detailed insights into protein structures guide the creation of effective and safe pharmaceutical interventions.
Food Industry : In the food industry, understanding protein structures through characterization is pivotal for developing innovative and nutritious products. Protein characterization informs the formulation of food products, ensuring their quality, functionality, and nutritional value meet consumer expectations.

Emerging Trends in Protein Characterization:

The field is evolving with more sensitive protein characterization methods, enhancing our ability to explore proteins' structural and functional intricacies, opening avenues for breakthroughs in various scientific and medical applications:

Development of New and More Sensitive Protein Characterization Methods : Technological progress has yielded highly precise protein characterization methods, enabling detailed analysis and providing new insights into complex biological processes.
Use of Machine Learning for Protein Characterization Data Analysis : Machine learning is revolutionizing protein characterization data analysis, enhancing efficiency and accuracy by uncovering patterns and insights within complex datasets.
Application of Protein Characterization to New Areas such as Single-Cell Proteomics and Spatial Proteomics : Protein characterization is expanding into innovative areas, such as single-cell proteomics and spatial proteomics, offering detailed analysis at the individual cell or spatial levels for insights crucial in personalized medicine and understanding complex biological systems.

Summary:

In this guide, we've delved into the essential aspects of protein characterization, from deciphering primary structures to exploring emerging trends like highly sensitive methods and machine learning integration. Emphasizing its pivotal role in various contexts, including research, clinical applications, pharmaceuticals, and the food industry, this guide underscores the necessity of a versatile and comprehensive approach. Whether unraveling intricate protein structures or staying ahead with the latest trends, this guide serves as an invitation for researchers to harness the power of protein characterization for groundbreaking discoveries in the dynamic landscape of bio-pharmaceutical research.

For expert assistance in protein characterization services tailored to your research needs, contact us today . Let's push the boundaries of scientific exploration together.

What is a Protein Linker?

Thu, 14 Mar 2024 03:41:30 GMT

Abstract:

In this article, we will be exploring and addressing fundamental questions regarding protein linkers. We will navigate the topic of protein linkers with regard to design, properties, applications, and emerging trends in research, catering to researchers, academia, and the commercial biopharmaceutical sector.

Introduction: What is a Protein Linker?

Protein linkers are sequences of amino acids within a polypeptide chain that connect distinct protein domains. These linkers lack a defined secondary structure, often adopting random coil configurations, providing flexibility crucial for the overall protein's structure and function. The amino acid composition influences properties like flexibility and rigidity, with amino acids such as glycine, serine, and proline contributing to conformational freedom. Cleavable linkers may incorporate specific amino acid sequences recognized by proteolytic enzymes, allowing controlled separation of linked domains. The molecular design of protein linkers is pivotal in tailoring their function, impacting diverse applications in protein engineering.

In simpler terms, protein linkers serve as crucial connectors between different protein domains. In essence, they are flexible segments that tether functional units, influencing the overall structure and function of the resulting protein construct. This article aims to describe the significance of protein linkers and provide a comprehensive understanding of their diverse aspects.

Protein linkers play a pivotal role in various biological and biotechnological applications. Their importance lies in facilitating the construction of fusion proteins, influencing the stability and activity of engineered proteins, and enabling the development of advanced biosensors and nano-materials.

Conformational Types of Protein Linkers:

The world of protein linkers is diverse, encompassing several types. Understanding the nuances of each type is crucial for effective protein engineering. Some of the fundamental types of protein linkers include:

Rigid Protein Linkers.
Flexible Protein Linkers
Short Protein Linkers
Long Protein Linkers
Cleavable Protein Linkers
Non-Cleavable Protein Linkers.

Specialized Types of Protein Linkers:

In the realm of protein engineering, specialized types of protein linkers extend beyond the traditional conformational model, offering diverse functionalities tailored to specific applications. This section explores various specialized linkers, each designed to fulfill unique roles in the intricate world of molecular engineering.

Tethered Linkers
Hinge Linkers
Crosslinkers
Cyclic Linkers

Membrane-Associated Linkers:

Membrane-associated linkers play crucial roles in maintaining structural integrity and facilitating communication between the extracellular environment and the cell's interior. This section explores diverse types of protein linkers that are intricately tied to cellular membranes, influencing various cellular processes.

Cell Membrane Linkers
Transmembrane Linkers
Membrane-Binding Linkers
Lipid-Anchored Linkers

Applications of Protein Linkers:

Protein linkers, acting as versatile connectors, play a vital role in various applications across scientific and biotechnological domains. From enabling multifunctional proteins in fusion protein engineering to contributing to targeted drug delivery in therapeutic protein development, protein linkers shape innovative advancements. This section explores key applications where protein linkers are instrumental.

Fusion Protein Engineering:

Seamlessly integrates different functionalities within a single protein construct, enabling multifunctionality and novel functionalities.

Therapeutic Protein Development:

Enhances protein stability and enables targeted drug delivery, fostering advancements in therapeutic applications.

Biosensor Creation:

Optimizes sensitivity and specificity, crucial for precise detection mechanisms in biosensor technologies.

Nano-material Design:

Plays a pivotal role in directing assembly and functionality, influencing the design and properties of nanomaterials.

Other Applications Worth Noting:

Protein linkers find additional applications in enzyme engineering, vaccine development, cell signaling studies, and drug delivery systems. Protein linkers continue to prove themselves invaluable in various scientific and biotechnological pursuits, with ongoing exploration uncovering new and diverse applications.

As molecular architects, protein linkers continue to shape the landscape of biotechnological applications, contributing to the development of novel therapeutics, advanced biosensors, and tailored nanomaterials. Their versatility remains a driving force in the ongoing exploration of innovative solutions across diverse scientific endeavors.

Protein Linker Design:

Designing an effective protein linker requires careful design considerations, and attention to computational and experimental methods employed in the process.

Protein Linker Design Considerations (Properties):

Crafting effective protein linkers comes with important design considerations, each shaping the functionality of these molecular connectors. Important properties to consider include:

Flexibility vs. Rigidity:

Achieving a balanced flexibility and rigidity influences the overall structure of linked protein domains. This involves selecting amino acids with specific properties to achieve the desired structural characteristics.

Optimal Length:

Linker length optimization ensures the desired spatial arrangement between functional units.
Short Linkers (5-10 amino acids): Ideal for close proximity applications, minimizing unnecessary spacing for efficient interactions.
Medium Linkers (15-20 amino acids): Balances flexibility and separation, suitable for moderate spatial distance between protein domains.
Long Linkers (25-30 amino acids or more): Optimal for extensive spatial separation, providing significant flexibility for large constructs or dynamic conformational changes.

Cleavability:

Cleavable linkers allow controlled separation of domains, offering flexibility in protein functionality.

Minimizing Immunogenicity:

Designing linkers to minimize immunogenicity avoids triggering unwanted immune responses.

Solubility:

Addressing solubility concerns ensures the fusion protein remains soluble in the intended environment.

Computational and Experimental Methods:

The design of protein linkers involves both computational and experimental methods. Computational tools enable predictive modeling, offering insights into the linker's behavior, while experimental methods validate these predictions, ensuring the designed linkers meet the desired criteria.

Molecular Dynamics Simulations:

Predicts dynamic behavior by simulating atom movements, offering insights into the linker's flexibility and interactions.

Bioinformatics Tools:

Analyzes amino acid sequences, predicting linker properties to inform design decisions efficiently.

X-ray Crystallography:

Determines 3D structure, providing high-resolution insights into the spatial arrangement of protein linkers.

Nuclear Magnetic Resonance (NMR) Spectroscopy:

Analyzes conformational flexibility and dynamics of protein linkers in solution using nuclear spin properties.

Mass Spectrometry:

Characterizes protein mass and composition, aiding identification and validation of linker sequences and modifications.

Site-Directed Mutagenesis:

Selectively alters amino acids to study their impact on linker properties and overall protein functionality.

Other Techniques:

These are fundamental, common methods used in the design and analysis of protein linkers. Additional techniques may be used depending on the specific goals and the complexity of the protein engineering project

These combined computational and experimental methods offer a holistic approach to protein linker design, integrating predictive modeling with empirical validation for more effective and tailored outcomes.

Emerging Trends in Protein Linker Research

In the dynamic field of protein engineering, emerging trends are transforming the role of protein linkers. Machine learning applications streamline linker design, predicting and optimizing properties efficiently. Novel linker types offer innovative structural possibilities, broadening the scope of protein engineering. Exploring new frontiers like gene editing and metabolic engineering reflects the evolving versatility of protein linkers in cutting-edge biotechnology. These trends signify a shift towards more sophisticated approaches, propelling protein linkers into exciting and uncharted territories.

Conclusion:

Understanding protein linkers is essential for researchers and professionals in bio-pharmaceutical fields. By exploring their design, properties, and applications, this article aims to serve as a comprehensive resource for those seeking clarity on the intricacies of protein linkers.

If you’d like to learn more about protein linkers, have specific questions, or would like to work with us on a project - reach out to us!

Precision delivery of drugs to disease sites. By combining therapeutic agents with targeting domains, Fusion Proteins can enhance drug delivery to specific tissues or cells, reducing side effects and improving treatment outcomes.

What are Fusion Proteins?

Tue, 06 Feb 2024 21:54:28 GMT

Abstract:

In the realm of life sciences and biopharmaceutical research, Fusion Proteins have emerged as powerful tools with a multitude of applications. This comprehensive article explores the definition, significance, types, engineering strategies, applications, and emerging trends on this topic.

Introduction: Unveiling Fusion Proteins

What are Fusion Proteins

These are molecular chimeras, combining two or more distinct protein domains into a single polypeptide chain. These hybrid proteins are integral to modern life sciences research and have opened new avenues in diagnostics, therapeutics, and industrial applications.

Why are Fusion Proteins Important?:

Fusion Proteins play a pivotal role in bridging the gap between diverse biological functions. By combining functional domains, researchers can achieve multifaceted objectives, such as targeted drug delivery, gene editing, and more.

Different Types of Fusion Proteins:

Reporter Gene : Used in molecular biology to study gene expression. For instance, researchers utilize Green Fluorescent Protein (GFP) to visualize and track specific proteins within living cells.
Therapeutic : These hybrids merge therapeutic proteins, enhancing both efficacy and specificity in disease treatment. Monoclonal antibodies fused to cytotoxic agents, known as immunotoxins, represent a prime example.
Affinity Tag : Facilitating protein purification and detection, these tags include His-tags, GST-tags, and FLAG-tags. They simplify the isolation and analysis of target proteins.

Applications of Fusion Proteins

For Diagnostics and Therapeutics : They serve as diagnostic markers, providing a targeted approach to identifying specific biomarkers associated with diseases. Moreover, Fusion Proteins form the basis of innovative therapies, such as antibody-drug conjugates (ADCs), which have revolutionized cancer treatment by delivering cytotoxic drugs specifically to cancer cells while sparing healthy tissue.
As Research Tools : Beyond diagnostics and therapeutics, these proteins act as invaluable research tools. They enable the investigation of protein-protein interactions, cellular processes, and signal transduction pathways. GFP, in particular, allow scientists to visualize the behavior of proteins within living organisms, providing critical insights into cellular dynamics.
For Industrial Applications : In the industrial sector, these proteins have ushered in a new era of biotechnology. They enable the production of biofuels, bioplastics, and valuable chemicals, significantly advancing sustainable manufacturing processes.

Fusion Protein Engineering

Strategies for Designing and Engineering Fusion Proteins:

The process of designing Fusion Proteins involves meticulous planning to ensure functionality and stability. Genetic fusion techniques, linker optimization, and domain shuffling are essential strategies. By carefully selecting the domains to be fused and optimizing the linkers connecting them, researchers can fine-tune the properties of these proteins for specific applications.

Expression and Purification of Fusion Proteins:

The choice of expression system depends on the complexity of the protein. E. coli is often used for simpler Fusion Proteins, while mammalian cells are preferred for more complex ones. Affinity tags, such as His-tags, simplify the purification process, ensuring high-quality protein yields.

Characterization of Fusion Protein Structure and Function:

To gain a deep understanding of these proteins, researchers employ advanced techniques such as X-ray crystallography and mass spectrometry. These methods allow for the detailed analysis of their structure and function, providing crucial insights into their potential applications.

Emerging Trends in Fusion Protein Research

For Gene Editing and Cell Therapy

As gene editing technologies like CRISPR-Cas systems continue to advance, Fusion Proteins are being utilized to enhance their precision. By fusing Cas proteins with targeting domains, researchers can achieve more specific and controlled gene editing, holding great promise for gene therapy applications.

For Nanotechnology and Biosensing:

Fusion Proteins are at the forefront of nanotechnology and biosensing. Conjugating nanoparticles with Fusion Proteins enables advanced biosensing and drug delivery. These nanoscale systems offer unprecedented control and targeting capabilities, opening doors to innovative medical and diagnostic applications.

For Synthetic Biology

In the emerging field of synthetic biology, Fusion Proteins play a pivotal role in creating synthetic biological systems and engineered microbes. These designer proteins can carry out specific tasks within synthetic organisms, advancing the development of novel biotechnological solutions.

Noteworthy Fusion Protein Applications

For Cancer Immunotherapy:

Harnessing the immune system's power to target cancer cells. Fusion Proteins designed to engage immune cells and enhance their ability to recognize and eliminate cancer cells represent a promising avenue in cancer immunotherapy.

For Infectious Disease Vaccines

The development of vaccines using these proteins as antigens. By incorporating specific pathogen-derived proteins into Fusion Proteins, researchers aim to create more effective vaccines, improving our ability to combat infectious diseases.

For Enzyme Replacement Therapy:

Treating genetic disorders by delivering functional enzymes. Fusion Proteins engineered to deliver missing or defective enzymes to affected cells hold great potential for the treatment of various genetic diseases.

For Targeted Drug Delivery:

Key Questions

What is a Recombinant Fusion Protein?

A Recombinant Fusion Protein is a genetically engineered protein that combines two or more protein domains, often with distinct functions, to create a single multifunctional molecule. This innovative approach allows researchers to design proteins with tailored properties, expanding the possibilities for scientific and medical advancements.

Learn more

What Are Recombinant Proteins Examples?

Examples include antibodies fused with toxins (immunotoxins), green fluorescent protein (GFP), and therapeutic antibodies fused to effector domains. These examples illustrate the versatility and diversity of these proteins in various applications.

What is the Difference Between a Fusion Protein and a Recombinant Protein?

While both Fusion and Recombinant Proteins are engineered, the key distinction lies in their design and purpose. Fusion Proteins combine multiple protein domains to create a multifunctional molecule, while Recombinant Proteins are proteins produced through genetic engineering, often for a specific function. These proteins offer enhanced versatility by merging distinct functionalities within a single molecule.

What is the Function of the Fusion Protein?

The function of a Fusion Protein depends on the specific domains it combines. Fusion Proteins can serve diverse roles, including targeted drug delivery, enhanced diagnostic capabilities, and precise gene editing. Their multifunctionality enables researchers to address complex challenges across the life sciences and biopharmaceutical fields.

Summary: Embracing the Power of Fusion Proteins

Fusion Proteins drive advancements in gene editing, nanotechnology, and synthetic biology, enabling precise corrections of genetic mutations, innovative drug delivery, and engineering of complex biological systems. Their versatility promises breakthroughs in science, medicine, and technology.

To learn more about fusion proteins, or any of our protein services, including off-the-shelf or custom tailor proteins, contact us right now for a free consultation and quote.

Custom Protein Services for Your Research Needs

Sat, 03 Feb 2024 21:17:26 GMT

Custom Protein Services

When it comes to cutting-edge life sciences research, having access to high-quality custom proteins is paramount. kbDNA, Inc. is here to meet your exact specifications with our Custom Protein Services. We produce top-tier recombinant proteins that will elevate your research to new heights. Discover why kbDNA, Inc. is the partner of choice for commercial biopharmaceutical companies and academia alike.

Get a Free Quote Today!

Why Choose Our Custom Protein Services?

At kbDNA, Inc., we understand that precision, quality, and efficiency are crucial in research. Our Custom Protein Services offer a myriad of benefits to help you achieve your research goals:

High Quality : Our proteins are produced to the highest standards of quality and purity. We take pride in delivering proteins that meet your exact specifications, ensuring accuracy and reliability in your experiments.
Fast Turnaround Times : Time is of the essence in research. We excel in delivering your custom proteins quickly and efficiently, allowing you to stay ahead of your research timeline.
Competitive Pricing : We offer competitive pricing for our custom protein services. High-quality custom proteins don't have to come at a high cost.
Flexible Options : We understand that every research project is unique. That's why we offer flexibility in producing proteins in various formats and quantities, tailored to your specific needs.
Precision : Our proteins are crafted to exact specifications, ensuring they are a perfect fit for your experiments.
Efficiency : We have a streamlined process in place to save you time and resources, so you can focus on your research.
Scalability : Whether you're working on a small-scale academic project or an industrial-level production, we have the capacity to meet your needs.
Expertise : With decades of experience in protein science, our team of experts is dedicated to supporting your research endeavors.

What Types of Custom Protein Services Do We Offer?

Our range of Custom Protein Services includes:

Recombinant Protein Production: We specialize in producing Recombinant Proteins tailored to your exact specifications.
Protein Purification : Ensure the purity of your proteins with our advanced purification techniques.
Protein Labeling : Customize your proteins with specific labels for tracking and analysis.
Protein Modification : We offer precise protein modification services to suit your research requirements.
Protein Library Development : Explore the world of possibilities with our protein library development services.

Process Overview

Our process is designed to ensure the highest quality and precision in every protein we produce:

Initial Consultation : We begin by understanding your unique research needs, allowing us to tailor our services to your requirements.
Design & Development : Our experts craft the blueprint for your custom protein, ensuring it meets your exact specifications.
Production : We utilize state-of-the-art labs and equipment to optimize protein yield, maintaining the highest quality standards.
Quality Control : Rigorous quality control measures ensure the purity and functionality of your custom protein.
Delivery : We offer fast and secure delivery to your doorstep, so you can start using your custom proteins without delay.

Technological Edge

At kbDNA, Inc., we stay at the forefront of technology to provide you with the best services possible. Our cutting-edge equipment and proprietary techniques set us apart, guaranteeing top-tier results for your research.

Contact Us

Ready to take your research to the next level? Contact us today to learn more about our Custom Protein Services or to get a free quote. We're ready to be your partner in advancing scientific discovery.

Monoclonal Antibodies: A Guide to Their Production, Application, and Future Prospects

Fri, 02 Feb 2024 21:02:01 GMT

Introduction

Monoclonal antibodies, often referred to as mAbs or MoAbs, are a cornerstone of modern biomedical research and therapeutic development. In this comprehensive guide, we will delve into this topic, answering key questions and shedding light on their remarkable history, production methods, diverse types, and crucial applications in medicine.

History of Monoclonal Antibodies

mAbs were first conceptualized by Nobel laureate César Milstein and Georges J. F. Köhler in 1975, marking a pivotal moment in the world of immunology and biomedicine. Their groundbreaking work paved the way for the development of these antibodies as powerful research tools and therapeutic agents. These antibodies, derived from a single parent cell, offer unparalleled precision in targeting antigens, a significant advancement compared to the polyclonal antibodies used before their discovery.

How Monoclonal Antibodies are Made

The production of monoclonal antibodies is a meticulous process that exemplifies the fusion of cutting-edge technology with biological expertise. It begins with the selection of a specific target antigen, a crucial step in ensuring the success of monoclonal antibody generation. The next milestone is the creation of hybridoma cells, which are achieved by fusing a B lymphocyte, responsible for producing the desired antibody, with a myeloma cell, providing longevity to the resulting hybrid. These hybridoma cells are then cultured and screened for monoclonal antibody production, with a focus on clones that produce antibodies with the desired specificity. This meticulous process yields mAbs that can be further customized to meet the exact specifications of researchers, ensuring precision in experiments and therapeutic applications.

Different Types of Monoclonal Antibodies

These antibodies come in various forms, each designed for specific purposes. There are naked antibodies, which directly target antigens and are extensively used in research and therapeutic applications. Additionally, antibody-drug conjugates (ADCs) combine antibodies with cytotoxic drugs, allowing for the selective destruction of cancer cells while minimizing collateral damage to healthy tissues. Bispecific antibodies are another remarkable development, possessing two different antigen-binding sites, which enable them to engage multiple targets simultaneously. These diverse types of antibodies provide researchers and clinicians with a wide range of options to address various challenges in the field.

Applications of mAbs in Medicine

Cancer Treatment: mAbs like rituximab, trastuzumab, and pembrolizumab have become integral in treating various types of cancer. By specifically targeting cancer cells, these antibodies have significantly improved patient outcomes while minimizing the harmful side effects associated with traditional therapies.
Infectious Disease Treatment: These antibodies have been at the forefront of the fight against infectious diseases, including COVID-19. They work by neutralizing the virus, reducing disease severity, and aiding in patient recovery.
Autoimmune Disease Treatment: In autoimmune disorders such as rheumatoid arthritis and multiple sclerosis, mAbs play a crucial role in modulating the immune response, alleviating symptoms, and improving the quality of life for patients.
Other Applications: Beyond the mentioned areas, monoclonal antibodies find use in transplantation medicine, diagnostics, and even as imaging agents in molecular imaging studies, further showcasing their versatility and importance in modern healthcare.

Advantages and Disadvantages of mAbs

mAbs offer numerous advantages, including their exceptional specificity, reduced side effects, and the ability to target previously challenging antigens. Their use has transformed the landscape of medical treatment and research. However, they also have limitations, such as high production costs and the potential for immunogenicity, which can lead to adverse reactions in some patients. Understanding these pros and cons is crucial in optimizing their use.

Future of Monoclonal Antibody Therapy

The future of monoclonal antibody therapy is incredibly promising. Researchers and biopharmaceutical companies are continually refining production techniques, improving antibody engineering, and expanding the range of applications. As personalized medicine gains traction, monoclonal antibodies will play a pivotal role in tailoring treatments to individual patients, maximizing their therapeutic efficacy.

Key Questions About Monoclonal Antibodies

Let's address some of the key questions researchers and professionals often have about mAbs:

What are mAbs made of?: They are proteins produced by a single type of immune cell known as a hybridoma cell.
What is the difference between monoclonal antibodies and polyclonal antibodies?: mAbs are derived from a single parent cell and exhibit high specificity, while polyclonal antibodies come from multiple cells and have less specificity.
How are mAbs used?: They are used for targeted therapy, research, diagnostics, and more, depending on their specific properties.
What types of diseases do monoclonal antibodies treat?: These antibodies are employed in the treatment of various diseases, including cancer, infectious diseases, autoimmune disorders, and more.
How are monoclonal antibodies used during a procedure?: They can be administered intravenously or subcutaneously, depending on the condition being treated.
What are the advantages & disadvantages of using monoclonal antibodies?: High specificity and reduced side effects are advantages, while production costs and potential side effects are disadvantages.
How are monoclonal antibody drugs used in cancer treatment?: They target specific proteins on cancer cells, inhibiting their growth and promoting immune responses against cancer.
What is monoclonal antibodies for COVID?: mAbs have been authorized for emergency use in COVID-19 patients to reduce symptoms and severity, particularly in high-risk individuals.
What are examples of monoclonal antibodies?: Rituximab, trastuzumab, and infliximab are examples used in various therapies, each targeting specific diseases or conditions.
How do monoclonal antibodies work?: They bind to specific antigens, either blocking their function, marking cells for destruction by the immune system, or delivering cytotoxic drugs directly to target cells, depending on their type and purpose.

Summary

mAbs have evolved from a scientific breakthrough to a cornerstone of modern medicine and research. Their precision, versatility, and expanding applications make them invaluable in addressing various medical challenges. As the field continues to advance, these antibodies will undoubtedly remain at the forefront of scientific innovation, contributing to improved healthcare outcomes and novel discoveries.

Intrigued by the potential of monoclonal antibodies? Explore their diverse applications, and consider how they could revolutionize your research or clinical practice. This is a vast and ever-evolving area of focus, offering endless opportunities for progress.

Reach out to us today to learn more!

Advantages and Applications of Recombinant Antibodies

Wed, 25 Oct 2023 18:03:38 GMT

Abstract:

Recombinant antibodies represent a groundbreaking advancement in biotechnology, offering significant benefits over traditional antibody production methods. This article delves into the advantages of recombinant antibodies, including high specificity and affinity, controlled production, reduced costs, engineering possibilities, and reduced animal use. We will explore their wide-ranging applications in research, diagnostics, and therapeutics, addressing key questions and future directions for this transformative technology.

Introduction:

What are antibodies?

Antibodies, also known as immunoglobulins, are proteins produced by the immune system to identify and neutralize foreign substances such as bacteria, viruses, and toxins. Traditionally, antibodies were produced using hybridoma technology, where animals were immunized to generate specific antibodies. However, the advent of recombinant antibody technology has revolutionized this field. Recombinant antibodies are produced in vitro using synthetic genes, providing numerous advantages over traditional methods.

Unlock the potential of recombinant antibodies with our cutting-edge technology and precision engineering. Our solutions offer unparalleled specificity and reproducibility, tailored to meet the demands of your research and development projects. Contact us today to discover how we can elevate your scientific breakthroughs.

Advantages of Recombinant Antibodies

High Specificity and Affinity

Recombinant antibodies are designed to have high specificity and affinity for their target antigens, enabling precise targeting and reducing off-target effects. This high specificity ensures that recombinant antibodies can accurately distinguish between different molecules, which is crucial for applications such as diagnostics and therapeutics. For instance, recombinant antibodies can be engineered to bind only to cancer cells, sparing healthy tissues and minimizing side effects.

Control over Production

One of the significant advantages of recombinant antibodies is the ability to control and standardize production processes. This control ensures consistent and reproducible results, which is essential for both research and clinical applications. Additionally, recombinant antibody production is scalable, allowing for large-scale manufacturing to meet the demands of commercial bio-pharmaceuticals. This scalability is particularly beneficial for producing monoclonal antibodies used in treatments for various diseases.

Reduced Costs

Recombinant antibody production eliminates the need for animal immunization, which is a time-consuming and costly process. By bypassing this step, researchers and manufacturers can significantly reduce costs. Moreover, the purification process for recombinant antibodies is simpler and more efficient compared to traditional methods, further lowering production expenses. These cost savings can be passed on to researchers and healthcare providers, making advanced antibody therapies more accessible.

Engineering Possibilities

Recombinant antibodies offer unparalleled engineering possibilities, allowing for the modification of antibody properties to suit specific applications. Scientists can design multispecific antibodies that can bind to multiple targets simultaneously, enhancing their functionality. For example, bispecific antibodies can be engineered to bring immune cells into close proximity with cancer cells, improving the effectiveness of immunotherapies. These engineering capabilities open up new avenues for innovative treatments and diagnostic tools.

Reduced Animal Use

The shift to recombinant antibody technology addresses ethical considerations and improves animal welfare. Traditional antibody production methods often involve the use of animals for immunization and hybridoma generation. By contrast, recombinant antibodies are produced in vitro, reducing the reliance on animals. This ethical advantage aligns with the growing emphasis on humane research practices and the reduction of animal use in scientific research.

Applications of Recombinant Antibodies

Research and Development

In research and development, recombinant antibodies play a critical role in various applications. They are extensively used in protein purification and characterization, allowing scientists to isolate and study specific proteins with high precision. Additionally, recombinant antibodies are instrumental in biomarker discovery and validation, aiding in the identification of disease-related markers. Furthermore, these antibodies are vital in drug discovery and development, enabling the screening and validation of potential therapeutic targets.

Diagnostics

Recombinant antibodies have revolutionized the field of diagnostics, providing tools for both in vitro and in vivo applications. In vitro diagnostics, such as immunoassays, rely on recombinant antibodies to detect and quantify specific antigens, facilitating disease detection and monitoring. In vivo diagnostics, including imaging techniques, use labeled recombinant antibodies to visualize disease states within the body. These applications enhance the accuracy and reliability of diagnostic tests, leading to better patient outcomes.

Therapeutics

The therapeutic potential of recombinant antibodies is vast, with applications spanning various diseases, including cancer, autoimmune disorders, and infectious diseases. Recombinant antibodies can be engineered to deliver drugs directly to target cells, such as in antibody-drug conjugates, improving the efficacy and reducing the side effects of treatments. Additionally, they play a crucial role in gene therapy, where viral vectors are used to deliver genetic material to specific cells. This targeted approach enhances the precision and effectiveness of therapeutic interventions.

Conclusion

Recombinant antibodies offer numerous advantages over traditional antibody production methods, including high specificity and affinity, controlled production, reduced costs, engineering possibilities, and reduced animal use. Their applications in research, diagnostics, and therapeutics are vast and transformative, driving advancements in biopharmaceuticals and healthcare.

The future of recombinant antibody technology is bright, with ongoing research and development paving the way for innovative treatments and diagnostic tools. As this technology continues to evolve, it will have a profound impact on the biopharmaceutical industry, research, and healthcare. Ethical considerations and challenges will remain at the forefront, guiding the responsible development and application of recombinant antibodies.

At kbDNA, we are committed to advancing recombinant antibody technology and providing cutting-edge solutions for researchers. Join us in exploring the limitless potential of recombinant antibodies and driving the future of biotechnology.

Contact kbDNA today to learn more, or to work with us for your reagent needs.

Explore kbDNA’s custom-tailored reagent libraries or our assay kits , and let us know your specific experimental needs by inquiring.
Interested in gene synthesis? Inquire with us or submit a project .

Enhancing Discovery Stage Research: The Importance of Research-Grade Reagents

laithik@gmail.com (L L) — Tue, 03 Oct 2023 21:16:50 GMT

Research-Grade Reagents - Introduction

In the dynamic field of life sciences research, the accuracy and reliability of experimental results are paramount. To achieve breakthroughs in the discovery stage of therapeutics, researchers must rely on high-quality tools and reagents. This article explores the significance of research-grade reagents in facilitating robust research outcomes

What is a Research-Grade Reagent?

A research-grade reagent is a meticulously crafted substance used in scientific experiments to drive accurate and consistent results. These reagents act as essential components in assays, experiments, and analyses within the life sciences domain.

Understanding "Research-Grade": RUOs, ASRs, and More

The term "research-grade" encompasses various classifications, such as Research Use Only (RUO) and Analytical Specific Reagents (ASRs). These designations signify the intended use, limitations, and validation of the reagent. Understanding these classifications helps researchers choose the right reagents for their specific needs.

The Crucial Role of Reagent Quality Control (QC)

Reagent QC involves a rigorous set of tests to ensure the reagent's performance, consistency, and safety . The highest form of QC validation involves third-party verification, where an independent organization confirms the reagent's quality, providing researchers with an additional layer of confidence.

Differentiating Reagents and Bioreagents

Reagents play a critical role in experimental setups, but there's a distinction between traditional reagents and bioreagents. While reagents encompass a broad range of chemicals used in various experiments, bioreagents are specialized substances derived from biological sources. This specificity allows bioreagents to interact accurately with complex biological samples, ensuring precision and reliability in research outcomes. Nucleotides (DNA/RNA), Proteins, Antibodies, and Enzymes are examples of bioreagents.

Key QC and Material Parameters for RUO Bioreagents

When assessing the quality of RUO bioreagents, tailoring these key parameters offers significant advantages to researchers:

Analyte/Gene of Interest : Tailoring ensures precise targeting for accurate results. By designing the reagent to interact only with the desired analyte or gene, researchers achieve specificity, reducing background noise and increasing the precision of outcomes.
Host/Immunogen : Customization guarantees compatibility with target species or samples. Selecting a host and immunogen that effectively recognize and interact with the biological material being studied enhances reliability and minimizes cross-reactivity.
Reactivity : Specificity is enhanced, minimizing non-specific interactions. By ensuring that the reagent binds only to the desired targets, researchers can confidently attribute observed effects to the intended molecules, reducing false positives and improving data reliability.
Concentration : Optimal levels prevent wastage and ensure reliable quantification. Customizable concentration provides researchers with the appropriate amount of reagent, avoiding signal weakness or excessive background noise.
Purity (1-100%) : High purity eliminates contaminants and enhances reliability. Tailoring purity ensures that the reagent contributes only to the intended effects of the experiment, minimizing potential sources of variability and error.
Endotoxicity (measured in EU or mg/mL) : Low endotoxicity avoids unintended effects. By minimizing the potential for immune responses, researchers confidently attribute observed responses to experimental conditions, not reagent-induced effects.
Reagent Formulation (Quantity, buffer, additives, pH, Format) : Tailored formulation matches the experimental setup for optimized results. Customizing quantity, buffer, additives, pH, and format ensures the reagent's compatibility with the experimental system, reducing errors and enhancing the reliability of results

The Limitations of Generic Off-the-Shelf Reagents

While generic reagents might be suitable for some applications, they often lack the precision required for the intricate demands of discovery stage research. Tailored research-grade reagents offer a higher level of specificity, sensitivity, and reproducibility, reducing the risk of false positives and unreliable data. kbDNA understands that precision matters, which is why our custom-tailored bio-reagents are meticulously crafted to match your experiment's exact requirements. Contact us for high-quality research-grade reagents today!

Adding Value through Custom Reagents

Unlike generic reagents, our company, kbDNA, specializes in providing custom research-grade reagents . This tailored approach ensures that researchers receive reagents that precisely match their experimental requirements, enhancing the accuracy and reliability of their results.

Advantages of Tailoring Reagent QC Parameters

Customizing reagent QC parameters offers several advantages to researchers:

Precision : Tailored parameters increase specificity, reducing false positives and enhancing the accuracy of results. By designing the reagent to interact only with the desired analyte or gene, researchers achieve specificity, reducing background noise and increasing the precision of outcomes.
Compatibility : Customization ensures that the reagent interacts optimally with the experimental system, improving reliability. Selecting a host and immunogen that effectively recognize and interact with the biological material being studied enhances reliability and minimizes cross-reactivity.
Minimized Interference : Tailoring prevents unintended interactions or influences from non-target molecules, reducing experimental noise. By ensuring that the reagent binds only to the desired targets, researchers can confidently attribute observed effects to the intended molecules, reducing false positives and improving data reliability.
Optimized Conditions : Custom parameters ensure that the reagent works optimally within the experimental context, improving data quality. Tailoring concentration ensures researchers have the appropriate amount of reagent to avoid signal weakness or excessive background noise.
Time and Resource Efficiency : Tailored reagents reduce the need for trial and error in optimization, saving researchers time and resources. Customizable purity ensures that the reagent contributes only to the intended effects of the experiment, minimizing potential sources of variability and error.

By understanding and customizing these parameters, researchers can optimize their experiments, achieve more accurate and reliable results, and accelerate their progress in the discovery stage of therapeutics research. This is where kbDNA comes in, providing a transformative solution with our custom-tailored reagents.

In the realm of discovery stage therapeutics research, precision, and reliability are non-negotiable. research-grade reagents empower researchers to delve deeper into their studies, confident in the accuracy of their findings.

Ready to Elevate Your Research with Precision? Contact kbDNA Today!

At kbDNA, we understand that your research demands accuracy, reliability, and tailor-made solutions. Our expertise in providing bespoke research-grade reagents is here to empower your discovery stage endeavors. Whether it's specific analyte targeting, optimized reagent formulation, or enhanced compatibility, our custom solutions bring your research to the next level.

Unlock the true potential of your experiments by partnering with kbDNA. Let's collaborate in pushing the boundaries of discovery and innovation. Contact us now to discuss how our custom research-grade reagents can elevate your research outcomes.

SVB Collapse; Long story short(er)

Mon, 13 Mar 2023 22:27:31 GMT

Silicon Valley Banks lending practices will influence biotech & pharma the most. Here's the crash course on what happened.

Background

From 2019 through 2021, Silicon Valley Bank (SVB) experienced period of great success. Credit losses were minimal, and deposits had increased threefold during that time.

On the surface, this appeared to be great news. Optimism abounded as the bank, clients, and investors reaped the rewards of growth. However, underlying factors would lead to an unexpected outcome, one that we’ve all seen play out in the headlines over the past week. To comprehend the rise and fall of SVB, its necessary to understand the following key factors at play.

When banks accept deposits from clients, they owe the client that money, converting these deposits into "liabilities" for the bank. It costs money to handle liabilities, as the bank pays interest out to checking accounts, and must cover the cost of servicing clients, including customer service, branch maintenance, back-office workers, etc.
To cover liability costs, banks turn liabilities into "assets" by lending deposits as small business loans or mortgages. If a bank is unable to lend deposits responsibly, it often uses excess funds to purchase loans or securities, such as US Treasury Bonds and Mortgage-Backed Securities (MBS).
US Treasury Bonds and Mortgage-Backed Securities have lower credit risk, but increased risk in terms of interest rates and inflation.

How Does This Relate to SVB?

From 2019-2021, SVB deposits tripled, and they needed to use those funds to acquire “assets” to pay its costs. Many of these deposits were from VC-backed companies looking for a place to deposit large sums of money.

SVB recognized that deposits were pouring in too quickly for them to be able to lend the money out responsibly. Therefore, it bought long-duration assets guaranteed by the US government, such as Treasuries and Mortgage-Backed Securities. However, it bought a large volume of long-term bonds (bonds with maturities greater than 10 years) at low-interest rates.

As noted above, these types of investments have an increased risk in terms of interest rates. The prices of these investments have an inverse relationship to interest rates. As interest rates rise, the prices of US Treasury Bonds and Mortgage-Backed Securities drop.

Another side-effect of rising interest rates is a decline in fund-raising for start-ups. As capital became less available, SVB’s clients began to withdraw their funds.

This meant that SVB was underwater on its securities investments just as clients withdrew increasing amounts of their funds. To cover their liabilities to these clients, the bank sold off $21 billion of its securities at a loss of nearly $2 billion dollars.

How Did This Lead to SVB’s Failure?

Many of SVB’s clients were large depositors, meaning their deposits were above the FDIC insurance threshold, putting them at risk of severe losses in the case of a bank failure. SVB’s financial loss led to a bank run on SVB by concerned clients, who had lost confidence in the bank and wished to withdraw their funds in case of a closure. This in turn caused shares to drop by 60% and led to the bank’s closure.

Impact on Biotech and R&D

Which brings us to now: March 13th. The Monday following a weekend filled with crisis management and emergency planning. After a hectic weekend, SVB had become a household name in the life sciences sector. The amount of biotech companies with startup capital, VC funds and partner commercial lending going through the SVB network is significant. While 2023 had not been the greatest start for biopharma, this was the last thing any R&D sector needed.

To put it in perspective; alongside a challenging period of unprecedented layoffs and budget cuts, many companies spent their weekend scattering to secure payroll for the employees they have left. On the bright side, most were successful in doing so and today brings much needed relief.

On the bright side-we have some refreshing updates released today:

Federal officials announced last night that they’ll fully protect all deposits at Silicon Valley Bank and people will have access to all their money when it reopens this morning. (Previously, only deposits up to $250,000 were 100% insured.)

Comment: Preventative measure deterring bank-runs

Gov. Maura Healey’s administration said Sunday that Massachusetts could be “uniquely impacted” by the failure of Silicon Valley Bank (which has locations in Boston, Beverly, Cambridge, Newton and Wellesley). (Cambridge and greater Boston is home to a majority of biotechs, software and health startups SVB was lending to)

Comment: Cambridge and greater Boston is home to a majority of biotechs, software and health startups SVB was lending to

All in all - It is too early to assess the long-term damages from the SVB crash, but the response of both federal regulators and regional agencies has been competent. From our position as researchers and supporting roles for research; the top priority is making sure the experiments never stop.

Microarrays Revisited [2025]

Fri, 06 Jan 2023 00:15:00 GMT

Microarray Protocol

Microarray technology represents a versatile and high-throughput technology to explore genome and parallel gene expression for thousands of genes with known and unknown functions using a variety of biological samples ^1,2

Overview:

In microarray technology, millions of probe molecules’ microspots are immobilized on a miniaturized solid support or chip in an array format, which are then exposed to study samples (cells, tissues, and bodily fluids) containing the corresponding target molecules. The probes utilized in this microarray technique include protein, antibody, cDNA, oligonucleotides etc., while the target molecules are DNA or RNA isolated from the biological samples (cells/tissues). The complementary base pairing of chip-immobilized fragments and target molecules produces fluorescence which is detected and quantified using a specialized machine. Moreover, the microarray technique allows simultaneous rapid detection and quantification of proteins or nucleic acids within a single reaction in an efficient manner along with comparative genomics analysis. Furthermore, it also allows the detection of specific DNA sequences (for example, single nucleotide polymorphisms or SNPs) useful for genome-wide association studies. The advantage of this technology includes its elimination of the need for sequencing, and its tremendous cost reduction unlike conventional large studies. Currently, there are different microarray formats available for the detection and analysis of specific biomolecules, namely, DNA microarrays, protein (antibody) microarrays, cell microarrays and tissue microarrays. These microarray formats either alone or in combination with other microarray techniques are being utilized for biological research and clinical studies. Using these techniques, one can examine the cell profiling treated with certain stimulators, gene expression profiling in response to drugs, serum analysis for diagnostic information and assessment of protein families, to name a few. The applications of microarray-based technology further extend to biomedical research, drug discovery and development, medical diagnostics to toxicogenomics.

Despite the variations in available protocols, the five major steps which are in essential in the microarray process include:

Synthesis of capture element (probes),
Solid support surface or chip preparation,
Capture elements (probes) immobilization using a robotic arrayer onto the solid support,
Immobilized capture elements binding with the target molecule present in the biological samples, and
Finally, target/capture element complex detection and quantification.

Deeper Dive:

DNA microarray technology was the first developed microarray technique for the detection of genes and genome analysis, however; little information related to proteins and their functions are provided using this technique. In this context, protein microarray, or protein chip was further developed as high throughput technique to detect different proteins, protein functions, proteins interactions, protein interactions with small molecules, proteins kinase substrates, and proteomic analysis in a single experiment ^3.4 [Figure 1]. Currently, in order to study the biochemical activities and functions of proteins, two protein microarray formats such as analytical and functional protein microarrays are mainly utilized. Analytical protein microarrays or antibody microarrays represents the most powerful multiplexed high throughput detection technologies for identifying specific proteins with high specificity and affinity. On the other hand, functional protein microarrays employ protein domains or full-length functional proteins for the identification of protein interactions with other biomolecules, immune responses, and biochemical activities. Nevertheless, both classes of protein microarrays have shown tremendous progress in the last decade in terms of sensitivity, specificity, and expanded applications.

The antibody microarray is the most representative type of protein microarray wherein antibodies are employed as the capture elements and arrayed on glass surfaces with high density for further specific detection of proteins of interest with high specificity. Herein, immobilized antibodies are tagged with fluorescent dyes namely, Texas Red, Cy3, Cy5, FITC or biotin-horseradish peroxidase enzyme systems for specific detection and visualization. In antibody microarray techniques, we employ the same well-established principles such as ELISA based immunoassays or Western blot-based immunoassays for detection of proteins, however; various advantages are offered by these microarray techniques. The advantages of antibody microarray techniques include one step detection of multiple proteins, increased number of data points for better detection accuracy, and reduced sample and antibody volume requirements. Additionally, ability to rapidly spot limitless copies using a robotic arrayer once the microarray is designed and all components are validated presents another major advantage for working with large sample groups.

In this protocol, we have highlighted mainly two formats of the antibody microarray, namely direct labeling and fluorescence-linked immunosorbent assay (FLISA). In both these formats, specific antibodies are employed as the capture element. However, in case of direct labeling microarray technique, all proteins present in the sample mixture are labeled prior to its capture unlike in the FLISA technique. In the FLISA microarray technique, the untreated proteins present in the sample mixture are captured first and followed by their detection using a biotinylated primary antibody and fluorophore-labeled secondary antibody. In both types of microarray techniques, the employed antibodies should be highly purified with minimal cross-reactivity, and able to work well in traditional ELISA formats. Firstly, a predetermined optimal concentration (usually 300-500 µg/ml) of antibody solutions are prepared followed by the preparation of spotted solid support or chip through assembly into a print plate or microtiter plate using a robotic arrayer. Generally, up to 500 different antibodies per array can be spotted and immobilized for comparison as per the researcher’s requirement using six to ten replicates of antibody. After the spotting and immobilization of antibodies, blocking agent bovine serum albumin (BSA) solution treatment is given for at least 1 hour to block the non-specific reactions. Thereafter, the biological samples of interest such as urine, serum, cell lysate etc. are exposed to the immobilized miniaturized solid support. Direct labeling antibody microarray format-based detection is depicted in Figure 2 (A and B). In this method, all proteins present in a sample mixture are labeled with either biotin or fluorophore prior to its incubation with the capture element. Furthermore, quantitative measurement for determination of relative amounts or expression levels measurement of detected proteins are performed after washing of arrays followed by scanning for data analysis. In an alternative strategy, quantitative measurement of exact expression levels by comparing different signal intensities of sample molecules can be carried out using established calibrated protein standards labeled with distinct fluorophores. The direct labeling antibody microarray technique is simple to use and requires only one specific antibody per target. However, increased background signal due to labeling of proteins in the sample mixture (for e.g., albumin in serum) represents a major challenge in detection using this technique. The concentration of the background protein (approximately 100 ng/ml) with respect to target protein concertation in serum reduces the detection sensitivity

In FLISA-based antibody microarray detection format, unlabeled protein targets are captured on immobilized antibodies spotted on the solid support or chip (Figure 3). After capturing of target proteins, the array is incubated with a cocktail of biotin-labeled antibodies (primary antibody) specific to one of the spotted capture antibodies. Furthermore, incubation of array with fluorophore labeled anti-biotin secondary antibody which acts as a suitable detection antibody for visualization is carried out. The FLISA detection format provides increased sensitivity compared to the direct labeling method owing to significantly reduced background signal production in this microarray format. The sensitivity of FLISA antibody microarray detection format can be further enhanced using rolling-circle amplification or tyramide signal amplification ⁵ . However, due to difficulty in optimization of assays for measurement using various targets, FLISA detection is suitable for measurement of a limited number of targets at concentration below the detection limit of direct labeling method. As different parameters such as the affinity and specificity of the antibodies used, utilized detection conditions, and protein background in the sample are crucial for the detection limits of the assay; the FLISA method can provide detection limits in the low pg/ml range.

References

Dubey, P.P., Kumar, D. (2013). Microarray Technology: Basic Concept, Protocols, and Applications. In: Arora, D., Das, S., Sukumar, M. (eds) Analyzing Microbes. Springer Protocols Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34410-7_17 .
Hoheisel JD. Microarray technology: beyond transcript profiling and genotype analysis. Nat Rev Genet. 2006 Mar;7(3):200-10. doi: 10.1038/nrg1809.
Fung, Eric ed. Protein arrays: methods and protocols. Fremont, CA: Humana Press Inc.; 2004.
Robinson WH, DiGennaro C, Hueber W, Haab BB, Kamachi M, Dean EJ, et al. Autoantigen microarrays for multiplex characterization of autoantibody responses. Nat Med (2002) 8:295–301. doi:10.1038/nm0302-295.
Zhou, Heping, et al. Genome Biology, Vol. 5, issue 4, R28; 2004.

Bioconjugation Chemistry: Challenges and Solutions

Thu, 01 Dec 2022 20:17:53 GMT

Bioconjugation Biochemistry: Challenges and Solutions

Bioconjugation represents the derivatization of biomolecules (proteins, carbohydrates, nucleic acids) which allows the site-specific creation of a covalent link between a biomolecule and an exogenous moiety in order to endow desirable properties using a different set of techniques. ^1,2 Bioconjugation biochemistry enables the creation of hybrid molecules that exhibit the properties of both biomolecules and exogenous moieties. Examples of bioconjugation based hybrid molecules include protein structure elucidation using tags, enzyme immobilization, antibodies binding to fluorophores, cellular imaging, microarrays, etc. ^3,4 . Bioconjugation typically involves the modification of biomolecules by adding distinct but complementary functional groups through a wide range of chemical techniques/reactions using different linkers. However, to develop new methodologies, site specific conjugation continues to garner much attention to match the ever-increasing requirements of preserving biomolecule integrity, stability, and mildness. Nevertheless, bioconjugation techniques have emerged as a powerful set of tools with applications in ground-breaking targeted biotherapeutics, disease diagnosis, ligand discovery, high throughput drug screening, biosensors. ^5,6,7

Criteria for successful bioconjugation :

Any functional bioconjugation strategy should meet certain criteria irrespective of the techniques employed

The bioconjugation reactions must take place in aqueous solutions in a controlled manner to maintain the biomolecules’ inherent functions.
The conjugation reaction should be stoichiometrically efficient with fast kinetics.
There should not be any additional agents which could potentially disrupt the biomolecules’ functions such as an oxidant, reductant, or metal during conjugation reaction.
There should not be any covalent side reactions during modification or conjugation.
Conjugate bonds should not form between endogenous functional groups present within the biomolecules, instead conjugate bonds should form only between the two complementary linkers incorporated on the biomolecules during modification.
Linkers should be easily incorporated on a variety of biomolecules (oligos and peptides) during solid-phase synthesis.
The quantitation of linker incorporation and conjugate formation should be easy through simple and non-destructive methods (For example, spectrophotometry).
The resulting bioconjugate should be stable under broad pH and temperature ranges to meet a variety of experimental needs.

Though various methodologies are currently being employed for the bioconjugation of biomolecules, still many methods are facing challenges, thus limiting their general applicability. Moreover, several critically important bioconjugation parameters have been completely neglected in the past, which needs to be addressed properly to increase the overall bioconjugation efficiency. For example, the number of samples utilized, the stability of the bioconjugation linkage, and the distribution of bioconjugation generated products are of utmost importance and should be given great attention. In addition, more exploration of the sensitivity of analytical methodologies is necessary to develop efficient and selective bioconjugation methods. In recent years, the advancement of bioconjugation techniques for the development of vaccines, emerging biomaterials, and new therapeutic conjugates has further necessitated the consideration of biocompatibility, biostability and bioselectivity in the context of the challenges associated with the bioconjugation methods being utilized. In this context, we have highlighted below the most important types of bioconjugates (protein bioconjugates, antibody bioconjugates, antibody-enzyme bioconjugates, protein-DNA bioconjugates), their associated challenges, and possible solutions to those challenges.

Protein Bioconjugates :

Proteins are the most utilized biomolecules in bioconjugation biochemistry, and are generally leveraged for labelling live proteins, stabilizing proteins being used in protein-based therapies, cellular imaging, and biological processes monitoring. The selection of a protein bioconjugation methodology primarily depends on:

The intrinsic reactivity of the targeted amino acid residue in the protein (oxido-reductive characteristics, acidity/basicity, electrophilicity/nucleophilicity),
Its protein-specific environment related to accessibility, whether its N- or C- terminal ends, the location of amino acids within the specific sequence or chain, etc...

Proteins greatly vary in terms of their modification as some proteins are easy to manipulate while others face problems during bioconjugation. Protein modification methods also widely vary related to the protein’s properties, such as functional group compatibility, inherent site selectivity, and overall yield ^7,8 . In recent years, various biochemical techniques and approaches have been utilized for the bioconjugation of proteins for the development of new protein-drug conjugates, targeted medical imaging agents, protein-hybrid materials with complex functions, and the improved understanding of biological processes.

Challenges with Protein Bioconjugates :

The challenges associated with protein bioconjugates include a lack of site-specificity, lack of access to the reaction site, and a lack of bioconjugation techniques for different amino acids.

Lack of Site Specificity

In some protein bioconjugation methods, a lack of site-specificity imposes an inability to create specific reaction sites to target the desired protein during a bioconjugation reaction acids.

Troubleshooting Tips

Use a catalyst to promote a site-specific protein conjugation reaction.
Incorporate an unnatural amino acid and synthesize your target protein with it. For example, the site-specific incorporation of an unnatural amino acid at the N-terminal end of a protein.

Lack of Access to the Reactive Site

While dealing with native proteins, the desired reactive groups can be limited or inaccessible. This represents a difficult problem due to protein folding. This protein reactive site inaccessibility leads to poor yields of protein bioconjugates, and sometimes even the failure of the bioconjugation reaction.

Troubleshooting Tips

Find an alternative reactive site
Directly modify the protein to attain better access to your target reactive site
Modify the target protein with genetic manipulation to make it more accessible.

Lack of Bioconjugation Techniques for Different Amino Acids

Different modification methods are available for different amino acids in proteins. Some amino acids are not easy to modify using routine bioconjugation techniques. For example: tyrosine has recently emerged as a bioconjugation target and does not have many bioconjugation techniques.

Troubleshooting Tips

Modify previously utilized bioconjugation techniques.
Develop new methods for the bioconjugation of specific amino acids.

Antibody Bioconjugates :

Antibody bioconjugates have also been significantly utilized in the field of bioconjugation science with fascinating applications in biological imaging and immunohistochemistry.

Challenges with Antibody Bioconjugates :

Antibody bioconjugates often encounter problems due to their fragile and complicated nature. The challenges include instability of the bioconjugate product, and degradation of the antibody.

Instability of the Antibody Bioconjugate Product

Once antibody bioconjugates are generated, you may face the issue related to their stability as they have a tendency to decompose immediately or during storage like normal antibodies.

Troubleshooting Tips

Cool your antibody bioconjugate. Cooling increases the storage life of bioconjugates.
Avoid freezing the bioconjugates
Use a specific antifreeze stabilizer in storage solutions to extend the shelf life. Such as 50% glycerol or ethylene glycol to increase the shelf life at -20 degrees.

Degradation of the Antibody

The utilization of harsh chemicals to produce stable chemical bonds between an antibody and another molecule generally leads to the degradation of generated bioconjugates.

Troubleshooting Tips

Control the reaction conditions. For example, performing the experiment in cooler conditions or in a nitrogen environment reduces degradation.
Reduce the use of harsh chemicals during bioconjugation. This may be achieved by using milder chemicals or simply changing the solvents or solutions.

Antibody-Enzyme Bioconjugates :

Antibody-enzyme conjugates are promising products for cancer therapy and in the area of immunohistochemistry research.

Challenges with Antibody-Enzyme Bioconjugates :

The challenges with antibody-enzyme conjugates include the degradation of enzyme activity and controlling linker length.

Degradation of Enzyme Activity

The enzyme activity may be negatively affected by the reagents and conditions used in bioconjugation reactions.

Troubleshooting Tips

Use an enzyme stabilizer to minimize the degradation of bioconjugates
Use alternative reagents and/or linkers.
Change the reaction conditions related to pH and solvent
Use a different conjugation strategy.

Controlling Linker Length

Linker length can range from “zero length” to extended length chains and affect the stability and reactivity of antibody-enzyme conjugates. Therefore, controlling linker length is important to maintain the stability and activity of enzymes in antibody-enzyme bioconjugates.

Troubleshooting Tips

Experiment with different linker lengths to assess how this affects the performance of the bioconjugates.
Use alternative linkers with prolonged stability.
Avoid using linkers that can be easily broken in reaction conditions.
Avoid peptide-based linkers.

Protein-DNA Bioconjugates :

DNA and proteins represent two of the most important classes of biomacromolecules in biology. Combining DNA and proteins opens several avenues for bioconjugation. Protein-DNA bioconjugates provide tools for structural hybridization, enzymatic catalysis, and molecular recognition.

Challenges with Protein-DNA Bioconjugates :

The challenges associated with protein-DNA bioconjugation techniques include low reaction yields and the introduction of reaction sites to the DNA.

Low Reaction Yields

One of the most frustrating problems encountered during the synthesis of protein-DNA bioconjugates is the production of small amounts of your desired bioconjugates.

Troubleshooting Tips

Optimize your reaction conditions. Using simple tweaks such as tailoring reaction time, solvent, and temperature may improve the yield of bioconjugates.
Try an alternative purification technique.

Introduction of Reaction Sites On DNA

During protein-DNA bioconjugation, it is necessary to introduce reaction sites to the DNA structure. The introduction of reaction sites on DNA is not straight forward and poses challenges.

Troubleshooting Tips

Use direct chemical modification to add the desired functional groups to the DNA structure.
Synthesize DNA with your desired functionality using emerging techniques and approaches. These include techniques such as enzymatic gene synthesis, or microarray mediated gene synthesis. ⁹

References :

Koniev O, Wagner A. Developments and recent advancements in the field of endogenous amino acid selective bond forming reactions for bioconjugation. Chem Soc Rev. 2015 Aug 7;44(15):5495-551. doi: 10.1039/c5cs00048c.
Wadhawan A, Chatterjee M, Singh G. Present Scenario of Bioconjugates in Cancer Therapy: A Review. Int J Mol Sci. 2019;20(21):5243. Published 2019 Oct 23. doi:10.3390/ijms20215243
Wang RE, et al. 2015. An immunosuppressive antibody–drug conjugate. Journal of the American Chemical Society
Zhao P, et al. 2018. Highly multiplexed single‐cell protein profiling with large‐scale convertible DNA‐antibody barcoded arrays. Advanced Science
Kalia J, Raines RT. Advances in Bioconjugation. Curr Org Chem. 2010 January; 14(2): 138–147.
McMahon NP, et al. 2020. Oligonucleotide conjugated antibodies permit highly multiplexed immunofluorescence for future use in clinical histopathology. Journal of Biomedical Optics
Chen C, Ng DYW, Weil T, Polymer bioconjugates: Modern design concepts toward precision hybrid materials, Progress in Polymer Science,105, 2020,101241.
Stephanopoulos N, Francis MB. Choosing an effective protein bioconjugation strategy. Nat Chem Biol. 2011 Nov 15;7(12):876-84. doi: 10.1038/nchembio.720.
Eisenstein, M. Enzymatic DNA synthesis enters new phase. Nat Biotechnol 38, 1113–1115 (2020). https://doi.org/10.1038/s41587-020-0695-9

Cloning of Single-Chain Fv Fragments (scFv's)

Wed, 26 Oct 2022 01:30:00 GMT

Cloning of Single-Chain Fv Fragments (scFv's)

Single-chain fragment variables (scFv’s) with a molecular weight of ~25 kDa represent the smallest unit of a functional antibody with complete antigen-binding activities ¹ as shown in Figure 1. scFv’s (single-chain fragment variables) are generated by fusion of immunoglobin heavy chain (V _H ) and light chain (V _L ) variable domains connected by flexible polypeptide linker ² . scFv’s are easily expressed in functional form for improvement of properties such as increased affinity, solubility, and modulation of specificity in various expression models such as E. coli, yeast, and mammalian cells. Among all the available expression systems, the bacterial expression system is most commonly utilized for the production of scFv antibody fragments. This protocol provides a quick guide related to the main aspects of scFv cloning.

Orientation of variable domain and location of tag in scFv fragment:

During construction of the scFv (single-chain fragment variable), there is no preferential orientation of one domain over the other variable domain. The orientation can be either V _H -linker-V _L or V _L -linker-V _H and both orientation types are equivalent. Owing to its nature as independent folding entities, ScFv fragments can be fused indistinctively on either end with other protein domains or epitope tags. For example, the N-terminal end of scFv’s has been tagged extensively with FLAG tag ³ , while the C-terminal end has been frequently tagged with PHEN1 in many vectors ⁴ . Furthermore, purification tags such as HIS tag, Streptag etc. must be located on the C-terminal side to prevent purification of truncated proteins. In order to make scFv more accessible, purification tags are often located first, followed by C-terminal epitope tags. In the case of phage display, free scFv are allowed to secrete in the periplasmic space using a combination of epitope tag plus amber codon between the scFv and the phage coat protein for binding and analysis purpose. In a recent study, P17 tag (a 33-residue peptide) was utilized as tag for improvement of scFv’s solubility (11.6-fold increase) and thermal stability ⁵ .

Length of linker and its sequence:

A flexible short peptide or linker must be designed once the orientation is finalized along with tagging with proteins or epitope tags as it plays a vital role in stabilizing the antibody. Earlier studies reported 3.5 nm (35 Ǻ) length for peptide linker between the C-terminal and N-terminal end of scFv’s variable domains without affecting the folding ability ⁶ . The length of the linker is critical to ensure the correct folding of different domains in scFv’s. If the length of the linker is too short (5-10 amino acids long), the physical association between the variable domains is hindered and leads to the formation of multimers (diabodies, tribodies, etc.) ⁷ . On the other hand, linkers that are too long would favor weak domain association or susceptibility to proteolysis. Therefore, choosing optimum length linkers is pertinent while constructing scFv’s or biospecific antibodies. In general, a linker length of>12 amino acid residues allows sufficient distance between the variable domains for interactions and monomer formation. Currently, linkers of length 15-20 amino acids long are being utilized to promote physical interactions of variable domains and prevent formation of dimeric forms.

Apart from the linker length, in order to design a viable and flexible peptide linker, their amino acid composition is also considered crucial. For example, hydrophilic amino acid in the linker sequence is essential to avoid intercalation of peptide within or between the variable domains throughout the protein folding ⁸ . Currently, amino acid motif (G4S) n (G: glycine, S: serine; G4S: four glycine and one serine residue) is most extensively utilized for linkers designs owing to its role in granting conformational flexibility, solubility improvement and minimal immunogenicity ⁹ . Most commonly utilized are multimers of pentapeptide (G4S) such as 15-mer (G4S) ₃ ¹⁰ , 18-mer GGSSRSSSSGGGGSGGGG ¹¹ , and 20-mer (G4S) ₄ ¹² . Apart from the Gly-Ser linker, other charged amino acid residues such as lysine and glutamic acid, sequences with functionalities (sequence containing a Cre-Lox recombination site) to enhance the scFv properties such as solubility.

Cloning methodology:

The most common method for the construction of scFv’s using either of the orientations include PCR assembly. In this method, V _H and V _L genes are inserted directly into the plasmid or phagemid through in vitro recombination after the PCR. This method allows cloning of variable domains of the antibody without prior information regarding amino acid composition and nucleic acids. Alternatively, sequential cloning or combinatorial infection are other methods being utilized for scFv (single-chain fragment variable) construction. A two-step overlapping PCR also known as Splicing by Overlap Extension (SOE-PCR) has been usually employed for cloning of the scFv. Herein, V _H and V _L domains are assembled using a single step of PCR assembly after amplification and gel-purification (Figure 2). Thereafter, using three-fragment assembly PCR (addition of linker primer) or by overlap of the two inner primers, linker is generated. An equal amount of V _H and V _L domains (50-100 ng of each domain) are utilized in the PCR assembly method in order to avoid preferential amplification of any one domain. There are two types of primers (outer and inner) being utilized in assembly PCR. The outer primers include the primers used for amplification or new pair of extension primers. The extension primers help extend the sequence from both sides of the scFv either by adding a restriction site or amplification of assembly independently for library creation. Sometimes, a few PCR cycles are performed to assemble the two variable domains before adding the outer primers. Although, the advantage of this step is not clearly established related to scFv generation.

Example of assembly reactions:

The most common assembly which have been extensively utilized include the classical (G4S)3 linker either as a three-fragment assembly or a two-fragment assembly ¹³ . The classical approach for the two-fragment assembly in scFv construction is shown below:

References

Brinkmann U., Kontermann R.E. The making of bispecific antibodies. MAbs. 2017; 9:182–212. doi: 10.1080/19420862.2016.1268307.
Ahmad Z.A., Yeap S.K., Ali A.M., Ho W.Y., Alitheen N.B., Hamid M. scFv antibody: Principles and clinical application. Clin. Dev. Immunol. 2012; 2012:980250. doi: 10.1155/2012/980250.
Krebber, A., Bornhauser, S., Burmester, J., Honegger, A., Willuda, J., Bosshard, H. R., & Pluckthun, A. (1997). Reliable cloning of functional antibody variable domains from hybridomas and spleen cell repertoires employing a reengineered phage display system. J Immunol Methods, 201(1), 35–55.
Hoogenboom, H. R., Griffiths, A. D., Johnson, K. S., Chiswell, D. J., Hudson, P., & Winter, G. (1991). Multi-subunit proteins on the surface of filamentous phage: methodologies for displaying antibody (Fab) heavy and light chains. Nucleic Acids Res, 19(15), 4133–4137.
Wang, Y., Yuan, W., Guo, S. et al. A 33-residue peptide tag increases solubility and stability of Escherichia coli produced single-chain antibody fragments. Nat Commun 13, 4614 (2022). https://doi.org/10.1038/s41467-022-32423-9 .
Huston J. S., M. Mudgett-Hunter, M. S. Tai et al., “Protein engineering of single-chain Fv analogs and fusion proteins,”Methods in Enzymology, vol. 203, pp. 46–88, 1991.
Gil, D.; Schrum, A.G. Strategies to stabilize compact folding and minimize aggregation of antibody-based fragments. Adv. Biosci. Biotechnol. (Print) 2013, 4, 73–84.
Argos P., “An investigation of oligopeptides linking domains in protein tertiary structures and possible candidates for general gene fusion,” Journal of Molecular Biology, vol. 211, no. 4, pp. 943–958, 1990.
Wang Q, Chen Y, Park J, Liu X, Hu Y, Wang T, McFarland K, Betenbaugh MJ. Design and Production of Bispecific Antibodies. Antibodies (Basel). 2019 Aug 2;8(3):43. doi: 10.3390/antib8030043.
Huston, J. S., Levinson, D., Mudgett-Hunter, M., Tai, M. S., Novotný, J., Margolies, M. N., Ridge, R. J., et al. (1988). Protein engineering of antibody binding sites: recovery of specific activity in an anti-digoxin single-chain Fv analogue produced in Escherichia coli. Proceedings of the National Academy of Sciences of the United States of America, 85(16), 5879–83.
Andris-Widhopf, J., Steinberger, P., Fuller, R., Rader, C., & Barbas, C. F. (2011). Generation of human scFv antibody libraries: PCR amplification and assembly of light- and heavy-chain coding sequences. Cold Spring Harbor protocols, 2011(9).
Schaefer, J. V, Honegger, A., & Pluckthun, A. (2010). Construction of scFv Fragments from Hybridoma or Spleen Cells by PCR Assembly. (R. Kontermann & S. Dübel, Eds.).
Marks, J. D., & Bradbury, A. (2004). PCR cloning of human immunoglobulin genes. Methods in molecular biology (Clifton, N.J.), 248, 117–34.

There Needs to Be Improved QC for Protein Reagents

Thu, 11 Aug 2022 15:38:16 GMT

Introduction

Proteins and peptides represent the most widely utilized research reagents and they are frequently employed in various therapeutic and diagnostic applications. In addition, proteins are also utilized to provide insights of functional mechanisms in structural biology, antibodies generation, cell biology experiments, chemical biology, genomics tools and microscopic assays ¹ . In order to utilize protein reagents for desired applications, there is urgent requirement of improved quality control (QC) in terms of purity, production and reproducibility. Quality control of protein reagents deemed essential for precise measurement system and ensures reproducibility over time under different operating conditions.

Despite of utilization of purified proteins in various research domains, quality control of protein reagents is not much explored and currently there are no clear standard or guidelines available to follow. The utilization of proteins and peptides are often restricted in therapeutics due to inadequate protein quality and poor data reproducibility. Moreover, there is a vast impact on both the quality and cost of research through usage of poor-quality peptides, proteins and antibodies as experimental reagents. As per statistics, a staggering economic cost of $28 billion per annum in the US alone is imposed with 50 percent irreproducible preclinical experiments from 2012 research data. Out of this $28 billion per annum economic burden, approximately $10.4 billion which equates to 36% is attributed to poor quality biological reagents and reference materials ² . In biomedical research, ability to utilize protein reagents identical to published research work is central to reproducibility. However, serious flaws in protein reagents quality and reproducibility of experimental data presents alarming situation to not only pharmaceutical industries but also to scientific community. Nevertheless, improved quality control of protein reagents is pertinent to ensure identification of poor protein quality and limit irreproducibility. Currently, with the increased awareness about the lack of reliability and reproducibility of protein reagents, there are few journals wherein authors are asked to include the quality control data of protein reagents in their studies ³ . Pharmaceutical industries generally keep a tab on quality control of reagents through highly regulated and controlled processes, however; there is no clear guidelines or standards in place in the academic research to ensure high protein quality. Consequently, there is urgent requirements of defined set of guidelines for the scientists, reviewers, editors and funding agencies to provide more reliable experimental data using protein reagents.

In order to address this obvious imbalance and the problem of data reproducibility when protein reagents are involved, a working group comprising of The Association of Resources for Biophysical Research in Europe (ARBRE-MOBIEU) and the Production and Purification Partnership in Europe (P4EU) laid down a list of recommended quality control guidelines to aid in the validation of high-quality protein samples being used in biological, biophysical and biochemical research ⁴ . The implementation of guidelines for protein quality evaluation should be considered as an entry point towards the development of improved quality control of protein reagents. The developed guidelines based on earlier available literature and extensive professional experience of a wide community of specialists from ARBRE-MOBIEU and P4EU for the quality control of protein reagents mainly comprises of three parts viz., minimal information, minimal QC tests, and extended QC tests.

1. Minimum information

Minimum information represents a list of sufficient information that should be provided in publications related to protein identity, expression and purification parameters. This information can be employed for reproducibility of experimental data in any laboratory.

Protein concentration quantification method should be provided along with storage conditions (for ex., buffer composition, pH, temperature, freezing or lyophilization techniques, wherever applicable).
Detailed description of expression and purification protocols along with complete storage conditions should be made available in case of recombinant proteins to accurately reproduce the results in any laboratory.
Complete sequence of amino acids of the final protein after cloning and expression should be given along with detailed cloning strategies to avoid unnecessary production trials.

2. Minimal Testing

Minimal QC tests comprises of simple widely available experimental methods to be tested on protein samples such as identity, purity, homogeneity, activity, and time stability and storage. These minimal QC tests provides reliable indicators regarding quality of protein being employed as reagents for yielding high reproducibility of experimental results.

Identity of protein samples should be preferably confirmed using either “bottom up” mass spectrometry (MS) (mass fingerprinting or tryptic digest) or “top down” mass spectrometry (by checking intact protein mass) ⁵ . “Bottom-up” MS identify the correct protein without any contamination. On the other hand, “top-down” MS confirm the identity of protein with information about intactness/micro-heterogeneity indicating whether proteolysis happened during purification or not. Other complementary method includes Edman sequencing.

Purity of protein samples should be assessed by using SDS-PAGE, capillary electrophoresis or Reversed-Phase-HPLC (RP-HPLC) ⁶ . These methods are being utilized to detect presence of any potential contaminants, proteolysis events etc. In addition to these methods other complementary method namely isoelectric focusing (IEF) should be employed to distinguish the protein of interest from closely related undesired products.

Homogeneity/monodispersity represents the size distribution of the protein sample and provide information regarding tendency to form aggregates or oligomeric state (monomer, dimer etc.). Polydispersity does not reflect protein instability, however the values less then 20% of dispersity (value of 0.2 and below) deemed acceptable in experimental set ups. Heterogeneity/aggregation can be preferable checked using Dynamic Light Scattering (DLS) and/or Size Exclusion Chromatography (SEC). Other complementary methods include Size Exclusion Chromatography in combination with Multi Angle Light Scattering (SEC-MALS), static light scattering (SLS), Field Flow Fractionation (FFF), or Field Flow Fractionation in combination with Multi Angle Light Scattering (FFF-MALS) or Analytical Ultracentrifugation (AUC).

3. Extended QC tests

The extended QC tests establish suitability of protein samples such as experimental reagents and are generally considered complementary in addition to the minimal QC tests. These tests are highly recommended for further characterization of proteins (folding state and specific activity) utilized in specific experimental downstream applications. Active and functional status of proteins are confirmed by measuring the activity of protein samples after homogeneity assessment.

The methods utilized for activity determination includes active concentration measurement using Surface plasmon resonance (SPR), and total concentration measurement using Bradford, bicinchonic acid or Lowry assays. The extended quality control tests include general quality testing by UV spectroscopy, protein competent fraction (specific activity) determination using surface plasmon resonance (SPR) technique, conformation/folding state determination using Fourier Transform InfraRed (FTIR), Circular Dichroism (CD), Differential Scanning Calorimetry (DSC), and Nuclear Magnetic Resonance (NMR) spectroscopy, endotoxin/lipopolysaccharides content analysis and batch to batch consistency assessment. In addition, extended QC tests include homogeneity assessment using complementary methods such as analytical Ion Exchange Chromatography (IEC), analytical Hydrophobic Interaction Chromatography (HIC) or Isoelectric Focusing (IEF).

Taken together, the ability to reliably reproduce the experimental data as well as the confidence level in the published data employing protein reagents would significantly improve with the proposed list of recommended QC guidelines.

References

____________________________________________________________________________________________

Raynal B, Lenormand P, Baron B, Hoos S, England P. Quality assessment and optimization of purified protein samples: why and how? Microbial Cell Factories 2014; 13:180.
Freedman, LP, Cockburn, IM, Simcoe TS. The economics of reproducibility in preclinical research. PLoS Biol. 13, e1002165 (2015).
Reproducibility: let’s get it right from the start. Nat. Commun. 9, 3716 https:// doi.org/10.1038/s41467-018-06012-8 (2018).
de Marco A, Berrow N, Lebendiker M, Garcia-Alai M, Knauer SH, Lopez-Mendez B, Matagne A, Parret A, Remans K, Uebel S, Raynal B. Quality control of protein reagents for the improvement of research data reproducibility. Nat Commun. 2021 May 14;12(1):2795. doi: 10.1038/s41467-021-23167-z.
Tipton JD, Tran JC, Catherman AD, Ahlf DR, Durbin KR, Kelleher NL. Analysis of intact protein isoforms by mass spectrometry. J Biol Chem 2011, 286:25451–25458.
Fekete S, Veuthey JL, Beck A, Guillarme D. Hydrophobic interaction chromatography for the characterization of monoclonal antibodies and related products. J Pharm Biomed Anal. 2016; 130:3-18.

In Response to Current Global Supply Disruption

Fri, 13 May 2022 16:39:14 GMT

kbDNA has ready-to-ship products in North America

Disruptions in Asia are weighing on the global supply chain. In the U.S, the effects can be felt all across research laboratories, especially in bioscience sectors. Whether it's equipment, consumables or specialty reagents; everyone seems to be waiting on overdue products and ambiguous delivery dates.

As domestic providers, we offer more flexibility to help resolve immediate laboratory needs. Contact us at kbDNA for general product inquiries.

Products Include:

If you are experiencing order delays...

Send us a brief description of your product needs. We will get back to you with pricing & lead time!

The Research Reagent Paradox: A Process Review

Fri, 01 Apr 2022 02:29:19 GMT

Research Reagent Paradox

Introduction

The topic of material and supply has been a mystery to many in the world of life science research. Mostly to the researchers who aren’t traditionally required to care about such distractions. For years, several support departments called procurement, vendor management, etc. have been the standard for delegating these responsibilities away from the scientists. However, things have changed in the past decade with the help of ecommerce, the commercialization of basically all laboratory research material has been commoditized directly to the end-user. In other words, researchers are now doing their own shopping of laboratory supplies-especially their critical reagents.

Critical reagents can be a range of biomolecules produced for research-use, and express special characteristics. Often in their genetic or sequence specificity, these reagents are referred to as “analyte-specific”. Examples include recombinant proteins or monoclonal antibodies (very popular) and nucleic acid sequences of DNA/RNA or their short strand oligo-form. Critical reagents are much more sophisticated products compared to other laboratory consumables.

Many researchers begin experiencing the similar patterns in handling reagents. Our background as end-users, suppliers, and producers enables our team to utilize our insight to make sense of these patterns through what we refer to as, The Research Reagent Paradox.

Research Reagent Paradox

The research reagent paradox is a diagram analyzing components connecting manufacturing, supply-chain, and scientific research. This serves as a novel approach for analyzing, combining, and interpreting relatively complex intricacies into a big picture design. The research reagent paradox aims to reinforce every scientist and research professional with proper understanding of the reagents they depend on.

The diagram applies a simplified view of a molecules journey to a reagent and features the unique role data plays in transforming the process into a cycle. By focusing on stages of manufacturing, selling, and applying a research reagent; our schema can illustrate how data leverages a strong feedback effect that deserves focus in center stage.

In this paper, we present brief summaries of significant factors in each stage and conclude with a case for optimizing the dynamic.

Current Data Dilemma

Data. What’s most precious inside a research laboratory loses significant consideration as moves away from the bench. In chemical manufacturing, data technology is generally low. With reagents, its low on both sides of the industry. Decades of scientific data being generated in different computing formats and no updates to legacy records has resulted in very rich scientific databases drowning in errors. Many of which serve as standard registries for their topic of focus. Whether it’s nucleic acid sequences, protein profiles or chemical libraries, the inconsistency and lack of uniformity in these databases has been a growing issue in use as reliable reference data. Additionally, the recent boom in bioinformatics further complicates the issue. The recent influx of computer scientists in life science research is historic. However, these new additions come pioneering their own data revolution in emerging and exciting fields such as the “complex-omics”. The rapid generation of their new sophisticated data is considerably more compelling and threatens to eclipse the issues of legacy databases. With minimal attention as is, decreased awareness further risks procrastinating a solution.

We want to be cautious with discussing data as it is easy to crossover to the topic of software and similar challenges in bioresearch. This is not about software or software engineering. Following sections will touch on some software components in relative terms. However, our focus is specific to data and its application.

Next, we will discuss how data translates into the beginning stage of reagent manufacturing and continues.

Stage 1. Production

Transforming an agent (molecule, chemical, formula, etc.) into a reagent begins with the production step. To clarify, the term “reagent” refers to the former (‘agent’) in the shape of a product. In other words, a reagent is the synthetic version of a certain biological molecule. Such molecules include nucleic acids, enzymes, antibodies, and other proteins- expressing specific genetic characteristics. Although this concept is generally understood, not many are familiar with the underlying development process and challenges-as is the case with many commodities. However, research reagents are different. The argument can be made that the commoditization of such complex material has been a leading factor to many of the manufacturing issues- faced today. To comprehend this, we must first understand the basics and state of specialty reagent manufacturing.

Production systems rely on the legacy databases as much as researchers, but in differing application. Almost all data required to design a manufacturing blueprint for reagents can be found in their respective registries. The planning time and labor saved is significant enough to rationalize against preliminary in-house validation. The approach of feeding these unvalidated blueprints into production systems has become common practice. Errors are then exposed throughout the process workflow. To counter errors, facilities use costly in-house troubleshooting by way of empirical methods and chemical trialing. The repeat success of troubleshoots optimize the initial blueprint and bring rise to a new practice of exclusive in-house formulations and in-house protocols. Unlike open-source data, the true value of these protocols is their inclusion of process variables and expert knowledge which often comes from analytical experience. This information cannot be calculated through modeling or computational methods. Its competitive gating further widens the gap between software and manufacturing.

Surrounding factors don’t leave much choice for production teams. Biomanufacturing systems are not versatile by nature. The equipment is insanely expensive/complex, the software is archaic, and there’s minimal automation between steps. This makes them incompatible to periodic innovation and impractical to renovate from scratch. Not to mention, manufacturing facilities are often running on an as-needed workforce. Meaning limited personnel – regularly overseeing a multitude of simultaneous production runs. What engineers have been able to achieve thus far using such raw data in suboptimal conditions is remarkable. It’s hard to ignore the potential with more flexibility and data integrity involved. For now, this system works in the sense that its capable of delivering a reagent in product form for research application. As a product, reagents become commercially available to research.

The next section provides an overview of how the marketplace operates. Continue reading as this process picks up in the hands of its sellers and buyers.

Stage 2. Supply Chain

Supply chain is its own phenomena in life science. We refer to it as the wild west of life sciences. An arena filled with manufacturers, distributors, 3 ^rd party resellers, foreign entity sales hubs and everything in-between! None of which are outlaws, technically. The term “wild west” refers to the untraditional and often confusing exchanges between these companies in order to meet demand. The landscape plays by its own economics. With a shared objective of getting a product or service into research, science finds a way to reject market principles and complicate the supply process like no other industry. As proud members of this landscape, we have seen and experienced this on the frontline. Having to support both an in-house R&D model along with a supplier origin, we can keep the insight relevant to reagents.

It is important to understand that when a reagent arrives to supply chain it is considered a final product. In other words, most datasheet specs are final and not designed to be modified. Doing so would be costly for most sellers and disrupt their cost model-which is often based on inventory logistics. However, scientific research is very specific. Seldom does a researcher approach procurement by asking what’s available and basing experiments off those options. The need is specific. They need specific analytes that meet specific parameters for specific features to try and achieve specific results. With the inability to modify final products, the popular approach has been to build extensive catalogs filled with thousands of analyte reagents in varying forms with diverse features. An overwhelming attempt at presenting a higher probability of compatibility to such specific demand. Thus, it’s impossible to manufacture this many reagents under one roof. Proven by what we’ve discussed so far; co-op, cross-selling deals between every and any company that can help meet a researchers criterion becomes natural practice. Although, counterproductive over time as many companies find themselves sharing identical catalogs from similar suppliers -who in random cases are reselling from resellers. One principle that does apply here is the increase in cost and lead time as a product exchange hands. This makes sense to why prices of reagents vary so drastically from different companies. With no standard pricing in place, the list price for a small-scale reagent (10uL-1mg) can range from hundreds to thousands of dollars depending on the supplier agreement.

Consequently, the growing trends of current supplier models are affecting the industry in more ways than price and lead time. With many catalogs selling reagents via ecommerce “add-to-cart” and little to no engagement of the end-user with the source manufacturer, product feedback quality remains poor. Feedback of how a reagent performs against different applications is critical for optimizing its blueprint. Data such as results under certain experiment conditions or in combination with other agents has been historic to developing new products. However, the online buying convenience and debased buyer communication model limits the level of value supply chain can offer research. While an efficient approach to meet short-term needs for small scale reagents, it proves unsustainable when a reagent enters scale-up demand for long term use. We’ve yet to see the latter be achieved without diligent communication.

Ultimately, the goal of supply chain is to get the product into the buyers’ hands which in this case is the “end-user”. It is generally agreed that the success of this is defined by your reagent performing well in an end-user’s research. This baseline is key for transitioning into the final stage of the reagent paradox. All roads lead to the end-user’s research.

Stage 3. End-User

The scientific end-user is the ultimate destination for any research reagent. Reagents are a critical for running experiments and driving results. Consequently, data produced from these results plays a novel role in our paradox. One might assume that a reagents journey ends once finally consumed by the end-user. We would argue that the journey, in fact does not end; but instead, proceeds into a cycle. Consider the prerequisite sharing practices of scientific research. Bulk of research data is distributed through journal publication or similar. As well as less formal methods such as posters, legacy databases, etc.

In any case, data is presented via strict guidelines which includes the experiment details. An essential section titled “materials & methods” is where a reagent lives on. For many years the materials section allowed scientists to effectively discover and source new reagents. It acted as a feedback system for performance and incentivized better production.

Although this is no mystery, it’s value has become underrated as search engines and other 3 ^rd parties quickly become the initial procurement tool. Materials and methods also serve as a quality reference for manufacturers to help tailor products to various applications and optimizing reagent formulation. Thus, contributing to the initial manufacturing stage keeping the cycle constant.

Concluding Analysis

The factors discussed for each stage are specific to the paradoxical dynamic of the process. With the analysis of scientific database deficiencies, production innovation limits, disconnects in supply-chain and the ultimate role of end-user’s research data – we provide insight on hindering factors to support a unique perspective for the value of reagents in scientific research. This allows process illustration of the significant stages throughout reagent development to its application via “The Research Reagent Paradox”. Emphasis on oversight of data and the misalignment of values at each stage suggest key areas of focus going forward.

In addition to greater focus, our diagram also serves as an immediate resource to researchers or similar buyers of reagents. The information can be essential in building a competitive sourcing strategy for laboratories. We recommend utilizing it to optimize due diligence when sourcing a reagent. In our experiences, this is the best way to minimize compromise and risk of experimental error,

References

____________________________________________________________________________________________

C.F. Mandenius

Recent developments in the monitoring, modeling and control of biological production systems

Bioprocess Biosyst Eng, 26 (2004), pp. 347-351

J.E. Bailey

Mathematical modeling and analysis in biochemical engineering: Past accomplishments and future opportunities

Biotechnol Prog, 14 (1998), pp. 8-20

A.S. Rathore, R. Bhambure, V. Ghare

Process analytical technology (PAT) for biopharmaceutical products

Anal Bioanal Chem, 398 (2010), pp. 137-154

M. Stojcev, T. Tokic, I. Milentijevic

The limits of semiconductor technology and oncoming challenges in computer micro architectures and architectures

Facta Univ - Ser Electron Energ, 17 (2004), pp. 285-312

H. Narayanan, et al.

Bioprocessing in the Digital Age: The Role of Process Models

Biotechnol J, 15 (2020), pp. 1-10

W. Sommeregger, et al.

Quality by control: Towards model predictive control of mammalian cell culture bioprocesses

Biotechnol J, 12 (2017), pp. 1-7

S. Shioya, T. Takamatsu, K. Dairaku

Measurement of State Variables and Controlling Biochemical Reaction Processes

IFAC Proc, 16 (1983), pp. 13-25

M. Kishimoto, T. Sawano, T. Yoshida, H. Taguchi

Application of a statistical procedure for the control of yeast production

Biotechnol Bioeng, 26 (1984), pp. 871-876

J.H. Lee

Model predictive control: Review of the three decades of development

Int J Control Autom Syst, 9 (2011), pp. 415-424

A predictive high-throughput scale-down model of monoclonal antibody production in CHO cells

Biotechnol Bioeng, 104 (2009), pp. 1107-1120

S. Nargund, K. Guenther, K. Mauch

The Move toward Biopharma 4.0

Genet Eng Biotechnol News, 39 (2019), pp. 53-55

Accelerating biologics manufacturing by modeling or: Is Approval under the QbD and PAT approaches demanded by authorities acceptable without a digital-twin?

Processes, 7 (2019), pp. 1-28

Pinu, F. R., Beale, D. J., Paten, A. M., Kouremenos, K., Swarup, S., Schirra, H. J., & Wishart, D. (2019). Systems biology and multi-omics integration: Viewpoints from the Metabolomics Research Community. Metabolites, 9(4), 76. https://doi.org/10.3390/metabo9040076

Manzoni, C., Kia, D. A., Vandrovcova, J., Hardy, J., Wood, N. W., Lewis, P. A., & Ferrari, R. (2016). Genome, transcriptome and proteome: The rise of OMICS data and their integration in Biomedical Sciences. Briefings in Bioinformatics, 19(2), 286–302. https://doi.org/10.1093/bib/bbw114

Reference: Compounds for DNA Synthesis

laithik@gmail.com (L L) — Thu, 02 Dec 2021 15:01:44 GMT

Compounds for DNA Synthesis

See the full list of in-house DNA Compounds used in our synthesis below:

Our DNA Synthesis Toolbox

Along with an extensive selection of base-carrying phosphoramidites, our DNA synthesis toolbox includes; standard and mild 3’ base protection options with a variety of CPG supports, functional backbone modifications, duplex stabilizers and more. These compounds allow our synthesis to pursue challenging techniques such as 5’->3’ synthesis and heavy reinforcements to the nucleotides. Additional in-house compounds are categorized into their respective applications. Most notably chain termination for PCR/Sequence Utility, structural studies, DNA mutagenesis/repair, diagnostics, and therapeutics.

See the full list of in-house DNA Compounds used in our synthesis below:

DNA Synthesis

DNA: 5'→ 3' Synthesis

DNA: Backbone modification

DNA: Duplex Stabilization

DNA: PCR/Sequence Utility

DNA:Structural Studies

DNA Modifiers

laithik@gmail.com (L L) — Wed, 01 Dec 2021 14:39:51 GMT

DNA Modifiers

See the full list of in-house DNA Modifiers used in our synthesis below:

Modifying DNA During Synthesis

Modifying DNA during synthesis involves a bit of creativity along with untraditional chemistry throughout the synthesis workflow. Different classes of modifiers have grown over time, but the most tried and true begins with 3’ or 5’ amino modifiers and the use of spacers and “branching” modifications. This paved the way for introducing more elaborate modifiers into sequences, such as compounded functional groups and a wide array of labels.

RNA DNA Modifiers

Labelling

Tackle Key PTMs Disrupting your Research Molecules

Tue, 05 Oct 2021 17:33:00 GMT

Post-translational modifications are extensive and challenging to study. We focus on 10 key chemistries:

In-Vivo Proteins Essentials [CATALOG]

laithik@gmail.com (L L) — Tue, 24 Aug 2021 17:26:57 GMT

Find your protein of interest using our novel catalog method. This guide offers an updated catalog on recombinant expression technology and features kbDNA's in-vivo protein products including key analytes for the following libraries: Biomarkers, Immune-targets,Hormones,Heat Shock,Cytokines,Infectious Disease,Glycobiology, Assay Proteins, biosimilars

Is it Time for COVID to Start Sharing the Spotlight?

Sun, 25 Apr 2021 05:11:56 GMT

A case for the unsung research achievements made during the pandemic.

Introduction

The events of the recent pandemic will stay with us forever, but it might be time for us to start paying more attention to what else has been going on in the world. It is tough to compete with the appeal of the COVID controversy, and for most news outlets, reader behavior decides what gets prioritized. This can be especially challenging for biotechnology and life science organizations considering the industry’s role in the pandemic response. In fact, a significant number of those organizations continued their non-COVID research during the crisis. Yet, the focus stays fixed on COVID19 at any cost. In turn, diluting the attention to the rest of the industry. Introduction

In the past 14 months, our team has been fortunate to work with various laboratory groups engaged in fascinating research unrelated to COVID. Many of these groups have made significant progress during the pandemic. Sadly, their major press releases could not compete with the number one globally trending topic.

In this article, we will outline key (life science) research advancements during the pandemic alongside our industry insight to support the case for increasing focus on compelling non-COVID research.

The Diagnostics Race

Armed with new data for improving biomarker specificity, kit sensitivity and production; diagnostics teams can begin applying this knowledge toward new platforms and other indications beyond SARS-CoV-2.

Before straying too far from the topic of COVID, it is worth recognizing its stimulatory effect on the R&D of certain industries. One such industry is that of diagnostics. If it felt like all your supplier websites suddenly became catalogs for SARS-CoV-2 primers and spike protein the past year, you are not alone. Kit developers were off to the races and nothing gets things started quicker than next day delivery research-use-only (RUO) reagents. Bringing with it a unique demand, the competition to build a screening assay to fast-track into market was an opportunity for both the Davids and Goliaths. While larger players such as PerkinElmer and Abbott Laboratories saw a way to expand their ready platforms, many smaller and emerging biotech’s differentiated by repurposing principal technology into optimizations. This led to more comprehensive and more rapid tests from many companies including Excelsior Diagnostic’s, GenMark, Hologic, etc.

Enhancing biomarker detection

Regardless of size or market position, all diagnostic companies relied on innovation to meet the novel challenges of COVID19. This dynamic is turning out to be much more favorable in the long term. Throughout all the hyper-research, the industry pumped out more editorials and optimizing protocols than before. Additionally, this information mostly related to the underlying principles of detection technology and manufacturing. Armed with new data for improving biomarker specificity, kit sensitivity and production; diagnostics teams can begin applying this knowledge toward new platforms and other indications beyond SARS-CoV-2.

The revival of neuroscience

One notable field that can greatly benefit from all of the aforementioned optimizations is Neuroscience. While attitudes toward neurobiology and neurodegeneration tend to be discouraging, it is hard not to get excited about some of the movements in neuro medicine. Sensory medicine took a big step forward in 2020 with the collaboration between Blueprint Medicines and Akouos to pioneer their resonate program’s genetic testing for auditory neuropathy.

Following the exodus of Alzheimer’s candidates a few years back, returning to the drawing board may have been beneficial for the researchers. Credit to material science, labs now have the advantage of using more advanced research molecules to support versatile characterization methods which can work against post-translational modifications and varying neurochemical conditions. In other words, the molecules in the brain are challenging to produce as reagents- and even more challenging to study. Tools like cell-free protein synthesis and bioinformatics are changing that. This was demonstrated during the pandemic as these tools were leveraged to support significant research discoveries with ALS biomarker detection.

Strides in Novel Therapeutics

Here is where things get a bit tricky. There is a lot of exciting stuff going on with therapeutics, making it a challenge to choose what information to leave out. Because therapeutics is a relatively sensitive market, the discussion will focus more on the science and research than names and examples.

Here are the two novel highlights worthy of attention in therapeutic medicine:

Melzer, D., Pilling, L.C. & Ferrucci, L. The genetics of human ageing.

Nat Rev Genet 21, 88–101 (2020). https://doi.org/10.1038/s41576-019-0183-6

Epigenetics

One of the most appealing fields of study, Epigenetics used the year to lay more bricks into its foundation. In addition to the original inhibitor and biologic, epigenetics was introduced to the degrader approach following published success in metabolomics. Meanwhile, the mechanism of RNA targeting enzyme modifications broke ground with the first epigenetics candidate selected for cancer treatment (STORM Therapeutics, UK). Great promise for epigenetics oncology continued with the spin-out from academia introducing a unique biotech utilizing microRNA to simultaneously suppress multiple oncogenic pathways

Immunology

Things have not been the same for immunology since recent breakthroughs with immune checkpoints targets such as PD1 and CTLA4. The field and its modestly sized immunologist community are scattered among laboratories who are researching one of a few specialties with passion. Meanwhile, the science has become a standard throughout all areas of discovery. This has occurred most notably in the form of assays or immunoassays, characterizing antibodies, cytokines, and other immune-related pathway molecules, etc. This has helped drive the natural curve of innovation with laboratory reagents and instrumentation. For example, at kbDNA - we rely on these same reagents to develop our products. Mostly as recombinant proteins/antibodies to run quality control and guide product optimization. We experienced how immune-related molecules played a role in all disciplines. These molecules are complicated and some of their structures are impossible to research without constant innovation. That is why we’ve separated immunology proteins into their own recombinant library, making them part of our material science and R&D process.

Immunology may be applicable in all areas, but the relationship is particularly unique with certain disease areas. This was also expressed in trends of recent researchs

Multiple Sclerosis

If you are familiar with the history of multiple sclerosis research, you’d understand the frustration with characterizing this indication. However, in the past year significant discoveries have surfaced with how the disease links to the gut microbiome. This is a big deal, as two distant scientists arrive at this in the same year, and the basis of the discovery relates to the study of inflammation-which happens to be a booming topic right now in immunology. To keep it general; we should assume that Interleukins will be coming up more in conversation in the near future (particularly IL-17 & IL-6)

TALON

The icing on the cake for AI was Merck’s acquisition of an emerging biotech called Pandion Therapeutics. Since CRISPR did nearly as well in the news as COVID this past year, people forgot there was another gene-editing tool named TALON that seemed to work well. Pandion was one of few adopters that stayed consistent with the method and from a commercial standpoint, there is humor in the TALON vs. CRISPR rivalry. Even now, after CRISPR has dominated the attention for years, a 2020 comparison study further suggests that TALEN outperforms Cas9 in key target editing(heterochromatin target sites). The irony continues.

Disruptive Proteomics

Degradation; as a mechanism, offers desirable advantages that can rival conventional inhibition.

In mid-December, Google announced a breakthrough in its machine learning program, DeepMind. There are rare moments where conglomerates outside the industry can captivate us in our own disciplines and when they do, the response is always mixed. DeepMind’s ability to match >90% conformity of a molecule’s structure was undeniably impressive. However, what was more impressive was how much more exposure it provided to the role of computer science in proteomics. The value of proteomics is not new, but the standardization of protein bioinformatics is. Along with expanding the analytical toolbox, software is proving just as crucial for new clinical methods. We recently saw the advancement of one of these game changing methods and the discovery of another. continued with the spin-out from academia introducing a unique biotech utilizing microRNA to simultaneously suppress multiple oncogenic pathways

Protein Patches

Cell signaling continues to be a challenge for biologists. Given the transient nature of the process (through endocytosis), the efficiency of therapies or monoclonal antibodies targeting signaling receptors is significantly reduced. To overcome this, researchers recently designed a self-assembling technology. This involves 2+ protein components to scaffold into flat patches for engineering signaling molecules. The technology is coined “protein patches”. Recognized as degronLOCKR, the approach shows potential for immunotherapy solutions along with greater capabilities off of which we can build. Designing proteins around cells opens new doors for a wide range of applications.

Protein Degraders

2020 was a big year for protein degradation. Pioneers of the degrader approach went beyond proof-of-concept by solving key scientific problems involving the ubiquitin challenges and ligase chemistry. The role of proteomics teams has proven essential in developing the science into disruptive platforms. In turn, the case for therapeutic degraders as a competitive front runner for drugging the undruggable grows stronger. With new candidates announced during the pandemic, these platforms show great promise for downstream diversification of their pipelines. It is worth considering the general principles that make degrader drugs special in potential. Degradation; as a mechanism, offers desirable advantages that can rival conventional inhibition. With a plethora of inhibitor drugs currently on the market, the fundamental question is “how far can the technology go? “-We won’t know for sure until more formulations/compounds are clinically tested. However, it is not every day that medical research sees a principal mechanism with broad range potential. That alone makes it worth keeping an eye on the protein degradation market.

RNA Continues to Interfere

mRNA

The world was officially (re)introduced to RNA last year. More specifically mRNA, as it became synonymous with the COVID19 vaccine. However, RNA’s fame was not limited to just COVID during the pandemic. Nucleic acid chemistry accelerated in a variety of different areas with RNA technology. Some areas, very unexpectedly, included the manufacturing sector. mRNA serves an underrated role in the innovation of cell free expression, an in-vivo protein synthesis system to produce research recombinant proteins. We witnessed the technology raise the stakes with the addition of over 100 new challenging, multi-dimer proteins to the catalog along with their application in a new bead array. The array holds ~20,000 human full-length proteins and can be used for studying protein-protein interactions such as binding specificity.

RNAi

The year of the pandemic was business as usual for the antisense market. As the technology continued to grow its presence in different disease areas, so did the list of antisense oligonucleotides (ASO) acronyms. As of May 2020, two siRNAs have received FDA approval: Patisiran and Givosiran. Both of those drugs are considered precision duplex silencers which come with significant design benefits in terms of reducing passenger strand activity and/or improved potency. Separate from that, data was published for the first in-human clinical trial for an saRNA(small activating RNA ) upregulating therapy in late-stage liver cancer patients, marking a key milestone for the saRNA technology. Meanwhile, new developments also occurred in this space related to spherical nucleic acids (SNA) in neuroscience and new exciting applications of siRNA to tackle central nervous systems disorders. However, the outcomes for those innovations are still in progress, so their potential is yet to be fully understood.

Conclusion

Research and scientific discovery did not pause during the pandemic, even within fields unrelated to COVID. A strong argument can be made for their importance, even compared to many of the over-prioritized COVID headlines of the past year.

Keep in mind that the information above is only a fraction of the significant research of the last year. It would be virtually impossible to mention all the achievements of 2020 in a short article, so we chose the topics that were most closely related to kbDNA’s research and areas of competency. However, we greatly appreciate and thank all other research efforts that marched on throughout the pandemic - both COVID and non-COVID. It makes us proud to work alongside such determined scientists despite all the challenges the industry has faced. Our team is looking forward to finding more ways to promote research discovery teams and their exciting science.

An Ultimate Guide for Building Oligos

laithik@gmail.com (L L) — Wed, 03 Mar 2021 18:21:46 GMT

An Ultimate Guide for Building Oligos

Reinforce Your Sequence Design:

Formatted for productive interpretation

Categorized by nucleotide function and structure class

Analyzing Purification for Optimal Bioseparation

Tue, 12 Jan 2021 21:02:13 GMT

Analyzing Purification for Optimal Bioseparation

Methods comparison; size-exclusion, ion-exchange and affinity chromatography

Introduction

Several biological products such as biochemicals, biopharmaceuticals, foods, nutraceuticals, and agrochemicals require extensive purification and analysis before they can be used for their respective applications. The efficient removal of interfering matrix components followed by fast and accurate quantitation of biomolecules has become increasingly important following any bioprocess. The practice of purifying biological analytes on a large-scale, using fundamental aspects of engineering and scientific principles is termed bioseparation . Separating complex mixtures into purified fractions containing specific molecules of interest is the end goal of bioseparation. It is a broader term than the slightly dated downstream processing which specifically referred to the separation and purification segment of a bioprocess which followed some form of biological reaction e.g. purification of an antibiotic following microbial fermentation. The purification of biological products from their respective starting material e.g. cell culture media is technically difficult and expensive. This could frequently be the critical limiting factor in the commercialization of a biological product.

Biomolecules such as carbohydrates, proteins and nucleic acids cannot withstand the rigors of traditional chemical separation techniques and require the use of special methods. For instance, organic solvents, which are widely used in chemical separations, have relatively limited usage in bioseparations on account of their tendency to promote degradation of many biological products. Bioseparation techniques have to be “gentle” in terms of avoiding extremes of physicochemical conditions such as pH and ionic strengths, hydrodynamic conditions such as high shear rates, and exposure to gas-liquid interfaces. Some biologically derived substances such as antibiotics and other low molecular weight compounds such as vitamins and amino acids are purified using conventional separation techniques such as liquid-liquid extraction, packed bed adsorption, evaporation and drying with practically no modifications being necessary. However, substantially modified separation techniques are required for purifying more complex molecules such as proteins, lipids, carbohydrates and nucleic acids. Often, totally new types of separation techniques have to be devised.

Biological products are separated and purified based on one or more of the following properties:

Size: e.g. filtration, membrane separation, centrifugation
Density: e.g. centrifugation, sedimentation, floatation
Diffusivity: e.g. membrane separation
Shape: e.g. centrifugation, filtration, sedimentation
Polarity: e.g. extraction, chromatography, adsorption
Solubility: e.g. extraction, precipitation, crystallization
Electrostatic charge: e.g. adsorption, membrane separation, electrophoresis
Volatility: e.g. distillation, membrane distillation, pervaporation

Bioseparation is frequently based on multi-technique separation. Typically, low-resolution techniques (e.g. precipitation, filtration, centrifugation, and crystallization) are used first, for recovery and isolation, as they significantly reduce the volume of material being processed. This is followed by high-resolution techniques (e.g. affinity separations, chromatography, and electrophoresis), for purification and polishing. Three key analytical and purification methods are: electrophoresis, ultracentrifugation, and chromatography. Each one relies on certain physicochemical properties of different biomolecules.

Electrophoresis:

Many important biological molecules such as proteins, deoxyribonucleic acid (DNA), and ribonucleic acid (RNA) exist in solution as cations or anions. Under the influence of an electric field, these molecules migrate at a rate that depends on their net charge, size and shape, the field strength, and the nature of the medium in which the molecules are moving. Thus, separation is based on both the molecular sieve effect and on the electrophoretic mobility of the molecules. This method determines the size of biomolecules. It is used to separate proteins, and especially to separate DNA for identification, sequencing, or further manipulation.

Ultracentrifugation:

Cells, organelles, or macromolecules in solution exposed to a centrifugal force will separate because they differ in mass, shape, or a combination of those factors. An ultracentrifuge generates centrifugal forces of 600,000 g and more. It is an indispensable tool for the isolation of proteins, DNA, and subcellular particles.

Chromatography:

Chromatography encompasses a diverse and important group of methods that allow the separation, identification, and determination of closely related components of complex mixtures. Chromatographic separation entails separation of sample components based on differential affinity for a mobile versus a stationary phase. The mobile phase is a liquid or a gas that flows over or through the stationary phase, which consists of spherical particles packed into a column. When a mixture of proteins is introduced into the mobile phase and allowed to migrate through the column, separation occurs because proteins that have a greater attraction for the solid phase migrate more slowly than do proteins that are more attracted to the mobile phase. Several different types of interactions between the stationary phase and the substances being separated are possible and hence various parameters can be used to categorize chromatographic methods (Table 1).

Table 1: c:

Table 1: Classification of chromatographic techniques based on various parameters.

Paper chromatography

In paper chromatography the support material consists of a layer of cellulose highly saturated with water. In this method a thick filter paper comprises the support, and water drops settled in its pores make up the stationary “liquid phase.” Mobile phase consists of an appropriate fluid placed in a developing tank. Paper chromatography is a “liquid-liquid” chromatography (Fig 1). It is primarily used to separate colored substances.

Fig 1: Paper chromatography

Gas Chromatography

In this method the stationary phase is a column which is placed in the device, and contains a liquid stationary phase which is adsorbed onto the surface of an inert solid. Gas chromatography is a “gas-liquid” chromatography. Its carrier phase consists of gases such as He or N2. An inert gas, which forms the mobile phase, is passed through a column under high pressure. The sample to be analyzed is vaporized, and enters into this gaseous mobile phase. The components contained in the sample are dispersed between the mobile phase, and the stationary phase on the solid support. Gas chromatography is a simple, multifaceted, highly sensitive, and rapidly applied technique for the extremely excellent separation of very minute molecules. It is used in the separation of very small amounts of analytes.

Thin Layer Chromatography

Thin-layer chromatography is a “solid-liquid adsorption” chromatography. In this method the stationary phase is a solid adsorbent substance coated on glass plates. As the adsorbent material all solid substances used in column chromatography (alumina, silica gel, cellulose) can be utilized. In this method, the mobile phase travels upward through the stationary phase. The solvent travels up the thin plate soaked with the solvent by means of capillary action. During this process, it also drives the mixture, priorly dropped on the lower parts of the plate with a pipette, upwards with different flow rates. Thus the separation of analytes is achieved. This upward travelling rate depends on the polarity of the material, the solid phase, and that of the solvent.

Fig. 2. Thin layer chromatography.

Ion-exchange Chromatography

Ion-exchange chromatography is based on the electrostatic interactions between charged protein groups, and solid support material (matrix). The matrix has an ion load opposite to that of the protein to be separated, and the affinity of the protein to the column is achieved with ionic ties. Proteins are separated from the column either by changing pH, concentration of ion salts or ionic strength of the buffer solution. Positively charged ion-exchange matrices are called anion-exchange matrices and they adsorb negatively charged proteins. While matrices bound with negatively charged groups are known as cation-exchange matrices, and they adsorb positively charged proteins.

Fig. 3. Ion exchange chromatography.

Gel Filtration Chromatography

Gel filtration (also called size-exclusion chromatography or SEC) uses a porous resin material to separate molecules based on size (i.e., physical exclusion). The sample is applied to the top of a column consisting of porous beads made of an insoluble but highly hydrated polymer such as dextran or agarose (which are carbohydrates) or polyacrylamide. Sephadex, Sepharose, and Bio-gel are commonly used commercial preparations of these beads, which are typically 100 μm (0.1 mm) in diameter. Small molecules can enter these beads, but large ones cannot. The result is that small molecules are distributed in the aqueous solution both inside the beads and between them, whereas large molecules are located only in the solution between the beads. Large molecules flow more rapidly through this column and emerge first because a smaller volume is accessible to them. Molecules that are of a size to occasionally enter a bead will flow from the column at an intermediate position, and small molecules, which take a longer, tortuous path, will exit last.

Fig. 4. Size-exclusion chromatography.

Hydrophobic Interaction Chromatography (HIC)

In hydrophobic interaction chromatography, hydrophobic residues on the protein’s surface interact with hydrophobic ligands attached to a hydrophilic chromatographic resin. The type of hydrophobic ligand and its concentration on the resin are important parameters that control its separation properties. The type of hydrophobic ligand, for example the varying links of alkyl chains, in its concentration on the resin are important parameters of the resin that control its hydrophobicity and separation properties. In HIC, the interaction of the protein with the resin is modulated by adding or removing anti-chaotropic salts, such as ammonium sulfate, to the buffer. High salt concentrations promote adsorption to the hydrophobic groups in the column. Therefore, to elute adsorbed proteins for the column, the salt concentration is decreased. As the salt concentration is decreased, proteins of increasing hydrophobicity will desorb and elute from the column. HIC is often most useful as a polishing step to remove higher molecular weight impurities that may not be removed by other methods.

Fig. 5. Hydrophobic interaction chromatography.

Affinity Chromatography

Affinity chromatography is one of the oldest forms of liquid chromatography. The first use may be considered as the isolation of α-amylase by using an insoluble substrate, starch, in 1910 just three years after the discovery of chromatography. This chromatographic technique has become increasingly important in work with pharmaceutical agents, biochemical and biological samples, clinical chemistry and environmental science.

It is one of the most diverse and powerful chromatographic method for the purification of a specific molecule or a group of molecules from a complex mixture by the selective non-covalent interaction of solute with a ligand (which is immobilized). The wide applicability of this method is based on the fact that any given biomolecule that one wishes to purify usually has an inherent recognition site through which it can be bound by a natural or artificial molecule. Thus, we can say that affinity chromatography is principally based on the molecular recognition of a target molecule by a molecule bound to a column.

Application of affinity chromatography has significant advantages. The important one is that affinity chromatography involves many types of interactions between ligand and target such as steric effects, hydrogen bonding, ionic interactions, van der Waals forces, dipole-dipole interactions and even covalent bonds while other chromatographic techniques involve just one or a few of them. The combination of these multiple interactions leads to separation with high selectivity and retention in affinity chromatography. In addition to its solute purification potential, affinity chromatography also possesses considerable potential for investigating the functional roles of the reactants purified.

Affinity purification involves three main steps (Fig. 6):

Incubation of a crude sample with the affinity support to allow the target molecule in the sample to bind to the immobilized ligand.
Washing away non-bound sample components from the support.
Elution (dissociation and recovery) of the target molecule from the immobilized ligand by altering the buffer conditions so that the binding interaction no longer occurs.

Fig. 6. Affinity chromatography.

Affinity Ligands

In order to distinguish the techniques according to the origin of the ligand, affinity chromatography with biological ligands may be termed as “bioaffinity chromatography” or “biospesific adsorption”.

Some typical biological interactions frequently used in affinity chromatography are:

Enzyme ↔ substrate analogue, inhibitor, cofactor.
Antibody ↔ antigen, virus, cell.
Lectin ↔ polysaccharide, glycoprotein, cell surface receptor, cell.
Nucleic acid ↔ complementary base sequence, histones, nucleic acid polymerase, nucleic acid binding protein.
Hormone, vitamin ↔ receptor, carrier protein.
Glutathione ↔ glutathione-S-transferase or GST fusion proteins.

Selectivity of the ligand, recovery process, throughput, reproducibility, stability and economic criteria are some of the factors that influence the success of the affinity chromatography process. Choice of the support material, ligand, activation method and conditions for adsorption and desorption are important considerations prior to setting up a typical affinity chromatography experiment.

Support material: The support within the column must contain an affinity ligand that is capable of forming a suitably strong complex with the solute of interest. Also, the support material must be biological and chemically inert. There are many commercially available support materials for affinity chromatography which can be divided into three groups: natural (agarose, dextrose, cellulose); synthetic (acrylamide, polystyrene, polymethylacrylate) and inorganic (silica, glass) materials.
Ligand: The selected ligand must be capable of selectively and reversibly binding to the substance to be isolated and have some groups which are available for modifications in order to be attached to the support material. It is very important to ensure that the modifications do not reduce the specific binding affinity of the ligands. There are general ligands such as dyes, amino acids, Protein A and G, lectin, coenzyme, metal chelates as well as specific ligands such as enzymes and substrates, antibodies and antigens.

Affinity ligands are classified as synthetic and biological. Biological ligands are obtained from natural sources such as RNA and DNA fragments, nucleotides, coenzymes, vitamins, lectins, antibodies, binding or receptor proteins, or in vitro from biological and genetic packages, employing display techniques including oligonucleotides, peptides, protein domains and proteins.

Synthetic ligands are generated using three methods:

The rational method features the functional approach and structural template approach.
The combinatorial method relies on the selection of ligands from a library of synthetic ligands synthesized randomly.
The combined method employs both methods and the ligand is selected from an intentionally prepared library based on a rationally designed ligand.

Many parameters have to be taken into account in order to select and design an appropriate ligand.

Determination of the binding site or possible biological interactions to use as a template for the modelling,
Initial design of the ligand using this template,
Preparation of a ligand library and chromatographic evaluation,
Selection of the ligand of interest,
Optimization and chromatographic evaluation of the adsorbent following the immobilization.

Table 2 exhibits the advantages and disadvantages of biological and synthetic ligands:

Table 2: Advantages and disadvantages of synthetic and biological ligands.

Selectivity and affinity are the main advantages of biological ligands. Such ligands can be generated by in vitro evolution approaches and selecting from large combinatorial ligand libraries based on biological/genetic packages. Protein ligands display special advantages for example; higher affinities, higher proteolytic stability, preservation of their biological activity when produced by fusion to a different protein or domain. However these ligands can be expensive and unstable to the sterilization and cleaning conditions used in manufacturing processes of biologics because of their biological origin, chemical nature and production methods.

The wide application potential of affinity chromatography led to the development of derived techniques some of which are listed below:

High performance affinity chromatography
Dye-ligand affinity chromatography
Lectin affinity chromatography
Immunoaffinity chromatography
Metal-chelate affinity chromatography
Covalent affinity chromatography

Immunoaffinity chromatography (IAC):

Immunoaffinity chromatography (IAC) is a very popular technique that enables the production of ligands in case the ligand required is not available. In this technique, the stationary phase comprises of an antibody or antibody-related agent. It is possible to isolate a variety of substances using this technique due to the high specificity of antibodies. It is reported that IAC may be used for natural food contaminants such as aflatoxins, fumonisins and ochratoxins. IAC is probably the most highly specific of all forms of bioaffinity chromatography and both large and small analytes can be purified using this technique.

Lectin affinity chromatography:

Lectin affinity chromatography Lectins are non-immune proteins produced by plants, vertebrates and invertebrates. Especially, various plant seeds synthesize high levels of lectins. Certain types of carbohydrate residues may be separated via this method as all lectins have the ability to recognize and bind these types of compounds. Mostly used lectins for affinity columns are concanavalin A, soybean lectin and wheat germ agglutinin. Concanavalin A is specific for α-D-mannose and α-D-glucose residues while wheat germ agglutinin binds to D-N-acetyl-glucosamine.

Fig.7. Lectin affinity chromatography.

Metal chelate affinity chromatography (Immobilized metal ion affinity chromatography or IMAC):

Metal chelate affinity chromatography (Immobilized metal ion affinity chromatography or IMAC) is based on the ability of certain amino acids acting as electron donors on the surface of proteins (histidine, tryptophan, tyrosine, or phenylalanine) to bind reversibly to transition metal ions that have been immobilized by a chelating group covalently bound to a solid support. Of these amino acids, histidine is quantitatively the most important in mediating the binding of most proteins to immobilized metal ions. Histidine binds selectively to immobilized metal ions even in the presence of excess free metal ions in solution. Copper and nickel ions have the greatest affinity for histidine. The affinity of histidine residues for immobilized Ni ²⁺ ions allows selective purification of proteins containing a high proportion of histidine residues on the surface. Nitrilotriacetic acid (NTA), has provided a convenient and inexpensive support for purification of proteins containing histidine residues.

Thus, chromatography plays a crucial role in the drug discovery and development process. In fact, the process of drug discovery and development would be incomplete without the use of appropriate chromatographic techniques for purification and analysis. The choice of a suitable chromatographic method coupled with an adequate detection technique, depending on the nature of the analyte, can greatly reduce the time and cost involved in all steps from the drug discovery to the manufacturing stage.

References:

Luxminarayan, L., Sharma, N., Viswas, A., Viswas, A., & Khinchi, D. (2017). A review on chromatography techniques. Asian Journal of Pharmaceutical Research and Development, 5(2), 1-08.
Karlsson E, Ryden L, Brewer J. Protein Purification. Principles, High Resolution Methods, and Applications, 2nd Edition, Ion exchange chromatography. Wiley-VCH, New York;1998.
Coskun O. Separation techniques: Chromatography. North Clin Istanb. 2016;3(2):156-160.
Porath J. Immobilized metal ion affinity chromatography. Protein Expr Purif. 1992;3:263–81.
Wilchek M, Chaiken I. An overview of affinity chromatography in affinity chromatography–Methods and protocols. Humana Press. 2000:1–6.
Determann H. Gel chromatography gel filtration, gel permeation, molecular sieves:a laboratory handbook. Chapter 2. Materials and Methods. 2012
Petty KJ. Metal-chelate affinity chromatography. Curr Protoc Mol Biol. 2001 May;Chapter 10:Unit 10.11B.

Characterization of Multi-Protein Complexes (MPCs) by BN-PAGE

Wed, 16 Dec 2020 16:50:21 GMT

Characterization of Multi-Protein Complexes (MPCs) by BN-PAGE

Introduction

What are MPCs:

MPCs are a group of two or more associated polypeptide chains. Two kinds of MPCs can be distinguished: Constitutive, abundant MPCs such as receptors or transcription factors; and signal-induced, transient, low copy number MPCs. These complexes typically play a crucial role in signaling. Identification and analysis of MPCs requires their separation under native conditions.

BN-PAGE:

Blue native polyacrylamide gel electrophoresis (BN-PAGE) can be used for one-step isolation of multi-protein complexes (MPCs) from biological membranes/organelles and total cell and tissue homogenates under native conditions. BN-PAGE is often used for the study of MPCs as it can provide information about the size, number, protein composition, stoichiometry, or relative abundance of MPCs.

Advantages of BN-PAGE:

It can be used to determine native protein masses, oligomeric states, and identify physiological protein–protein interactions.
It has a higher resolution for separation than gel filtration or sucrose density ultracentrifugation.
It can be used to analyze abundant, stable MPCs from 10 kD to 10 MD.
It allows the determination of the size, the relative abundance, and the subunit composition of an MPC, in contrast to, immunoprecipitation and two-hybrid approaches.
It is useful for determining how many different complexes exist that share a common subunit, whether free monomeric forms of individual subunits exist, and whether these parameters change upon cell stimulation.

Protocol

1. Sample preparation for BN-PAGE:

Note about detergents : Before preparing the samples for BN-PAGE, the optimal detergent and its appropriate concentration that will preserve the MPCs yet solubilize the cells should be determined. Non-ionic detergents are considered best for maintaining MPC stability. Commonly used detergents that can be tested include digitonin (0.5 to 1%), Triton X-100 (0.1 to 0.5%), Brij 96 (0.1 to 0.5%), or dodecylmaltoside (0.1 to 0.5%). Other detergents can also be used [information about detergents can be found online or on request]. Even if soluble MPCs are being analyzed, detergents must be present in the dialysis step to prevent aggregation during the stacking step of the gel run.

Samples for BN-PAGE may be prepared from several sources such as total cell lysates, cellular organelles and membranes. A basic protocol for MPC sample preparation from total cell lysates or from lysates of tissue samples for BN-PAGE analysis is provided below. The details of cell culture will be specific to the cells used for the experiment and are therefore not included here.

1a. Preparation of total cell lysates

Harvest 2 x 106 cells and pellet by centrifugation at 350g for 5 min at 4°C.
Note: Suspension cells can be harvested by centrifugation; cells that grow attached to the culture dishes should be released from the dishes with 0.5 mM EDTA (avoid trypsin, because it digests extracellular proteins). Tissues should be homogenized with a Dounce homogenizer in PBS (Mix 1).
Wash the cell pellet three times with 0.5 ml of ice-cold PBS (Mix 1), and pellet after each wash by centrifugation at 350g for 5 min at 4°C.
Resuspend the cell pellet at 2 x 106 cells per 100 µl of ice-cold BN-Lysis Buffer (Mix 3)
Incubate on ice for 15 min.
Centrifuge at 13,000g for 15 min at 4°C.
Melt a hole in the cap of a microcentrifuge tube using a hot Pasteur pipette, and then place the tube on ice to chill.
Transfer the supernatant from step 5 into the chilled tube with the hole in the cap.
Place a dialysis membrane with forceps over the opened tube and close the cap (F2, B and C).
Note: Ensure that there are no folds or tears in the dialysis membrane.
Seal the cap carefully with Parafilm.
Invert the tube and centrifuge upside-down at the lowest speed possible in the adaptor cavity for 50-ml conical tubes in a cell culture centrifuge for 10 s at 4°C.
Note: Remove the inverted tube from the centrifuge using large tweezers to avoid turning the tube right side up.
Prepare a 100-ml beaker with cold BN-Dialysis Buffer (Mix 4) and a magnetic stirrer. Use at least 10 ml of BN-Dialysis Buffer per 100-µl sample.
Affix the tube with tape upside-down inside the beaker and remove air bubbles from the hole beneath the cap using a bent Pasteur pipette.
Switch on the magnet stirrer and leave it for 6 hours or overnight in the cold room. Check occasionally to ensure that stirring is not creating air bubbles at the dialysis membrane.
Collect the dialyzed cell lysate in a new chilled microcentrifuge tube.

It might sometimes be necessary to increase the likelihood of detection of less abundant MPCs. For this purpose, we provide two alternative sample preparation methods that allow enrichment of samples for MPCs with i. phosphotyrosine-containing proteins and ii. MPCs associated with cell membranes or organelles.

1b. Enrichment of MPCs containing phosphotyrosine residues

Immunoprecipitation methods commonly used for enrichment of proteins cannot be combined with BN-PAGE, because elution of MPCs under native conditions from the antibody-coupled beads is impossible. MPCs with components that are phosphorylated on tyrosine residues may be immunopurified using antibodies against phosphotyrosine. The MPCs are then eluted with an excess of phenylphosphate, which competes with phosphotyrosine for binding to the antibody. Provided below is a detailed protocol for preparation of phosphotyrosine-enriched samples. Alternatively, affinity-purification protocols, such as the tandem affinity purification (TAP-tag) method, that allow native elution of the proteins from the affinity matrix could also be used.

Harvest 2 x 107 cells and pellet by centrifugation at 350g for 5 min at 4°C.
Note: Cells may be stimulated with ligands, agonists, antagonists, or other conditions, depending on the experiment.
Wash the cell pellet once with 1 ml of ice-cold PBS (Mix 1) and pellet by centrifugation at 350g for 5 min at 4°C.
Resuspend the cell pellet at 2 x 107 cells per 1 µl of ice-cold Lysis Buffer (Mix 5).
Incubate for 15 min on ice.
Centrifuge at 13,000g for 15 min at 4°C.
Transfer the supernatant from step 5 into a new chilled tube.
Add 10 µl of beads coupled to antibodies against phosphotyrosine residues and incubate on a rotating wheel for 2 hours to overnight in the cold room.
Centrifuge at 400g for 2 min at 4°C.
Wash the beads three times with 1 ml of ice-cold BN-Dialysis Buffer (Mix 4), centrifuging 400g for 2 min at 4°C
Add 40 µl of ice-cold BN-Dialysis Buffer Containing Phenylphosphate (Mix 6) and resuspend the beads using a 20-µl pipette tip that has been cut at the narrow end to make the opening larger.
Resuspend beads every 5 min for 30 min while incubating on ice.
Note: If desired, proteins may be dephosphorylated by adding one unit of alkaline phosphatase to the eluate during the last 5 min of the elution procedure.
Centrifuge at 400g for 2 min at 4°C and collect the supernatant (eluate) in a new, chilled tube.
Note: These samples do not have to be dialyzed and are ready for BN-PAGE.

1c. Preparation of membranes for BN-PAGE

MPCs that are associated with cell membranes or inside organelles can be enriched before preparing the lysate for analysis by BN-PAGE.

Prepare membrane fractions of cells using standard protocols.
Wash the membrane pellet once with 0.5 ml of ice-cold BN-Lysis Buffer (Mix 3) without detergent.
Resuspend the membrane pellet completely without generating air bubbles in ice-cold BN-Lysis Buffer (Mix 3), including detergent. Use the equivalent of 4 x 107 cells per 100 ul of BN-Lysis Buffer.
Incubate for 1 hour at 4°C, resuspending the pellet every 15 min.
Centrifuge at 20,000g for 10 min at 4°C.
Collect the supernatant (membrane lysate) in a new, chilled microcentrifuge tube.
Note: These samples do not have to be dialyzed and are ready for BN-PAGE.

2. BN-Gel preparation

Carry out gradient gel pouring at room temperature with a gradient mixer. Because of its high glycerol content, the gel mix with the higher-percentage (15%) acrylamide-bisacrylamide is heavier than the low-percentage (4%) gel. This density difference aids in establishment of a uniform gradient between the glass plates. Gloves must be worn because polyacrylamide is highly neurotoxic.

Note: Precast BN-gels and buffers are commercially available from Invitrogen (NativePAGE Novex Bis-Tris Gel System).

Place the gradient maker on a stir plate and attach to a peristaltic pump. Close the channel using the valve and close the tubing with a clamp.
Attach a syringe needle to the end of a piece of flexible tubing that comes out of the peristaltic pump and place the needle into the top, between the two glass plates of the gel apparatus. Place the needle close to the bottom and raise it slowly as the gel pours.
Prepare 4% and 15% Separating Gels (Mixes 9 and 10), adding APS and TEMED only immediately before use.
Note: The volumes of the two gel solutions combined should be exactly equal to the volume required to fill the space between the glass plates to the required height.
Pour these gel solutions into the corresponding cylinders of the gradient mixer (4% into the “low” and 15% into the “high” cylinder).
Open the valve and force out the air bubble inside the channel connecting the two gel reservoirs by pressing over the left cylinder with your thumb.
Switch on the pump to 5 ml per minute, remove the clamp, and allow the gel to slowly flow between the glass plates. Ensure that the needle is always above the height of the liquid so that the gradient is not disturbed
Allow all liquid to enter the gel apparatus, and then overlay gently with isopropanol. Allow the gel to polymerize for at least 30 min at room temperature.
Clean the pouring apparatus with dH2O (do not use detergent).
Remove the isopropanol, wash with dH2O, and remove the dH2O carefully with a slip of absorbent paper without touching the gel.
Prepare a 3.2% Stacking Gel (Mix 11), adding APS and TEMED only immediately before use.
Pour the stacking gel on top of the separating gel and immediately introduce the comb between the glass plates, avoiding bubbles at the interface between the gel solution and the comb. Allow the gel to polymerize.
Note: Make sure that at least 0.5 cm (for 5-ml minigels) or 2.5 cm (for large, 30- to 50-ml gels) of stacking gel remain between the comb and the separating gel.
Remove the comb slowly, pulling it out at an angle to the plane of the gel. This allows air to enter the pockets rapidly, which improves the quality of the wells.

3. Separation of the prepared sample of MPCs by BN-PAGE

Coomassie blue is present in the solution at the cathode that is overlaid onto the samples that have been added to the wells. This dye interacts with the MPCs inside the wells of the gel and enters the gel during electrophoresis, preventing aggregation of proteins in the stacking gel. Once the samples are prepared, the remainder of this part of the procedure should be performed at 4°C. It is recommended to boil an aliquot of the sample with SDS to disrupt the MPCs as a control and loading this control also on the BN-PAGE.

Boil an aliquot of the sample, to be used as a control, in 1% SDS for 5 min to dissociate all MPCs. Leave one lane empty between this control and the “non-SDS samples.”
Load 1 to 20 µl of sample in the dry wells, before adding the Cathode Buffer (Mix 12).
Note: If the sample contains phosphorylated proteins and the phosphorylation is to be preserved, add 1/100th volume of 100x Pervanadate (Mix 13) to the dialyzed lysate.
Load 10 µl of Marker Mix (Mix 14).
Note: Only ferritin is visible during the electrophoresis due to its brown color. The other markers will be visible following Coomassie or silver staining.
Overlay the samples in each well with Cathode Buffer (Mix 12).
Fill the inner chamber with Cathode Buffer (Mix 12) and the outer and lower chambers with Anode Buffer (Mix 15)
Apply voltage to a minigel at 100 V or a large gel at 150 V, until the samples have entered the separating gel.
Increase the voltage to 180 V (minigel) or 400 V (large gel) and run until the dye front reaches the end of the gel.
Note: The gel run takes between 3 and 4 hours for a mini-gel, and between 18 and 24 hours for a large gel.

4. Second Dimension SDS-PAGE

After performing the first-dimension BN-PAGE, it is possible to run a second-dimension SDS-PAGE to separate each MPC into its components. The protocol for this is provided below.

Prepare a standard SDS-PAGE gel with a single large lane and one lane for molecular weight markers.
Note: To make it easier to load the BN-PAGE gel slice onto the second-dimension gel, tape (Tesafilm or Cellotape) the spacers and comb of the SDS-PAGE gel. This results in a slightly thicker gel, which is sufficient to allow the BN-PAGE gel slice to slip between the plates and into the well easily, but still remain fixed between the glass plates.
Remove the BN-PAGE gel in the plates from the electrophoresis apparatus and gently pry up one plate.
Cut out the lane of the BN-PAGE gel containing the proteins of interest and remove the stacking gel.
Place the BN-PAGE gel slice in SDS Sample Buffer (Mix 16) (5 ml for a minigel slice) in a small dish or cell culture plate, and incubate for 10 min.
Boil the BN-PAGE gel slice briefly (not more than 20 s) in the microwave.
Note: Excessive boiling will cause the gel slice to shrink.
Continue incubating the BN-PAGE gel slice in the hot SDS Sample Buffer (Mix 16) for another 15 to 20 min.
Load the BN-PAGE gel slice over the stacking gel of the SDS-PAGE gel and overlay the slice with SDS Sample Buffer (Mix 16).
Perform electrophoresis according to standard protocols.

5. Visualization of MPCs

Several methods are available for visualizing the protein complexes. The protein constituents of MPCs that have been isolated by BN-PAGE or second dimension SDS-PAGE can be analyzed by Coomassie blue staining or silver staining. Coomassie blue is a good choice for highly abundant MPCs (mg amounts), whereas silver staining is good for visualization of 50 to 1000 ng amounts of the protein of interest. These methods are standard, and the details are not provided here.

For detailed information and formulation of referenced mixes or chemicals, please request list via our contact form

The Rise of Cryo-EM Among Structural Characterization Methods: NMR, X-Ray Crystallography

Tue, 01 Dec 2020 20:24:33 GMT

The Rise of Cryo-EM Among Structural Characterization Methods

Reviewing NMR, X-Ray crystallography and electron microscopy

Introduction

Structural biology is the study of the molecular structure and dynamics of biological macromolecules, by utilizing techniques and principles of molecular biology, biochemistry and biophysics. In order to determine the spatial relationship of the hundreds of thousands of atoms, and to follow the changes in their relative locations within a biological macromolecule, multiple methodologies with very different physical principles, such as X-ray crystallography, NMR spectroscopy, cryo-electron microscopy (cryo-EM), X-ray solution scattering, neutron diffraction, and other spectroscopic techniques have been implemented. Amongst these, X-ray crystallography, NMR, and (cryo-EM) represent the three main methods widely employed to reveal structural information pertaining to a large variety of macromolecules.

X-Ray Crystallography

Principle:

Given its ability to resolve structures of macromolecules at atomic resolution, X-ray crystallography is the most powerful tool in modern structural biology. This technique uses X-rays to determine the position and arrangement of atoms in a crystal. Its foundation principle lies in Bragg’s law of X-ray diffraction by crystals, i.e. by well-ordered packing of homogenous molecules in three-dimension. Illuminated by a beam of X-ray light, the crystal can diffract the light at various angles, some of which have stronger intensity than others (Fig. 1). This kind of intensity variation at different angles can be recorded on media as a “diffraction pattern”. The diffraction pattern, normally appearing as a series of sharp spots, reflects the structural arrangement of atoms within the crystal and therefore can be used to deduce the original structure of the crystal using Bragg’s Law.

In order to solve the structure of the molecule of interest, besides the measured intensities of the diffraction spots, additional information called phases of the spots is required which is obtained by other experimental or computational means. The intensity and phase information of multiple diffraction patterns of the crystal can then be reconstructed and Fourier transformed in a computer to generate a virtual structure for interpretation.

The quality of the structure heavily depends on the sharpness of the diffraction spots, which in turn is determined by the degree of order of the crystal.

Therefore, modern X-ray crystallography’s essential step is to obtain highly-ordered three-dimensional crystals. In order to achieve this, a large amount of highly purified macromolecules may be necessary when screening a large number of crystallization conditions. Also engineering of the molecules, e.g. stability promotion, side-chain modification, proteolysis, may be important to improve the crystal quality.

Fig.1. The principle of X-ray crystallography

Workflow:

The technique of single crystal X-ray crystallography has three basic steps. The first and usually most difficult step is to produce an adequate crystal of the studied material. The crystal should be sufficiently large with all dimensions larger than 0.1 mm, pure in composition and regular in structure, and have no significant internal imperfections such as cracks or twinning. The crystal is subsequently placed in an intense beam of X-rays, usually of a single wavelength, to produce a regular reflection pattern. The angles and intensities of diffracted X-rays are measured with each compound having a unique diffraction pattern. Previous reflections disappear and new ones appear along with the gradual rotation of the crystal, and the intensity of every spot is recorded at every orientation of the crystal. Multiple data sets may have to be collected since each set covers slightly more than half a full rotation of the crystal and typically contains tens of thousands of reflections. Ultimately, these collected data are combined computationally with complementary chemical information to obtain and refine a model from the arrangement of atoms within the crystal (Fig. 2). The final refined model of the atomic arrangement is called a crystal structure and is usually stored in a public database.

Fig. 2. Workflow for solving the molecular structure using X-ray crystallography.

Advantages:

Most advanced method available for obtaining high-resolution structural information.
High atomic resolution.
Not limited by molecular weight of the sample.
Suitable for water-soluble proteins, membrane proteins and macromolecular complexes.
Can reveal considerable information about the mobility (dynamics) and heterogeneity of protein structures.

Disadvantages:

Sample must be crystallizable.
Crystallization of biological macromolecules with high molecular weight can be difficult. Particularly, membrane proteins are more challenging to crystallize because of their large size and relatively poor solubility.
An organized single crystal must be obtained to allow appropriate diffraction.
Obtained three-dimensional structure of biological sample only represents a static form of the tested molecule (one of many possibilities), rather than a dynamic one.

NMR Spectroscopy

Principle:

The nuclei in the atoms in materials are spinning and charged and, as such, most form magnetic dipoles (hence the nuclear magnetic in NMR). As a simple explanation, these dipoles are often compared with little bar magnets with north and south poles (Figure 3A). Normally these nuclear bar magnets are randomly oriented. The result is that no net magnetic field arises from them and thus no NMR signal can be generated. However, when placed in a strong magnetic field, B _o , on average some of the nuclei “align” with B _o . The result is a net magnetic moment, M, from the sample (Figure 3B).

Fig 3. (A) Nuclear dipole equated to a bar magnet. (B) When placed in a magnetic field, Bo, the nuclear moments align with Bo and generate a net magnetic moment, M.

Nuclei in differing chemical environments (different chemical structures) bond to other nuclei by the sharing of electrons; thus, different chemical groups are subsequently surrounded by different electron shells. These electrons also have associated magnetic fields that have the effect of shielding the nuclei from the applied Bo by slightly differing amounts, depending on the number of electrons in the shell. Consequently, nuclei in different chemical groups will resonate at slightly different frequencies, an effect referred to as the chemical shift. When excited, complex chemical samples thus generate multiple signals at different frequencies corresponding to all of the distinct chemical groups (Fig. 4.) that are detected simultaneously in the signal. A technique called the Fourier transform is used to work out the frequencies of the signal, generating a NMR spectrum. This is the basis of NMR spectroscopy, and the information contained within the NMR spectrum can be used to determine the chemical makeup and structure of materials.

Fig. 4. Distinct chemical groups emit signals at different frequencies.

Workflow:

There are four main steps in an NMR experiment: sample preparation, data acquisition, spectral processing, and structural analysis. NMR analysis is performed on aqueous samples of protein with high purity, high stability, and high concentration. A sample volume ranging from 300 to 600 μL with a concentration range of 0.1-3 mM. The use of stable isotopes ¹⁵ N, ¹³ C and ² H for protein labeling can effectively increase signal intensity and resolution. Selective labeling of certain amino acids or chemical groups of proteins can greatly reduce signal overlap. Multidimensional NMR experiments are utilized to acquire information about the protein (Fig. 5). The spectral processing is then performed to determine the atoms of the protein corresponding to each spectral peak on different NMR spectra. Finally, a series of spatially structured information such as NOE and J coupling constants are used to calculate the spatial structure using distance geometric or molecular dynamics methods.

Fig. 5. Workflow of NMR spectroscopy

Although the amount of three-dimensional structure data of proteins obtained by NMR technology is not comparable to that of X-ray crystallography, the unique advantages of NMR technology have been widely noticed: NMR is able to provide information on a kinetic basis, such that the internal movement of proteins over multiple time scales and their binding mechanism to ligands can therefore be solved. Currently, with continuing advancements in magnet and gradient technology coupled with increasingly powerful computers, NMR spectroscopy and imaging can be used to investigate a wide range of biological processes in systems as diverse as a single cell, isolated perfused organs, and tissues in vivo.

Advantages:

Dynamic technique.
Flexibility - wide range of biological processes can be investigated.
Non-destructive and non-invasive.
Three-dimensional structures in their natural state can be measured directly in solution.
Can provide unique insights into dynamics and intramolecular interactions.
Macromolecular three-dimensional structure resolution can be as low as sub-nanometer.

Disadvantages:

Limited to small (<40 kDa), stable, soluble proteins that do not aggregate at the high concentrations required for data collection.
Large amounts of pure samples are needed to achieve an acceptable signal to noise level.
Highly sensitive to motion which can lead to signal distortions and artifacts.
The high-magnetic field can cause problems with other equipment in a laboratory. Therefore, extra precautions may need to be taken, especially if working space is limited.

Cryo-EM:

Principle:

In this method, fully preserved samples are imaged by freezing them in a thin layer of a non-crystalline form of solid water, called amorphous or vitreous ice. Given that vitreous ice is maintained at liquid nitrogen temperatures, this technique was termed ‘cryo-EM’. Although we mainly associate the term cryo-EM with macromolecular electron microscopy, the 3D study of macromolecules, viruses, organelles and cells using a transmission electron microscope (TEM), cryo-EM is a general term for the observation of low-temperature specimens using an electron microscope. This term can also be used for the observation of frozen material by a scanning electron microscope (SEM), which produces vastly different images from those of a TEM.

Electron microscopes are imaging devices that use electrons instead of light and electromagnetic lenses instead of glass lenses to produce magnified images of an object being studied. Electrons can either pass through the sample, and in doing so get slightly scattered (as in TEM), or ‘bounce off ’ the sample (as in some forms of SEM). The interaction of these electrons with the sample gives rise to various types of images. Macromolecules imaged by a TEM in ice are referred to as projections and can be thought of as a sum of the density through the macromolecule from a particular orientation, similar to looking through one’s hand in an X-ray picture taken at a hospital. Due to the scattering nature of electrons, a very high vacuum is required inside the microscope which means that biological specimens have to be stabilized accordingly.

Workflow:

A typical cryo-EM workflow includes sample preparation, low dose data acquisition, and model building. Before using Cryo-EM to observe the sample, negative staining EM can be utilized for rapid screening of homogeneous sample. The Cryo-EM single particle analysis technique begins with sample vitrification. During this process, the protein solution is instantly cooled, so that the water molecules do not crystallize, forming an amorphous solid. The frozen sample is then screened and data is collected in the system. A series of two-dimensional images can be taken during this period. Next, based on plenty of two-dimensional images acquired, particle alignment and classification are carried out. In the end, the data is processed by reconstruction software to generate a three-dimensional structural model (Fig. 6).

Fig. 6. Schematic representation of three-dimensional single-particle reconstruction using Cryo-EM.

Advantages:

Rapid freeze treatment of the sample maintains it closer-to-native state.
Small amount of sample (0.1 mg) required.
Protein does not need to crystallize.
Poses fewer restrictions on sample purity.

Disadvantages:

The low signal-to-noise ratio (or low contrast) of the captured images limits the size of the macromolecules observed (ideally these should be larger than 250 kDa).
Electron beam-induced movement during exposure results in degradation of the image quality.

Summary of the Advantages and Limitations of Each Structural Biology Technique

X-ray crystallography

NMR

Cryo-EM

The Rise of Cryo-EM

For many years, structure determination of biological macromolecules by cryo-EM was limited to large complexes or low-resolution models. With recent advances in electron detection and image processing, beginning in early 2013, the resolution of cryo-EM is now starting to rival that of X-ray crystallography. These advances are provided by two major innovations. One is the employment of a direct electron detector (DED) for electron microscopy. DED can detect electrons directly and read them at high frame rate without a mechanical shutter. Their higher performance is due to greatly improved quantum efficiency as compared to previous generations of detectors. Motion correction has become the standard to compensate for the blurring effect of stage drift and beam-induced movement. The other is advancement of image processing methods and the constant increase of microprocessor performance, which allow accurate classification of hundreds of thousands of EM images with computationally expensive algorithms.

These two technologies have led to a “resolution revolution” with atomic structures no longer being the exclusive prerogative of X-ray crystallography or NMR spectroscopy, and have made cryo-EM an important tool to analyze the structure of dynamic biomolecules.

The three-dimensional structures of biological molecules provide great insights into the laws of life activities and mechanisms of diseases, and thereby allow rational design of novel diagnostic and therapeutic agents. Cryo-EM is gradually adding to a better structural understanding of various complex systems and even helping resolve structures that have proven intractable to other methods. One such area is the working of the respiratory chain. Answering questions as to how the proton gradient is harnessed by ATP synthase to produce ATP, and resolving structures of large protein complexes such as cytochrome bc ₁ and complex I, as well as super-complexes such as the 1.7 MDa respirasome have been possible due to cryo-EM analysis. Our understanding of several important neurodegenerative diseases has rapidly changed recently with a series of landmark papers detailing the structure of tau and amyloid-b proteins facilitated by cryo-EM analysis. The structures reveal some unprecedented details in this important class of proteins.

Although still limited in resolution compared to both X-ray crystallography and NMR, cryo-EM can provide valuable insights into inhibitor binding and therefore open up new avenues for structure-based drug design pipelines. For instance, since 2013, ~50 new single-particle cryo-EM structures have been determined from all the major clades within the transient receptor potential channel membrane-protein family where there had been a paucity of structural information on the full channels. Another example is of the yeast isoform of imidazoleglycerolphosphate-dehydratase, an essential enzyme in histidine biosynthesis, which is more sensitive to small-molecule inhibitors and intractable to crystallization, has recently been determined by cryo-EM. The power of cryo-EM when tackling proteins from a native source has been highlighted by the recently solved structure of the malarial translocon to 3.5 Å, which can now effectively support inhibitor design. N

The large amount of screening space that is required to find a suitable crystallization condition can be a limiting factor when using X-ray crystallography for structure determination. For large protein complexes this becomes more challenging, and specialized cellular machinery may be required for the synthesis of sufficient protein for extraction from host tissue. In contrast, cryo-EM is less demanding on the quantity of sample than a typical X-ray or NMR experiment. An important challenge with cryo-EM are the high costs of the purchase and maintenance of the powerful microscopes that are required to elucidate high-resolution structures. The computation-time requirements of the image-processing pipeline are also important and require supercomputers. Poor access to these instruments (in relation to the growing demand) and their costs call for coordinated funding models and group use. Also, correct sample preparation, image collection and analysis is not as easy as it sounds and appropriate training is required.

Moreover, even with recent developments in cryo-EM, the poor signal to noise in the raw images of sub-65 kDa molecular masses makes particle identification and alignment a significant challenge. On the other hand, in X-ray crystallography, multi-protein complexes, particularly those which involve membrane proteins or where the complexes are not stable over the crystallization time scale, present an important limitation.

Atomic resolution is critical to defining the minute structural details that can clearly elucidate enzyme mechanisms and thereby improve disease understanding and support inhibitor design for drug discovery. Therefore, the use of cryo-EM as a complementary tool to X-ray crystallography to obtain structural information on large protein complexes and for systems that exhibit multiple conformational or compositional states is gaining increasing importance. The cryo-EM approach, although limited in resolution, could also provide a link by being suitable for the study of systems in which protein is more limiting. The richness of structural biology can best be harnessed by combining various methods where practical and possible. The path forward thus appears to lie in the use of a combination of these techniques for structure elucidation, rather than heavy reliance on any single technique.

References:

Stock D, Perisic O, Lowe J. Robotic Nanolitre Protein Crystallisation at the MRC Laboratory of Molecular Biology. Prog Biophys Mol Biol, 2005, 88(3): 311–327.
John C. Chatham, Stephen J. Blackband, Nuclear Magnetic Resonance Spectroscopy and Imaging in Animal Research, ILAR Journal, Volume 42, Issue 3, 2001, Pages 189–208.
Bai XC, McMullan G, Scheres SH. How cryo-EM is revolutionizing structural biology. Trends Biochem Sci. 2015 Jan;40(1):49-57.
Egli M. Diffraction techniques in structural biology. Curr Protoc Nucleic Acid Chem. 2010;Chapter 7:Unit-7.13.
Vénien-Bryan C, Li Z, Vuillard L, Boutin JA. Cryo-electron microscopy and X-ray crystallography: complementary approaches to structural biology and drug discovery. Acta Crystallogr F Struct Biol Commun. 2017 Apr 1;73(Pt 4):174-183.
Muench SP, Antonyuk SV, Hasnain SS. The expanding toolkit for structural biology: synchrotrons, X-ray lasers and cryoEM. IUCrJ. 2019 Mar 1;6(Pt 2):167-177.

Optimizing CRO Strategies For Discovery Research Projects

Mon, 23 Nov 2020 19:58:55 GMT

Become Your Lab's CRO Managing Expert

4 ways to improve data management and communication

What's Inside?

EXPERIENCE-BASED QUALIFYING
DEEP DATA ANALYSIS MANAGEMENT
CRITICAL REAGENTS PLANNING

Biochemical Overview of Key Post-Translational Modifications

Mon, 23 Nov 2020 19:55:03 GMT

Post-Translational Modifications (PTM’s)

Reviewing Read our latest white paper on Post-Translational Modifications (PTM's)

Protein synthesis occurs during a process called translation. Most proteins undergo some modification before undertaking any function assigned to them. Post-translational modification (PTM) of proteins refers to these covalent chemical modifications, protein may undergo after translation. This poses a much bigger phenomena when it comes to the synthetic production of these proteins. Chemical reagents undergo certain processes that are a part of fixed manufacturing systems. Many of which are unable to adapt or disrupt in order to tailor to a PTM’s biochemical properties.

PTM’s have become a growing focus in protein and bioreagent production : As more complex and difficult-to-express proteins extend into the commercial market, the industry is facing bottlenecks and PTM obstacles to producing certain proteins of interest.

The biochemistry behind these modifications are not universally updated: This piece will help outline and review the top key PTM’s and their latest understandings with mechanics and chemistry.

Biomanufacturing solutions are crucial to counter these PTM obstacles: With proper understanding of the biochemistry, researchers will be more equipped to understand what to expect from the manufacturing end when scouting difficult proteins with key PTM’s.

Gain insight from our experts and solve the PTM puzzle in your lab!

Reagents for RNA Synthesis

Mon, 09 Nov 2020 17:50:33 GMT

Reagents for RNA Synthesis

As the application of oligonucleotides continues to grow in research, advancements in nucleic acid chemistry are expanding manufacturing capabilities-particularly with RNA. Key innovations have optimized traditional synthesis with automation and specialty compounds to help deliver versatile-stable and pure RNA tools to support discovery analysis and solutions for therapeutic designs.

In this eBook, we delve deeper into the building block reagents, modifications and technologies guiding the way for versatile synthesis of RNA.

Download the RNA Synthesis eBook to explore:

Conventional Amidites & Support Reagents
Modified Compounds Advantages
Specialty Solid-Phase Technology
Purification & QC Standards

Aptamers & Antibodies: A Cooperation, Not a Competition

Wed, 21 Oct 2020 18:49:19 GMT

Aptamers & Antibodies: A Cooperation, Not a Competition

Reviewing the utility of both aptamer and antibody reagents in your discovery applications

Introduction

Since their first reported use in immunoassays, oligonucleotides have made significant advancements for their application in detection assays. Most notably, as aptamers in a sandwich assay called ELONA. Aptamers have since been coined the direct alternative to antibodies as either capture or detection reagents in discovery platforms.

We cover the technical specifics of ELONA assays in a separate technical note. Find i t here

With several studies presenting competitive analysis of the two reagents and some going as far as suggesting the potential of aptamers to completely replace antibodies-we feel that it is necessary to depress some of the exaggerations promoting this rivalry. In principle, both options offer their own features and aptamers do seem to have advantages in some key areas such as size, multiplexing capabilities, and cost. However, as is everything in science; things are not always as straightforward as they seem and this topic is no exception.

In this piece, we review the conventional aptamer : antibody side by side comparison, use our professional experiences with both reagents to highlight some essential oversights between the two, and make a case for implementing both reagents in your experimental workflow to reinforce your discovery platform.

Side-by-Side Comparison

The traditional case between aptamers and antibodies primarily focus on two factors; Biophysical structure and target affinity/specificity.

Physical properties

In figure 1 we show a common image for the size representation of antibodies relative to aptamers. The significantly lower molecular weight of aptamers suggests a series of advantages including; versatility, low toxicity, and cheaper cost manufacturing benefits. Although, these may be safe theories on paper-the specifics behind the material science in manufacturing these reagents is more complicated. For example, aptamers often become highly modified oligonucleotides as they develop to their target which disrupts their stability. In order to counter the loss in stability and retain purity, additional chemical modifications are required, such as phosphothioation of the oligomer backbone. All these modifications require more attention and specialty expertise in synthesis for production. In turn, increasing both the cost and toxicity risk of the final product.

Fig 1 . Size: Antibody vs. Aptamer. Opinion in chem. bio

Affinity & Specificity

While affinity to proteins ranges from nanomolar to picomolar, aptamers against small molecules tend to have an affinity in the micromolar range (Kd ~ μM). Both aptamers and antibodies are highly specific to their target molecules. However, aptamers are able to discriminate enantiomers and protein isoforms during detection.

Figure 2 provides a useful side-by-side analysis outlining the observed differences in affinity properties between oligo-aptamers and protein antibodies.

Fig 2. Aptamers rival antibodies in affinity analysis (Science, 2000, 287, 820-825)

Rivalry Oversights

Based on the current comparative studies; aptamers generally, do offer preferable advantages to a laboratory’s scientific projects and material budget. Nonetheless, it remains that these studies lack consideration of certain factors that are key in providing a complete understanding these reagents -as research tools. Factors such as their commercial landscape and mechanistic chemistry are too challenging for traditional studies to communicate alongside their analytical design. To help clarify on this point, we translated our diverse commercial experiences with these reagents into examples of some of the key factors being disregarded respectively:

Aptamer patents

Contrary to monoclonal technology, the initial patents surrounding aptamers were heavily controlled. There are notable recent changes, as some of those patents begin to lapse and alternative open methods develop. However, intended downstream application of these reagents for diagnostic or therapeutic use still requires extra due diligence on proper rights early in the discovery research phase.

The mAb standard

Monoclonal antibodies have been an established global standard in a large majority of laboratories for many years. The process of replacing a standard in bioscientific research involves widespread validation over a significant period. So even if there is a likelihood of succession, it would still require long, comprehensive consistency which may cause delays and/or surprises in downstream data criteria for anyone pioneering sole-aptamer platforms.

Biochemical limitations

The counter-selection factor during nucleic acid partitioning of the background library is not always able to preclude unwanted aptamers relative to the immobilizing label’s -which in turn complicates the aptamer design. Ironically, the biophysical characteristics of nucleic acids; (ex. 2' amine and 2'-O-Me) aptamers turns out to be much more restricted than that of antibodies. Since oligonucleotides are very hydrophobic and negatively charged by design-binding to targets on proteins that are hydrophobic or acidic becomes more challenging than the scientists expect.

Conclusion

Despite the pessimistic tone of this piece, I am actually a very strong believer in aptamers. They have great potential in their advantages against antibodies. However, it is important to remain more pragmatic than optimistic when it comes to their current role in laboratory research. Particularly if our goal is to effectively enable their advancement. To do that, aptamers need to stop being looked at as competing reagents for antibodies and instead be considered as partners for application alongside antibody experiments. In other words, antibodies have established themselves in certain methodologies, where the advantage of aptamers pose little to meaningless innovation. It is new and relevant areas of research, where the utility of aptamers shows great potential and offer the greatest return in capitalizing on their advantages.

For example; published studies, using aptamers as specific inhibitors against diverse target protein families in vitro and in vivo-highlight their potential as effective inhibitors and degraders for various drug targets. Focusing on their application in such promising areas where antibodies are not as established helps establish both aptamers and the principal research objective. If this is done alongside established antibody applications throughout a discovery workflow, it would be the most ideal approach for utilizing the advantages of both aptamers and antibodies without unnecessary bias.

References

Annu. Rev. Med 2005, 56, 555-83.
Science, 2000, 287, 820-825
Translational Medic S1:001. doi:10.4172/2161-1025. S1-001
Banner image by Biorendr

Top Ten Modifications for Nucleotide Synthesis

Tue, 13 Oct 2020 18:35:45 GMT

Top Ten Modifications for Nucleotide Synthesis

We've whittled the list down to ten major modifications and their compounds

In a previous note , Rethink Modifications ; we provide a general understanding for the two main classes of synthesis modifications. We also mentioned how increasingly difficult it has become to keep up with the multitude of list options for each class. With over a hundred elements and endless chemical possibilities, these lists of modification aren’t going to get any shorter. Especially with the growing trends, incorporating nanotechnology (upcoming technical note). We leveraged kb’s competency in this field to help filter out mods weak in principle and outlined the ten major modifications and their differing compounds.

Base Modifications

A base modification focuses on the amino acid base of one or more nucleotides within the nucleic acid sequence. There are three notable modifications to consider. They are as follows:

Sequence Modifications

A sequence modification is any mod that adds or edits features to the nucleic acid sequence. This class offers the highest opportunity for new and different compounds, explaining why most of the modification confusion and errors arise within this category. Many are imitations or slight alterations to similar formulations that result in unnecessary cost and low proof of concept.

We encourage exploring the following seven sequence modifications, prior to making a decision:

Choose by function…

Ultimately, your intended function provides 90% of a modifications requirements. That is why we encourage spending more time understanding your experimental objective before even considering the different modifications. Once this aspect is understood, it is a matter of identifying and matching biochemical components. kb’s synthesis is focused on proper intervention in the latter, as it is more challenging for scientists who don’t have time to follow the trends of commercial synthesis. Our platform building tool and proofreading services have been able to consistently match the right modification solution to the right function without any fees or added cost. Providing a proper resource has helped many of our end-users avoid errors and unnecessary costs to meet the following functions:

Substrate for DNA ligase
Attaching nucleotide to another biomolecule or surface
Targeted detection
3’ blocking or steric hindrance
Altering hybridization characteristics
Nuclease degradation concerns
Novel transfection into cell

Our resources are openly available to all researchers on our nucleotide synthesis page . Please visit for more information!

References

Korreck. J. Eur. J. Biochem. 2003, 270, 1625.
Wilson, C. Curr. Opin . Chem. Biol. 2006, 5487-5502.
Grimm. D. Adv. Drug, Deliv. Rev. 2009, 61,672-703.
Lin, C. et. al. Biochemistry 2009, 48, 1663-1674.
Dubendorff, J. W.; de Hasett, P. L.; Rosendahl, M. S.; Caruthers, M. H. J. Biol. Chem. 1987, 262, 892.
Brennan, C. A.; Van Cleve, M. D.; Gumpert, R. I. J. Biol. Chem. 1986 261, 7270-7279.

kbDNA Solutions [3rd edition]

laithik@gmail.com (L L) — Wed, 07 Oct 2020 16:57:08 GMT

Discover More with kbDNA's Solutions

Access your free copy of kbDNA's 3rd edition booklet and discover how our reagent solutions are helping optimize early-stage research applications:

Biomarker Analysis
Characterization Experiments
Assay Development
Compound Synthesis
and more!

Gain insight on kbDNAs latest technology:

Learn how the right solutions can enable your experiment workflow…

Take the next step in reinforcing your discovery and get your free copy of our booklet!

Utilizing Nucleotide-Based Methods for Optimal Detection

Mon, 21 Sep 2020 18:21:13 GMT

Utilizing Nucleotide-Based Methods for Optimal Detection

The tactical application of oligonucleotide and aptamer assays in drug discovery

Principles for Oligo and Aptamer Methods

Aptamers are single stranded DNA or RNA oligonucleotides that have high affinity and specificity towards a wide range of target molecules. Since aptamers exist in nature but can also be artificially isolated from pools of random nucleic acids through an in vitro selection process - Selective Evolution of Ligands by Exponential Enrichment (SELEX), they can potentially bind a diverse array of compounds. They have therefore attracted immense interest and found wide applications in a range of areas.

They also offer significant advantages as recognition elements over traditionally used antibodies. They are small in size, chemically stable and cost effective. Aptamers bind to their targets with high affinity, particularly with macromolecules (e.g., proteins), with dissociation constants in the picomolar to nanomolar range. More importantly, aptamers offer remarkable flexibility and convenience in the design of their structures. Their conformational adaptability provides better affinity and selectivity than antibodies. Since aptamers can be generated by a chemical process, thereby bypassing the use of biological systems in their synthesis, aptamers against non-immunogenic agents or compounds that may be toxic to cells can also be developed. While antibodies generally have multiple binding sites, most aptamers have limited specific binding sites. Thus, there is potentially far less nonspecific binding of non-target compounds when aptamers are utilized in immunoassays as antibody alternatives. This necessitates a minimum blocking strategy and provides a more reliable detection signal for the presence of the target compound. Most importantly, unlike antibodies, aptamers can be generated against virtually any kind of biomolecules, including lipids, sugars and even small molecules.

Analogous to immunoassays based on the antigen-antibody interaction, aptamer-based bioassays can adopt different assay configurations to transduce bio-recognition events. Accordingly, various assay configurations have been designed and reported. Nevertheless, the majority of these designs fall into two categories (Fig. 1.): a. Single-site binding and b. Dual-site binding. For small molecular targets, nuclear magnetic resonance studies have indicated that they are often buried within the binding pockets of aptamer structures (Fig. 1A), leaving little room for the interaction with a second molecule. Hence, small-molecule targets are often assayed using the single-site binding configuration.

Fig. 1 . Aptamer-based assay formats. (A) Small-molecule target buried within the binding pockets of aptamer structures; (B) single-site format; (C) dual-site (sandwich) binding format with two aptamers; and, (D) ‘‘sandwich’’ binding format with an aptamer and an antibody.

In contrast, protein targets are structurally complicated, allowing the interplay of various discriminatory contacts (e.g., stacking, shape, complementarity, electrostatic interactions, and hydrogen bonding). As a result, protein targets can be assayed via both single-site binding (Fig.1B) and dual-site binding (Fig.1C and 1D). The dual-site binding (aptamer only) assay relies on the availability of a pair of aptamers that bind to different regions of the same protein.

A very important immunoassay that has found varied applications in research, food safety analysis, and diagnostic medicine is the Enzyme-linked immunosorbent assay (ELISA). One approach of ELISA, commonly referred to as sandwich ELISA, involves the simultaneous use of two antibodies or analyte-binding receptor proteins to capture the analyte of interest and to report target detection. Following this idea of sandwich ELISAs, the first dual site-binding, mixed ELISA–aptamer-based bioassay was described by Drolet and colleagues in 1996 (Fig. 2.). This new detection method was appropriately coined ELONA (Enzyme-Linked Oligonucleotide Assay) in which the reporting antibody/ protein of ELISA is substituted for a fluorescein-tagged aptamer specific for detecting the target of interest (Fig. 1). Drolet et al. used a fluorescein-tagged nuclease-resistant aptamer derived through the SELEX process against human VEGF (hVEGF) and a monoclonal hVEGF capture antibody as a model. Signal was collected for quantitation of hVEGF in human sera using a chemiluminescent alkaline phosphatase detection system after final incubation with alkaline-phosphatase-conjugated anti-fluorescein Fab fragments. The authors showed that error, precision, accuracy, interference, and specificity analyses show equivalence to a conventional sandwich ELISA assay, demonstrating that ELONA represents a viable alternative to ELISA in clinical and research applications.

Fig. 2. First sandwich ELONA described by Drolet et. al. (1996). This assay made use of antibodies to capture hVEGF and fluorescein-labelled aptamers as a reporter

To further exclude the use of antibodies in sandwich assays, Vivekananda and Kiel devised a method that employs aptamers as the target capturing and reporting elements. This technique was coined ALISA (Aptamer-Linked Immobilized Sorbent Assay). It was applied to examine the specificity of an aptamer against an antigen associated with Francisella tularenis, a bacteria which causes tularemia or rabbit fever, an infectious endemic disease. ALISA is also referred to as Enzyme-linked aptamer sorbent assay. ALISA relies on two different aptamers generated against one target. One aptamer attached to the surface (chip, microtiter plate, nanoparticles etc.) is called the capture probe while the second aptamer labelled with the reporter is called the reporter probe. The reporter probe gives a signal upon binding to the target. Reporter probes are often conjugated with signalling moieties (e.g., fluorophores, enzymes or nanoparticles). Generally speaking, capture and reporter probes have different nucleic acid sequences; however, in limited cases, some proteins (e.g., dimeric) contain two identical binding sites, thus allowing the use of a single aptamer for the sandwich assay.

ELONA, also known as Enzyme-linked aptamer assay (ELAA), can also be used in the direct or indirect competitive bioassay configuration to detect small amounts of analyte. Similar to competitive ELISA, in competitive ELAA, the labelled and unlabelled analyte compete for a limited amount of binding aptamer. In the indirect competitive ELAA after allowing binding of the labelled analyte to the microtiter plate and blocking with an appropriate blocking agent, suitably labelled aptamer probe along with unlabelled analyte is added. After binding completes, a suitable read-out method is used to collect the signal generated from the bound labelled aptamer probe. In the direct competitive assay, the labelled aptamer is adsorbed on the microtiter plate. After suitably blocking the plate, a mix of labelled and unlabelled analyte is added and the signal is collected for quantification.

Outline of Steps and Materials in the Experimental Workflow

The ELONA method consists of the following steps:

Immobilization of the analyte/labelled aptamer on the assay platform

This step involves binding of either the analyte or capture probe, depending on the assay format being employed, to an appropriate platform such as a microtiter plate or chip. Immobilization can be achieved through covalent binding, adsorption, affinity coupling etc. After this step, is a blocking step that ensures all non-specific binding sites are blocked.

Sample preparation

This step varies depending on the specific analyte of interest. For e.g. it could include genomic DNA from a pathogen, patient sera or blood samples, protein lysate from bacteria etc. Appropriate steps need to be followed for sample extraction as the case may be.

Sensing the analyte

In case of direct, single-site binding ELAA, where the analyte is immobilized on the plate support, this step involves addition of labelled aptamer. Following binding and washing, the signal can be detected using an appropriate method depending on the label associated with the aptamer probe, i.e. fluorophores, enzymes etc. In case of direct, single-site binding ELAA, where the capture probe is immobilized on the solid support, this step involves addition and binding with labelled analyte, signal from which can then be detected after washing. For dual site-binding/sandwich ELAAs there is an additional step where the reporter probe is added following binding of analyte to the capture probe.

As described earlier, ELAA can be run as a competitive binding assay too. An example of indirect and direct competitive ELAA for quantification of residual tetracycline (TC) from antibacterial treatment of hives during the production of honey are described below (Fig. 3). In the indirect format, the microtiter plates are first coated with TC-BSA (competitor antigen). After blocking with Hammerstein bovine casein, biotinylated aptamer and unlabelled TC are added and binding allowed. After washing Streptavidin-Horseradish peroxidase (SA-HRP) is added. Finally TMB solution (HRP substrate) is added, followed by H ₂ SO ₄ to stop the reaction and absorbance is measured. In the direct competitive ELAA for TC using the same biotinylated aptamer, the plate is first coated with SA, blocked and then binding of biotinylated aptamer along with unlabelled TC is carried out. After washing, TC-HRP conjugate is added and TMB solution is used for the signal readout as earlier.

Fig. 3. Direct and indirect competitive ELAA for detecting residual tetracycline in honey

Value of This Application in the Discovery Stage of Research

Since the first reported ELAA in 1996, significant progress has been made in utilizing aptamers in detection assays.

Recently, several groups have reported aptamer-based biomarker discovery platforms with multiplexing capabilities. Gold and co-workers have described a biomarker discovery system that is capable of simultaneously measuring thousands of proteins from serum or plasma samples. Using their system, they discovered 58 potential biomarkers for chronic kidney disease. The same group, using their patented aptamers called SOMAmers, reported a large-scale study of screening serum samples to discover biomarkers for non-small cell lung cancer. These two reports showcase the significant improvements in the development of highly sensitive, aptamer-based biomarker discovery platforms.

A novel electrochemical sensor system based on two different aptamers for the detection of thrombin was developed by Ikebukuro et al. The authors integrated two aptamers recognizing different epitopes of thrombin (fibrinogen and heparin binding sites) in their sandwich assay. One of the aptamers was thiol-modified and immobilized on a gold electrode for capturing thrombin, while the other aptamer, labeled with a pyrroquinoline quinone glucose dehydrogenase, indicated complex formation.

To overcome the limitations associated with colorimetric or fluorescent readout in ELONAs, Morena et al, have combined the mid-range sample throughput potential of ELONA with the sensitivity of SYBR green-based, real-time quantitative PCR(qPCR). The use of aptamers as (RT)qPCR-amplifiable reporter molecules excludes the need for aptamer or target labelling, allowing a straightforward assay with enhanced sensitivity.

Their specific binding properties and antagonistic effect on protein function makes aptamers well suited as artificial ligands for target validation applications in context with high-throughput screening. Green et al. provided the first evidence that known small-molecule inhibitors can compete with aptamers in biochemical displacement assays. Researchers have expanded this concept to novel inhibitors of disease-relevant targets. For example, screening with inhibitory aptamers led to the identification of functionally equivalent low molecular weight compounds for the guanosine 5′-diphosphate (GDP)/guanosine 5′-triphosphate (GTP) exchange factor cytohesin-1 and the HIV rev protein. These aptamer-based competitive screening assays were successfully adopted to different readouts, such as fluorescence intensity, fluorescence resonance energy transfer, fluorescence polarization, fluorescence lifetime, radioactivity, and enzyme-linked reactions.

Along with the rapid progress of modern analytical technologies and the application of novel analytical reagents (e.g., nanomaterial-based probes), more and more aptamer-based bioassay formats are being developed. These technologies have been introduced into analytical applications, target validation, and drug discovery processes. In contrast to many other drug discovery technologies, neither target nor small-molecule labeling is required in the aptamer approach. It is especially useful when the natural ligand/substrate is unknown, too expensive to produce, or an x-ray structure is unavailable. Furthermore, these assay systems can be applied when new sites on a protein need to be explored, aiming for small-molecule drugs with potentially new mechanisms of action.

References

Mok W, Li Y. Recent Progress in Nucleic Acid Aptamer-Based Biosensors and Bioassays. Sensors (Basel). 2008;8(11):7050-7084.
Ikebukuro K, Kiyohara C, Sode K (2005) Novel electrochemical sensor system for protein using the aptamers in sandwich manner. Biosens Bioelectron 20:2168–2172.
Moreno M, et al. Combined ELONA-(RT)qPCR Approach for Characterizing DNA and RNA Aptamers Selected against PCBP-2. Molecules. 2019;24(7):1213.
Gold L , Ayers D, Bertin J, Bock C, Bock A, et al. (2010) Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery. PLoS ONE 5: e15004.
Drolet, D.W.; Moon-McDermott, L.; Romig, T.S. An enzyme-linked oligonucleotide assay. Nat. Biotechnol. 1996, 14, 1021-1025.
Dong Y and Wang S, Enzyme-linked aptamer assay. Aptamers for Analytical Applications: Affinity Acquisition and Method Design, 2018 Wiley-VCH Verlag GmbH & Co. KGaA
Somasunderam A, Gorenstein DG, Aptamers as Novel Reagents for Biomarker Discovery Applications. Translational Medic 2011. S1:001. doi:10.4172/2161- 1025.S1-001
Proske, D., Blank, M., Buhmann, R. et al. Aptamers—basic research, drug development, and clinical applications. Appl Microbiol Biotechnol 69, 367–374 (2005).

Addressing the Poor Stability Issues in Fusion Protein Cleavage

Tue, 08 Sep 2020 18:07:27 GMT

Addressing Poor Stability Factors During Fusion Protein Cleavage

Measures in preparing your proteins for optimal yield and purity

Introduction

Expression of recombinant proteins as translational fusions is commonly employed to enhance stability, increase solubility, and facilitate purification of the desired protein. Affinity tags are appended to proteins so that they can be purified from their crude biological source using an affinity technique. Affinity resins are available as capture reagents to purify these tagged proteins. Affinity tags that are commonly fused to proteins of interest using various expression vector systems, include (polyhistidine), FLAG (DYKDDDDK), glutathione S-transferase (GST), and Myc tags (1).

In general, such fusion proteins must be cleaved to separate the fused tag and release the mature protein in its native form (2). Purification and on-column fusion protein cleavage methods have been developed to isolate recombinant, untagged proteins in a single chromatographic step. Use of a GST-fusion partner in conjunction with glutathione affinity media and application of an on-column cleavage strategy is one of the most effective methods in terms of simplicity, flexibility, robustness, efficiency, and fusion protein purity (3,4,6).

However, all fusion protein systems present an inherent problem - the fusion partner (affinity tag) is often difficult to remove. Most systems rely on proteolytic cleavage to separate the fusion partner from the target protein. Several problems may be encountered during proteolytic cleavage, including:

spurious, non-specific proteolytic attack of the fusion protein;
the need for elevated temperatures for efficient cleavage, which can denature or cause aggregation of the fusion protein;
incomplete cleavage, which reduces the yield and/or introduces heterogeneity in the purified protein;
the need for additional steps to separate the cleaved fusion protein from the fusion tag, deactivate and remove the protease, and exchange buffer or desalt.

The pGEX E. coli expression vectors, available as part of the GST Gene Fusion system, encode for N-terminal GST molecules followed by protease cleavage sites in all three reading frames and with three different protease cleavage sites. In this study, pGEX-6P-1, pGEX-5X-1, and pGEX-2T which encode optimal recognition sites for PreScission Protease, factor Xa, and thrombin, respectively, have been used.

The performance of PreScission Protease, factor Xa, and thrombin was compared by screening their enzymatic stability, efficiency in removing the GST-fusion partner, and proteolytic specificity on cleavage of a diverse range of fusion proteins.

Preparation of GST-fusion proteins and binding to GSTrap ^TM FF column

PreScission Protease, recombinant polyhistidine-tagged factor Xa, and thrombin, (2 units enzyme/mg of bound fusion GST-fusion protein) were diluted in the appropriate cleavage buffer equal to 90% of the volume of the two 5 ml GSTrap ^TM FF columns. The enzymes were injected into the columns at a flow rate of ~5–7 ml/min using a syringe. Following injection, the column was placed in a closed flow status and the system was incubated online for 3–18 h at 4–22°C according to the proteolytic enzyme used.

The Spin-Column Based Method

The easiest and safest method, readily available in a kit format, is the spin-column based method. The binding element in spin-column systems is usually composed of glass particles or powder, silica matrices, diatomaceous earth, and ion exchange carriers. In this method, nucleic acid binding is optimized with specific buffer solutions and extremely precise pH and salt concentrations. Sample lysates are passed through the silica membrane using centrifugal force, with the RNA binding to the silica gel at the appropriate pH. The membrane containing residual proteins and salt is then washed to remove impurities, and flow-through is discarded. RNA is subsequently eluted with RNase-free water.

Elution of cleaved fusion protein

Prior to elution, an auxiliary 1 ml HiTrap column was connected downstream of the 5 ml GSTrap ^TM FF proteolytic cleavage columns, in-line with the fraction collector. The auxiliary column was matched to the protease used for cleavage. The column used was either GSTrap ^TM FF, Ni2+-charged HiTrap Chelating HP, or HiTrap Benzamidine FF (high sub) with specific affinity for PreScission Protease (GST-fused enzyme), recombinant polyhistidine tagged factor Xa, or thrombin, respectively. Each column was pre-equilibrated with the appropriate cleavage buffer specific for the enzyme used.

The auxiliary column is beneficial for:

Detaining any cleaved material upon flow start-up, which minimizes loss of cleaved product and allows for rapid baseline recalibration before peak elution.
Filtering and removing the proteolytic enzyme from the released target protein.

Elution of the released target protein occurred immediately upon flow start-up (flow rate of ~1 ml/min). Following elution and the return of absorbance to the baseline, the GST-affinity peak was eluted with elution buffer (optimized buffer for each enzyme) containing 10 mM reduced glutathione applied in a one-step gradient (100% elution buffer).

The GST moiety, any uncleaved GST-fusion protein, endogenous E. coli proteins that have affinity for glutathione, and PreScission Protease, if it was used for cleavage, are all eluted in this step.

Eluted protein fractions were analyzed with SDS-PAGE according to standard procedures (7) and protein quantitation was determined using Coomassie ^TM Protein Assay Reagent (Pierce).

Temperature-dependence of proteolytic cleavage

The effect of temperature on cleavage of GST-p52 fusion protein was tested using a 12 h digestion period (Fig. 1). Each enzyme was tested at 4°C, 12°C, and 22°C, the optimum temperatures for PreScission Protease, factor Xa, and thrombin, respectively.

Fig.1. SDS gel electrophoresis of eluates following on-column cleavage of GST-p52 fusion protein at different temperatures. The incubation time was 12 h. Proteases and incubation temperatures are shown above the lanes. The arrow indicates the location of the released p52 protein. M = molecular weight markers.

PreScission Protease shows stable proteolytic processing at 4°C with the highest enriched fraction migrating to the appropriate theoretical molecular weight of the cleaved p52 fusion protein. At 12°C and 22°C, an increase in degraded p52 protein was observed relative to cleavage reactions at 4°C.

Factor Xa cleavage significantly increases degradation of the p52 protein with increasing temperature. When the temperature was elevated to 12°C and 22°C, the band corresponding to p52 protein decreased in intensity and shifted to a lower molecular weight breakdown product of ~Mr 26,000.

Thrombin cleavage is temperature dependent with poor cleavage occurring at 4°C. The majority of cleaved p52 protein was in the form of a breakdown product migrating at ~Mr 32,000. In addition, aggregation and precipitation of p52 occurred upon elution from the column. At elevated incubation temperatures for thrombin, cleavage activity was increased. Aggregation and proteolytic breakdown of p52 protein occurred and the formation of a stable p52 degradation product with ~Mr 32,000 was observed. Upon sample loading on the SDS polyacrylamide gel, cleaved p52 protein aggregated and precipitated, necessitating resolubilization prior to electrophoresis.

Time-dependent proteolytic cleavage

The effect of incubation time on cleavage of GST-p40 was examined using each protease at its optimum temperature (Fig. 2). Samples were incubated for 6, 12 and 18 h.

Fig. 2. SDS gel electrophoresis of eluates following on-column cleavage of GST-p40 fusion protein for different incubation times at optimum temperatures. Proteases, optimum incubation temperatures, and incubation times are shown above the lanes. The arrow indicates the location of the released p40 protein. M = molecular weight markers.

Longer incubation times did not affect results when using PreScission Protease at its optimum temperature.

Factor Xa displayed a slight increase in p40 protein degradation with longer incubations. More p40 breakdown products were observed after each successive incubation period.

Thrombin cleavage resulted in immediate spurious proteolytic attack on the p40 protein. The primary breakdown product yields (~Mr 37,000) appeared after 6 h of incubation. After 18 h, the yield of the breakdown product is approximately equal to that of intact p40 protein. In addition, observed levels of p40 protein were significantly decreased following thrombin cleavage because of protein aggregation and precipitation upon elution from the column.

pH-dependent proteolytic cleavage

The effect of pH on cleavage of GST-p28 was tested at three pH values using a 12 h digestion (Fig. 3). Each enzyme was tested at its optimum temperature at pH 7.4 (phosphate buffered saline), 7.7 (HEPES), and 8.0 (Tris-HCl).

Fig. 3. SDS gel electrophoresis of eluates following on-column cleavage of GST-p28 fusion protein at different pH values at optimum temperatures. The incubation time was 12 h. Proteases and pH values are shown above the lanes. The buffers used at each pH value were phosphate buffered saline, pH 7.4; HEPES, pH 7.7, and Tris-HCl, pH 8.0. The arrow indicates the location of the released p28 protein. M = molecular weight markers.

pH did not affect purity or concentration of the final p28 protein during cleavage with PreScission Protease.

For factor Xa or thrombin, pH did not considerably affect the final p28 protein in terms of homogeneity. The final yield of p28 is, however, generally reduced compared with normalized protein levels due to aggregation and precipitation of the p28 protein after on-column cleavage.

Salt-dependent proteolytic cleavage

Salt sensitivity of the cleavage reactions was tested at two commonly used salt concentrations; 30 mM (NH4) ₂ SO ₄ and 300 mM NaCl. Digestions were performed at optimum temperatures for the proteases for 6 h with GST-p71 as substrate (Fig. 4).

Fig. 4. SDS gel electrophoresis of eluates following on-column cleavage of GST-p71 fusion protein at different salt concentrations at optimum temperatures. The incubation time was 6 h. Proteases and salt concentrations are shown above the lanes. The arrow indicates the location of the released p71 protein. M = molecular weight markers.

Under these conditions, PreScission Protease did not affect the homogeneity of the final p71 protein product in the presence of the selected salts.

Factor Xa cleavage reduced the level of soluble cleaved p71 protein relative to PreScission Protease, due to cleaved p71 protein aggregation and precipitation following column elution. A stable p71 break- down product of ~Mr 53,000 was observed.

Thrombin cleavage also reduced the level of soluble cleaved p71 protein relative to PreScission Protease. The presence of 30 mM (NH4) ₂ SO ₄ appears to be more effective in terms of soluble p71 protein yield. As in the case of the factor Xa-cleaved product, a stable p71 breakdown product of ~Mr 53,000 was observed.

Additive-dependent proteolytic cleavage

The on-column cleavage strategy was used to examine the effect of additives on cleavage of GST-p105 fusion protein (Fig. 5). The additives used were 2 mM DTT, 2% (v/v) glycerol, or 0.1% (v/v) TritonTM X-100. Cleavage reactions were incubated at the optimum time and temperature for each enzyme (12 h, 4°C for PreScission Protease; 6 h, 12°C for factor Xa; 3 h, 22°C for thrombin).

Fig. 5. SDS gel electrophoresis of eluates following on-column cleavage of GST-p105 fusion protein in the presence of various additives. Cleavage reactions were incubated at the optimum time and temperature for each enzyme as indicated above each lane. The arrow indicates the location of the released p105 protein. M = molecular weight markers.

Negligible differences among the additives were observed in the final p105 protein product following cleavage with PreScission Protease. In the presence of 0.1% (v/v) Triton X-100, the PreScission Protease cleaved p105 protein displayed a diffuse migration pattern on the gel.

Factor Xa cleavage in the presence of the additives resulted in low yields of p105 protein. A common degradation pattern was observed, with a predominant degradation product of Mr ~75,000.

Thrombin cleavage reactions displayed poor solubility following on-column cleavage and elution. Soluble, cleaved p105 protein was not detected following thrombin cleavage in the presence of the additives. In the presence of 0.1% Triton-X-100, a minor soluble p105 protein breakdown product migrating at Mr ~75,000 was observed. Additional breakdown products migrating at Mr ~30,000 were also detected. The Mr ~75,000 degradation product is similar in size to the product observed in the Factor Xa experiments. The remaining cleaved p105 protein material was precipitated on-column or immediately following elution in all experiments with thrombin.

Conclusion

Recombinant proteins are commonly expressed as translational fusions to Glutathione S-transferase (GST) for facilitating large-scale expression and purification. Removal of the GST tag is often necessary to be able to perform functional or structural studies of the target protein. In this study three protease sites (PreScission protease; factor Xa; and thrombin) were tested on a variety of target proteins to elucidate a trend in proteolytic behavior.

Although protease digests have to be optimized for each protein of interest, some general conclusions can be made.

Performing the digest at optimum temperature is crucial for efficient cleavage. PreScission protease was superior to the other enzymes tested, primarily for its activity at 4°C, making this protease a good choice when working with temperature-sensitive proteins.

Thrombin performed the poorest in these sets of experiments, demonstrating that non-specific cleavage is more likely to take place with this enzyme. Thrombin also possesses a relatively high temperature optimum (22°C), which can adversely affect protein stability.

With factor Xa, problems concerning specific cleavage were frequently observed.

Salt concentrations and pH values tested in this study did not make a significant difference in the proteolytic behavior of these proteases, indicating a relatively high tolerance for variation in these parameters.

The cleavage conditions are more dependent on the protein of interest and should be optimized for each target protein separately taking into consideration protein instability, cleavage efficiency, aggregation, and purity of the final cleaved protein product.

-It is your turn now-

References

Kimple ME, Brill AL, Pasker RL. Overview of affinity tags for protein purification. Curr Protoc Protein Sci. 2013;73:9.9.1-9.9.23. Published 2013 Sep 24.
Coligan,J.E., Dunn,B.M., Ploegh,H.L., Speicher,D.W. and Wingfield,P.T. (eds) (2001) Current Protocols in Protein Science, Vol. 2. Wiley, New York.
Cordingley M. G. et al., J. Biol. Chem. 265, 9062–9065 (1990).
Walker P. A. et al., BioTechnology 12, 601–605 (1994).
Ausubel, F. M. et al. (eds.), Short Protocols in Molecular Biology, John Wiley & Sons, New York, (1992).
Knaust, R. et al., Life Science News 6, 12–13 (2000).
Fling, S. P, and Gregerson, D. S., Anal. Biochem. 155, 83–88 (1986).

Cleavage of GST Fusion Proteins With PreScission Protease

Tue, 08 Sep 2020 15:58:47 GMT

Cleavage of GST Fusion Proteins With PreScission Protease

Introduction

Recombinant proteins are commonly expressed as translational fusions to Glutathione S-transferase (GST). GST is a naturally occurring 26 kDa protein found in eukaryotic cells. The GST moiety binds with high affinity to glutathione coupled to a Sepharose matrix (Glutathione Sepharose). This binding is reversible and the protein can be eluted under mild, non-denaturing conditions by the addition of reduced glutathione to the elution buffer.

Removal of the GST tag is often necessary to be able to perform functional or structural studies of the target protein. A specific protease site engineered between the GST moiety and the protein of interest allows removal of the GST moiety from the target recombinant protein. The GST can then be removed from the sample by re-chromatography on a glutathione column, and the protein of interest purified to homogeneity by other techniques such as gel filtration or ion exchange.

Fusion proteins produced from a variety of E. coli pGEX vectors carry a PreScission Protease cleavage motif between the GST moiety and the cloned fusion partner. PreScission Protease is a genetically engineered fusion protein consisting of human rhinovirus 3C protease and GST. It specifically cleaves between the Gln and Gly residues of its recognition sequence of LeuGluValLeuPheGln/GlyPro .

PreScission Protease itself has a GST tag and therefore will bind to Glutathione Sepharose; it will thus not co-elute and contaminate the cleaved target protein. Cleavage with PreScission Protease is very speciﬁc, and maximum cleavage is obtained in the cold (the protein is most active at 5°C), thus improving the stability of the target protein. It can be used either following affinity purification or while fusion proteins are bound to Glutathione Sepharose columns. The molecular weight of PreScission Protease is approximately 46 kDa.

Protocol

The following protocol describes the steps for cleavage of GST-fusion proteins with PreScission Protease:

Note : The amount of PreScission Protease, temperature, and length of incubation required for complete digestion varies according to the speciﬁc GST-tagged protein produced. Optimal conditions should always be determined in pilot experiments. It is recommended that samples be removed at various time points and analyzed by SDS-PAGE to estimate the yield, purity, and extent of digestion during pilot experiments.

PreScission Protease is provided at a concentration of 2U/μl (833 to 1000 U/mg) in Storage Buffer (50 mM Tris-HCl, 150 mM NaCl, 10 mM EDTA, 1 mM dithiothreitol, pH 8.0, 20% glycerol). Store the solution in small aliquots at -20°C in order to preserve activity.

Unit Definition: One unit will cleave ≥ 90% of 100 μg of a test GST-fusion protein in Cleavage Buffer at 5°C for 16 hours.

Cleavage buffer preparation (before digestion): 50mM Tris-HCl, 150 mM NaCl, 1 mM EDTA, 1 mM DTT, pH 7.0 at 25°C. Chill to 5°C prior to use.

Note : Digestion may be improved by adding Triton ^TM X-100, Tween ^TM 20, Nonidet ^TM , or NP40 to a concentration of 0.01%. Concentrations of these detergents up to 1% do not inhibit PreScission Protease activity.

Prescission protease can be used for fusion protein cleavage in two ways:

1. On-column cleavage

2. Cleavage in solution

On-column cleavage protocol: The removal of GST tags from target fusion proteins while they are still bound to the purification column is recommended as it facilitates cleavage of target protein and removal of the PreScission Protease from the sample in the same step. The fusion partner which has been cleaved from the GST moiety will be present in the flow-through whereas both PreScission Protease and the GST moiety will remain bound to the Glutathione Sepharose. Residual PreScission Protease remaining in the flow-through, if any, can be removed by passing the sample over fresh Glutathione Sepharose.

Step 1.

Bind the GST fusion protein sonicate to the…..

Why Nucleic Acids Need Better Quality Testing

Tue, 28 Jul 2020 17:13:28 GMT

Extensive Quality Testing Suitable for Nucleic Acid Reagents

Workflows fit for research DNA & RNA

The case for quality control of commercial oligonucleotides remains a challenge. Particularly for research-grade (RUO) DNA/RNA reagents. While QC for these RUO reagents remain notoriously underrated, kbDNA delivers a solution for upping the standard. More testing at the same low price.\

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~10 applications testing

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Rational Reagent Tactics for Optimizing Biomarker Analysis

Tue, 21 Jul 2020 21:05:09 GMT

Rational Reagent Tactics for Optimizing Biomarker Analysis

The selection or rational design of a linker to join fusion protein domains is an important, under-explored area in recombinant fusion protein technology

Background

Sourcing and applying multiple proteins into a specific biomarker assay involves a variety of moving pieces. Particularly during discovery stage research, where molecules of interest are constantly changing relative to hit identification. In other words, protein reagents play a significantly underrated role in developing early assays for biomarker analysis.

This article explores key material components and common oversight in recombinant protein approaches to help demonstrate factors effecting assay design. Additionally, we present a set of rational tactics for optimizing biomarker analysis through the procurement and criteria of laboratory/assay reagents.

Topics Covered

Insight on various aspects of the biomarker workflow, such as:

Expression Hosts
Tag/labeling
Qualifying quality

Critical reagents development relative to vendor consistency

Take the next step in optimizing your biomarker analysis.

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Viral RNA Isolation Methods Reviewed: Spin vs. Magnetic

Fri, 22 May 2020 17:49:14 GMT

Viral RNA Isolation Methods Reviewed: Spin vs. Magnetic

Shalaka Samant, Ed Hamdeh, Cindy Lee

kbDNA INC. – Cambridge, MA U.S.A

Introduction

Nucleic acid extraction is the primary step for many downstream applications in molecular biology. Genomic (or chromosomal) DNA, plasmids, and different types of RNAs represent the broad categories of intracellular nucleic acids that are typically isolated from a variety of samples. High-quality yields of contamination-free RNA are required for downstream use in various applications such as cDNA library preparation, microarrays , RT-PCR and other PCR-based assays. It is also critical for high-throughput transcriptome analysis and high-throughput sequencing. A rapid and efficient isolation method to obtain high purity sample with maximal yield of non-degraded RNA is the key to the success of all these analyses.

Due to the delicate nature of RNA, the RNA purification process consists of a variety of unique challenges, one of which is ribonuclease (RNAse) contamination. RNAses are abundant in the environment and even a trace amount of RNase contamination can sabotage RNA-based experiments. Several precautions such as the use of RNase-free reagents, dedicated pipettes, glassware, gloves, and working in an RNAse-free environment need to be followed to achieve a good RNA yield.

Often minute amounts (low viral load per ml, typically 7812062235 particles/ml) of viral RNA need careful extraction from samples such as tissues, nasopharyngeal/oropharyngeal swabs, sputum, blood, plasma, or other body fluids. Viral RNA might also be extracted from water or other environmental samples. Sometimes investigators might need to quantify the viral particles contaminating medicinal products such as vaccines. Since the viral load of these biological, medicinal, and environmental samples is usually exceptionally low, RNA isolation consists of two major steps - virus concentration followed by RNA extraction. Viral concentration is usually achieved by applying various precipitation, flocculation, and filtration techniques.

The three most common RNA extraction strategies are:

Organic extraction method
Spin-column based method
Magnetic bead-based method

The Organic Extraction Method

The organic extraction method is the most tried-and-tested method for RNA extraction and removal of cellular proteins. Here RNA isolation is achieved through organic extraction followed by RNA precipitation. This technique involves lysis/extraction in a monophasic solution of phenol and guanidine isothiocyanate. Chloroform is then added. The phenol-chloroform mixture is immiscible with water. Therefore, when centrifuged, the sample forms two distinct phases. The lower (organic) phase and phase interface contain denatured proteins, while the less-dense upper (aqueous) phase contains the RNA. The aqueous phase containing the RNA is carefully removed by pipetting (with care not to touch the interface or organic phase, as this can contaminate the sample). The RNA is then precipitated with isopropanol and rehydrated for further analysis.

Organic extraction protocols are well-established and are useful for most sample types. Proteins are rapidly denatured, and RNA is quickly stabilized. The process is scalable and can be completed in 30-60 minutes. However, this method is not amenable to high-throughput processing and is difficult to automate. New users find the phase separation and careful pipetting of aqueous phase challenging to master. Chemical fume hood needs to be used due to the hazardous chemicals. This method also requires consideration of appropriate disposal of these chemicals. Manual handling of large number of samples is cumbersome.

The Spin-Column Based Method

Fig 1: Schematic of RNA isolation using spin-column technology

Column-based RNA extraction is one of the best techniques among the options available, playing a vital role in ion exchange methods, as it provides a robust stationary phase for a rapid and reliable buffer exchange and thus nucleic acid extraction. This method is fast and reproducible, and its main drawback is the need for a small centrifuge. Vacuum-based systems can also be used in place of centrifugation to separate impurities. Researchers can also combine the organic extraction method with the spin column method for faster and greater RNA yield. This method is fast (20 minutes) and amenable to large-scale and high-throughput processing, including automated methods. Protein or DNA contamination is possible if the sample amount is large or remains incompletely homogenized or lysed. Incomplete lysis can also lead to low yields of viral RNA. Automation can be complex and expensive due to need for setting up centrifugation or vacuum-based separation systems.

The Magnetic Bead Based Method

The magnetic bead based method relies on the use of magnetic beads and reagents optimized for RNA extraction. The beads have a paramagnetic core, usually coated with silica for nucleic acid binding. Sample is lysed in a buffer with RNase inhibitors and then incubated with the magnetic beads, allowing the particles to bind RNA molecules. The magnetic beads can then be quickly collected by being placed in proximity to an external magnetic field. The supernatant is removed, and beads are subsequently washed in a suitable wash buffer with removal of the magnetic field. This process can be easily repeated for multiple washes. The RNA is eluted from the magnetic beads with RNase-free water into solution, and the supernatant (containing the pure RNA) can then be transferred.

Fig 2: Schematic of RNA isolation using magnetic bead-based technology

The magnetic bead collection steps are simple and quick to perform. There is a reduced risk of clogging as no column is involved. This technique is the most amenable to scale-up, high-throughput separation, and automation. The clean-up is more effective due to the movement of the beads. However, viscous samples could impede the movement of the beads and occasionally the final sample maybe contaminated with magnetic beads. A magnetic stand is required for manual separation and a magnetic particle handler for the automation of this process.

Table 1: Summary of key differences between spin column based and magnetic bead based viral RNA isolation

References

Ali N, Rampazzo RCP, Costa ADT, Krieger MA. Current Nucleic Acid Extraction Methods and Their Implications to Point-of-Care Diagnostics. Biomed Res Int. 2017; 2017:9306564.
Burgener M, Candrian U, Gilgen M. Comparative evaluation of four large-volume RNA extraction kits in the isolation of viral RNA from water samples. Journal of Virological methods, 2003, 108(2): 165-170.
Kok T, Wati S et al, Comparison of six nucleic acid extraction methods for detection of viral DNA or RNA sequences in four different non-serum specimen types. J Clin Virol. 2000 Feb;16(1):59-63.
Hjelmsø MH, Hellmér M, Fernandez-Cassi X, Timoneda N, Lukjancenko O, Seidel M, et al. (2017) Evaluation of Methods for the Concentration and Extraction of Viruses from Sewage in the Context of Metagenomic Sequencing. PLoS ONE 12(1): e0170199.
Seah C, Chow V, Chan Y, Doraisingham S (1995) A comparative, prospective study of serological, virus isolation and PCR amplification techniques for the laboratory diagnosis of dengue infection. Serodiagnosis and Immunotherapy in Infectious Disease 7: 55-58.
Comparison of five viral nucleic acid extraction kits for the efficient extraction of viral DNA and RNA from cell-free samples. DOI: 10.15761/TiM.7812062235.

An Overview of Linkers for Recombinant Fusion Proteins

Fri, 08 May 2020 20:44:13 GMT

An Overview of Linkers for Recombinant Fusion Proteins

The selection or rational design of a linker to join fusion protein domains is an important, under-explored area in recombinant fusion protein technology

Introduction

A fusion protein is a protein consisting of at least two domains that are encoded by separate genes that have been joined so that they are transcribed and translated as a single unit, producing a single polypeptide. By genetically fusing two or more protein domains together, the fusion protein product may obtain many distinct functions derived from each of its component moieties. Three of the most frequent uses of fusion proteins are: as aids in the purification of cloned genes, as reporters of gene expression levels, and as histochemical tags to enable visualization of the location of proteins in a cell, tissue, or organism. More recent applications of the fusion protein technology also include creating novel protein therapeutics and improving the performance of current protein drugs.

Two indispensable elements are required for the successful construction of a recombinant fusion protein: the component proteins and linkers. In most cases, the choice of the component proteins is relatively straightforward as it is based on the desired functions of the fusion protein product. However, the selection of a suitable linker(s) to join the protein domains together can be complicated and is often neglected in the design of fusion proteins. Direct fusion of functional domains in the absence of a linker may lead to many undesirable outcomes, including misfolding of the fusion proteins, low yield in protein production, or impaired bioactivity. Therefore, the selection or rational design of a linker to join fusion protein domains is an important, yet under-explored, area in recombinant fusion protein technology.

Summarized below is the current knowledge of linker properties, design and functionality in recombinant fusion protein technology.

Linkers from Naturally Occurring Multi-Domain Proteins

Similar to recombinant fusion proteins, naturally-occurring multi-domain proteins are composed of two or more functional domains joined by linker peptides. These linker peptides serve to connect the protein moieties, and also carry out many other functions, such as maintaining cooperative inter-domain interactions and preserving biological activity. Two studies by Argos (1) and George and Heringa (2) have independently compared several properties of natural linkers, such as length, hydrophobicity, amino acid residues, and secondary structure. The results of these studies are summarized in Table 1.

Table 1: Properties of linkers derived from natural proteins

The main findings of these two studies are:

Structural environment of linkers : These studies calculated the average normalized solvent accessibility and hydrophobicity of various linkers. Higher solvent accessibility was observed with increasing length of linkers, suggesting that longer linkers were more likely to be exposed to the solvent. Consistent with this finding, the average hydrophobicity of the linkers decreased with increase in their length, indicating that longer linkers were more hydrophilic and therefore more exposed to the aqueous solvent than shorter linkers.
Amino acid residue preferences : These studies also determined the amino acid preference in natural linkers by calculating the ratio of the occurrence of a single amino acid in the linker vs the full protein (Table 1). Values greater than 1 indicate a higher occurrence of a particular amino acid in the linker. Threonine (Thr), serine (Ser), proline (Pro), glycine (Gly), aspartic acid (Asp), lysine (Lys), glutamine (Gln), asparagine (Asn), and alanine (Ala) were identified as preferable linker constituents by Argos (1), whereas Pro, arginine (Arg), phenylalanine (Phe), Thr, glutamic acid (Glu) and Gln were preferred in the George and Heringa study (2). In general, preferable amino acids were polar uncharged or charged residues, which constitute approximately 50% of naturally encoded amino acids. Both studies suggested that Pro, Thr, and Gln were the preferable amino acids for natural linkers. Among them, Pro is a unique amino acid with a cyclic side chain which causes a very restricted conformation.
Secondary structures of linkers : Natural linkers adopt various secondary structures, such as helical, β-strand, coil/bend and turns, to exert their functions. From George and Heringa’s analysis, most linkers on average exhibited α-helix (38.3%) or coil/bend (37.6%) secondary structures (Table 1). The conformations were slightly changed when small vs. large linkers were compared, where the majority of linkers adopted coils. On the other hand, the study by Argos showed that the majority of the linkers adopted coil structures (59%).

Overall, natural linkers primarily adopted extended conformations, and had independent structures that did not interact with the adjacent protein domains. Their length, composition, hydrophobicity, and secondary structure together made important contributions towards achieving the desirable functions. Natural linkers could serve as a general reference for the rational design of empirical linkers in recombinant fusion proteins.

Empirical linkers in recombinant fusion proteins

In addition to the many candidate linkers identified from studies on naturally occurring protein linkers, scientists have also designed empirical linkers with a variety of sequences and confirmations for recombinant fusion protein production. These empirical linkers are broadly classified into: flexible linkers, rigid linkers and cleavable linkers.

Flexible linkers : Flexible linkers are usually applied when the protein domains that need to be joined require a certain degree of movement or interaction. They are generally composed of small, non-polar (e.g. Gly) or polar (e.g. Ser or Thr) amino acids. The small size of these amino acids provides flexibility, and allows for mobility of the connecting functional domains. The incorporation of Ser or Thr can maintain the stability of the linker in aqueous solutions by forming hydrogen bonds with the water molecules, and therefore reduce the unfavorable interaction between the linker and the protein moieties. An example of the most widely used flexible linker is the sequence (Gly-Gly-Gly-Gly-Ser)n.
Rigid linkers : While flexible linkers have the advantage of connecting the functional domains passively and permitting a certain degree of movement, the lack of rigidity of these linkers can be a limitation. There are several examples in the literature where the use of flexible linkers resulted in poor expression yields or loss of biological activity. For instance, a Tf-granulocyte colony stimulating factor (G-CSF) fusion protein failed to be expressed with a flexible (GGGGS)3 linker. In another report, the immunoglobulin binding ability of the protein G domain in a protein G-Vargula luciferase fusion protein was not recovered after inserting a flexible GGGGS linker. The ineffectiveness of flexible linkers in these instances was attributed to an inefficient separation of the protein domains or insufficient reduction of their interference with each other. Under these situations, rigid linkers have been successfully applied to keep a fixed distance between the domains and to maintain their independent functions. Rigid linkers exhibit relatively stiff structures by adopting α-helical conformations or by containing multiple Pro residues. Examples of some rigid linkers are: (EAAAK)n and (XP)n, with X designating any amino acid, preferably Ala, Lys, or Glu.
In vivo cleavable linkers : Flexible and rigid linkers represent stable linkers that covalently join functional protein domains together to act as one molecule throughout the in vivo processes that the component protein(s) are involved in. This stable linkage between functional domains provides many advantages such as a prolonged plasma half-life (e.g. albumin or Fc-fusions).

However, it also has several potential drawbacks including steric hindrance between functional domains, decreased bioactivity, and altered biodistribution and metabolism of the protein moieties due to the interference between domains. Under such circumstances, cleavable linkers are used to release free functional domains in vivo. This type of linker may reduce steric hindrance, improve bioactivity, or achieve independent actions/metabolism of individual domains of recombinant fusion proteins after linker cleavage. The design of in vivo cleavable linkers in recombinant fusion proteins is quite challenging. Unlike the versatility of crosslinking agents available for chemical conjugation methods, linkers in recombinant fusion proteins must necessarily be oligopeptides. Some examples of in vivo cleavable linkers are described below:

An in vivo cleavable disulfide linker (LEAGCKNFFPR↓SFTSCGSLE), based on the reversible nature of the disulfide bond, was designed for recombinant fusion proteins by Chen et al. (3), and offered the advantage of generating a precisely constructed, homogeneous product by recombinant methods. This disulfide linker was based on a dithiocyclopeptide containing an intramolecular disulfide bond formed between two cysteine (Cys) residues on the linker, as well as a thrombin-sensitive sequence (PRS) between the two Cys residues (Figure 1). This linker was inserted between G-CSF and Tf to construct a model fusion protein (designated as “G-C-T”). The in vitro thrombin treatment of G-C-T resulted in the cleavage of the thrombin-sensitive sequence, while the reversible disulfide linkage between the two domains of the fusion protein remained. The resultant disulfide-linked protein was designated as “G- S-S-T”. This disulfide-linked fusion protein was demonstrated to be cleavable in vivo following intravenous administration to CF1 mice. A rapid release of G-CSF from G-S-S-T in the blood was observed as early as 5 minutes, with a peak at ~15 minutes post injection. The released free G-CSF exhibited a quick elimination due to its short in vivo half-life. In contrast, no detectable amount of free G-CSF was released in vivo from G-C-T, which has a stable peptide linker. This study demonstrated the construction of a disulfide-linked fusion protein for use in applications where the in vivo separation of protein domains is desired.

Fig.1: Illustration of in vivo cleavable linkers

More recently, a similar cyclopeptide linker was designed to create an in vivo cleavable disulfide linker in an interferon-α2b (IFN-α2b) and HSA fusion protein (4). The dithiocyclopeptide sequence (CRRRRRREAEAC) contains an intramolecular disulfide bond between 2 Cys residues, as well as a peptide sequence sensitive to the secretion signal processing proteases resident in the yeast secretory pathway. During the protein expression, the linker was first cleaved by protease Kex2 at CRRRRRR↓EAEAC, followed by cleavage of proteases Kex1 and Ste13. As a result, the amino acids between two Cys residues in the linker were completely removed during secretion, and the disulfide linked fusion protein was directly expressed from Pichia pastoris.

The in vivo cleavage of the linkers in recombinant fusion proteins may also be carried out by proteases that are expressed in vivo under pathological conditions (e.g. cancer or inflammation), in specific cells or tissues, or constrained within certain cellular compartments (Figure 1). Such in vivo cleavable linkers are designed to incorporate specific protease-sensitive sequences. Unlike the reduction of disulfide bonds which happens rapidly in the blood circulation (3), the specificity of many proteases offers slower cleavage of the linker in constrained compartments. Thus, this type of cleavable linker can be applied to activation of fusion protein bioactivity at specific sites in vivo.

Overall, linkers can adopt various structures and exert diverse functions to fulfill the application of fusion proteins (Table 2). The flexible linkers are often rich in small or hydrophilic amino acids such as Gly or Ser to provide structural flexibility and have been applied to connect functional domains that favor interdomain interactions or movements. In cases where sufficient separation of protein domains is required, rigid linkers may be preferable. By adopting α-helical structures or incorporating Pro, the rigid linkers can efficiently keep protein moieties at a distance. Both flexible and rigid linkers are stable in vivo, and do not allow the separation of joined proteins. Cleavable linkers, on the other hand, permit the release of free functional domains in vivo via reduction or proteolytic cleavage. They can be utilized to improve the bioactivity of chimeric proteins, or to specifically deliver prodrugs to target sites where the linkers are processed to activate bioactivity. The rational choice of linkers should be based on the properties of the linkers and the desired fusion proteins.

Table 2: Summary of empirical linkers

Functionality of linkers in fusion proteins

Apart from their most basic function of covalently joining functional domains of proteins and release them under desired conditions, they also contribute to derived functions such as improving expression yields, biological activity and stability. Some important additional functions of linkers are described below-

Linkers can improve folding and stability of fusion proteins:

The flexible GS linker has been shown to improve folding and stability in several fusion proteins. A very important application of the flexible GS linker is the construction of single-chain variable fragment (scFv), an antigen-binding fusion protein composed of antibody light-chain variable region (VL) tethered to heavy chain variable region (VH) via an oligopeptide linker (5). A flexible linker (GGGGS)3 was designed by Huston et al. to construct a scFv, since its flexible structure would allow for the correct orientation of the VH and VL domains, and would not interfere with the folding of the protein domains (6). The length of the linker was adjusted according to the distance between the C-terminus of the VH domain and the N-terminus of the VL domain under its natural orientation (3.5 nm). The length of the (GGGGS)3 linker was calculated to be about 5.7 nm, and was expected to bridge the VH and VL domains (6). This (GGGGS)3 linker was shown to be suitable for constructing scFv due to its high flexibility, and has since been applied to many other scFvs (7-9). In addition to flexible linkers, helical linkers can also improve fusion protein folding and stability.

Linkers can improve expression of fusion proteins:

Besides impaired biological activity, the difficulty to express stable and high levels of recombinant fusion protein is often another hurdle encountered during the application of fusion proteins for drug delivery. Due to the structural perturbation between protein domains, fusion proteins may be misfolded, unstable and appear as a heterogeneous product, often resulting in a low expression yield. Although the expression of fusion proteins can sometimes be improved by simply switching the orientation of the component protein domains, the interference may not be effectively reduced due to the short distance between domains. Since many linkers can keep domains at proper distance and allow for their independent folding, they can serve as practical tools to enhance the expression yield of recombinant fusion proteins.

Linkers can improve bioactivity of fusion proteins:

By fusing two or more protein domains, a fusion protein usually acquires the biological activities from each component. However, the direct fusion of proteins often results in impaired biological activity, probably because the functional domains are brought too close to properly interact with their corresponding binding proteins (i.e. receptors or ligands). Under these circumstances, linkers may be very effective tools to maintain an appropriate distance between domains to reduce their interference, restore or improve folding, or allow for the in vivo release of the free protein drug domain to ultimately improve bioactivity. The bioactivity of fusion proteins can also be improved by adjusting the length of linkers to increase the space between component proteins.

Linkers can target fusion proteins to specific sites in vivo:

Linker insertion between fusion protein domains can also improve or enable targeting of fusion protein to specific sites in vivo. One way in which linkers can improve targeting is simply by increasing the binding affinity of the targeting protein domain for its receptor. Linkers can provide distance between domains, reduce their interference, and ultimately improve their receptor binding affinity. A second approach for application of linkers to improve drug targeting involves introduction of a linker sequence that will enable specific activation of the fusion protein at the target site. In this approach, the intact fusion protein shows reduced or no biological activity, but the cleavage of the linker at specific sites releases the free, biologically active protein drug domain at the target site (Figure 2).

Fig. 2: Use of linkers to target fusion proteins to specific sites in vivo

For example, a protease present in the lysosome, cathepsin B, has been applied for targeted intracellular activation of cytotoxic proteins. Cathepsin B substrate peptides have previously been utilized as cleavable peptide linkers in many bioconjugates (10, 11). For instance, a dipeptide of Phe-Lys was applied to serve as part of a cleavable linker in an albumin-binding prodrug of doxorubicin 1, for the in vivo release of doxorubicin after Cathepsin B cleavage in the tumor. The cathepsin B-cleavable linkers have recently been applied to fusion proteins. Yuan et. al. used a cathepsin B sensitive peptide of GFLG together with a furin cleavage sequence of R2KR6, to link a tumor-targeting moiety (fragment of C. perfringens enterotoxin) and a toxin (recombinant gelonin) in order to release the toxin in the lysosome (12).

Linkers can affect the PK of fusion proteins:

Fusion proteins provide many advantages over the parent proteins, such as improved PK and PD properties as in albumin- and Fc-fusion proteins, as well as the drug targeting effects seen in immunotoxins. Although several fusion proteins have been applied in the clinic, the mechanisms underlying PK of bifunctional fusion proteins are still largely unexplored, and a generalized PK model for fusion proteins is not established. Target-mediated drug disposition (TMDD), which describes the process where drug-target binding significantly influences the PK and PD of the drug, has been established as a crucial mechanism for the elimination of many single domain protein and peptide drugs (14). Generally, for many protein drugs, the disposition processes affecting their PK are relatively simple, e.g., binding to their cell surface receptor leads to endocytosis and lysosomal degradation. However, the disposition of bifunctional fusion proteins are affected by two different domains/binding sites, and therefore their PK/PD properties are much more complicated. Since linker insertion may alter the receptor binding affinity of each protein domain, it can affect the in vivo disposition of fusion proteins and increase the complexity of PK studies.

Summary

During the development of therapeutic recombinant fusion proteins, linker design has become a valuable means to achieve desired characteristics of the products. Linker sequences derived from natural multi-domain proteins may provide useful references for designing empirical linkers. Various empirical linkers such as flexible, rigid or cleavable linkers have been designed for various purposes, such as passively joining domains, spatially separating domains, or releasing free functional domains in vivo. Optimal linkers can provide many advantages for the production of fusion proteins, including improving structural stability, enhancing bioactivity, increasing expression levels, altering the PK profiles and enabling the in vivo targeting of the fusion proteins. Although many examples of various types of linkers have been developed in the past, the rational design of linkers for the construction of fusion proteins is still in its infancy. Systematic, strategic scientific endeavors are in demand to greatly advance the science of linker design and application. Many technology platforms may be investigated in more depth towards understanding the connection between linker composition and structure, and ultimately tie them to linker function.

The study of linker composition and structure, and the investigation of linker function should go hand in hand when designing a novel linker. A good example of the rational design of linkers are the rigid helical linkers (A(EAAAK)nA) by Arai et al. (15, 16). The idea of using these sequences as a linker developed from the finding that they form an α-helical conformation in water as determined by circular dichroism (17). It was then proposed to apply them to effectively separate protein domains in fusion proteins.

Another fruitful direction would be the establishment of more databases and searching programs for linkers. With the rapid advancement of protein science and biotechnology, the design of linkers in fusion proteins has become more important than ever before. With a thorough understanding of their structures, conformations, and functions via future biomedical research, the incorporation of linkers will greatly facilitate the construction of stable and bioactive recombinant fusion proteins for drug delivery applications.

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Can the Application of siRNA Help Improve Our Targeting of Coronavirus?

Wed, 08 Apr 2020 03:20:13 GMT

Can the Application of siRNA Help Improve Our Targeting of Coronavirus?

Here’s what research has learned so far

As the race for the COVID19 vaccine continues to dominate headlines, we wanted to try and get ahead with a topic that will inevitably become a major focus for those developing antiviral therapies. That topic is centered around the challenges in targeting a coronavirus’ polyprotein structure with high selectivity. This is due to several factors such as the virus’ genomic size, its sequence mutation rate and in-vitro experimental limitations. Consequently, increasing the demand for strategic approaches and creative tools for a laboratories design of experiments. In this review, we make a case for utilizing short-interfering RNA (siRNA) tools and antisense or RNA interference (RNAi) technology as potential solutions to the coronavirus targeting challenges along with highlighting key considerations for identifying viral structural regions.

The Virus

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or COVID-19 has been referenced by many via its various synonyms and some inaccurate names. This has caused a bit of confusion with audiences who aren’t too familiar with viral taxonomy. For the sake of consistency, we will stick with COVID19. COVID19 belongs to the coronaviridae family in the nidovirales order and is one of the largest RNA viruses with a genomic makeup of almost 30 kb ¹ . Although COVID19 is characteristically distinct from other coronaviruses, its viral encoded genes and their assembly conform to the shared principles. The primary gene order from 5’ to 3’ follows; ORF1a + ORF1b (ORF1ab), spike (S), envelope (E), membrane (M) and nucleocapsid (N) proteins. ORF1ab encodes most of the viral regulatory proteins for transcription and translation ² . Next the virus’ primary structural proteins; S, M, E form the lipid bilayer while N proteins build the helical nucleocapsid ³ . In addition, approximately eight accessory or group specific genes are interspersed between these structural proteins ^2,4 . A visual representation of COVID19’s genomic organization can be found in the following schema (Fig. 1).

Fig 1: Genomic Organization SARS-CoV-2 (COVID-19)

Targeting Structural Regions

Proteomic analysis suggests that the interactions between structural proteins present attractive opportunities for anti-SARS agent development ^5,6 . Therefore, the next step would be individually analyzing each domain and determining optimal regions for targeting. Since RNA viruses are variable due to their replications high mutation rate, the underlying challenge in analyzing their structural genes - involves identifying consistent regions with low or complying sequence mutation rates. Published data on coronavirus’ E and N genes suggests that siRNA targeting their proteins leader sequence, terminal repeat short (TRS) and 3’-untranslated (3’-UTR) regions could effectively inhibit the expression of these targets ¹⁴ . However, current literature focus and reproducibility has not been strong enough to support them as top candidates.

Instead- in this review, we evaluate the two structural proteins, S and M in the context of siRNA antisense qualifying standards.

(S) Spike Proteins

The spike is a glycoprotein surface projection which is critical for viral attachment and entry into host cells. Variations of S protein throughout strains of coronavirus have also shown it to be responsible for host range and tissue tropism ⁷ . Results from prior genetic sequencing of patients with similar SARS virus have shown significant variation of S gene in the viral strain. The S1 subunit of S protein is the major antigenic moiety for coronaviruses ³³ . Therefore, as the virus evolves in host environments; it is shown to be prone to having high mutation rates ³³ . Notably, cases have been made for S and S1 domain as ACE2 blocking regions for monoclonal antibody development. It is also worth noting that articles have reported the possibility of inhibiting replication by targeting S gene at U6 promoter site using short-hairpin RNA (shRNA) ¹⁶ . Although this finding does support the application of RNAi, the technical and safety differences between shRNA and siRNA does not directly transfer and demands further exploration. Thus, in principle; S protein would be a potential domain for investigating targeting regions for siRNA compounds.

(M) Membrane Protein

The membrane protein is a triple-spanned transmembrane protein. M gene codes for the most abundant of all the structural proteins and plays an essential role for viral assembly ¹⁰ . The specifics of assembly such as sequence of co-expressing interactions and minimal criteria for viral like particle (VLP) assembly are still controversial for COVID19. As a reference, we can use similar studies of SARS-CoV which indicate that either combination of M & N or M & E are enough to form and release VLPs. Contrary, others showed that N and E, both must co-express with M; in order to efficiently produce and release VLP ^5,6 . While we continue to refine our understanding of the full series of interactions, the current knowledge is enough to highlight the comprehensive role of M protein while influencing the focus on it during analysis.

An attractive feature of M protein is its interactions with intracellular signaling pathways. SARS M protein has been shown to inhibit the nuclear factor kappa B (NF-kB) pathway through direct contact with upstream kinase IKKB ¹¹ . It can also inhibit dsRNA-induced interferon B production by disrupting the formation of the TRAF3-TANK-TBK1/IKKE complex ¹² . Signaling blockades such as these can significantly impair both the hosts innate and adaptive immune responses. Many researchers would agree that this is a clear opportunity for an inhibition strategy. Ultimately, supporting M gene as a high potential targeting candidate for anti-SARS drug development.

Application of siRNA

Site-specific inhibition of cellular mRNA by antisense technology can be achieved in mammalian cells by using 21-25 nucleotide (nt) duplexes of synthetic RNA. This category of synthetic RNA is referred to as siRNA and the discovery of their RNAi utility has been successfully adopted by the infectious disease community for a variety of viruses. This has been the case for inhibiting expression and replication in; poliovirus, HIV-1, HCV, Hepatitis B and influenza virus. Therefore, it only makes sense that siRNA will be explored for RNAi strategies against COVID19.

The complexity of antisense technology, particularly RNAi can be simplified as a two-step process. First, long double-stranded RNA (dsRNA) is processed by the RNAse III enzyme, Dicer into the intended 21-25 nt siRNA. Alternatively, siRNA can be introduced directly via RNA-induced silencing complex (RISC). Secondly, the RISC system ultimately pairs the siRNA by means of antisense to its target messenger RNA (mRNA) complimentary sequence. RISC then proceeds to degrade the target mRNA at the non-paired siRNA sites. To understand how this translates into the research setting, its helpful to analyze previously published work on similar SARS viruses and RNAi applications.

For example, studies developing siRNA to the S gene have reported that targeting the genomeat S protein and NSP12-coding regions has shown success in silencing SARS-CoV expression in cell culture, in-vitro ¹³ . Further evaluation of efficacy in rhesus macque models, found that this approach decreased viral presence, provided relief from infection-induced fever and reduced acute diffuse alveolar damage ¹³ .

Other findings strongly support siRNA targeting of the M gene. It has been demonstrated that cross-analyzing M gene sequences from 15 different SARS-CoV isolates, allowed the identification of two novel conserved targeting regions for siRNA testing ¹⁴ . Real-time quantitative RT-PCR (qRT-PCR) testing of the regions confirmed that siRNA targeting the 3’ half of M gene (si-M2) and the 5’ half (si-M1) both significantly downregulated M gene mediated upregulation of interferon B expression. With si-M2 having induced higher inhibition potency ¹⁴ . Similar findings have also helped support the theory that M gene-specific siRNA might function in a sequence-dependent manner.

The Technical Reality

The innovations in RNAi and its application of siRNA targeting viruses shows clear potential. However, it is imperative to understand that the laboratory research behind this is very rigorous and technically demanding. Those familiar with the methods involved will be the first to emphasis the high degree of experimental analysis required throughout all the steps in developing and testing siRNA. Not to say that this isn’t the case with other research applications, but there is a significantly higher level of consideration for efficacy and safety when planning to transfer this technology into a clinical setting. Not to mention the conflicting relationships between key data such as chemical concentration and toxicology. However, that topic is a rabbit hole of its own. To keep it relevant and help provide an understanding of the technical methodology; we outlined the common experiment workload for the research analysis of siRNA (Fig. 2).

Fig 2: Schematic representation of the general research process in early development of siRNA compounds-specific to target molecule regions. The left-side process displays the sequence of objectives and listed on the right, are the applications relevant to each stage.

What makes this research process even more challenging is its application toward a novel or complex virus. As mentioned, viruses like SARS mutate, and their structures operate in sophisticated fashion. Therefore, thorough analysis is required to go beyond observation to also help identify opportunities for introducing methodologies. In the case of antisense targeting COVID19, each structural domain must undergo individual evaluations to qualify for candidate regions. Following, siRNA sequences are designed against those regions of interest. Then both sequences and regions are tested for validations and optimization is pursued accordingly. Throughout this principled approach, discovery of complicating factors is anticipated along with demand for creative intervention. This has been the case with similar coronaviruses, particularly SARS-CoV which resulted in an array of findings to consider in experiment protocols.

These findings include:

Human coronaviruses are difficult to culture in-vitro. However, their direct cytopathic effects can be demonstrated by inoculating viral isolates into Vero E6 cells – making the cells model suitable enough for studying the effects of siRNA ¹⁵ .
Beyond the study of siRNA properties and aiding sequence alignment, Vero E6 cells are limited in downstream value. Anything more comprehensive requires cell lines derived from preferably mammalian. It is suggested that human embryonic kidney cell line (HEK293) and SV40 T transformed HEK293 (HEK293T) are the most stable for this SARS-CoV application ¹⁴ .
The incorporation of fluorescent control protocols into flow cytometry analysis is strongly recommended for thorough expression inhibition analysis and tracking benchmark ¹⁵ .
The use of partial regions of viral proteins in assay validation are shown to be unreliable and non-compliant with commercial antibodies. Native donor purified protein is the standard. However, they aren’t always an option. The closest alternative would ideally be full sequence whole recombinant protein, untagged ⁹ .
Thermodynamic properties will play a large role in modifying siRNA design, particularly in the sense strand. In one case, functional siRNA duplexes displayed a lower internal stability at 5’ antisense terminal base pair end than the non-duplexes. This prompted changes in nucleotides at certain positions of the sense strand (that expressed low inhibition activity); to unpair the 5’ end of the antisense strand. This allowed the siRNA to reduce target gene expression more effectively ¹⁵ .

Discussion

At present, several potential SARS therapies are under development such as vaccines, treatments and interferons. In terms of COVID19, the urgent priority in the market respectively are vaccines. However, what we have learned from pandemics is that coronaviruses are packed with uncertainty. Whether they are within their structural chemistry, proteomics or behavioral features (ex. symptoms) - this class of virus requires a combination of therapies to help strategically tackle it medically. This demands research to innovate our toolkit with sharper solutions for better precision medicine. One essential solution that correlates with medical efficacy, is the level of selectivity our drugs can target these viruses. Due to being highly customizable and versatile; the application of antisense RNAi using modified siRNA present a made-to-measure opportunity for improved targeting of coronavirus structures.

As explained, coronaviruses present various research challenges such as sequence variability during in-vitro analysis. Of similar importance is the difficulty producing proof of efficacy and safety in the in-vivo setting. Despite their published potential and manufacturing capability, it is important to understand that siRNA compounds come with their own drawbacks as well. Making synthetic RNA clinically safe is very labor intensive and requires a very elaborate biochemistry strategy. siRNA compounds are also transient and thereby limited as core mechanisms in an infectious disease drug. Thus, one would theorize that its targeting advantages are more of a companion technology than a comprehensive solution. As is everything in scientific research, further exploration and validation is required on several components of the topic. In order to do so, it is important to consider a lot of what has already been observed and simultaneously follow similar research currently in-progress. The contents of this article are intended to support guiding readers with the former.

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Application of Covalent Bonds Between Small Molecules and Proteins for Improved Drug Discovery

Mon, 24 Feb 2020 04:06:06 GMT

Application of Covalent Bonds Between Small Molecules and Proteins for Improved Drug Discovery

Insight on current warhead modalities and the potential of covalence chemistry earlier in the target discovery process

Introduction

Covalent bonds play a key role in guiding the mechanisms of biology. Along with binding nucleic acids, amino acids, protein and the other biomolecules of life; covalence principles are rooted into all the drugs developed in today’s market. Although their dependency is high, our capabilities in manipulating covalent bond-forming reactions to correlating biofunction remains restricted. This impediment demonstrates areas for improvements in our discovery approaches and platform technologies.

For example, the conventional methods for identifying novel hits involves a series of technologies - built around: high-throughput or phenotypic screening, fragment-specific analysis, and DNA library parsing. All which utilize chemical matter that binds to targets of interest via non-covalent interactions while neglecting covalent factors. Reason being that these systems are not fit to handle the attrition caused by reactive functionalities. Therefore, covalent compounds are often disregarded from these approaches. In recent years the successes of targeting covalent inhibitors has increased the consideration of covalent molecules in drug discovery. This revolution is due to the improved understanding of the factors governing the binding of covalent compounds and it has generated a growing focus on enhancing the non-covalent recognition to biological targets of interest – along with reducing off-targeting risks. There are other reports available that do a much better job reviewing these concepts and platforms for drug discovery. In this piece, we will focus on surveying select examples of electrophile modalities advancing the small molecule chemistry in drug discovery. ^1-17

Common nucleophile warheads

Covalent bond formation is a result of an electrophile reacting with a nucleophile. The preferred nucleophile has traditionally been a cysteine thiol in biological systems because its high reactivity and low prevalence in the proteome – making it a low risk candidate for random reactions. Cysteine-based covalent chemistry has been very successful overall in delivering safe and specific drugs. This has made it an essential tool in the drug hunters toolbox against challenging targets. ^12,13,18-25

Beyond the cysteine-based domain, novel nucleophile to electrophile pairs are breaking ground throughout scientific literature. One amino acid that has been rising in fame is lysine. Various papers are detailing the effectiveness of lysine-reactive warheads. Particularly in; activated esters, sulfur-based reactive centers and α, β-unsaturated modalities. While featuring high stability and selectivity, lysine-reactive warheads present notable advantages than structurally similar reversible inhibitors. ^26-31

Increasingly novel modalities

Serine is one of a few alcoholic side chains that can be targeted via multiple electrophile warheads including activated esters, fluorophosphates and sulfur centers. While histidine has been proven to react with α, β -unsaturated systems, epoxides, phosphorus reagents and sulfonyl fluorides. ^34-40

With minimal success, negatively charged side chains such as aspartic acid and glutamic acid are rare considerations in this area. However, they should not be completely disregarded since there is evidence to support their application as warheads with Woodward’s reagent K. ⁵⁴

Contrary in its properties, recent success with methionine in hypervalent iodine reagents and redox-based systems earns it an honorable mention. A more novel modality, methionine presents an unattractive characteristic of low nucleophilicity. However, covalent modifications of its residues have suggested promising solutions in countering such negative features along with better compliance towards native proteomics. Which in turn hints that both the application of modifying covalent residues and methionine as a modality will likely pick up traction and popularity in future warhead concept designs. ^{55-57, 68}

To help visualize all the electrophiles we explained, we generated a corresponding figure chart below.

Fig 1: Chemical modalities chart of select neutrophilic amino acides relative to electrophile warhead designs as mentioned pairs throughout the text. ⁵⁸

A lot of these electrophiles involve more complex factors and information beyond what is presented. The list of references provided at the end is our recommended source for the appropriate comprehensive information.

Chemical Criteria

Warheads are complicated and the potential for new or mixed pairs are endless. Ultimately, this comes down to three major principles in design. First, the electrophiles need to meet a minimum reactivity threshold, demonstrating low risk for promiscuous reactivity and off-target binding. This can be determined by testing the chemical reaction rate against a model nucleophile or analogue. Second, it must be optimizable so that the warhead can be positioned in favor of the target residue. This is critical in achieving efficiency between the covalent reaction and the desired targets (Kinact). Optimizing this type of structural confirmation can be supported by traditional medicinal chemistry techniques, guided by the required chemical mechanism for achieving a covalent reaction (i.e. sigma, Pi bond, orbital overlap). Finally, a reactive functional group must be available on the target protein in order for any of the warhead chemistry to be achieved.

Functional Target

The principle of targeting an appropriate functional group on a protein mainly applies when developing covalent drugs in a clinical application. This is an important note because unlike in clinical applications, non-clinical settings provide the utility of external factors which can support guiding target function. So, factors such as light can be harnessed in this sense. One popular example for light is the photoaffinity labelling (PAL) method. PAL utilizes probes that contain photoactivate functions and binds them to nearby bonds via UV irradiation activation. This method has helped develop several probes and is frequently used to target novel binding pockets in proteins (that may be absent nucleophilic amino acids). ^9,38,60-63

Along with binding support, PAL is one of several applications useful for identifying specifics of an interaction that go beyond time-dependent techniques. Employing these applications with conventional methods shows great promise in providing the missing pieces for characterizing small molecules for drug discovery platforms. Particularly when it comes to target engagement/validation , selectivity profiling and covalent frameworks for protein modification. ^64-67

By providing this overview of the relationship between chemical warhead modalities and covalent bonding, we will be able to follow up with reviews expanding on the individual application technologies mentioned such as PAL.

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Protein Concentration SOP: Bradford Assay

Tue, 21 Jan 2020 18:05:10 GMT

SOP: Protein Reagent Concentration

Determining Sample Consistency

Whether your lab already has an SOP in place for new protein analysis or would benefit from a revised procedure, we provide a simplified version of kbDNAs in-house Bradford Assay protocol for concentration testing commercial protein reagents.

Why concentration and why now?

> LAB REPLENISHING

Many researchers have begun ordering recombinant reagents as part of their material replenishing & it's important to revisit the role of concentration

> COVID IMPACT

Due to the unique disruption in the manufacturing sector, the likelihood of receiving proteins from the same batch (or lot) prior to COVID is low

> CONCENTRATION FACTOR

Measuring sample concentration and comparing it to the data on the certificate of analysis is the most direct way to determine whether any quality was impacted

> VERIFYING QUALITY

We suggest running Bradford assay tests on both same and different lot samples since the disruption could have occurred during the production or storage period

The Synthetic Dogma

Wed, 04 Dec 2019 03:56:17 GMT

The Synthetic Dogma

How nature's molecules flow in bio-research

Introduction

Many are familiar with the central dogma of molecular biology, which demonstrates the flow of genetic material; DNA-> RNA-> Protein. However, the movement of these biomolecules as research tools requires a bit more elaboration. Fascinating as they are complex; using biomolecules to study the data, encompassing genetic material has forced the development of synthetic imitation tools. These tools are often referred to as “reagents” (or “bioreagents”). To help represent the flow of these synthetic biomolecules, kbDNA introduces its synthetic dogma.

Our synthetic dogma demonstrates the profiles of DNA, RNA & Protein as synthetic reagents and their roles throughout the flow of applications that help research genetic material:

cDNA | ssDNA

DNA is the traditional focus when it comes to genetic material.

Molecular cloning helped put genes in the hands of biologists with the production of complementary DNA (cDNA) clones. Popular formats for cDNA reagents are full length, open reading frame (ORF), 3’ untranslated region (UTR) and mutant clones. Each option designed to support specific applications.

Synthetic DNA can also be achieved by way of assembly. Using basepair fragments, called gBlocks; double-stranded A,C,T,G fragments can be chained together into a target DNA sequence. The method of choice for this technology is the infamous Gibson Assembly Protocol. gBlock DNA has contributed significant improvements in the application of DNA libraries for both molecular analysis and commercial product development.

Single-stranded DNA (ssDNA) also plays a key role in genetic studies such as expression analysis. ssDNA is part of the oligonucleotide (oligo) family and derives from the methods of solid-phase synthesis. They help target the short-sequence capacity of DNA rather than functional genes. ssDNA sequences are often customized to fit a wide range of applications. Their use can be as simple as being primers for PCR or as difficult as libraries for biosensors.

ssRNA | dsRNA

RNA is quickly climbing as the solution to research design.

Available in its various forms, RNA has been a key player in understanding the bridge between genetics and proteomics. Traditional focus has centered around its translational properties as messenger RNA (mRNA) and a good deal of mRNA reagents were developed to support an added layer of gene expression analysis. mRNA is part of the single-stranded RNA (ssRNA) oligo family, making it a benchmark in solid-phase synthesis and synthetic biology.

Most recently, RNA has taken a larger position in both experimental analysis and therapeutic design. In contrast to ssRNA, double-stranded RNA (dsRNA) synthesis showcases the advancing structural capabilities in therapeutic design. More specifically in antisense technology or “RNAi”. RNAi involves a collection of both ssRNA and dsRNA variations including; micro (miRNA), small interfering (siRNA), short hairpin (shRNA) designed to carry out the RNAi silencing mechanisms. With improving chemical compounds, RNA is matched with extensive modifications, continuing to extend its influence into more technology and applications. Two great examples are guide RNA (gRNA) in gene-editing and lipid nanoparticles (LNP-RNA) in transfection/drug delivery.

Recombinant Protein | Peptides

Protein is at the center of all bioscientific research.

Most genes are protein-coding DNA. Meaning their objective is to express a specific peptide or protein of interest-specific to its function. Protein reagents can be simplified into 3 categories; antibody, antigen, functional/enzyme. Each which have their own extensive list of subcategories based on their structure, pathway, etc. In short; antibodies detect, antigens are detected, functional/enzymes perform a target mechanism. Although it is definitely not that simple, they are all produced by way of recombination. Recombination systems use a variety of organisms (bacterial, mammalian, yeast, insect) cells to chemically express DNA (often cDNA) into a protein. This now recombinant protein is then used in a long list of applications; immunoblotting, flow cytometry, crystallography and of course assays, assays, assays. All which collect very complex data to support and/or validate the research.

All roads lead to protein and that responsibility comes with its own list of complications. Not only are protein structures very difficult to achieve beyond a certain threshold, but their precise functional data is very laborious to collect. These issues have created bottleneck-like limitations in assay development and relational proteomics. While methods such as cell-free expression systems build production solutions, the road to bioinformatics shows promise to organizing both commercial and research protein data.

Microarray Spotting & Hybridization

Thu, 19 Sep 2019 15:41:32 GMT

Microarray Spotting & Hybridization

Chemical coating of slides is a widely used practice for optimizing microarray methods and analysis. The use of various chemicals and compounds has traditionally proven to significantly improve technical features such as; molecule retention and post-hybridization signal amplification, for covalent attachment of unmodified and modified fragments. One of the most critical stages in a microarrays workflow is the spotting of slides. Spotting techniques can strongly impact the quality of hybridization along with the array analysis. The use of slides coated with chemical or functional compounds requires special handling during these steps. The following series of protocols demonstrate the proper handling of the three most common coated-slides; Epoxy, Aldehyde, & Amine-based.

Epoxy Coated Arraying Slides
Aldehyde Arraying Slides
Amine Arraying Slides
Aldehyde Spotting Solution
Amine Spotting Solution

Epoxy Coated Arraying Slides

Introduction

Epoxy slides are epoxy-coated arraying slides that provide a uniform substrate for the creation of high-quality nucleic acid microarrays. These slides provide robust immobilization chemistry as the epoxy coating reacts with amino, hydroxy, or thiol-containing biomolecules and forms a covalent bond with the activated glass surface. Therefore, efficient covalent and directed binding of molecules, such as oligonucleotides and/or PCR products is possible. Unmodified DNA can be directly spotted on these slides. These slides can also be used for covalent binding of proteins and cells. The epoxy substrate supports low endogenous fluorescence and provides high signal-to-noise ratio. The epoxy bond is probably the most robust attachment chemistry available to the microarray scientist today.

Protocol

Array Printing

Use an appropriate spotting solution to array your DNA targets on the slides. Resuspend your DNA targets at a concentration of 0.1-1.0 µg/µl in the spotting solution for arraying. Coupling between DNA and the epoxy-coated surface should be complete within 15 minutes of spotting.

Slides should be stored unprocessed. They should be processed, as needed, for hybridization. The slide processing protocol is provided below:

Slide Processing

Wash slide twice in 2X SSC / 0.1% SDS at room temperature for 2 minutes.
Denature in dH ₂ 0 at 95-100°C for 2 minutes. Allow to cool for 30 seconds.
Dry the slides by placing in a slide dryer and centrifuging for 1 minute at 100 x g (1000rpm).

Hybridization of the processed slide can be carried out as per protocol below:

Hybridization and Imaging

Hybridize the slide with a labeled probe in genHYB microarray hybridization buffer, using a hybridization chamber or similar, sealed humid chamber.
Hybridize the slide according to the protocol for the genHYB microarray hybridization buffer.
Transfer the slide to a slide washer and wash according to the genHYB hybridization protocol.
Place the slide in a slide dryer and centrifuge at 100 x g (1000 rpm) for 1 minute.
Visualize the array by scanning with an appropriate fluorochrome channel on a scanner.

Aldehyde Arraying Slides

Introduction

Aldehyde slides are aldehyde-coated slides designed for microarray production. The slides carry functional aldehyde groups for the covalent attachment of reactive amine-containing molecules. They covalently bind targets to the glass surface via the Schiff base aldehyde-amine chemistry. Lysine residues of proteins or primary amines in DNA bases can participate in Schiff base formation. Uniform coating and high binding capacity allow consistent and reproducible arraying of amine rich or modified target molecules including PCR products, oligonucleotides, and amine rich protein.

Note: Most aldehyde coated slides are not compatible for spotting DNA samples in DMSO, or standard Amine Spotting Solution.

Protocol

Array Printing

Array your targets onto the slides using industry-standard Aldehyde Microarray Spotting Solution or another appropriate spotting solution, such as 3X SSC). Resuspend your DNA targets at a concentration of 0.1-1.0 µg/µl in the appropriate spotting solution for arraying.

Following arraying, leave the slides for a minimum of 4 hours in a constant humidity environment. Slides should be processed as per protocol below before hybridization.

Slide Processing

Wash slide twice in 0.2% SDS at room temperature for 2 minutes.
Wash slide twice in dH ₂ 0 at room temperature for 2 minutes.
Wash in dH20 at 95-100°C for 2 minutes. Allow to cool for 30 seconds.
Wash for 5 minutes in Sodium borohydride mix at room temperature (1g Sodium borohydride dissolved in 300ml 1x PBS, and 100ml 100% ethanol).
Wash 3 times in 0.2% SDS at room temperature for 1 minute.
Rinse twice in dH ₂ 0 for 2-3 seconds at room temperature.
Dry the slides by placing in a slide dryer and centrifuging for 1 minute at 100 x g (1000rpm) for 1 minute.
Store slides in the dark at room temperature. At this point, the processed slides can be stored for several months.

Hybridization of the processed slide can be carried out as per protocol below:

Hybridization and Imaging

To hybridize your slide, react the slide with a labeled probe in genHYB microarray hybridization buffer, using a hybridization chamber or similar sealed humid chamber.
Hybridize the slide according to protocol for the hybridization buffer.
Transfer the slide to a slide washer and wash according to the genHYB hybridization protocol.
Place the slide in a slide dryer and centrifuge at 100 x g (1000 rpm) for 1 minute. Visualize the array by scanning with an appropriate fluorochrome channel on a scanner.

Amine Arraying Slides

Introduction

Amine slides are slides designed for microarray production. The slides bind your targets through amine-reactive groups on the slide surface. Ionic bonds are formed between the surface amine groups and the targets positively charged groups. This is supplemented by the UV treatment of the spotted slide which gives additional non-specific covalent binding of the target to the slide. They are particularly suited to spotting unmodified PCR products. This has the advantage of not requiring the user to amino-modify all their targets i.e. amino-modified primers need not be used for amplification of the targets.

Protocol

Array Printing

Array your targets onto the slides using industry standard Amine Microarray Spotting Solution or another appropriate spotting solution, such as 3X SSC). Resuspend your DNA targets at a concentration of 0.1-1.0 µg/µl in the appropriate spotting solution.

UV crosslink the targets to the surface of the slide (approximately 120 mJoules per cm ² .) Alternatively, bake the slides at 80°C for 1-2 hours. Process slides as per protocol below:

Slide Processing

Wash slide twice in 0.1% SDS at room temperature for 5 minutes.
Treat the slides in blocking solution (0.75g succinic anhydride dissolved in 125ml 1-methy-2-pyrrolidinone then 125 ml 0.2M boric acid pH 8 added) at room temperature for 20 minutes.
Wash 3 times in dH ₂ 0 at room temperature for 1 minute.
Denature the double-stranded DNA by washing in dH ₂ 0 at 95-100°C for 2 minutes.
Dry the slides by placing in a slide dryer and centrifuging for 1 minute at 100 x g (1000 rpm) for 1 minute.
Store slides in the dark at room temperature. At this point the processed slides can be stored for several months.

Hybridization and Imaging

To hybridize your slide, react the slide with a labeled probe in genHYB microarray hybridization buffer using a hybridization chamber or similar sealed humid chamber.
Hybridize the slide according to protocol for the hybridization buffer.
Transfer the slide to a slide washer and wash according to the genHYB hybridization protocol.
Place the slide in a slide dryer and centrifuge at 100 x g (1000 rpm) for 1 minute. Visualize the array by scanning with an appropriate fluorochrome channel on a scanner.

Aldehyde Spotting Solution

Introduction

Aldehyde Microarray Spotting Solution can be used to generate consistent and robust spotting of your DNA targets on microarray slides with surface aldehyde chemistry (aldehyde arraying slides). Its unique constituents stabilize the DNA during the target printing and drying process, which gives a more uniform spot size and shape, thus improving the overall quality of the array.

Protocol

Re-suspend your DNA samples in an appropriate volume of dH ₂ 0 to give you a concentration of 20-100 pmole/µl for oligonucleotides or 0.4-2.0 µg/µl for cDNAs. Alternatively, if you have performed a clean-up on your PCR samples, calculate the DNA concentration in the eluate and adjust to a concentration of 20-100 pmole/ml for oligonucleotides or 0.4-2.0 µg/µl for cDNAs.
Add an equal volume of Microarray Spotting solution. Mix by pipetting up and down several times.
Using an appropriate volume for each well, transfer the sample to a 96-well or 384-well microplate.
Print the samples onto suitable slides using a robotic microarrayer.
Process the slides for hybridization, according to the protocol for the chosen substrate type.

Amine Spotting Solution

Introduction

Amine Microarray Spotting Solution can be used to generate consistent and robust spotting of your DNA targets on microarray slides with surface amine chemistry (amine arraying slides). Its unique constituents stabilize the DNA during the microarray fabrication and drying, which gives a more uniform spot size and shape, thus improving the overall quality of the array. This spotting solution is recommended for use with cDNA and oligonucleotide spotting on amine slides.

Protocol

Re-suspend your DNA samples in an appropriate volume of dH ₂ 0 to give you a concentration of 20-100 pmole/µl for oligonucleotides or 0.4-2.0 µg/µl for cDNAs. Alternatively, if you have performed a clean-up on your PCR samples, calculate the DNA concentration in the eluate and adjust to a concentration of 20-100 pmole/ml for oligonucleotides or 0.4-2.0 µg/µl for cDNAs.
Add an equal volume of Microarray Spotting solution. Mix by pipetting up and down several times.
Using an appropriate volume for each well, transfer the sample to a 96-well or 384-well microplate.
Print the samples onto suitable slides using a robotic microarrayer.
Process the slides for hybridization, according to the protocol for the chosen substrate type.

Molecular-Weight Standards Chart : Proteins

laithik@gmail.com (L L) — Sun, 16 Jun 2019 15:54:42 GMT

Molecular-Weight Standards Chart : Proteins

The Reference Proteins as Molecular-Weight Standards

How to Improve Your Search for Reagents

laithik@gmail.com (L L) — Wed, 05 Jun 2019 02:26:51 GMT

How to Improve Your Search for Reagents

What researchers can learn from our experience with reagent data tools

On the hunt for a new antibody or antigen?

It’s likely that your pursuit will either start with or involve a search engine throughout the process. This trend has become the preferred approach as researchers are often unaware of the disadvantages involved. Search technologies have greatly improved in recent times, but they aren't sophisticated enough to effectively present complex biomaterial such as reagents...yet.

Having developed a reagent-specific search tool, the late kbFINDER; we gained direct exposure to the back-end requirements and functional limitations of search technology. The experience provided us with the following insight that every researcher should consider…

Counter-productivity

It became increasingly evident that utilizing search tools to find a specific reagent wasn’t exactly reliable and was, in some cases, misleading to researchers. Often recognized by search result messages like “no results found” or “1,639 products match your query” ; varying search tools can lead you down different rabbit holes, when you are simply trying to find a target protein with a specific feature or data. Subsequently, when you do find a potential candidate, the reagent data is in a datasheet you need to request. Next thing you know, you’ve downloaded multiple pdf files that you need to sort and compare… which may not even match your needs. The underlying issues that lead to these situations are not intentional, but rather a consequence of some of the limitations we have dissected below.

Data Consistency

The challenges of getting bio-reagents to play nice with search technology go beyond a simple IT (Information Technology) problem. These challenges largely stem from the high complexity of bio-reagent data. Getting this data to fit within a structured database can very difficult, and many organizations find themselves making compromises either by simplifying the data, or dealing with an unwieldy database that becomes ever more difficult to work with as the needs of the organization change, or as they add new reagents and target proteins in batches with customized features.

With a lot of forethought, planning, and properly leveraging data relationships - bio-reagent data can be standardized within a functional and flexible database, but this is rare, and never translates across different organizations. The case of organizations regularly failing to properly structure their bio-reagent data within a database has resulted in consistently unfriendly user experiences, and the development of user fatigue among scientists.

E-commerce Centricity

Online shopping or “e-commerce” is ultimately designed to get you from the search bar to the shopping cart. Very little focus has been invested in the qualifying process in-between. This is because most products dominating this space are commodities. As much as we would love for antibodies, antigens and enzymes to be commodities, they simply are not. They are highly specific, and the closer they relate to your experiments' design, the more you'll come to learn this (the hard way).

The reality is that before e-commerce, all these reagents were sold via distributors and vendors who piled a bunch of manufacturers products onto their cluttered catalogs, resulting in a sales rep saving the day with their process. Today, the internet empowers the manufacturer, and we are seeing them become more exclusive and in control of their products. One might argue that manufacturers trusting their products with distributors enabled the commodification of reagents, but that is not relevant to the topic at hand. The point is that all these print catalogs were converted to online catalogs, and their manually copy/pasted data populate standard searches (Google, Bing. etc.). This means search results regularly list two or more identical products from different vendors (including the manufacturers) and they would all lead to a page that was built around making the end-user hit “add to cart”. This is now dramatically changing (especially on Google). The search giants recognize these issues of data overlap and redundancy, and are increasingly omitting e-commerce pages from their results. Results are now based on scoring valuable content. Which is great, except now the researcher is at the mercy of the companies with the best search engine optimization (SEO) strategy. The best content for reagents are their citations, application data and technical literature. Which happen to be indistinguishable from other forms of content. Other (repeat) content can easily populate the first few pages of results, when the right protein can actually be found in the deeper pages.

In the end-relational databases, SEO and other approaches are essentially workarounds with an unchanged goal; prioritize a product or page in search to initiate an “add to cart”. In other words, they are solutions to problems the seller faces. They are not focused on solving for any problems of the end-user or researcher.

Not too long ago, our website search bar looked like this….

Now, search and e-commerce features are completely gone from the platform. After multiple releases of improved versions, kbFINDER was a very precise search tool, reinforced with a consistent and elaborate database. The more we advanced it, the more we realized that it was just another workaround the real problems.

We’ve measured greater success matching researchers with the right protein since the introduction of our recombinant libraries . The short-term benefits and long-term potential for AI compatibility make it an exciting novel solution to consider. However, libraries as an alternative to search is a challenge that will take time and effort to build correctly. Regardless of what the end-user prefers, we encourage researchers to develop a sourcing strategy that involves multiple tools/resources and to always measure the data against the standard databases (uniprot, refseq, etc.). The primary objective now is to use this insight to your advantage. Consider the outlined points in your next reagent hunt and see if you can identify any new errors!

Obsessing Over CRISPR Isn’t Making It Any Safer, but RNA Might

Thu, 02 May 2019 02:13:43 GMT

Obsessing Over CRISPR Isn’t Making It Any Safer, but RNA Might

Overcoming the challenges of off-targeting with synthetic guide RNA

Every now and then, a breakthrough discovery can be significant enough to introduce new technology that disrupts traditional scientific research. These discoveries are often easy to identify by their ability to dominate headlines and attract obsessive attention from all audiences. With respect to this article, I am referencing the groundbreaking discovery of Clustered Regularly Interspaced Short Palindromic Repeats or CRISPR for short. Not to say that the attention generated by CRISPR is not entirely deserved. If anything, CRISPR/Cas9 and its technology has proven a very innovative molecular tool toward various lab applications. CRISPR is coined the ‘cute & paste’ of gene-editing (as if it were that easy) and though the technology has been very progressive, it’s limitations continue to hang over our heads. To put it simply, the CRISPR-associated protocols are riddled with errors. They have to be run repeatedly and tweaked to reduce the principal obstacle; off-targeting. (thunder clap!)

Off-target genome editing refers to nonspecific and unintended genetic modifications that can arise through the use of engineered nuclease technologies such as CRISPR/CAS9. Previously, we've seen off-targeting effects cause a major set-back to a generation of CAR-T potential. However, in the case of off-targeting with prior models of CAR-T; the issue was random binding to healthy surface protein (antigens) - similar to the ones being targeted on hard tumors. With CRISPR, the off-targeting effect is a little more complex. To better understand it, let us revisit the fact that the CRISPR/CAS9 system is directed to its target DNA region via an attached nucleic acid sequence, referred to as the “guide RNA (gRNA)”. This gRNA is designed to bind to a specific area along the DNA, complementary to its sequence. Once successfully (or unsuccessfully) attached, the CRISPR/Cas9 gene-editing mechanism initiates a base; deletion, mutation, or introduction. If this is done in the incorrect location, side effects are limitless. This has been a recurring issue in both class I and II CRISPR systems. Several off-targeting solutions are being trialed, which include the use of multiple protein supports and digging into the other proteins of the Cas family. However, no solution shows greater promise than optimizing the single guide RNA (sgRNA) design.

Fig 1. This base template provides a general overview of a CRISPR/Cas9 system for genome editing. Cas9 protein cleaves a specific DNA sequence guided by sgRNA.

This approach does not require adding more components to the process and is centered around specificity - thereby limiting incompatibility which is a recurring issue with other CRISPR off-targeting solutions. The gRNA design is not exactly a new approach. However, the employment of more rational design and extending engineering to its secondary structure; introduces new capabilities of applying hairpin formations, which can be attached to the 5’ end of the sgRNA (hp-sgRNA). The resulting hairpin structure could then function as a support barrier to an R-loop formation. Notably, this offers a kinetic model of R-loop design, that can provide more specificity to the on-target site and regulate more against the off-target ones.

...employment of more rational design and extending engineering to its secondary structure; introduces new capabilities of applying hairpin formations

A recent study at Duke University tested their own version of this methodology with significant results. Following their successful synthesis of the concept RNA structure and functional experimentation; the research team assessed the effects on multiple Cas variants including; spCas9 and saCas9. The study did leave a few questions unanswered, such as the consistency of this approach or the influence of varying conditions relative to R-loop stability. Not to mention, the ability to synthesize RNA structures to meet such novel design is strenuous in itself - and one that has been challenging different areas of therapeutic RNA (RNAi) for some time now. Regardless, the data being collected with this approach is definitely progress and the more we focus on building off of it and less on sci-fi applications of CRISPR, the better we are. Unfortunately, science fiction seldom converts into therapeutic application.

Fig 2. This schema represents an overview of the CRISPR/Cas9 system with the incorporation of a hairpin formation in the secondary structure of the sgRNA

To do our part; we try and relieve some of the manufacturing challenges by further considering stability and structural components, when reviewing RNA sequence submissions, prior to synthesis. As part of our standard proofreading service, we offer this consultation at no-cost and we encourage other manufacturers to incorporate a similar approach to help keep the traction going for the use of RNA against off-targeting.

References

Kocak, D. D., Josephs, E. A., Bhandarkar, V., Adkar, S. S., Kwon, J. B., & Gersbach, C. A. (2019). Increasing the specificity of CRISPR systems with engineered RNA secondary structures. Nature Biotechnology.
Wright, A. V., Nunez, J. K. & Doudna, J. A. Biology and applications of
CRISPR systems: harnessing Nature’s toolbox for genome engineering. Cell 164, 29–44 (2016).
Shmakov, S. et al. Discovery and functional characterization of diverse class 2 CRISPR–Cas systems. Mol. Cell 60, 385–397 (2015).
Burstein, D. et al. New CRISPR–Cas systems from uncultivated microbes. Nature 542, 237–241 (2017).
Barrangou, R. & Doudna, J. A. Applications of CRISPR technologies in research and beyond. Nat. Biotechnol. 34, 933–941 (2016).
Fig1. & Fig2 Created with BioRender.com

An Updated Overview of Protein Tags

laithik@gmail.com (L L) — Wed, 24 Apr 2019 01:55:12 GMT

An Updated Overview of Protein Tags

A guide to recent and growing trends in protein tags

Introduction

Protein tagging has been around for decades, but their traditional uses are not frequent enough to make them common lab knowledge. Recent improvements in biochemical techniques have been increasing their frequency as creative design and analysis tools. In this overview, we offer a guide for the variety of different protein tags that are trending in recent growth.

This guide will cover:

Principle Affinity Tags
Biotin Tags
Epitope Tags
Fluorescent Tags

Principle Affinity Tags

Arg- tag

His-tag

GST

Biotin Tags

Strep-tag

Streptavadin-tag

Epitope Tags

c-myc-tag

FLAG-tag

HA-tag

Fluorescent Tags

Luciferase

GFP

S-tag

Points to Consider

FLAG mAb purification systems have not always been stable and often require expert intervention.
The presence of C-terminal tags can potentially contribute to a protein's loss of function. Particularly in the case of enzymes.
Streptavadin-binding peptide (SBP) is only attachable to the C-terminus
S-tag in low pH elution may alter protein properties and limit the matrix reproducibility
anti-myc antibody antibody purification is inconsistent and has been proven to result in poor yields

References

Nilsson et al. (1997a)
Lazzaroni et al. (1985)
Goldstein et al. (1992)
Crespo et al. (1997)
Makrides (1996)
McLean et al. (2001)
Nilsson et al. (1997b)
Wang et al. (1996)
Podbielski et al. (1992)
Jones et al. (1995)
Morandi et al. (1984)
Kaldalu et al. (2000)
Jones et al. (1995)
Rubinfeld et al. (1991)
Smith (2000)
Gerdes and Kaether (1996)
Los et al. (2008)
Terpe (2003)
Imagawa et al. (1982)
Fritze and Anderson (2000)
Tai et al. (1988)
Kuliopulos and Walsh (1994)
Kwatra et al. (1995)
Tai et al. (1988)
Karp and Oker-Blom (1999)
Kolodziej and Young (1991)
Terpe (2003)
Kimple and Sondek (2002)
Stevens (2000)
Bornhorst and Falke (2000)
Stevens (2000)
Abdulaev et al. (2005), Biao et al. (2004), Ruan et al. (2004)
Fritze and Anderson (2000)
Berlot (1999)
Nilsson et al. (1997b)
Skerra and Schmidt (2000)
Sano et al. (1998)
Terpe (2003)
Stevens (2000)
Li (2011)
Terpe (2003)
Nelson et al. (1999)

It May Seem like It’s Raining Reagents, but It’s Only Companies with the Same Catalogs

Wed, 17 Apr 2019 00:48:02 GMT

It May Seem like It’s Raining Reagents, but It’s Only Companies with the Same Catalogs

Understanding the factors limiting novelty in reagent supply chain

A high-pitched squeak of an expo marker being capped concludes the lab meeting. A collective exhale sweeps the room, confirming anxiety- induced by the reminder of the infinite workload and expectations. Before exiting, the investigator assigns a junior lab member with a task of finding a specific reagent that needs ordering. They accept and begins their search online. A few hours later, the lab member turns in a letter of resignation to pursue a career in human resources.

Obviously that was an exaggeration, but I cannot say that with complete confidence. Everyone knows reagents are growing in demand and marketing (check your Facebook ads). However, only few are aware of how complex this growth actually is. Many companies are attempting to address the challenges of sourcing proper reagents by way of ecommerce innovation - but they end up sedated in the same cycle as everyone else. This cycle sits Juxtaposed to the countless resellers, distributors and imitators in the supply chain- making it almost impossible to distinguish who is who and what is what. As biotechnology providers; our proactive involvement in multiple disciplines of bioscientific research has allowed us to analyze this phenomenon from a novel perspective.

Here Are the Factors Complicating Reagents:

1.The Term “Life Sciences” Is Too Broad

Have you ever met a researcher with the title “Life Scientist”? Chances are low. This is because the term term “life sciences” essentially means; any research profession, studying any bio-respective discipline. Life science itself is not a real discipline. It is the best community we have to integrate all the thriving interdisciplinary research fields, but it is not exactly “business-friendly”. Therefore, from a marketing perspective; treating life science professionals as one big customer is as successful as blindly asking every researcher you come across whether they are interested in your product.

2. Labeling Reagents

What constitutes a reagent is not well-defined. A reagent traditionally referenced chemical mixtures or specialty solutions. As molecular biology advanced alongside chemistry, “reagent” became the go-to term for categorizing commercial end products for; nucleic acids, antibodies, proteins - in addition to preceding products; bottled transfection and isolation formulas. Along with the inconsistent marketing, universal practices are arguably making these materials harder to utilize as products. Reagents are complex and obscure on their own. Their unique properties do more than just match them to a customer - they define them as components of nature.. We need to do better than generalizing as a means of converting complex material into sell-able products.

3. Marketing Resistance

Here's a fact that keeps supply chain up at night; scientists don’t care and it’s not their job to care about any reagent company or their promotional marketing. Even if they did, there is still the paradox of need. Need is by far the biggest limiting factor to all the ecommerce solutions. In bioresearch, reagents are bought when they are needed. Since we already established that reagents are very specific; need can be reintroduced as; ‘specific reagents are bought, only when their varying properties are a degree specific to the researchers varying requirements”. That was as hard to write as it was to read. In other words, a company must be able to relatively measure three pieces to meet demand; multiplexed reagent properties, the varying end-user requirements, and the acceptable degree of compatibility between the two. This is not your traditional supply and demand scenario. Some of these cases require biochemical calculations, expert intervention, prediction and strategy. Automating this process requires progress beyond the current AI machine learning, bioinformatics and relational software.

Such ecommerce tools are not even accessible to the technology titans like Amazon or Google. It will require something truly novel to jump the innovation curve and I think we will all recognize it when it happens. Meanwhile - providing literature, scientific diagrams, or sending newsletters may demonstrate educational value, but it will not influence a lab to buy a reagent it does not specifically need. Companies diverting to this content-type marketing approach also need to be cautious about the authenticity of their intentions. It turns out researchers are pretty good at identifying differences between genuine content and retraced figures from their old textbooks.

4. Innovation Demand

If a company relies on a market report suggesting the profitable opportunities in supplying reagents - their days are likely numbered. In Life sciences, the only thing reliable about these market reports (and financial forecasts) are their consistently poor accuracy rates. Their predictions are never close and far from being significant. Those wall street formulas are not designed to measure the volatile and variable factors of bioresearch. These factors are rooted into the infrastructure of scientific research. Their influence is capable of dramatically altering the direction of research and its commerce trends. Discovery and breakthroughs are the best examples. Their significance has promoted increased collaborations, adoption of interdisciplinary methods and an overall demand for innovation. We are a solution-based industry and there is no shortage of problems to solve. Whether a manufacturer, supplier, or researcher; they are expected to bring something to the table. Large catalogs and ecommerce tools are not solutions that predict success in this industry. Yet so many companies end up stuck in those directions. Solutions have to stay relative to the industry focus and the focus in research will always be; innovation.

Despite this narrative, a majority of reagent companies have a genuine interest in advancing research. The fact that there are players in your field that get excited over manufacturing is positive in itself. I believe there is a certain critique not being voiced among us and it is due to the lack of answers. We see a lot of other great companies with novel innovation complicate themselves-trying to overcome these hard problems. It may be time to agree that the solution will not be a single breakthrough innovation - but as a collaborative platform between all the players of supply/manufacturing. Whether it is improving practices between each other, promoting product data standards, or cross-functional collaboration; anything that helps prioritize our responsibility to the researcher. Which has always been to get them the products that work best for their experiments.

Difficult-To-Express Proteins Are Not Going to Solve Themselves

Wed, 10 Apr 2019 00:40:29 GMT

Difficult-To-Express Proteins Are Not Going to Solve Themselves

Innovating commercial manufacturing to meet the demand of unconventional recombinant proteins

Every now and then a researcher is tasked with finding a target recombinant protein - which ends up being a nightmare of a process. Targets such as Tissue inhibitors of metalloproteinases (TIMPs) and 6-phospho-beta-glucosidase (BGLA) are frequent candidates of this experience. These proteins fall under the dreaded list of difficult-to-express (DTE) proteins. Overcoming the complexities of DTE proteins has been an ongoing frustration - for both manufacturers and researchers. It is clear that there are multiple pieces to the DTE puzzle. There may not be a 'one size fits all' solution, but that doesn't mean DTE's are unsolvable. The main focus has always been on building and integrating tailored chemical solutions to support expression systems. My goal is to gear the focus more toward the actual expression systems and highlight their limitations from the manufacturing angle.

Problems Within a Problem

The principal issue with DTE proteins isn’t much of a mystery. The process of protein production, in one sentence, is; inserting a gene in a host cell for target protein expression(cell-free method excluded). The technical reality is that the host cell remains foreign to the target protein to some degree, regardless of conditions. The discord can be marginal enough to go unnoticed or significantly present. Consider producing a protein that is not expressed naturally in the host domain (eukaryotic, prokaryotic). This plan, expects the host to comply with potential conditions outside of its nature. In other words, it is similar to expecting a motorcycle mechanic to build a car or an auto mechanic, a bike. A degree of compatibility presents inevitable limitations.
The folding process is arguably the most condition-based step in expression. So naturally, proper confirmation is the hardest objective to achieve. It is also the priciest and most inconvenient due to its downstream position. This topic of condition compliance, however, is a door with many locks. Protein folding may be the most popular one, but it rarely acts alone. Expression difficulties are specific to target protein properties. Therefore, a more popular challenge would be overcoming varying sets of condition factors. For example, translation efficiency, codon bias, redox potential, membrane solubility, and post-translational modifications are regular contributors to improper folding and overall expression failure.

A Solution for Solutions

Given the many factors altering conditions, we can expect a multitude of correlating methods to develop over time. This builds an arsenal of solutions, which is not uncommon in bioresearch. However, once the list reaches a certain size, it becomes increasingly difficult to pinpoint where and which approach is the right solution for an expression. Current solutions can be sorted into the following approaches; host strain modification, manipulating gene of interest, refolding steps and chemical tweaking of conditions. Notably, the practice of utilizing tag labels has become more intuitive. Protein tags can help guide or support proteins through stages in the production process (i.e. membrane insertion, comply solubility). Their ability to measure chemistry and track key interactions has also lead to innovative screening methods. These screens have been called different names, but we know them as “expression scouts”.
Expression scouts, in short, analyze a series of varied expression systems. Their results help identify optimal factors to better achieve successful production - along with error calculation. In terms of DTE protein, this technique shows the ideal potential as a companion tool. The targeted efficiency from expression screening disempowers the role of uncalculated production errors while introducing an approach for pinpointing the right solution for an expression.

System Limitations

Pre-screening for errors is effective, but it’s not a complete approach. There is still the consideration of the standard expression systems in place. These aren’t exactly “flexible” processes. On a commercial level, expression systems set the framework for a company's manufacturing platform. Inventory, production deadlines, consumables, chemicals, and even staff expertise are all relative to these systems remaining fixed. Implementing a specialty solution for a DTE protein to them can result in a mess of outcomes. In most cases, DTE projects require their own isolated or trial expression called pilots. Even then, enduring the inflated cost and lead time can’t guarantee success. Pilots are equivalent to a company saying “sure we will try”, but their success rates aren’t traditionally comforting. The incorporation of preliminary expression scouts prior to pilots have shown rate improvements, but they aren’t dramatic. There needs to be improvements from the application process. Meaning, our standard expression systems have to become more versatile in order to meet the required changes for different protein conditions.

Suggesting “versatility” doesn’t offer any real actionable value. Not to mention, proposing such a dramatic innovation may not be received too lightly. Respectively, It is only right to acknowledge that there are a few key companies that have been working hard to build solutions. DTE proteins are just too complex to properly cover in one post. They are also too complex for just a few key companies' efforts. Not too long ago, a company required a scale of resources and funds in order to R&D such solutions. However, that excuse is starting to expire. Innovations from all angles have influenced trends in reagent manufacturing (material) cost. The price of producing protein is becoming increasingly cheaper - to the point where you would get more bang for your buck choosing custom service for > 1mg quantity than you would buying it at catalog cost. It is an opportunity for collaborative innovation. We encourage others to take advantage of this affordability and to consider implementing solutions such as expression scouts.

At the end of the day, the researcher does not need more options for the same proteins. They expect more solutions and new targets. Difficult-to-express proteins are our indirect responsibility as industry providers. They aren't going to solve themselves.

Rethink Modifications

laithik@gmail.com (L L) — Wed, 20 Mar 2019 00:31:25 GMT

Rethink Modifications

ssDNA, siRNA, gRNA, LNA, BNA; the list goes on.

Overview

Advancements in biochemistry continue to add new and innovative tools to help build DNA and RNA sequences. As tools are added, it becomes increasingly difficult to determine the right tool for the right objective.

In this case; "tools” refer to modifications, or 'mods'. In Nucleotide synthesis; modifications are specialty synthetic reagents or compounds that can be introduced into a nucleotide sequence. Applying these modifications in design allows researchers to customize and manipulate various aspects of their sequence including its biochemical properties. This can help achieve a variety of goals, including improved stability, specific directional form, higher affinity, and other goals stemming from the primary application objectives of researchers.. The recent boom in oligonucleotide applications has resulted in more modifications and variations from which to choose, and more companies offering their own variations of all types of modifications. Naturally, this has begun to generate confusion in the marketplace.

Finding the right modifications to build a DNA or RNA sequence can be overwhelming, a problem that has resulted in a growing trend of laboratories dedicating valuable time and money to unnecessary and expensive modifications, sequence designs that overlook biochemistry fundamentals, and widespread misinformation. With a growing need for biochemists in nucleotide synthesis labs, there is an equal need to re-establish an understanding of the different types of modifications and the roles they play in synthesis.

Introducing nucleotide synthesis modifications using an alternative approach
Outlining sequence versus base modification methods
Categorized explanations of modification types and their value

Introduction

In many cases, modification errors occur with novel sequence designs that overlook one or more biochemical principles. In other cases, errors can usually be attributed to confusion about or misunderstanding of modification chemistry in general. Before taking into account their biochemical properties, it is important to consider nucleotide modifications within the following framework;

A modification can be one of the following primary types:

Sequence Modification

Base Modification

Categorizing your modification of interest as either a sequence or base mod will help establish its hierarchy of influence within your sequence design. This will also provide an organized structure to calculate its effects on the chemistry as it relates to the nucleotide synthesis project.

Sequence Modifications

A sequence modification is any mod that adds or edits features to the nucleic acid sequence. The primary distinction with this class of modifiers is that they target the structure and function of the final molecule. The demand for sequence modifications is relative to experimental challenges. For example:

Improving stability or protecting from degradation

Introducing markers for detection in analysis experiments and higher affinity

Troubleshooting nucleic acid conformation issues and directional form

Sequence Modification Subcategories

a) Backbone | Sequence Modification to the phosphate backbone structure

b) Chain | Sequence Modification to the chain of nucleotides via attachment of different compounds and functional groups

Base Modifications

Where-as sequence modifications impact the nucleic acid sequence, a base modification focuses on the amino acid-base of one or more nucleotides within the nucleic acid sequence. It can be introduced as:

A deletion or removal of one or more nucleotides
An insertion or addition of one or more nucleotides
A mutation or change in the amino acid of one or more nucleotides

Base mods often address the more pivotal objectives of an application and can range from a single base mutation to a series of deletions and insertions. However simple they may seem, base mods are also routine inducers of experimental complications that require the use of complementary sequence modifications. This is where expertise in biochemistry and synthesis technology becomes crucial.

Base modifications come with a high level of uncertainty. This is especially true when working with different applications. It can be very difficult to accurately predict certain performance outcomes after base modifications are applied. We refer to these unpredictable outcomes as 'blind spots'. Conducting analysis experiments is the current standard for calculating blind spots and the integration of these analysis models into sequence design platforms is a growing area of demand.

Understanding the Available Options

Over the years, many companies have developed extensive catalogs with overwhelming numbers of modifications from which to choose. In order to effectively apply any modification - it is essential to first understand what class or function it fits into. We refer to these as the mod’s subcategory. kbDNA applied the less-is-more approach and focused on optimizing each modification in relation to its subcategory. The resulting selection consists of modifications focused on the following options:

Affinity Tags
Fluorescent Labels
Structural Modifiers
Stabilizing Assistants
Degenerate Carrying Bases
Peptide Conjugates
Terminal Phosphates

We plan on following up with more detailed profiles for each modification option including their individual structures and biochemical properties. As part of our conservative approach to developing a more precise tool for building nucleotide sequences; more effort is being channeled into a valuable release of this material rather than a generic presentation. Our modification abilities and options are currently well represented in kbDNA’s nucleotide synthesis builder. The builder resource was also used to produce the figures depicted in this note and is available to everyone. We encourage researchers to explore the building resource here to learn more about the right options for their laboratories.

Oligos: How the Lego Pieces of DNA Are Shaping Research

Thu, 07 Mar 2019 01:04:08 GMT

Oligos: How the Lego Pieces of DNA Are Shaping Research

ssDNA, siRNA, gRNA, LNA, BNA; the list goes on.

What were once conceptual niches, derived from the principles of nucleic acid (NA) chemistry have now standardized into our everyday experiments and methodologies.

Oligonucleotides (or oligos) in particular; after see-sawing in research for almost 60 years, had a breakout season last year. The explosion of CHIP-based ventures fueled the race in diagnostics. Refined assembly of gene fragments and library pools is expanding commercial synthesis with more alternative services.

No news compares to drug news, however, and the approval of Alnylam's ONPATTRO™ (patisiran) in the final months was the icing on the 2018 cake. Patisiran's approval served as more than therapeutic innovation in rare diseases. It provided key validation for researchers who were championing antisense technology, in addition to demonstrating the potential of therapeutic oligonucleotides.

In other words, oligonucleotides may have stood a running chance in beating CRISPR in the 2018 headlines. Assuming that is even possible, it wasn't entirely necessary. Recent achievements with oligos have already begun to change the landscape of biomedical research by rekindling the flame between research biologists and biochemists. This is made evident by increasingly interdisciplinary trends, such as the incorporation of biochemists in traditionally molecular laboratories and the demand for shared topics at conferences.

All of this amounts to greater promise for new discovery (ex. pathway analysis), innovative tools (ex. biosensors, nanotechnology) and pipeline medicine (ex. novel drug delivery, effective companion diagnostics). As always with research; results are still in progress and dependent upon downstream outcomes.

The persistence of pioneers like Alnylam, Arrowhead, Ionis, Bluebird and many others helped drive the therapeutic applications of oligos. They also helped ignite material innovations from the supply and manufacturing sector. As the genomic sequencing boom increased demand for efficient oligos, new manufacturing platforms responded with rapid turn-around time and lower cost for the development of custom DNA oligos. In contrast, the therapeutic revolution has been moving at a much slower pace, and with more limited capabilities.

These limitations are starting to give way to improvements with building block reagents, which are crucial to the manufacturing process. Chemical optimization of these synthesis reagents and click chemistry methods are helping to enhance overall production capabilities and enabling labs to achieve more challenging sequence designs. This has helped exceed limitations in yield, stability, and purity. Chemical innovations are proving essential to the progress in developing RNA oligos and RNA technology.

It's safe to say the seeds of NA chemistry have begun to bud, and we can expect a future bloom that goes beyond oligos. The recent progress with nucleic acids is a positive indicator of how much our knowledge of the science has advanced, and it bodes well for our capabilities with handling small (or short) sequence oligomers in the lab.

Oligos continue to integrate into ever more applications with newer innovations on the horizon. This includes the rebirth of peptide nucleic acids (PNA), improved modifications for sensitive transfection/drug delivery, nucleic acid-antibody labeling and of course... more sequencing devices. As previously mentioned, synthesis manufacturing must keep pace with ever-increasing creative demand, and both sectors must run parallel with innovation. This requires both sectors to know what they're moving toward.

Genomic sequencing technology helped validate the way we read and analyze. We believe synthesis technology will lead to validating how we write and build life's genetic material. In order to support that vision, it is important to continue bridging the gaps between the various disciplines and technologies that are involved.

This means integrating data and biological science into a unified system (calculated biosimulation). It entails the collaboration of biochemistry and nanophysics to build process solutions. It means the software and computational biology must provide tools that allow researchers to correctly build their sequences, short and long; binary-to-bioreagent.

Oligonucleotides will always be the originals of NA chemistry - the ones that started it all. But there will be many more NA acronyms added to the list as we progress, and it's time to start looking beyond Oligos!

I for one, am excited to contribute to this process and to see where it takes us.

Synthesis Attachment Chemistry

Thu, 21 Feb 2019 00:54:12 GMT

Synthesis Attachment Chemistry.

Building with Biochemistry

Whether performed in-house or as a commercial service; synthesis efficiency and sequence
integrity depends on two major chemical components; attachment chemistry and ancillary reagents.

The biochemical properties at the base level of synthesis are generally not well known, or they are ineffectively presented.
This piece provides a technical introduction regarding the chemical components involved in nucleotide synthesis
The information provided will help serve as a starting point for delving into technical biochemistry and its relation to DNA and RNA synthesis .

Attachment Chemistry & Ancillary Reagents

Attachment Chemistry involves two classes of reagents; amidites and supports. These are the primary building blocks of nucleotide synthesis. Their properties and features help construct sequences to meet specific objectives. Their level of quality is one of the tell tale signs of a company’s synthesis expertise.

To support the mechanisms of attachment, ancillary reagents are produced for specific applications. These reagents play an essential role in synthesis optimization. They are formulated to ensure performance within their respective stage and can help direct the synthesis process.

Amidites & Supports

A simpler way to understand nucleotide synthesis is to regard it as the attachment of one amidite to the next via a phosphate backbone. This results in a chain of amidites or nucleotides. Amidites are nucleoside structures that are either carrying a base at the 1' position or modifications labelled on its ribose ring. They are often referred to as phosphoroamidites due to the presence of a phosphate group (synthetic nucleotides) and offer extensive chemical and/or structural modification possibilities.

Supports are much easier to understand since their function is in the name. Supports are protective material that attach to the amidite and follow the reagent along the synthesis process until it is time for removal. The relationship between amidites and supports makes it easy to understand why they are referred to as the building blocks of nucleotide synthesis. However, their varying features present changes in biochemical properties and often require adjustments in handling. It is very important to understand the requirements of every amidite and its modifications to build the right sequence for its application.

It is important to have a reasonable understanding of the intended reagent building blocks for a synthesis project due to their lack of experimental cooperation. Adjustments in protocol concentration, dilutions, temperature and time are often required to achieve proper coupling or yield of differing reagents to individual standard. As an example; kbDNA uses a selection of building blocks that are strictly within their realm of competence. Doing so allows for quality synthesis and the confidence to offer technical support and recommendations for optimization. The selection is a bit more strict than others, however it does offer a great visual of the different patterns that help signify expertise in a particular area of service.

The selection includes:

Quenchers
Etheno DNA Amidites and Supports
Phosphate Generating Reagents
Biotin Amidites and Supports
Psoralen Amidites and Supports
Fluorescein Amidites and Supports
Etheno RNA Amidites and Supports
TAMRA and ROX
Amino Modifiers
Cholesterol Amidites and Supports
DNP-TEG Amidites and Supports
Dabcyl Amidites and Supports
Branching Amidites & 3'-Spacer Supports
Spacer Amidites
3'-Carboxyl Linker Amidites
Thiol Modifier Amidites and Supports
Lipophilic Amidite

Ancillary Reagents

In order to aid attachment chemistry, ancillary reagents are formulated to enhance or guide the synthesis process at target stages. By chemical tweaking and solvent mixing--the resulting reagent mixes and solutions contribute to capping efficiency, positive oxidation reduction, safe deblocking, and more. Contrary to building block reagents, these ancillary chemicals are usually rather standard in their quality. It is difficult to come across competitive differences. However, the useful knowledge required with ancillary chemicals is less about quality and more about qualifications. There are varying mixes out there, and quality tends to come down to matching the right solution with the situation. That is why we recommend organizing your internal lab synthesis chemicals relative to their value and unique chemical properties.

The following is how we stack the ancillary reagents in our chemical arsenal to ensure the qualifying option is applied in each synthesis project:

Capping-Stage Solutions

CAP A (Acetic Anhydride/Pyridine/THF)
CAP A (N-Methyl imidazole; 20% in Acetonitrile)
CAP B (10% N-Methylimidazole in THF)
CAP B (16% N-Methylimidazole in THF)
Cap B1 (Acetic Anhydride; 40% (v:v) in Acetonitrile)
Cap B2 (Symmetrical Collidine; 60% (v:v) in Acetonitrile)

Oxidation-Stage Solutions

Oxidation Solution (0.02M Iodine/Pyridine/H2O/THF)
Oxidation Solution (0.05 M Iodine in Pyridine(90%) and Water(10%))
Oxidation Solution (0.1M Iodine/Pyridine/H2O/THF)

Deblocking-Stage Solutions

Deblock (3% DCA in Toluene)
DMT Removal Reagent (3% Dichloroacetic Acid/Dichloromethane)
DMT Removal Reagent (3% Trichloroacetic Acid/Dichloromethane)

In summary; the process of nucleotide synthesis is heavily dependent on the mechanisms of attachment chemistry. Attachment chemistry involves different classes of reagents, primarily building blocks and ancillary reagents. Building block amidites represent the synthetic form of a nucleotide or modified compound via the reinforcement of a support. Both of these building blocks are promoted and directed throughout each stage of the synthesis cycle by ancillary reagents.

This should help provide a better understanding of the technical components that drive attachment chemistry in nucleotide synthesis. We look forward to building off this note with more technical insight regarding the different mechanisms and method of attachment chemistry. This includes click chemistry, classes of modifications, application protocols, and much more.

Compounds for RNA Synthesis

laithik@gmail.com (L L) — Thu, 30 Nov 2017 22:20:23 GMT

RNA Synthesis

See the full list of in-house RNA Compoundsused in our synthesis

Improving RNA Synthesis

The synthesis of RNA is conventionally more sensitive than DNA. This poses challenges in developing very similar synthesis compounds such as amidites and supports, but with the right chemistry to counter RNA-specific hurdles. Stability and structural confirmation are routine offenders, and both can be countered by utilizing backbone phosphorothioation and reverse synthesis techniques. β-L-RNA-Spiegelmers and minor RNA phosphoramidites offer novel solutions to end-user specificity. While TOM-amidites are highly suitable for large scale therapeutic grade RNA synthesis, long RNA sequences, aptamers, and biologically significant RNA molecules.

See the full list of in-house RNA Compounds used in our synthesis below:

RNA Synthesis

A: CE Phophoroamidites: TBDMS Protected

B: Supports

C: Backbone modification:Methyl Phosphoramidite

RNA: 5'→ 3' Synthesis

A: CE Phophoroamidites: TBDMS Protected

Minor RNA Bases

A: Minor RNA Phosphoramidites

B: Supports-Minor-RNA-TBDMS Protected 3'-CPG

RNA Modifiers

laithik@gmail.com (L L) — Sat, 25 Nov 2017 21:55:03 GMT

RNA Modifiers

See the full list of in-house RNA Modifiers used in our synthesis

Optimized Nucleotide Synthesis

While most modifications to RNA are built for maintenance, demand in new and improved compounds is growing for various use of synthetic RNA. A major one is gRNA for recent CRISPR/CAS9 systems, but the more veteran application for RNA modifiers is undoubtedly antisense RNA . In order to harness the mechanistic advantages of RNA interference, custom nucleotide sequences need to be equipped with the ability to permeate cell walls, bind to the target and protect itself from degradation. We offer an advanced selection of 2’-O-alkyl/methyl compounds along with affinity and fluorescent labels to follow a sequence in experiments all throughout its development.

RNA Synthesis/Modifiers & Labelling

2'- O -Methyl-RNA Synthesis

2'-O-Me 5'→ 3' RNA Synthesis

2'-F RNA Synthesis

2'- O -Butyne RNA Synthesis

RNA: 2'- O -Propargyl RNA Synthesis (Combiclick ^TM Chemistry)

RNA: 2'-O-Hexyne RNA Synthesis

RNA: 3'-O-Alkyl RNA Synthesis

Reagents for Nucleic Acid Chemistry

laithik@gmail.com (L L) — Fri, 24 Nov 2017 21:31:54 GMT

Reagents for Nucleic Acid Chemistry

See the full list of in-house Reagents used in our synthesis

Optimized Nucleotide Synthesis

Our nucleotide synthesis is modeled to introduce technical & chemical optimization from start to finish. We achieve that by utilizing our precision arsenal of formulations to aid & improve very specific moments throughout our solid-phase production. Activation, sulfurizing, phosphorylating and capping reagents help add an extra layer of customization to every project we synthesize. NHS Esters enhance affinity and fluorescence and our mono-,di-, triphosphates offer more control to certain chemical reactions.

Reagents for nucleic acid chemistry

NHS ester/Monophosphate/Diphosphate: NHS esters

Monophosphates

Diphosphates

Triphosphates

Solvents/Reagents-DNA Synthesis

Nucleosides & Amidites

laithik@gmail.com (L L) — Fri, 17 Nov 2017 21:03:04 GMT

Nucleosides & Amidites: The Building Blocks of DNA & RNA

See the full list of in-house Amidites used in our synthesis

Building Blocks

Often referred to as the building blocks of DNA & RNA, a nucleoside is essentially a ribose or deoxyribose sugar carrying a base (adenine, guanine, thymine, cytosine, or uracil) at it’s 1’ position. This complex plays a defining role in the production of quality oligonucleotide sequences. Synthetic versions of nucleosides called amidites are chemical compounds are available in various structures to support principals in sold phase synthesis-such as 5’ protection, directional confirmation, and coupling consistency. With the addition of an open phosphate group at the 3’, phosphoramidites introduce the most complete synthetic compound to simply plug into a custom synthesis design.

See the full list of in-house Amidites used in our synthesis below:

Nucleosides: Unprotected mononucleosides

I-Unprotected deoxy mononucleosides

Nucleosides: II-Unprotected ribo mononucleosides

Base ( N -protected) mononucleosides: I-Base (N -protected) deoxy mononucleosides

Base ( N -protected) mononucleosides: II-Base ( N -protected) ribo mononucleosides

DMT Protected mononucleoside: I-DMT Protected deoxy Mononucleoside

DMT Protected mononucleoside: II-DMT Protected ribo Mononucleosides

P LACEHOLDER

kbdna

Solid Phase Oligonucleotide Synthesis Is Not Obsolete - It Is Ascending

Why phosphoramidite‑based, flow‑enabled solid‑phase synthesis remains the manufacturing backbone of therapeutic oligonucleotides

Abstract:

1. What “Standard” Means in Regulated Oligonucleotide Manufacturing

2. Therapeutic Oligonucleotides Are Chemical Objects, Not Just Sequences

3. Impurity Science: Predictability is an Advantage

4. Flow Chemistry: The Modern Form of Solid‑Phase Synthesis

5. Regulatory Maturity Follows Lifecycle Continuity, Not Novelty

6. Recent Advances (2020–2025): Evolution, Not Replacement

7. Timeline of Advances (2020-2025)

8. Where Enzymatic and Hybrid Approaches Fit

Without Displacing SPOS

Conclusion

References

A CMC Philosophy for Scientists Who Think Beyond the Bench

AI in Biotech: Hype vs Reality

AI in Biotech

Balancing Hype with Reality – An Experienced Perspective

Executive Summary: ﻿

Why the Gap?

AI Promises vs. Reality in Biotech

kbDNA’s Approach – Building a Foundation for Productive AI

The Path Ahead – Realizing AI’s Potential, Responsibly

An Optimistic, Grounded Outlook

Citations

From Bottleneck to Benchmark: kbDNA’s Rituximab Biosimilar Purification Success Story

Bottleneck to Benchmark

Repurification of a Rituximab Biosimilar by Hydrophobic Interaction Chromatography (HIC) with Analytical SEC Confirmation and Endotoxin Control

Use Case

Raise monomer purity of a rituximab biosimilar by ~1–2 percentage points to meet a ≥97.5% monomer cutoff for RUO assay use, while maintaining yield and controlling endotoxin.

Summary

Background & Objectives ﻿

Materials & Equipment (Representative) ﻿

Workflow Overview

Detailed Procedure

1) Pre‑HIC Characterization

2) HIC Mode Selection

3) Scaling Strategy

4) Endotoxin Reduction (Post‑HIC)

5) Buffer Exchange & Concentration

6) Release & QC

Results from the Project (SEC)

Discussion & Practical Notes

Troubleshooting Guide

Example Buffer Recipes

﻿

Quality Control Checklist (Release)

Appendix A — Project Exchange Excerpts (Context)

One‑Page SOP (concise)

﻿

Data Images

SEC Analysis

Figure 1. SEC-HPLC overlay (Control vs kb_Cleaned Final). Normalized UV280; monomer near ~7.9 min.

Figure 2. SEC-HPLC overlay (Control vs UF-Purified Intermediate).

Figure 3. SEC-HPLC overlay (Control, UF-Purified, kb_Cleaned Final).

SDS-PAGE Analysis

Figure 4. Non-reducing SDS-PAGE schematic: lanes ladder, control, UF, HIC pool, final.

Figure 5. Reducing SDS-PAGE schematic: heavy (~50 kDa) and light (~25 kDa) chains.

Current State of Discovery R&D | UnderReport kb

Current State of Discovery R&D

The Life Sciences Crisis Nobody Wants to Talk About

Introduction

Unfiltered Realities, Data-Driven Trends, and the Hard Truths Shaping Discovery-Stage R&D

Recent Timeline

Key Events (2020–2025)

Funding & Investment Landscape

“High-Risk, High-Reward” Hits a Wall

Therapeutic Discovery

Trends and Harsh Realities

Diagnostic Discovery

Trends and Harsh Realities

Organizational Approaches

Who Does Discovery and How Are They Faring?

Vendors, Suppliers & Manufacturers

The Support Ecosystem Under Strain

CASE STUDY

Logistics as a Strategy

kbDNA Inc.

Domestic Expansion for Supply Chain Resilience

Executive Summary:

Background & Objectives

Materials & Equipment (Representative)

Biosimilars and kbDNA