The hottest Proteomics Substack posts right now

And their main takeaways
Category
Top Health & Wellness Topics

Future Of Protein Sequencing

ASeq Newsletter • 29 implied HN points • 11 Mar 26
🔬 Science Proteomics
  1. Protein sequencing is much harder than DNA sequencing and has fewer broad, foundational applications, making commercial success expensive and difficult.
  2. Without big academic champions and large research projects to drive adoption, companies are forced into niche revenue paths that pull development away from a general-purpose sequencing platform.
  3. There are realistic niche opportunities like biopharma QA/QC and sensitive biomarker detection, but turning protein sequencing into a widely used tool will require sustained funding, risk tolerance, and strong research adopters.

BGI Nanopore Peptide Profiling

ASeq Newsletter • 21 implied HN points • 10 Mar 26
🔬 Science Proteomics
  1. BGI demonstrated a scaled-up method for classifying peptides with nanopores, showing the approach works beyond small proofs of concept.
  2. They attach DNA handles to peptide ends so peptides can be threaded and paced through a nanopore using existing DNA sequencing control.
  3. The study revealed more technical detail about BGI’s nanopore platform, indicating it could be adapted for larger-scale protein or peptide analysis.

Illumina Q50, Q70 Reads

ASeq Newsletter • 36 implied HN points • 04 Mar 26
🔬 Science Proteomics
  1. Illumina has renamed the Constellation product to TruPath.
  2. Illumina unveiled a new 35B flowcell for the NovaSeq X.
  3. They announced Q70 Duplex reads but didn’t share details, and also highlighted progress in spatial genomics, single‑cell, and proteomics.

DNA And Protein Sequencing Companies

ASeq Newsletter • 58 implied HN points • 02 Feb 26
🔬 Science Proteomics
  1. Protein sequencing is becoming a growing startup space, with many companies now working to make protein readouts practical.
  2. Two main technical routes dominate—optical methods and nanopore-based sequencing—while a smaller set of firms pursue other novel approaches, and multiple companies are active in each category.
  3. An updated directory of DNA sequencing companies is maintained, and contributors are invited to share additional firms to keep the list current.

Why No Japanese Sequencing Companies?

ASeq Newsletter • 36 implied HN points • 03 Feb 26
đź•ą Technology Proteomics
  1. Japan has deep expertise and built many key components for sequencing — from contributions to the Human Genome Project to ISFET sensing and imaging sensors — yet it has produced almost no homegrown DNA or protein sequencing companies.
  2. Possible reasons include a lack of strong domestic genome centers and expert customers, structural problems with the startup ecosystem, and past institutional missteps that discouraged local product development.
  3. The shift toward clinical, sample-to-answer sequencing and the still-open field of protein sequencing are clear opportunities Japan could exploit with its research and manufacturing strengths, and funding startups would build domestic talent and capability even if many ventures fail.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Epstein Unfortunateness. HYP-FREE - A Hypothesis Free Testing Initiative

ASeq Newsletter • 14 implied HN points • 05 Feb 26
đź•ą Technology Proteomics
  1. Build sample-to-answer DNA and protein sequencers for hypothesis-free diagnostics so clinics can detect known and novel pathogens or biomarkers without guessing, ideally at qPCR-like cost.
  2. Japan is well positioned to lead this effort because it has strong manufacturing and technical capabilities but currently lacks domestic DNA or protein sequencing platform companies, creating a strategic market opportunity.
  3. Use an SBIR-style, commercialization-first program to fund and spin out startups, prioritize simplified sample prep and advanced sequencing (long reads, protein), and engage investors early to scale devices for global clinical use.

Nautilus Early Access

ASeq Newsletter • 14 implied HN points • 25 Nov 25
🔬 Science Proteomics
  1. Nautilus has been pushing an early-access program and that push seems to have increased market interest by showing the platform can support early-access projects.
  2. A recent scientific demo focused on Tau proteoforms (about 768), which is a useful small-scale result but doesn’t demonstrate the claimed ability to interrogate billions of wells or many different proteins.
  3. Because the demo was small, it’s unclear how well the high-density patterning and machine-learning pattern matching perform at scale, so fuller multi-protein or high-well-count demonstrations are needed.

The Ultima Genomics/Olink BioBank Deal

ASeq Newsletter • 51 implied HN points • 11 Jan 25
🔬 Science Proteomics
  1. Ultima Genomics has won a significant project with the UK Biobank to analyze 700,000 samples. This partnership is a major step for them in the field of proteomics.
  2. Despite the project size, Ultima is expected to generate only $10 million to $20 million in revenue. This highlights the tough financial realities in the biotech industry.
  3. To stay viable, Ultima needs to secure more large projects, as its costs are high. Achieving the necessary volume of work may be challenging given the current economic situation.

Synthesis - Switchback Systems, Inc.

ASeq Newsletter • 7 implied HN points • 04 Jul 25
🔬 Science Proteomics
  1. Switchback Systems appears to own some interesting technology but isn't using it in the expected way. Instead of focusing on protein sequencing, they're exploring a new method for synthesis.
  2. There's some confusion about the direction of Switchback Systems because they don't seem to align with the typical work associated with their intellectual property.
  3. The discussion highlights the importance of understanding how companies adapt their technologies and where they might lead in the future.

Functional protein mining with conformal guarantees

Axial • 14 implied HN points • 28 Nov 24
🔬 Science Proteomics
  1. A new method is developed for predicting protein functions using something called conformal prediction. This makes the predictions more reliable and provides a clear way to understand risks when selecting proteins.
  2. The approach helps in annotating genes and predicting enzyme functions more accurately without needing new training models. This is great for speeding up research in life sciences.
  3. It also offers a smart way to reduce the number of proteins needing full analysis, making the process quicker and cheaper while still keeping good accuracy.

Unbiased mapping of cereblon neosubstrate landscape by high-throughput proteomics

Axial • 14 implied HN points • 24 Nov 24
🔬 Science Proteomics
  1. A new method helps find powerful compounds that can target hard-to-reach proteins for drug development. These compounds are called molecular glue degraders, and they can help break down unwanted proteins in the body.
  2. The study found many new targets for these compounds, including some that haven't been studied much before. This expands the potential for developing new treatments for diseases like cancer.
  3. The researchers created a process that combines different scientific techniques, making it easier to design and improve these drugs. This means we might see more precise and effective medicines in the future.

Rapid proteome-wide prediction of lipid-interacting proteins through ligand-guided structural genomics

Axial • 7 implied HN points • 05 Jan 25
🔬 Science Proteomics
  1. Researchers developed a new tool called SLiPP that helps quickly find proteins that interact with lipids. This is important because lipids play key roles in cell functions and diseases.
  2. SLiPP uses machine learning to distinguish between protein pockets likely to bind lipids and those that won't. This makes it easier to identify potential targets for drug discovery.
  3. The tool has been successfully tested on different organisms, showing it can accurately predict lipid-binding proteins. This helps scientists explore new areas in lipid biology and disease research.

Axial Discovery - Kidney disease

Axial • 29 implied HN points • 06 Mar 23
🏥 Health & Wellness Proteomics
  1. Over 30 million people in the US are affected by kidney disease, leading to high healthcare costs and lowered quality of life.
  2. New tools like genomics, proteomics, and metabolomics are transforming drug development for kidney diseases.
  3. Companies like Goldfinch Bio and Chinook Therapeutics are developing medicines for rare kidney diseases with defined clinical milestones.

Maybe Nanopore Protein Sequencing Is Easier Than I Thought?... Maybe Not?...

ASeq Newsletter • 7 implied HN points • 12 Mar 24
🔬 Science Proteomics
  1. Protein sequencing can potentially be easier than expected with nanopore technology, allowing for detection of PTMs and obtaining unique fingerprints from proteins.
  2. Proteomics differs from DNA sequencing in that it allows for estimating protein abundance and identifying PTMs in samples, possibly through aligning multiple protein traces.
  3. Challenges in proteomics applications with nanopore platforms include achieving the necessary dynamic range for accurate measurements, which may require advancements in technology.

Axial Discovery - Kidney disease

Discovery by Axial • 3 implied HN points • 06 Mar 23
🏥 Health & Wellness Proteomics
  1. Kidney disease affects over 30 million people in the US with high healthcare costs.
  2. New tools like genomics, proteomics, and metabolomics show promise in understanding kidney biology and drug development.
  3. CKD is a big opportunity for new treatments, focusing on new MoAs like loss of podocytes, chemokines, JAK inhibitors, and ECM deposition.