New protein sequencing method
Researchers at Stanford rolled out a protein sequencing approach that maps many cellular proteins in new detail, opening up ways to trace how cells behave at scale. (x.com) The reporting highlights this as a lab technique that can reveal previously invisible molecular states across tissues, not just single proteins. (x.com)
Proteins are the cell’s working parts, and Stanford researchers reported a way on March 18 to read them by turning their sequences into DNA that standard sequencers can process. (news.stanford.edu) Deoxyribonucleic acid carries four chemical letters, but proteins are built from 20 amino acids, and those amino acids are smaller and harder to distinguish one by one. That gap has left protein sequencing far behind DNA sequencing in speed and scale. (nature.com) The Stanford team, led by H. Tom Soh and first author Liwei Zheng, described a “reverse translation” method in *Nature Biotechnology* on March 18, 2026. The paper says the approach sequences single peptide molecules with single-amino-acid resolution. (nature.com) The method works like reading beads off a string, one at a time. A modified Edman degradation removes amino acids from the peptide’s front end, tags each released amino acid with a peptide-specific DNA barcode, and converts those signals into polymerase chain reaction-amplifiable DNA reporters for high-throughput sequencing. (nature.com) That matters because DNA sequencers are already fast, cheap, and common in research labs. Stanford said the chemistry lets researchers use those existing machines to identify protein sequences from minimal samples at single-molecule sensitivity. (news.stanford.edu) The paper also says the system generated millions of reads with full sequence coverage and could distinguish native peptides from peptides carrying post-translational modifications, the chemical edits cells add after a protein is made. Those edits often shape signaling, immune response, and disease behavior in ways DNA alone does not show. (nature.com) Researchers have been pushing toward this goal for years with nanopore and other single-molecule approaches, but a 2025 *Nature Biotechnology* perspective described full protein sequencing at single-amino-acid resolution as an emerging capability rather than a solved problem. Stanford’s strategy reframes that challenge as a DNA sequencing problem. (nature.com; nature.com) The work also lands as spatial biology is moving from measuring genes alone to combining gene and protein maps in intact tissue. A 2023 paper from Xiao Wang’s group introduced STARmap PLUS, which paired spatial transcriptomics with protein detection in the same tissue section to map Alzheimer’s-related changes in mouse brain. (nature.com) A 2024 *Nature Methods* comment said spatial proteomics is most useful when integrated with other “multi-omic” layers, including gene expression and tissue structure. That is the setting in which more scalable protein readouts could help researchers sort cell states across tumors, brains, and inflamed tissue. (nature.com) Stanford said the long-term aim is a comprehensive map of proteins in healthy and diseased states. For now, the result is a new way to make proteins legible to machines built for DNA. (news.stanford.edu)
