Community benchmarking and evaluation of human unannotated microprotein detection by mass spectrometry based proteomics.
Publication Title
Nat Commun
Document Type
Article
Publication Date
1-21-2026
Keywords
Humans; Proteomics; Benchmarking; Mass Spectrometry; Open Reading Frames; Peptides; Molecular Sequence Annotation; Proteins; Databases, Protein; washington; isb
Abstract
Thousands of short open reading frames (sORFs) are translated outside of annotated coding sequences. Recent studies have pioneered searching for sORF-encoded microproteins in mass spectrometry (MS)-based proteomics and peptidomics datasets. Here, we assessed literature-reported MS-based identifications of unannotated human proteins. We find that studies vary by three orders of magnitude in the number of unannotated proteins they report. Of nearly 10,000 reported sORF-encoded peptides, 96% were unique to a single study, and 12% mapped to annotated proteins or proteoforms. Manual curation of a benchmark dataset of 406 manually evaluated spectra from 204 sORF-encoded proteins revealed large variation in peptide-spectrum match (PSM) quality between studies, with immunopeptidomics studies generally reporting higher quality PSMs than conventional enzymatic digests of whole cell lysates. We estimate that 65% of predicted sORF-encoded protein detections in immunopeptidomics studies were supported by high-quality PSMs versus 7.8% in non-immunopeptidomics datasets. Our work stresses the need for standardized protocols and analysis workflows to guide future advancements in microprotein detection by MS towards uncovering how many human microproteins exist.
Specialty/Research Institute
Institute for Systems Biology
DOI
10.1038/s41467-025-68002-x
