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<p>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.</p>

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Community benchmarking and evaluation of human unannotated microprotein detection by mass spectrometry based proteomics

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月21日

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  • Aaron Wacholder,
  • Eric W. Deutsch,
  • Leron W. Kok,
  • Jip T. van Dinter,
  • Jiwon Lee,
  • James C. Wright,
  • Sebastien Leblanc,
  • Ayodya H. Jayatissa,
  • Kevin Jiang,
  • Ihor Arefiev,
  • Kevin Cao,
  • Francis Bourassa,
  • Felix-Antoine Trifiro,
  • Michal Bassani-Sternberg,
  • Pavel V. Baranov,
  • Annelies Bogaert,
  • Sonia Chothani,
  • Ivo Fierro-Monti,
  • Daria Fijalkowska,
  • Kris Gevaert,
  • Norbert Hubner,
  • Jonathan M. Mudge,
  • Jorge Ruiz-Orera,
  • Jana Schulz,
  • Juan Antonio Vizcaíno,
  • John R. Prensner,
  • Marie A. Brunet,
  • Thomas F. Martinez,
  • Sarah A. Slavoff,
  • Xavier Roucou,
  • Jyoti S. Choudhary,
  • Sebastiaan van Heesch,
  • Robert L. Moritz,
  • Anne-Ruxandra Carvunis

摘要

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.