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<p>Small open reading frames (smORFs), which encode proteins under 100 amino acids, represent an underexplored dimension of the human gut microbiome, despite growing evidence of their essential biological roles. Due to small size and poor annotation, smORFs are typically excluded from metagenomic/metaproteomic analyses. Here, we present a high-resolution multi-omic workflow that integrates smORF prediction into metaproteome searches and enables ultra-deep detection of smORF-encoded proteins (SEPs), without experimental size-based enrichment, utilizing state-of-the-art mass spectrometry instrumentation. Applied to human gut microbiomes, this approach resulted in the largest number of detected SEPs to date, allowing identification of over 25,000 SEPs in the metaproteome, alongside the measurements of the larger proteins. Our multi-omics integrative strategy is critical for advancing human metaproteome research. It also provides a generalizable strategy for comprehensive SEP discovery across diverse microbial ecosystems greatly expanding the previously hidden proteomic landscape.</p>

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High-resolution multi-omics enhances prediction and detection of smORF-encoded proteins in the human gut microbiome

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月9日

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  • Megan E. Davin,
  • Júlia Ortís Sunyer,
  • Luis F. Delgado,
  • Steven L. Tavis,
  • Tuesday Lowndes,
  • Zainab Zafar,
  • Jordan Caussin,
  • Rashi Halder,
  • Oskar Hickl,
  • Cédric C. Laczny,
  • Etienne Hanslian,
  • Daniela A. Koppold,
  • Anika Rajput-Khokhar,
  • Nico Steckhan,
  • Sebastian Schade,
  • Jochen Schneider,
  • Brit Mollenhauer,
  • Andreas Michalsen,
  • Patrick May,
  • Robert L. Hettich,
  • Paul Wilmes

摘要

Small open reading frames (smORFs), which encode proteins under 100 amino acids, represent an underexplored dimension of the human gut microbiome, despite growing evidence of their essential biological roles. Due to small size and poor annotation, smORFs are typically excluded from metagenomic/metaproteomic analyses. Here, we present a high-resolution multi-omic workflow that integrates smORF prediction into metaproteome searches and enables ultra-deep detection of smORF-encoded proteins (SEPs), without experimental size-based enrichment, utilizing state-of-the-art mass spectrometry instrumentation. Applied to human gut microbiomes, this approach resulted in the largest number of detected SEPs to date, allowing identification of over 25,000 SEPs in the metaproteome, alongside the measurements of the larger proteins. Our multi-omics integrative strategy is critical for advancing human metaproteome research. It also provides a generalizable strategy for comprehensive SEP discovery across diverse microbial ecosystems greatly expanding the previously hidden proteomic landscape.