Universal, untargeted detection of bacteria in tissues using metabolomics workflows

Nat Commun. 2025 Jan 2;16(1):165. doi: 10.1038/s41467-024-55457-7.

Abstract

Fast and reliable identification of bacteria directly in clinical samples is a critical factor in clinical microbiological diagnostics. Current approaches require time-consuming bacterial isolation and enrichment procedures, delaying stratified treatment. Here, we describe a biomarker-based strategy that utilises bacterial small molecular metabolites and lipids for direct detection of bacteria in complex samples using mass spectrometry (MS). A spectral metabolic library of 233 bacterial species is mined for markers showing specificity at different phylogenetic levels. Using a univariate statistical analysis method, we determine 359 so-called taxon-specific markers (TSMs). We apply these TSMs to the in situ detection of bacteria using healthy and cancerous gastrointestinal tissues as well as faecal samples. To demonstrate the MS method-agnostic nature, samples are analysed using spatial metabolomics and traditional bulk-based metabolomics approaches. In this work, TSMs are found in >90% of samples, suggesting the general applicability of this workflow to detect bacterial presence with standard MS-based analytical methods.

MeSH terms

  • Bacteria* / classification
  • Bacteria* / genetics
  • Bacteria* / isolation & purification
  • Bacteria* / metabolism
  • Biomarkers / analysis
  • Biomarkers / metabolism
  • Feces* / microbiology
  • Gastrointestinal Microbiome
  • Humans
  • Mass Spectrometry / methods
  • Metabolomics* / methods
  • Phylogeny
  • Workflow*

Substances

  • Biomarkers