1. Universal, untargeted detection of bacteria in tissues using metabolomics workflows
- Author
-
Wei Chen, Min Qiu, Petra Paizs, Miriam Sadowski, Toma Ramonaite, Lieby Zborovsky, Raquel Mejias-Luque, Klaus-Peter Janßen, James Kinross, Robert D. Goldin, Monica Rebec, Manuel Liebeke, Zoltan Takats, James S. McKenzie, and Nicole Strittmatter
- Subjects
Science - Abstract
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.
- Published
- 2025
- Full Text
- View/download PDF