Chen, Wei and Qiu, Min and Paizs, Petra and Sadowski, Miriam and Ramonaite, Toma and Zborovsky, Lieby and Mejias-Luque, Raquel and Janssen, Klaus-Peter and Kinross, James and Goldin, Robert D. and Rebec, Monica and Liebeke, Manuel and Takats, Zoltan and Mckenzie, James S. and Strittmatter, Nicole (2025) Universal, untargeted detection of bacteria in tissues using metabolomics workflows. NATURE COMMUNICATIONS, 16 (1): 165. ISSN , 2041-1723
Full text not available from this repository. (Request a copy)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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | MASS-SPECTROMETRY; FATTY-ACID; IDENTIFICATION; CLASSIFICATION; PLATFORM; |
| Subjects: | 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Lehrstuhl für Immunologie |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 23 Apr 2026 11:52 |
| Last Modified: | 23 Apr 2026 11:52 |
| URI: | https://pred.uni-regensburg.de/id/eprint/67550 |
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