Evidence map›Paper›PMID 39747039›Full record

ArticleNature communications2025

Universal, untargeted detection of bacteria in tissues using metabolomics workflows.

Wei Chen, Min Qiu, Petra Paizs, Miriam Sadowski, Toma Ramonaite, Lieby Zborovsky, Raquel Mejias-Luque, Klaus-Peter Janßen, James Kinross, Robert D Goldin and 5 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Review
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  7. Metabolism-Based Biomarkers for Rapid Phenotypic Antibiotic Susceptibility Testing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  8. Article
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  10. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Wei ChenDepartment of Bioscience, School of Natural Sciences, Technical University of Munich, Garching, Germany.
Min QiuDepartment of Bioscience, School of Natural Sciences, Technical University of Munich, Garching, Germany.
Petra PaizsDepartment of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.
Miriam SadowskiDepartment of Symbiosis, Max Planck Institute for Marine Microbiology, Bremen, Germany.
Toma RamonaiteDepartment of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.
Lieby ZborovskyDepartment of Bioscience, School of Natural Sciences, Technical University of Munich, Garching, Germany.
Raquel Mejias-LuqueInstitute for Medical Microbiology, Immunology and Hygiene, School of Medicine and Health, Technical University of Munich, Munich, Germany.ORCID 0000-0002-4602-4927
Klaus-Peter JanßenDepartment of Surgery, School of Medicine and Health, Technical University of Munich, Munich, Germany.ORCID 0000-0002-4707-7887
James KinrossDepartment of Surgery and Cancer, Imperial College London, London, United Kingdom.ORCID 0000-0002-0427-7643
Robert D GoldinDepartment of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.ORCID 0000-0001-5184-4519
Monica RebecNorth West London Pathology, Imperial College Healthcare NHS Trust, London, United Kingdom.
Manuel LiebekeDepartment of Symbiosis, Max Planck Institute for Marine Microbiology, Bremen, Germany.ORCID 0000-0002-2339-1409
Zoltan TakatsDepartment of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.ORCID 0000-0002-0795-3467
James S McKenzie *Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom. j.mckenzie@imperial.ac.uk.ORCID 0000-0002-1007-317X
Nicole Strittmatter *Department of Bioscience, School of Natural Sciences, Technical University of Munich, Garching, Germany. nicole.strittmatter@tum.de.ORCID 0000-0003-1277-9608

Funding

Cancer Research UK (CRUK) C52720/A25038Cancer Research UK (CRUK) P64610China Scholarship Council (CSC) 202208320033Deutsche Forschungsgemeinschaft (German Research Foundation) 505372148Deutsche Forschungsgemeinschaft (German Research Foundation) CRC1182DH | National Institute for Health Research (NIHR) ICL BRC Molecular Phenomics
6 · The paper itself

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.

Indexed as

BacteriaFecesMetabolomicsWorkflowBiomarkersGastrointestinal MicrobiomeHumansMass SpectrometryPhylogenyBiomarkers

Identifiers

PMID39747039
PMCPMC11697447

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.