{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Chen W"],"funding":["Cancer Research UK","Deutsche Forschungsgemeinschaft (German Research Foundation)","National Institute for Health Research (NIHR)","China Scholarship Council (CSC)"],"pagination":["165"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11697447"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16(1)"],"pubmed_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 a"],"journal":["Nature communications"],"pubmed_title":["Universal, untargeted detection of bacteria in tissues using metabolomics workflows."],"pmcid":["PMC11697447"],"funding_grant_id":["P64610","505372148","ICL BRC Molecular Phenomics","202208320033","C52720/A25038","CRC1182"],"pubmed_authors":["Ramonaite T","Janßen KP","Kinross J","Qiu M","Liebeke M","Goldin RD","Rebec M","Zborovsky L","McKenzie JS","Chen W","Paizs P","Strittmatter N","Sadowski M","Mejias-Luque R","Takats Z"],"additional_accession":[]},"is_claimable":false,"name":"Universal, untargeted detection of bacteria in tissues using metabolomics workflows.","description":"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 a","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jan","modification":"2025-04-04T12:02:22.918Z","creation":"2025-04-04T12:02:22.918Z"},"accession":"S-EPMC11697447","cross_references":{"pubmed":["39747039"],"doi":["10.1038/s41467-024-55457-7"]}}