A MALDI-TOF MS library for rapid identification of human commensal gut bacteria from the class Clostridia.
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2023
- doi: 10.3389/fmicb.2023.1104707
- issn: 1664-302X
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info:eu-repo/semantics/altIdentifier/doi/10.3389/fmicb.2023.1104707
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info:eu-repo/semantics/altIdentifier/pmid/36896425
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info:eu-repo/semantics/altIdentifier/pissn/1664-302X
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info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_3CB9A6F82FA05
info:eu-repo/semantics/openAccess , CC BY 4.0 , https://creativecommons.org/licenses/by/4.0/
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P.T. Asare et al., « A MALDI-TOF MS library for rapid identification of human commensal gut bacteria from the class Clostridia. », Serveur académique Lausannois, ID : 10.3389/fmicb.2023.1104707
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Résumé
Microbial isolates from culture can be identified using 16S or whole-genome sequencing which generates substantial costs and requires time and expertise. Protein fingerprinting via Matrix-assisted Laser Desorption Ionization-time of flight mass spectrometry (MALDI-TOF MS) is widely used for rapid bacterial identification in routine diagnostics but shows a poor performance and resolution on commensal bacteria due to currently limited database entries. The aim of this study was to develop a MALDI-TOF MS plugin database (CLOSTRI-TOF) allowing for rapid identification of non-pathogenic human commensal gastrointestinal bacteria. We constructed a database containing mass spectral profiles (MSP) from 142 bacterial strains representing 47 species and 21 genera within the class Clostridia. Each strain-specific MSP was constructed using >20 raw spectra measured on a microflex Biotyper system (Bruker-Daltonics) from two independent cultures. For validation, we used 58 sequence-confirmed strains and the CLOSTRI-TOF database successfully identified 98 and 93% of the strains, respectively, in two independent laboratories. Next, we applied the database to 326 isolates from stool of healthy Swiss volunteers and identified 264 (82%) of all isolates (compared to 170 (52.1%) with the Bruker-Daltonics library alone), thus classifying 60% of the formerly unknown isolates. We describe a new open-source MSP database for fast and accurate identification of the Clostridia class from the human gut microbiota. CLOSTRI-TOF expands the number of species which can be rapidly identified by MALDI-TOF MS.