Frontiers in Microbiology (Feb 2023)

A MALDI-TOF MS library for rapid identification of human commensal gut bacteria from the class Clostridia

  • Paul Tetteh Asare,
  • Paul Tetteh Asare,
  • Paul Tetteh Asare,
  • Paul Tetteh Asare,
  • Chi-Hsien Lee,
  • Chi-Hsien Lee,
  • Chi-Hsien Lee,
  • Vera Hürlimann,
  • Vera Hürlimann,
  • Youzheng Teo,
  • Aline Cuénod,
  • Aline Cuénod,
  • Nermin Akduman,
  • Nermin Akduman,
  • Cordula Gekeler,
  • Cordula Gekeler,
  • Afrizal Afrizal,
  • Myriam Corthesy,
  • Claire Kohout,
  • Vincent Thomas,
  • Tomas de Wouters,
  • Gilbert Greub,
  • Thomas Clavel,
  • Eric G. Pamer,
  • Adrian Egli,
  • Adrian Egli,
  • Lisa Maier,
  • Lisa Maier,
  • Pascale Vonaesch,
  • Pascale Vonaesch,
  • Pascale Vonaesch

DOI
https://doi.org/10.3389/fmicb.2023.1104707
Journal volume & issue
Vol. 14

Abstract

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IntroductionMicrobial 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.MethodsWe 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.ResultsFor 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.DiscussionWe 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.

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