AUTHOR=Asare Paul Tetteh , Lee Chi-Hsien , Hürlimann Vera , Teo Youzheng , Cuénod Aline , Akduman Nermin , Gekeler Cordula , Afrizal Afrizal , Corthesy Myriam , Kohout Claire , Thomas Vincent , de Wouters Tomas , Greub Gilbert , Clavel Thomas , Pamer Eric G. , Egli Adrian , Maier Lisa , Vonaesch Pascale TITLE=A MALDI-TOF MS library for rapid identification of human commensal gut bacteria from the class Clostridia JOURNAL=Frontiers in Microbiology VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2023.1104707 DOI=10.3389/fmicb.2023.1104707 ISSN=1664-302X ABSTRACT=Introduction

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.

Methods

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.

Results

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.

Discussion

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.