Back to Search
Start Over
A MALDI-TOF MS library for rapid identification of human commensal gut bacteria from the class Clostridia.
- Source :
- Frontiers in Microbiology; 2023, p1-11, 11p
- Publication Year :
- 2023
-
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 (CLOSTRITOF) 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 CLOSTRITOF 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1664302X
- Database :
- Complementary Index
- Journal :
- Frontiers in Microbiology
- Publication Type :
- Academic Journal
- Accession number :
- 164142045
- Full Text :
- https://doi.org/10.3389/fmicb.2023.1104707