Toxin-Antitoxin Systems: A Tool for Taxonomic Analysis of Human Intestinal Microbiota.
gut microbiota
metagenomes
strain identification
toxin-antitoxin systems
Journal
Toxins
ISSN: 2072-6651
Titre abrégé: Toxins (Basel)
Pays: Switzerland
ID NLM: 101530765
Informations de publication
Date de publication:
12 06 2020
12 06 2020
Historique:
received:
06
05
2020
revised:
08
06
2020
accepted:
10
06
2020
entrez:
18
6
2020
pubmed:
18
6
2020
medline:
3
3
2021
Statut:
epublish
Résumé
The human gastrointestinal microbiota (HGM) is known for its rich diversity of bacterial species and strains. Yet many studies stop at characterizing the HGM at the family level. This is mainly due to lack of adequate methods for a high-resolution profiling of the HGM. One way to characterize the strain diversity of the HGM is to look for strain-specific functional markers. Here, we propose using type II toxin-antitoxin systems (TAS). To identify TAS systems in the HGM, we previously developed the software TAGMA. This software was designed to detect the TAS systems, MazEF and RelBE, in lactobacilli and bifidobacteria. In this study, we updated the gene catalog created previously and used it to test our software anew on 1346 strains of bacteria, which belonged to 489 species and 49 genera. We also sequenced the genomes of 20 fecal samples and analyzed the results with TAGMA. Although some differences were detected at the strain level, the results showed no particular difference in the bacterial species between our method and other classic analysis software. These results support the use of the updated catalog of genes encoding type II TAS as a useful tool for computer-assisted species and strain characterization of the HGM.
Identifiants
pubmed: 32545455
pii: toxins12060388
doi: 10.3390/toxins12060388
pmc: PMC7354421
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Russian Foundation for Basic Research
ID : 18-34-00011
Pays : International
Organisme : Russian Science Foundation
ID : 19-74-00146
Pays : International
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