Employing toxin-antitoxin genome markers for identification of Bifidobacterium and Lactobacillus strains in human metagenomes

PeerJ. 2019 Mar 4;7:e6554. doi: 10.7717/peerj.6554. eCollection 2019.


Recent research has indicated that in addition to the unique genotype each individual may also have a unique microbiota composition. Difference in microbiota composition may emerge from both its species and strain constituents. It is important to know the precise composition especially for the gut microbiota (GM), since it can contribute to the health assessment, personalized treatment, and disease prevention for individuals and groups (cohorts). The existing methods for species and strain composition in microbiota are not always precise and usually not so easy to use. Probiotic bacteria of the genus Bifidobacterium and Lactobacillus make an essential component of human GM. Previously we have shown that in certain Bifidobacterium and Lactobacillus species the RelBE and MazEF superfamily of toxin-antitoxin (TA) systems may be used as functional biomarkers to differentiate these groups of bacteria at the species and strain levels. We have composed a database of TA genes of these superfamily specific for all lactobacilli and bifidobacteria species with complete genome sequence and confirmed that in all Lactobacillus and Bifidobacterium species TA gene composition is species and strain specific. To analyze composition of species and strains of two bacteria genera, Bifidobacterium and Lactobacillus, in human GM we developed TAGMA (toxin antitoxin genes for metagenomes analyses) software based on polymorphism in TA genes. TAGMA was tested on gut metagenomic samples. The results of our analysis have shown that TAGMA can be used to characterize species and strains of Lactobacillus and Bifidobacterium in metagenomes.

Keywords: Bifidobacterium; Gut microbiota; Lactobacillus; Metagenomes; Toxin-antitoxin systems.

Grant support

Work in the reported study such as creating database TASs, analysis and data processing and developing the program was funded by RFBR according to the research project № 18-34-00011. Sequencing and following bioinformatics analysis of bacterial communities in human gut were funded by the Russian Science Foundation grant N 14–15-01083. Vsevolod Makeev received support from the Presidium of Russian Academy of Sciences Program for Basic Research in Molecular and Cell Biology and Post Genome Technologies #18. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.