Synergy between culturomics and metagenomics of health status-associated gut bacteria originating from non-IBD and IBD populations

The bacteria in the human intestinal tract are important for health and associate with diseases, such as inflammatory bowel disease (IBD). Although metagenomic studies can identify certain bacteria or even specific strains and associate their presence or specific phenotypes with health or diseases, actual isolates for experimental validation of metagenomic associations are often lacking. Therefore, this study sets out to culture health- and IBD-associated bacteria from 32 fecal samples from 2 cohorts, for which extensive metadata is available. The cultivation of those samples resulted in 4,347 isolates, of which 1,362 isolates were obtained from IBD patients. Irrespective of health or IBD, Actinomycetota, Bacillota and Bacteroidota were the most represented phyla and members of 5 other phyla were less frequently isolated (Campylobacterota, Fusobacteriota, Pseudomonadota, Thermodesulfobacteriota and Verrucomicrobiota). Comparison of the genus richness between the culturomics approach and available metagenomic sequencing data of the corresponding participants revealed that both methods largely capture the same genera. Although not all genera could be identified in both methods, our results show that combining both methods has a synergetic effect, providing a higher identification rate. Furthermore, genetic analysis of 2 isolates of Bifidobacterium adolescentis strains shows that these isolates closely resembled the metagenome-assembled genome that was identified within the same participant. This showcases that it is possible to isolate specific strains that are important in the experimental validation of specific associations within a species. The culture collection that is presented in this study contains bacterial isolates that are strongly associated with health or IBD. Our results show that we are able to generate a valuable culture collection that opens a promising avenue for functional validation experiments of associations that are identified with metagenomic data.