Gut microbial interactions based on network construction and bacterial pairwise cultivation

AbstractBackground: Association networks are widely applied to predict bacterial interactions in the human gut microbiome studies. However, experimental validation of the predicted interactions is challenging due to the complexity of microbial composition and the limited number of cultivated bacteria.Results: In this study, we addressed this challenge by integratingin vitrotime series network association inference and co-culture of taxon pairs in network. Fecal samples were cultivated on YCFA agar plates for 13 days. Cells from agar were temporally harvested for DNA extraction and metagenomic sequencing. A total of 198 metagenome-assembled genomes (MAGs) were recovered and 360 bacterial isolates were cultivated belonging to 59 species. Temporal dynamics of bacteria growing on the YCFA agar were used to infer microbial association networks. To experimentally validate the interactions of taxon pairs in networks, we selected 43 bacterial strains that represented 43 MAGs. Among these, 19 strains were collected from the human Gut Microbial Biobank (hGMB) and 24 were isolated from this study. The co-culture experiments revealed that the majority of the interactions between taxa in networks were identified as neutralism (51.67%), followed by commensalism (21.67%), amensalism (18.33%), competition (5%) and exploitation (3.33%). Genome-centric analysis further revealed that the commensal members in human gut extensively involved the exchange of amino acids with greatest biosynthesis cost, short-chain fatty acids, and vitamins. We also validated the 12 beneficiaries by adding 16 additives into the basic YCFA medium. As a result, we found that the growth of 66.7% of the strains was significantly promoted.Conclusions: We have established a method that infers microbial interactions from association networks and validates these interactions using representative strains. This approach provides new insights into reducing the complexity of gut community and confirming microbial interactions in association networks through co-culture experimental. Our work highlights that the inferred gut microbial association networks tend to overestimate positive relationships in the real-world gut microbial communities. Moreover, the confirmed positive relationships between gut microbes are likely mediated by the exchange of amino acids, fatty acids, and vitamins.