Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities.

ABSTRACT: The behaviour of microbial communities depends on environmental factors and on the interactions of the community members. This is also the case for urinary tract infection (UTI) microbial communities. Here, we devise a computational approach that uses indices of complementarity and competition based on metabolic gene annotation to rapidly predict putative interactions between pair of organisms with the aim to explain pairwise growth effects. We apply our method to 66 genomes selected from online databases, which belong to 6 genera representing members of UTI communities. This resulted in a selection of metabolic pathways with high correlation for each pairwise combination between a complementarity index and the experimentally derived growth data. Our results indicated that Enteroccus spp.

SUBMITTER: Lara EG 

PROVIDER: S-EPMC8393552 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature