Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.

ABSTRACT: Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbiology. Different methods, relying on experimental or mathematical approaches based on the diverse properties of bacteria, are currently employed to study these interactions. Recently, the use of metabolic networks to understand the interactions between bacterial pairs has increased, highlighting the relevance of this approach in characterizing bacteria. In this study, we leverage the representation of bacteria through their metabolic networks to build a predictive model aimed at reducing the number of experimental assays required for designing bacterial consortia with specific behaviors. Our novel method for predicting cross-feeding or compet

SUBMITTER: Silva-Andrade C 

PROVIDER: S-EPMC11064492 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature