A key challenge in microbiome research is to predict functionality from microbial community composition. As central microbiota functions are determined by bacterial community networks it is important to gain insight into the principles that govern bacteria-bacteria interactions. Here, we focused on growth and metabolic interactions of the Oligo-Mouse-Microbiota (OMM
) synthetic bacterial community, which is increasingly used as model system in gut microbiome research. Using a bottom-up approach, we uncovered the directionality of strain-strain interactions in mono- and pairwise co-culture experiments, as well as in community batch culture. Metabolomics analysis of spent culture supernatant of individual strains in combination with genome-informed pathway reconstruction provided insights into the metabolic potential of the individual community members. Thereby, we could show that the OMM
interaction network is shaped by both, exploitative and interference competition
KB1 was identified as important driver of community composition by affecting the abundance of several other consortium members. Together, this study gives fundamental insight into key drivers and mechanistic basis of the OMM
interaction network, which serves as knowledge base for future mechanistic studies.