Systems Modelling of the Skin Microbiome

The skin microbiome is a complex ecosystem comprising diverse microorganisms inhabit distinct microenvironments. The nature of interactions within the microbial community and with the host, have far-reaching implications for skin health and disease. In this study, we present several insights into these interactions, through a systems-level graph-theoretic analysis of the skin microbiome, by studying the metabolic networks of constituent organisms. We illustrate several dependencies amongst the skin species by considering the possible metabolic exchanges that can take place, and also look into the preferred mechanisms, if any, adopted by species to support each other. Using MetQuest, a graph-theoretic algorithm previously developed in our laboratory, we quantify the extent and nature of support one organisms offers to another within a community, which forms the basis of our community. Interestingly, we observe a clear dependence of Staphylococci and other species on Corynebacteria. We further show that the metabolic exchanges between organisms are predominated by enzyme classes such as transferases and translocases, across many genera. Our approach presents several testable hypotheses for experimental verification and is a generic approach to unravel the complexity of diverse microbiomes, as seen through the lens of metabolism.