Systems biology of the human microbiome: From big data to models

The human microbiome – the diverse ensemble of microorganisms that populate the human body – represents a vastly complex ecosystem that is tightly linked to our health. Multiple molecular assays now enable high-throughput profiling of this system, providing large-scale and comprehensive characterization of its ecology, functional capacity, and metabolic activity. To date, however, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms, dependencies, and regularities linking these various facets of the microbiome. In this talk, I will highlight the pressing need for the development of predictive systems-level models of the microbiome and of model-based computational methods for integrating and analyzing microbiome multi-omic data. I will further introduce several novel computational frameworks for linking taxonomic, genomic, metagenomic, and metabolomic information about the microbiome. Combined, such frameworks lead to an improved comprehensive, multi-scale, and mechanistic understanding of the microbiome in health and disease, informing efforts for personalized microbiome-based therapy.