Metagenomic systems biology: frameworks for modeling and characterizing the gut microbiome

Thesis (Ph.D.)--University of Washington, 2014

Though invisible to the naked eye, microbes are crucial to life as we know it. These tiny single-celled organisms are found in almost every known environment, helping to maintain balance across a vast array of ecological niches plays. Within each site, microbes may form intricate multi-species communities capable of carrying out diverse and complex metabolic processes. The set of microbes inhabiting the human gut (the human gut microbiome) comprises one of the richest and most well-studied of these communities, and shifts in the composition of this microbiome have been shown to have significant implications for host health. However, while current comparative studies mostly focus on characterizing gut microbiomes in terms of the relative abundance of individual species or genes, such profiles offer limited translation to overall community capabilities, and may thus offer limited predictive capacity for effect on the host. Here, I develop frameworks for characterizing and comparing microbiomes as integrated systems, leveraging concepts from systems biology to provide a deeper context for interpreting differences in community composition. In chapter 1, I describe current efforts to characterize microbial communities and the potential advantages of a systems-level perspective. In chapter 2, I present a method for constructing and characterizing topological network models of microbial community metabolism, and then identify specific topological differences between human gut communities from healthy, obese, and IBD-afflicted individuals. The results suggest that the gut environment plays a critical role in shaping microbiome topology, or structure. In chapter 3, I examine gut communities from host species across the mammalian phylogenetic tree and identify groups of functionally-related genes that co-occur across hosts. I term these gene groups `assembly modules', and demonstrate their value for understanding the functional units of microbiome assembly and adaptation. In chapter 4, I relate differences in community function back to individual microbial strains, focusing on functions whose representation across organisms within a given species is community-dependent. Establishing a computational pipeline to detect these strain-specific functions, and generating a database of their frequency across 109 human gut microbiomes, I show that strain-specific functions are widespread among species associated with the gut environment, and that some of the most prominent, such as virulence, antibiotic resistance, and nutrient transport, may have significance for host-microbiome stability. Finally, in chapter 5, I offer some perspective on how the systems-level frameworks presented here may be used in future studies of microbial communities, potentially incorporating burgeoning new technologies and growing data resources, and how continued work in this vein may advance our understanding of the microbial world in relation to our own.