UC San Diego

We are more than humans. Our mammalian cells are intimately associated with roughly an equivalent number of microbial cells, which contain more than 100 times more genes than mammalian cells. There is constant cross-communication between our cells and these microbial cells through the molecules (i.e. metabolites and proteins) that are produced by microbe and man. We are currently amidst a revolution in our understanding of these interactions through the use of large-scale systems approaches utilizing technological developments in sequencing and mass spectrometry. While sequencing and metabolomic profiling are rapidly becoming standard practice in the field, the use of mass-spectrometry based proteomics is less commonly applied when considering host-microbiome interactions. Given the central role that proteins play in all biological organisms, the integration of this field into the wider context of microbiome research promises abundant insights.

This work describes the use of technological improvements in the field of quantitative multiplexed proteomics for understanding host-microbiome interactions. In the first chapter, I introduce the current state of human microbiome research, what diseases it is associated with and the technologies used to study it. Further, I describe the use of proteomics to study multispecies communities (metaproteomics). In the second chapter, I utilize proteomics to understand the response of different organ systems to a lack of microbes in mice. In the third chapter, I evaluate the differences that result from using genomic versus proteomic technology when studying the microbiome of a patient with a disease strongly connected to the microbiome, inflammatory bowel disease (IBD). In the fourth chapter, I study a cohort of IBD patients using a combination of six –omic datasets, and through the use of metaproteomics, identify a new therapeutic treatment avenue for IBD patients targeting bacterial proteases. I further evaluate this therapeutic approach experimentally in colonic epithelial cells and germ-free mice. The fifth chapter outlines the potential of quantitative multiplexed metaproteomics to better understand other microbiota-associated diseases. Specifically, I observe a potential of the technology to understand and predict obesity outcomes in mice. In the final chapter, I discuss the implications of this work.