Metaproteomics as a systems-biology approach to characterize the microbiome functionality and interactions in the human gut

Microbial communities are composed of bacteria, archaea, microbial eukaryotes, and viruses. Organisms in these communities assist with critical functions across diverse environments. In host-associated microbiomes, such as the human gut microbiome, microbiota carry out activities that modulate the host immune system and provide metabolic benefits to the host. Due to their diverse and important roles in ecosystem processes, many questions exist about microbial community establishment, partitioning of function, and interactions between microbiota with each other and the surrounding environment. High-throughput meta-omics technologies are powerful methods to address the complexity of microbial communities and give unprecedented insights into the potential and active functions of microbiota within these communities. Among these meta-omics methods, metaproteomics can identify and quantify thousands of proteins from a single environmental sample and can be used to directly measure the active function of individual members of the community. This dissertation combines LC-MS/MS-based metaproteomics with other meta-omics approaches to study interkingdom community interactions and functions in environmental samples, with a focus on the human gut microbiome using tractable models. The projects presented here show (1) the application of critical parameters in LC-MS instrumentation and informatics approaches dictate the measurement depth and quality for complex microbiome samples, (2) interspecies competition and cooperation shape relative community composition and are the driving forces behind community utilization of fiber-derived glycans, (3) interactions with the host immune system and functional partitioning among community members facilitates establishment and persistence in the gut environment, and (4) uncultivated gut bacteriophages can use genetic codes different than their bacterial hosts as a regulatory mechanism during infection. In total, this dissertation makes a major step forward by showing that carefully designed metaproteomic measurements can explain the mechanisms of microbiome interactions and functionality.