Revealing host-gut microbiome interactions : a metaproteomic perspective

The host gut and its associated microbiome, the resident bacteria, eukaryotes, viruses, and archaea, are part of a dynamic community that spans the entire digestive tract. Their various interactions, often through the use of lipids, metabolites, nucleic acids, and proteins, result in highly complex biological networks that play a large role host. Indeed, to date, gut-microbiome interactions have been linked to a myriad of healthy and diseased states including irritable bowel disease, cancer, autoimmune disorders, and neuropsychiatric conditions. These complex networks are bolstered further complicated by the addition of dietary constituents to the intestinal environment, which act as a nutrient substrate for both the host and microbes. Together, the proteins present in these three constituents, host, microbes, and diet, comprise the host gut metaproteome. Given their importance to health, efforts have recently begun to attempt to unravel these networks using ingenious biological and computational methods. Despite the current efforts, our understanding of the gut metaproteome is far from complete. This thesis will describe my contributions to the field of metaproteomics. Chapter 1 describes current efforts in the field of mass-spectrometry-based gut metaproteomics. More specifically, it describes the promise metaproteomics holds in helping biomedical science understand the myriad of ways in which microbes and hosts communicate and the pathways involved. Moreover, it documents current computational and theoretical challenges that must be overcome in order for metaproteomics to develop into a readily useful technology. Chapter 2 describes the mass-spectrometry-based gut metaproteomics interrogation of a model of multiple sclerosis, experimental autoimmune encephalomyelitis. We focus specifically on the latent period prior to disease onset to show that metaproteomics can be used to distinguish pre- and post-immunization states. Furthermore, we show that a specific class of proteins are inversely correlated with disease severity. Lastly, we show that combining multi-omic strategies may be useful in elucidating connections between microbe and protein levels. Chapter 3 describes the invention of a novel stool proteomic pipeline development, the Stool High Throughput Proteomic Pipeline (SHT-PP). We show that compared to the previous pipeline, it can process samples at over 80% faster, leading to increased sample throughput and as a result, an increased ability to tackle larger sample sets from large longitudinal studies. When this was applied to such a data set, we revealed a subtle but distinct difference that correlated with increased ingestion of either fiber or fermented food diet augmentation. Data generated from these studies were successful in classifying diet participants based solely on a handful of host- or microbe generated proteins. This protocol may serve as a springboard that launches stool-based metaproteomics into a commonly used assay for both biological questions and diagnostic biomarker discovery. Chapters 4 describes one of my collaborative efforts with the Sonnenburg lab where we highlight the discovery of shifting seasonal microbial patterns in hunter-gatherer tribes (Hadza) in Africa. These patterns were largely driven by the alternating seasonal diets consumed by tribe members. We compared this population of subjects to those eating a more westernized diet and noted the absence of some of the more dynamically regulated in western diet subjects. Overall, these results shed light on the loss of microbial diversity resulting from western diets, as well as give us insight into more traditional patterns of microbiome seasonal changes

Keywords: Chemical and Systems Biology.
Advisor: Elias Joshua
Wandless Thomas 
Grimes Kevin
Sonnenburg Justin