Recent efforts to characterize the gut microbiome have significantly increased our knowledge of the composition and abundance of host-associated bacteria communities in healthy and diseased states. However, translation of these results into clinically informative therapeutics has been slow. Beyond antibiotic strategies, fecal microbiota transplantation is the only other clinically validated approach to restore microbiome health. A key roadblock has been the lack of detailed mechanistic understanding for how gut microbiota colonize the gastrointestinal tract and specific factors that enable their success. Detailed understanding of local microbial biogeography are not available, leading to inference of contribution of microbiota on health only from bulk- averaged datasets. Delineating the precise spatial distribution and heterogeneity of microbiota at a micron-scale and their specific association with host-specific cell types may lead to improved understanding of their role in gastrointestinal health and disease. This proposal aims to develop a new approach through ?spatial metagenomics? to map the micron-scale microbial biogeography along the gastrointestinal tract and apply the system for understanding gut microbiota colonization in a murine model. We hypothesize that the healthy gut microbiota are organized in defined spatial patterns at the micron-scale along the gastrointestinal tract that reflect an underlying robust and homeostatic network of inter-microbial and host-microbial interactions, which is disrupted by specific environmental exposures and host factors that lead to dysbiosis and diseased states. We will first generate cell particles that encapsulate groups of microbiota cells in their native co-association states for high-throughput profiling by next-generation sequencing. Deconvolution of the data results in co-localization networks that inform the spatial architecture of the population in their native habitat. We will characterize how the microbiome biogeography changes along different parts of the murine gastrointestinal tract and their responses to dietary changes in healthy states. Then, we will probe these spatial changes upon exposure to various antibiotics that may selectively or broadly disrupt the underlying microbiota interaction network. These disrupted communities will then be subjected to fecal microbiota transplantation, and the effects of such recolonization on the establishment of new spatial microbiota architectures will be explored. Concurrently, we will develop metabolic and network-based models to analyze the detailed mechanisms that underlie microbial spatial architectures in the gastrointestinal tract under these healthy and disrupted states. If successful, this project will demonstrate for the first time the spatial organization of the gut microbiota in health and disrupted states using an unbiased and high-throughput method and generate key datasets and insights into the microbial distribution along the gastrointestinal tract at a micron-scale resolution. These insights can potentially translate into novel biomarkers for microbiota spatial organization that can be applied to study human cohorts in future microbiome studies.
Dysbiosis of the gut microbiome is associated with a variety of gastrointestinal, inflammatory, metabolic and systemic diseases, but detailed understanding of how microbes colonize the gastrointestinal tract is not available. This proposal aims to develop a new high-throughput and unbiased method to map the spatial biogeography of gut microbiota at a micron-size spatial resolution and will delineate this microbiome organization and function using a well-established mice gut model. The results of this study will have direct relevance for understanding microbial colonization of the mammalian gut in both healthy and diseased states to improve clinical strategies to promote or modify gut microbiota states through prebiotics, probiotics, antibiotics, or microbiota transplantation manipulations.
| Sheth, Ravi U; Wang, Harris H (2018) DNA-based memory devices for recording cellular events. Nat Rev Genet 19:718-732 |
