Large-scale mapping and modeling of human gut microbiota stability and activity.
Abstract
The human gastrointestinal tract is colonized by a dense community of microbes, which collectively realize functions to influence human physiology. Alterations in the composition of the gut microbiota are associated with diseases including inflammatory bowel diseases, obesity and type 2 diabetes. The gut microbiota protects against pathogens, performs key metabolic transformations and modulates the immune system. While the identities of constituent members of the gut microbiota have been identified, the inter-species interactions that shape community dynamics are unknown, as well as the mapping between community structure and collective outputs. A detailed understanding of the molecular and ecological basis of community-level properties would have profound implications on our ability to remodel the microbiome to optimize human performance. The inter-species interactions that shape the microbiome, including resource competition and interchange, biomolecular warfare and signaling, remain largely unexplored. We are interested in deciphering interactions beyond simple resource competition and key environmental factors that influences a critical function of the gut microbiota that impacts human healthÑshort chain fatty acid synthesis (mainly--butyrate, propionate and acetate). We will develop methods to perform large-scale analysis of inter-species interactions using droplet-microfluidics on a defined human gut microbiome synthetic ecology that mirrors the diversity and dimensionality of the natural system. The inferred co-occurrence networks based on these data combined with high-throughput fitness measurements of combinatorial assemblages will be used to down-select species for detailed characterization. Using the selected species, we will leverage a data-derived computational modeling approach to decipher inter-species interactions to allow for analysis of ecological stability and resilience to perturbations, as well as design of community behaviors by applying tools from dynamical systems theory. We will map community structure to activity (SCFA profiles) using gas-chromatography mass spectrometry (GC-MS) in response to physiologically relevant inputs. Further, we will leverage flow cytometry coupled to dyes to quantify single-cell properties to link community structure, phenotypic properties and community-level utputs. Dynamic computational and statistic models at different resolutions will be used to define key inter-species interactions and environmental parameters that control SCFA profiles and single-cell phenotypes. Using these models, in silico approaches will be used to navigate the vast design space of community memberships and environmental inputs to optimize and regulate SCFA production. For selected microbiome assemblages, we will interrogate intracellular network activities and genetic determinants involved in microbial behaviors. Transcriptional profiling of monospecies and consortia will provide information about shifts in regulatory network activities across ecological contexts. To elucidate genetic factors underlying the assembly and functionality of communities, randomly barcoded and fluorescently-tagged transposon libraries of specific species will be constructed. We will measure the mutant fitness across disparate ecological contexts or in response to external parameters via next-generation sequencing. Beyond the scope of this proposal, the identified genetic factors mediating microbial behaviors will be exploited to control the structure and activity of the gut microbiota. Together, this work will significantly advance our ability to harness the potential of the microbiome via rationally designed synthetic consortia coupled to specific environmental interventions. More broadly, our model-guided framework to dissect diverse community-level functions of microbial communities can be applied to other areas including bioenergy, agriculture and human health.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 07, 2018
- Source ID
- W911NF1710296
Entities
People
- Ophelia S Venturelli
Organizations
- Army Contracting Command
- United States Army
- University of Wisconsin–Madison