The complex relationship between humans and their microbiome and the changes of the microbiome during onset of human disease are poorly understood. The Michael Snyder (Stanford University)/George Weinstock (Jackson Laboratory for Genomic Medicine) team has formed a multiomics center for the detailed longitudinal analysis of both the microbiome, its activity, and its interconnected relationship with the host during healthy and disease states by omics profiling.

The team is conducting a closely-spaced longitudinal study of the microbiomes of a small cohort (~40-50 subjects) of prediabetic subjects with the goal of evaluating immunological triggers for diabetes. This team is testing the hypothesis that typical colds or flu or other stressors (trauma, antibiotics, etc) can induce the onset of type 2 diabetes in prediabetic patients. Building upon their broad expertise, this team will analyze human microbiomes (fecal, nasal, and exogenous viral) in conjunction with host blood and urine components. Samples will be collected and analyzed during healthy and viral infections from the same individuals over the course of at least three years.

Through analysis of the microbiome and host biological activities as measured through a variety of ‘omics approaches (metagenome, genome, transcriptome, proteome, metabolome), they will follow the dynamic changes in the microbiome and host pathways that occur during viral infections and other potential stresses, and obtain an unprecedented view of the molecular pathways that change during this period. They will focus on subjects at risk for diabetes, and will correlate the molecular changes in microbiome (endogenous and viral) activity with changes in host glucose levels and diabetes onset.

Overall, more than 1000 different physiological states will be analyzed in ‘omic detail and the microbiome and corresponding host information will be deposited in a public repository and serve as an invaluable resource to the scientific community. These multiple data types will form the integrated dataset for the Snyder/Weinstock project and will be made publically available.