The complex relationship between humans and their microbiome and the changes of the microbiome during onset of human disease are poorly understood. We propose to form 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. Building upon our broad expertise, we will analyze several 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), we 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. We will focus on subjects at risk for diabetes, and we will correlate the molecular changes in microbiome (endogenous and viral) activity with changes in host glucose levels and diabetes onset. Overall, more than 1080 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. To accomplish this goal we have assembled a uniquely qualified team.

Public Health Relevance

Both viral and endogenous microbiomes are thought to have an enormous influence on human health but exactly how this occurs is not known. By analyzing in detail the gut and nasal microbiome and how its activity changes during viral infection in people we hope to understand in detail its influence on human physiology, particularly those at risk for diabetes. This information may help in understand how diabetes is acquired and ultimately may be useful for disease detection and treatment.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54DK102556-03
Application #
8901159
Study Section
Special Emphasis Panel (ZDE1)
Program Officer
Sechi, Salvatore
Project Start
2013-09-06
Project End
2017-08-31
Budget Start
2015-09-01
Budget End
2017-08-31
Support Year
3
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Stanford University
Department
Genetics
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Piening, Brian D; Zhou, Wenyu; Contrepois, Kévin et al. (2018) Integrative Personal Omics Profiles during Periods of Weight Gain and Loss. Cell Syst 6:157-170.e8
Sailani, M Reza; Jingga, Inlora; MirMazlomi, Seyed Hashem et al. (2017) Isolated Congenital Anosmia and CNGA2 Mutation. Sci Rep 7:2667
Li, Xiao; Dunn, Jessilyn; Salins, Denis et al. (2017) Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information. PLoS Biol 15:e2001402
Contrepois, Kévin; Liang, Liang; Snyder, Michael (2016) Can Metabolic Profiles Be Used as a Phenotypic Readout of the Genome to Enhance Precision Medicine? Clin Chem 62:676-8
Araya, Carlos L; Cenik, Can; Reuter, Jason A et al. (2016) Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations. Nat Genet 48:117-25
Kuleshov, Volodymyr; Jiang, Chao; Zhou, Wenyu et al. (2016) Synthetic long-read sequencing reveals intraspecies diversity in the human microbiome. Nat Biotechnol 34:64-9
Chennamsetty, Indumathi; Coronado, Michael; Contrepois, Kévin et al. (2016) Nat1 Deficiency Is Associated with Mitochondrial Dysfunction and Exercise Intolerance in Mice. Cell Rep 17:527-540
Contrepois, Kévin; Jiang, Lihua; Snyder, Michael (2015) Optimized Analytical Procedures for the Untargeted Metabolomic Profiling of Human Urine and Plasma by Combining Hydrophilic Interaction (HILIC) and Reverse-Phase Liquid Chromatography (RPLC)-Mass Spectrometry. Mol Cell Proteomics 14:1684-95
Wu, Linfeng; Snyder, Michael (2015) Impact of allele-specific peptides in proteome quantification. Proteomics Clin Appl 9:432-6
Reuter, Jason A; Spacek, Damek V; Snyder, Michael P (2015) High-throughput sequencing technologies. Mol Cell 58:586-97

Showing the most recent 10 out of 17 publications