Abstract

Much has been learned about the diversity and distribution of human-associated microbial communities, but we still know little about the biology of the microbiome, how it interacts with the host, and how the host responds to its resident microbiota. The Integrative Human Microbiome Project (iHMP, http://hmp2.org), the second phase of the NIH Human Microbiome Project, will study these interactions by analyzing microbiome and host activities in longitudinal studies of disease-specific cohorts and by creating integrated data sets of microbiome and host functional properties. These data sets will serve as experimental test beds to evaluate new models, methods, and analyses on the interactions of host and microbiome. Here we describe the three models of microbiome-associated human conditions, on the dynamics of preterm birth, inflammatory bowel disease, and type 2 diabetes, and their underlying hypotheses, as well as the multi-omic data types to be collected, integrated, and distributed through public repositories as a community resource.

Highlights

  • The human microbiome is important for human health, behavior, and disease, yet its function and dynamics during healthy and disease states are only partially understood

  • Much has been learned about the diversity and distribution of human-associated microbial communities, but we still know little about the biology of the microbiome, how it interacts with the host, and how the host responds to its resident microbiota

  • The first phase of the NIH Human Microbiome Project (HMP, fiscal years 2008–2012, http://www.commonfund.nih.gov/hmp) examined the diversity and composition of the human microbiome to evaluate (1) common patterns of microbial diversity associated with health and (2) whether taxonomic or functional features of the microbiome correlated with diseases by analyzing a large healthy cohort and a set of demonstration projects

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Summary

Introduction

The human microbiome is important for human health, behavior, and disease, yet its function and dynamics during healthy and disease states are only partially understood. Sequence-based analysis of all genes in total DNA extracts; the data are used to develop microbial community compositional, functional, and genomic profiles.

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