Decoding Strain-Level Variation in the Human Microbiome

Information

  • NSF Award
  • 1563159
Owner
  • Award Id
    1563159
  • Award Effective Date
    8/1/2016 - 7 years ago
  • Award Expiration Date
    7/31/2020 - 3 years ago
  • Award Amount
    $ 399,999.00
  • Award Instrument
    Continuing grant

Decoding Strain-Level Variation in the Human Microbiome

The human body is host to a diverse array of microorganisms. Collectively known as the human microbiota, our microbial cells are a significant factor in human health, not only through causing disease but also by promoting wellness. The microbiota must be understood to fight antibiotic resistance, to stop the rise of autoimmune diseases, and to deliver precision medicine. Microbes also carry information about our ancestry and environmental exposures. Metagenomic sequencing allows researchers to explore what is there and what they are doing. But the field has only recently begun to link differences in metagenomic data to specific microbes, because strain-level analysis is computationally and statistically challenging. The goal of this project is to develop efficient and accurate computational methods for studying the human microbiome at the strain level, so that the full extent of variation in our microbial cells and its association with our biology can be elucidated. The novel associations discovered could be used to identify microbial biomarkers for diagnosis and personalized treatments or to design microbiome targeted drugs, prebiotics, and probiotics. The tools developed will also be useful for characterizing strain-level variation in microbes from environments such as soils and oceans. The investigators will use the cyberinfrastructure and discoveries from this project in graduate teaching, for outreach and communication through public media.<br/><br/>This project will create new statistical methods, models, and software for microbiome research that enable characterization of gene copy number and single nucleotide variants of the microbial strains in shotgun metagenomes. The investigators hypothesize that strain-level analysis will reveal cryptic diversity and associations between host and microbes, which are missed by approaches that ignore differences in gene content amongst strains. The researchers have discovered massive differences in gene content (<50% shared genes) between strains of common human-associated bacteria from different people, which no doubt has functional consequences. Microbial species therefore are not sufficient biomarkers for precision medicine and evolutionary studies of the microbiome, because a person's strain may not harbor the pathways (e.g., for pathogenicity or drug-metabolism) identified in another strain of the same species. With novel tools for quantifying microbiome genomic diversity, thousands of publicly available metagenomes will be analyzed to comprehensively assess the global population structure of human-associated microbes. By comparing this biogeography across species with different functional capabilities and correlating it with human traits and demography, the aim is to discover how microbes adapt to and affect diverse human hosts.

  • Program Officer
    Mary Ann Horn
  • Min Amd Letter Date
    7/25/2016 - 7 years ago
  • Max Amd Letter Date
    7/25/2016 - 7 years ago
  • ARRA Amount

Institutions

  • Name
    The J. David Gladstone Institutes
  • City
    San Francisco
  • State
    CA
  • Country
    United States
  • Address
    1650 Owens Street
  • Postal Code
    941582261
  • Phone Number
    4157342000

Investigators

  • First Name
    Katherine
  • Last Name
    Pollard
  • Email Address
    kpollard@gladstone.ucsf.edu
  • Start Date
    7/25/2016 12:00:00 AM

Program Element

  • Text
    NIGMS
  • Code
    8047

Program Reference

  • Text
    NSF/NIGMS Initiative-Mathematical Bio
  • Code
    4075