Exploiting Viral Genomics to Understand Disease

Information

  • Research Project
  • 9032437
  • ApplicationId
    9032437
  • Core Project Number
    U19AI110819
  • Full Project Number
    5U19AI110819-03
  • Serial Number
    110819
  • FOA Number
    RFA-AI-13-009
  • Sub Project Id
    6907
  • Project Start Date
    -
  • Project End Date
    -
  • Program Officer Name
  • Budget Start Date
    4/1/2016 - 8 years ago
  • Budget End Date
    3/31/2017 - 7 years ago
  • Fiscal Year
    2016
  • Support Year
    03
  • Suffix
  • Award Notice Date
    3/9/2016 - 8 years ago

Exploiting Viral Genomics to Understand Disease

Research' Project 1 focuses on significant endemic viral pathogens from humans and viruses from animal hosts that have strong zoonotic potential. High-throughput whole-genome next-generation sequencing (NGS), combined with bioinformatics algorithms, will be used to sequence and analyze the genomes from more than 10,000 strains representing seven viral species. This will characterize the genetic diversity over a range of virus families, including many NIAID priority pathogens, to understand critical evolutionary mechanisms central to viral evolution, pathogenesis, transmission, and/or antiviral resistance. Specifically we aim to: 1) compare and contrast the genetic diversity and evolutionary dynamics of viruses circulating within and/or between humans and animal reservoirs, 2) elucidate viral-host-microbiome determinants that influence viral pathogenesis, and 3) perform deep sequencing to understand intra-host viral diversity, transmission dynamics, and antiviral resistance. Collectively, this project will use multiple genomics approaches (e.g., genomic sequencing, metagenomics, and transcriptomics) to provide the scientific community with genomic data sets of broad use from important viral families. These data will be analyzed using phylogenetics and other bioinformatics algorithms to show the spatial and temporal evolution of these pathogens. Finally, the data generated will identify, track, and predict antigenic drift/shift, recombination, escape from natural or vaccine-induced host immune responses, antiviral resistance, inter- and intra-species transmission, and the response of a host's commensal microbiota to viral infection. The information generated from these studies will help us to produce superior vaccines and antivirals, and the data sets will prove critical for rapid responses to the emergence of novel pathogens (i.e., pandemic preparedness) that arise naturally or as a result of bioterrorism.

IC Name
NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES
  • Activity
    U19
  • Administering IC
    AI
  • Application Type
    5
  • Direct Cost Amount
    1633337
  • Indirect Cost Amount
    1455276
  • Total Cost
  • Sub Project Total Cost
    3088613
  • ARRA Funded
    False
  • CFDA Code
  • Ed Inst. Type
  • Funding ICs
    NIAID:3088613\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    ZAI1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    J. CRAIG VENTER INSTITUTE, INC.
  • Organization Department
  • Organization DUNS
    076364392
  • Organization City
    ROCKVILLE
  • Organization State
    MD
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    208503343
  • Organization District
    UNITED STATES