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sector_ico_Agrifood_trans Agrifood

Genomic Analysis of Wetland Sediment as a Tool for Avian Influenza Surveillance and Prevention

UPP025
  • Project Leaders: Chelsea Himsworth, William Hsiao, Jane Pritchard, Natalie Prystajecky
  • Institutions: University of British Columbia (UBC)
  • Budget: $2,460,630
  • Competition: User Partnership Program
  • Genome Centre(s): Genome BC
  • Fiscal Year: 2016
  • Status: Active

  Avian Influenza (AI) is a viral disease that can cause significant mobility and mortality in domestic poultry.  In the Fraser Valley in 2014/2015, 11 commercial poultry production farms and two non-regulated farms were involved in an outbreak of highly-pathogenic AI, which resulted in approximately 240,000 birds died or were culled. The similar outbreak in the US were estimated to cost ~$3B and resulted in shortages and price increases for certain poultry products such as eggs.

   The current AI surveillance programs in the USA and Canada are focused on PCR-based testing of individual wild waterfowl, since they are the reservoir for AI (shedding virus in their faces). However, these programs failed to predict 2014/2015 outbreaks in either country. Therefore BC Ministry of Agriculture (the project end user) are seeking a better approach to detect and characterize AI in waterfowl. In the Genome BC/Genome Canada – sponsored 2015/2016 pilot study, the project team used the genomics technology “targeted resequencing” to identify the 2014/2015 outbreak AI virus in wetland sediments, which demonstrated up to 24% detecting of AI as compared to a <1% rate of detection in the current Canadian national wild bird AI surveillance program.

   The success of the pilot study was a direct result of the trans-disciplinary team. The Academic Leads are based out of the University of British Columbia but are also appointed to the BC Ministry of Agriculture Plant and Animal Health Branch (PAHB, the End User and with expertise in AI science and policy) and the BC Centre for Disease Control Public Health Laboratory (with expertise in genomics, bioinformatics, and disease surveillance using environmental samples). The same team is being carried forward for the present study. The goals are to refine the AI sediment surveillance technology and methodology, to validate the sediment surveillance approach in the field, and to identify the optimal combination of AI surveillance techniques for maximum efficiency and efficacy. Ultimately the research findings will be taken up by PAHB to develop and implement a new Provincial Waterfowl AI Surveillance Program, with genomic analysis of wetland sediment as the cornerstone of this program. In addition, this approach is anticipated to be adopted both nationally and internationally due to its revolutionary nature.