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Antimicrobial Resistance: Emergence, Transmission, and Ecology (ARETE)

Status: 
Active
Competition: 
2017 Bioinformatics and Computational Biology Competition
Sector: 
Agriculture and Agri Food
Environment
Genome Centre(s):
Genome Atlantic, Genome British Columbia
Project Leader(s):
Robert Beiko (Dalhousie University), Fiona Brinkman (Simon Fraser University)
Project Description: 

Bacteria are becoming increasingly resistant to antimicrobial agents, causing concern for the agri-food industry, where overuse and mismanagement of antibiotics have played a significant role. There is no single solution that will reverse this trend, nor reinvigorate the antimicrobial discovery pipeline. A better understanding of the genes that make bacteria resistant and how they spread is, therefore, a priority worldwide. A key element in the transmission of resistance is the sharing of resistance genes among pathogenic bacteria. Resistant bacteria also move between habitats, such as agricultural soil and farm animals, but we need a better understanding of key transmission points in order to prioritize surveillance and regulation activities.

Drs. Robert Beiko of Dalhousie University and Fiona Brinkman of Simon Fraser University are leading a large team made up of academic and government partners who are seeking to determine which genes are being shared, which bacteria are sharing genes, and how bacteria are moving between habitats. They are developing bioinformatics algorithms and software that will shift how we look at antimicrobial resistance (AMR) from a static “snapshot” to a dynamic view of AMR transmission. They will validate their tools using thousands of genomes of Salmonella, E. coli, and other pathogenic bacteria collected by partners in the Public Health Agency of Canada and Agriculture and Agri-Food Canada. The integrated software pipeline that will result from this project will be open-source and freely available.

The rigorous bioinformatics framework developed through this project will enable more-informed approaches to minimize the risks posed by resistance and foster a national framework to apply genomics and bioinformatics to the “farm to fork” continuum for AMR.