Project Snapshot
Surveillance Pillar
Molecular Epidemiology of Antimicrobial Resistance in Enterococcus From Poultry, Cattle, Humans, and the Environment
Project Key Words: Enterococci, Comparative Genomics, Virulence, Antimicrobial Resistance
Principal Investigator: Sylvia Checkley, PhD; Tim McAllister, PhD
Co-Investigator(s): Karen Liljebjelke, PhD; Rahat Zaheer, PhD; Susan Cork, PhD, Richard Reid-Smith PhD, Simon Otto PhD, Cheryl Waldner PhD, Sheryl Gow PhD
Trainees: Lindsay Rogers, DVM; Kayla Strong, MA; Alyssa Butters, DVM
The Aim
Using whole genome sequencing (WGS) data, this project aims to assess the genetic relatedness of core genomes, mobile genetic elements and antimicrobial resistance genes (ARG) of Enterococcus sourced from poultry farms, beef feedlots, and retail meat products. In collaboration with WP3a and WP3b, we will predict the AMR phenotype using bioinformatics approaches, and use an integrated assessment model to determine potential transmission of resistant bacteria and associated public health risks.
Why is this important?
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Enterococci are leading causes of nosocomial infections. Specifically, E. faecium and E. faecalis represent opportunistic nosocomial pathogens that cause difficult-to-treat infections as a result of intrinsic and acquired antimicrobial resistance. Entercocci are also prevelant in livestock and poultry where they often exhibit high levels of resistance to macrolides, a family of antibiotics considered of high importance in human medicine. Entercocci can also be used as an indicator of fecal contamination. |
Outcomes
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- Information that supports the mitigation of AMR.
Research Questions
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Our Approach
We use a One Health approach to investigate this issue. We will complete a scoping review as well as use comparative genomics, molecular epidemiology, and sophisticated bioinformatics tools with an extensive “One Health” collection of enterococci from humans, livestock, poultry, sewage, surface water, lagoons, and meat processing plants. In addition, use of an integrated assessment model and other epidemiologic techniques will be used to look at specific associations between outcomes and risk factors.
Research questions 2 and 3 have linkages with Project 3a (AMR phenotype prediction tool development component) and 3b (integrated assessment modeling component), respectively.