Metagenomic characterization of antimicrobial resistance and bacterial community interactions in Canadian dairy herds

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Antimicrobial resistance (AMR) has been identified by the United Nations and World Health Organization as one the most important global threats that require a global response to curb the spread in populations. This research program will contribute to the understanding of the transmission pathways of AMR in dairy farms. This unique NSERC initiative is based on the use of novel molecular epidemiological tools to assess the diversity and abundance of the microbiome in association with antimicrobial resistance genes (AMRgs). Results from this NSERC Discovery Grant (NSERC-DG) program will allow us to integrate epidemiological modeling with genomic information to assess risk factors for AMR in animals and animal products and its transmission pathways. The main goal of this NSERC-DG proposed research is to determine the pathways of transmission of AMRgs between animals, animal products, and different ecological niches of the bacterial communities within the dairy herds. The short-term objectives are 1) to determine the diversity (richness) and abundance of a community of microbes (e.g. commensal and pathogenic microorganisms) present in feces from dairy cattle, the dairy farm environment, and bulk tank milk (BTM) samples; 2) to determine the frequency and distribution of AMRgs from samples obtained from dairy cattle, their farm environments, and BTM, and to compare these resistance genes to those isolated in other parts of world; 3) to determine interactions among bacterial communities using horizontal gene transfer (HGT) events amongst the genomic sequences; and 4) to explore the relationship between milk quality parameters, microbial diversity, and AMRgs abundance on dairy farms. Using DNA next generation sequencing (e.g. shotgun metagenomics), I endeavor to determine the diversity and abundance of the microbiome and the abundance of AMR genes among the samples collected, and to identify HGT events in association with antimicrobial exposure, using both bioinformatics and epidemiological analytical tools. Moreover, I will explore the HGT network of the microbial communities present in the farm to determine the hot-spots of AMR gene transfer in different farms compartments. Using shotgun metagenomics, I will be able to characterize the profiles of the main microorganisms present in the microbial community, as well as the AMRgs associated with different levels of antibiotic exposure in dairy cattle and their milk. The results from this program will contribute to the understanding of the transmission pathways of AMR genes in the microbial community of samples from dairy farms, and will also help the use of novel molecular techniques to address population level questions. Findings from this NSERC-DG will be beneficial for the development of prudent use guidelines for antimicrobial use in food animal agriculture and risk assessment models for policy development.