Grant: Alliance Grants

Antimicrobial resistance (AMR) is a growing threat to global health, causing around 1.2 million deaths each year, with projections suggesting this could rise to 10 million by 2050. Understanding and tracking AMR is challenging due to historical underfunding, inconsistent detection methods, and fragmented monitoring systems. There are significant gaps in knowledge about how AMR spreads across different environments, species, and microbes. To address this, there is a need for new methods to identify and catalog antimicrobial resistance genes (ARGs) in non-clinical environments, especially those that are new or not yet seen in clinical settings. Environmental surveillance has proven valuable during the pandemic by providing crucial information to public health units. It shows promise for enhancing our understanding of AMR through sampling wastewater, built environments, and agricultural settings. Working with local public health units as partners, we propose a comprehensive plan to detect AMR in human populations that current clinical sample-focused methods might miss. Using functional metagenomics, which doesn't require isolating microbial cultures, we can identify AMR more effectively. This approach leverages experience from constructing metagenomic libraries from various environmental samples and can address significant knowledge gaps. By conducting detailed comparisons and computational analyses, we aim to establish functional metagenomics as a key method for understanding AMR in local populations in Ontario.