Grant: Project Grant

Antimicrobial resistance (AMR) is among the most pressing public health crises of the 21st Century as bacteria are evolving drug resistance faster than we can discover new drugs. Once treatable infectious diseases now include nearly untreatable strains. In addition, many of the 'miracles' of modern medicine, such as chemotherapy or routine surgery, are under threat due to a degraded ability to control secondary infection. Discovery of new antimicrobials is furthermore at an all-time low, making stewardship of our current antimicrobial arsenal critical. Yet, we have recently seen emergence of very serious threats to our last two 'drugs of last resort' - carbapenem effectiveness has been undermined by emergence of NDM-1 in 2006 and colistin effectiveness by emergence of MCR-1, first reported in November 2015. As such, while there is an urgent need to re-boot the drug discovery process for antimicrobials, we have an increasing need for better data for clinical practice, antimicrobial stewardship, and public health policy. In both a Canadian and global perspective, we need to know which resistance genes are prevalent, which genes are moving around, and which pose a threat. This Project Scheme proposal is focused on the accurate detection of resistome (the complement of resistance genes and mutations) and subsequent accurate prediction of antibiogram (the range of antimicrobial resistance and susceptibility) from raw DNA sequencing data. Building upon our successful Comprehensive Antibiotic Resistance Database, we propose development and application of AMR gene detection models, high resolution prediction of resistance phenotype, and powerful prediction of molecular epidemiological context to push AMR genomic surveillance beyond its current state. Our key scientific objective is to supersede the current paradigm of basic sequence similarity detection tools with intelligent systems for DNA sequencing based molecular epidemiology of infectious pathogens.