Grant: JPIAMR Final Conference Travel Awards

Antibiotic resistance is one of our greatest public health threats globally. Rapid identification of antibiotic resistant organisms, and their paths of transmission, can help patients to receive effective treatment for their infections sooner and improve outcomes. We set out to use real-time genome sequencing of patient specimens to identify resistant organisms and predict their patterns of resistance to help guide therapy. We also sought to use the same approaches to help identify whether bacteria that might have been transmitted from other patients and help with recognizing outbreaks of antibiotic resistant organisms. With a multinational team from Canada, Germany, and The Gambia, we generated large bacterial genomic reference databases for performing rapid k-mer analyses and validated these on sequenced primary specimens and isolates from clinical settings. We found that for some of the most common bacterial pathogens encountered, we could improve prediction of antibiotic susceptibility and resistance in a rapid and meaningful way, with the potential to help rescue antibiotics that would otherwise be unusable. Similarly, our approach showed that it could identify infections that are likely to be resistant, which can help inform appropriate use of broad-spectrum antibiotics – deploying them for those who need them most. Lastly, we were able to use the same techniques to rapidly generate measures of relatedness and recapitulate genetic trees. These rapid approaches have the potential to guide infection prevention and control practice in real time, offering a distinct advantage over slower reference standards (e.g. whole genome sequencing). We have communicated our findings at multiple international conferences, shared large sequence and k-mer reference databases, and generated abstract and manuscript publications. In the process, we have also trained numerous technicians, graduate students, and postdoctoral trainees, in state-of-the-art sequencing and bioinformatics approaches. Data and results from this work has already helped fuel new funding applications and spin off projects, and a review paper of rapid diagnostics featuring the techniques evaluated in the KSTAR project is currently underway.