Global Antibiotic Resistance Surveillance and Epidemiology Using Whole Genomes

President's Global Innovation Fund
Paul J. Planet
Columbia Global Centers | Latin America (Santiago)
Additional locations: 
Rio de Janeiro, Brazil

Antibiotic resistance (AR) has been identified by the WHO as one of the biggest threats for public health in the 21st century. Modern patterns of travel and immigration make the epidemiology of AR a global problem. Until recently, the tools for tracking the spread of resistant strains of bacteria (eg., MRSA, VRE, CRE) have been hampered by a lack of resolution for distinguishing between strains. Inexpensive, whole genome sequencing (WGS) of pathogenic bacteria offers the possibility of tracing outbreaks and transmission with unprecedented resolution. Coupling WGS with bioinformatic tools from phylogenetics and population genetics we can reconstruct origins, transmission patterns and rates, and make credible forecasts about future spread.

Principal Investigator

Paul J. Planet
Assistant Professor of Pediatrics

The impact of the WGS approach is most effective when it can rapidly identify emerging patterns and lead to prompt interventions that help curb the spread of disease. This effort requires strengthening connections between researchers from distinct disciplines (bioinformatics, genomics, infectious disease, microbiology, and epidemiology), and also training a new generation of scientists who can tackle this problem going forward. It also requires sustainable, international collaborations that can effectively identify threats across borders. Through the support offered by Columbia Global Centers in Latin America, we propose to strengthen and expand scientific collaboration by fostering a network of investigators focused on WGS approaches to monitoring for the spread of AR. The network includes researchers, clinicians and genomic centers from across the Western Hemisphere. Our goal is to provide a platform for scholarly collaboration and training while simultaneously beginning to collect data that can be used to positively impact public health.