COS 68-7
Using ecology to quantify the spread of antibiotic resistance among bacterial reservoirs

Wednesday, August 12, 2015: 10:10 AM
326, Baltimore Convention Center
Benjamin J. Koch, Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ
Bruce A. Hungate, Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ
Lance B. Price, Division of Pathogen Genomics, Translational Genomics Research Institute, Flagstaff, AZ

The problem of antibiotic resistance is growing rapidly with increasing incidence of resistant human infections and growing evidence suggesting that antibiotic use in non-medical settings may be driving a substantial portion of those infections.  New whole-genome sequencing data can reveal the evolutionary history of individual bacterial strains with a level of phylogenetic precision that enables tracing the transmission pathways of drug-resistant lineages and the mobile genetic elements themselves.  When combined with traditional epidemiological sampling of pathogen reservoirs through time, such data can be used to quantify the emergence of novel resistance elements and the clonal expansion of newly resistant strains that underlie the spread of antibiotic resistance through heterogeneous bacterial reservoirs.  However, current epidemiological models are inadequate for linking the ecological factors that govern these processes to the patterns of resistance that emerge from them.  Here we assess the ways in which ecological theory can be used to better understand the spread of antibiotic resistance.  We use a whole-genome sequence-based dataset of Escherichia coli isolates simultaneously collected from food and from human urinary tract infections (UTIs) to model the fluxes of drug-resistant strains among ecologically linked bacterial reservoirs.


The strain-level richness of E. coli isolated from food and from UTIs was high and many strains exhibited antibiotic resistance.  Using mass-balance assumptions, we parameterized a three-compartment box model of strain-level fluxes and standing stocks in food and in infected and asymptomatically colonized humans, and estimated a carriage rate of <10% for food-associated E. coli strains that go on to cause urinary tract infections.  Furthermore, for each E. coli strain, our model constrained the magnitudes of successful transmissions from the food reservoir to the human gut reservoir and from the gut reservoir to the UTI reservoir.  Nonetheless, data on the relative abundances of specific strains in human gut are needed to test these predictions and to accurately estimate the flux of antibiotic-resistant E. coli from food to people.

From the perspective of bacteria subjected to antibiotic use in food animals and in people, the acquisition and spread of antibiotic resistance traits is an ecological phenomenon.  Bidirectional exchange of resistant bacteria between the food-animal sector and the human population is analogous to cross-ecosystem resource subsidies.  Ecosystem models of stocks and fluxes of material or energy among reservoirs are useful for predicting the spread of antibiotic resistance in an increasingly interconnected world.