Modeling the Emergence of MRSA Strains

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ABSTRACT Methicillin-resistant Staphylococcus aureus (MRSA) causes healthcare- and community- associated infections that are among the leading causes of death due to antibiotic-resistant bacteria in the US. Most MRSA infections in the US over the past 20 years have been caused by two ecologically successful strains. Although we have extensive knowledge about how MRSA strains are transmitted, we still lack a basic understanding of the emergence process by which strains spread from their origin to achieve their current geographic distribution, genetic diversity, and fitness. Here, we propose to explore and develop a population genetics model of MRSA strain emergence. Our hypothesis is that the origin and spread of MRSA strains can be accurately modeled as a geographic range expansion with a strong serial founder effect. We will test this hypothesis with two Specific Aims. Aim 1 will characterize the extent to which a range expansion model explains the population genetics of the two predominant MRSA strains in the US, by sequencing and analyzing bacterial genomes from a geographically diverse isolate collection and by modeling the data with Approximate Bayesian Computation. Aim 2 will characterize the fitness consequences of range expansion and the prediction of fitness from genome sequences, by using an innovative assay of MRSA growth on a surface and by calculating a novel genomic score that can accurately predict the surface fitness of individual isolates. The discovery of geographic gradients underlying the genetic diversity and fitness of MRSA strains, as predicted by this model, could revolutionize our understanding of strain emergence and change how we interact with geographically different populations of a strain. This understanding ultimately may be essential for controlling and predicting the emergence of new strains.