Modeling the Emergence of MRSA Strains

摘要 耐甲氧西林金黄色葡萄球菌（MRSA）导致医疗保健和社区- 相关感染是耐药性结核病导致死亡的主要原因之一， 美国的细菌在过去的20年里，美国的大多数MRSA感染都是由以下原因引起的： 两种生态上成功的菌株。尽管我们对MRSA如何 虽然我们对病毒的传播过程仍缺乏基本的了解， 菌株从它们的起源传播，以实现它们当前的地理分布，遗传多样性， 和健身。在此，我们建议探索和建立MRSA菌株的群体遗传学模型 出现。我们的假设是，MRSA菌株的起源和传播可以准确地 被建模为具有强烈的连续创始人效应的地理范围扩张。我们将测试这个 有两个具体目标的假设。目标1将说明范围扩大的程度 该模型解释了美国两种主要MRSA菌株的群体遗传学， 对来自地理位置不同的分离株集合的细菌基因组进行测序和分析， 通过近似贝叶斯计算对数据进行建模。目标2将描述适应性 范围扩展的后果和从基因组序列预测适应性，通过使用 通过计算一种新的基因组得分， 可以准确预测单个分离物的表面适合度。地理学的发现 根据该模型预测，MRSA菌株的遗传多样性和适应性的梯度， 可以彻底改变我们对菌株出现的理解， 地理上不同的种群。这种理解最终可能是必不可少的 用于控制和预测新菌株的出现。

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.