Modeling the Emergence of MRSA Strains

对 MRSA 菌株的出现进行建模

• 批准号: 10471947
• 负责人: David Ashley Robinson
• 金额: $ 15.5万
• 依托单位: UNIVERSITY OF MISSISSIPPI MED CTR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-19 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10471947
• 关键词: Alleles; Bacteria; Bacterial Antibiotic Resistance; Bacterial Genome; Bayesian Analysis; Biological Assay; Cause of Death; Collection; Communities; Complex; Data; Development; Distant; Epidemic; Epidemiology; Evolution; Founder Effect; Frequencies; Genes; Genetic Models; Genetic Recombination; Genetic Variation; Genome; Genomics; Geographic Distribution; Geography; Growth; Individual; Infection; Knowledge; Lead; Measures; Metadata; Modeling; Nucleotides; Persons; Phenotype; Population; Population Genetics; Population Heterogeneity; Population Sizes; Process; Protocols documentation; Public Health; Sampling; Staphylococcus aureus infection; Surface; Testing; Time; United States; base; community setting; data modeling; fitness; genetic analysis; geographic population; health care settings; healthcare community; healthcare-associated infections; innovation; methicillin resistant Staphylococcus aureus; novel; predictive modeling; prevent; public health relevance; transmission process

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.

抽象的 耐甲氧西林金黄色葡萄球菌 (MRSA) 会导致医疗保健和社区 - 相关感染是抗生素耐药性导致死亡的主要原因之一 美国的细菌。过去 20 年来，美国大多数 MRSA 感染都是由以下原因引起的： 两个生态上成功的菌株。尽管我们对 MRSA 如何 病毒株是可以传播的，但我们对病毒株的出现过程仍然缺乏基本的了解。 菌株从其起源传播到目前的地理分布、遗传多样性、 和健身。在这里，我们建议探索和开发MRSA菌株的群体遗传学模型 的出现。我们的假设是 MRSA 菌株的起源和传播可以准确地确定 建模为具有强烈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 将描述范围扩展的程度 该模型解释了美国两种主要 MRSA 菌株的群体遗传学： 对来自不同地理位置的分离物集合中的细菌基因组进行测序和分析， 通过使用近似贝叶斯计算对数据进行建模。目标 2 将描述健身状况 范围扩展的后果和基因组序列适应性的预测，通过使用 表面 MRSA 生长的创新测定，并通过计算新的基因组评分 可以准确预测单个分离株的表面适应度。地理的发现 正如该模型所预测的，MRSA 菌株遗传多样性和适应性的梯度， 可能会彻底改变我们对菌株出现的理解，并改变我们与菌株互动的方式 同一菌株的地理上不同的种群。这种理解最终可能是至关重要的 用于控制和预测新菌株的出现。