Department of Statistics and Actuarial Science, University of Iowa, Iowa City, IA 52242-1409, USA.
Epidemics. 2010 Dec;2(4):165-72. doi: 10.1016/j.epidem.2010.08.002. Epub 2010 Sep 9.
Modern advances in genetic analysis have made it feasible to ascertain the variant type of a pathogen infecting a host. Classification of pathogen variants is commonly performed by clustering analysis of the observed genetic divergence among the variants. A natural question arises whether the genetically distinct variants are epidemiologically distinct. A broader question is whether the different variants constitute separate microbial species or represent minor variations of the same species. These important issues were addressed in the context of analyzing dynamics of genetically distinct variants of Bartonella bacteria in cotton rat hosts. Frequencies of acquiring a new variant were measured in relation to the genetic differences between variants successively infecting an individual rodent host. Two statistical techniques were introduced for performing such analysis, and the methodologies were illustrated with a set of data collected from a particular multi-strain Bartonella system. We carried out a frequency analysis of co-infection patterns, and a Markov chain analysis of panels of successive mixed infection time series for testing some particular gene-based grouping of the Bartonella variants with a panel of observed disease data from a rodent population. Our analysis suggests that the three genogroups A, B and C of Bartonella function as independent species but the variants within each genogroup enjoy some cross-immunity against each other. The newly developed methodologies are broadly applicable for analyzing other multi-strain pathogen data which are increasingly collected for diverse infectious diseases.
现代遗传分析的进展使得确定感染宿主的病原体的变异类型成为可能。病原体变异的分类通常通过观察到的变异之间的遗传差异的聚类分析来进行。一个自然的问题是,遗传上不同的变异是否在流行病学上不同。更广泛的问题是,不同的变异是否构成单独的微生物物种,还是同一物种的微小变异。这些重要问题是在分析棉鼠宿主中巴尔通体细菌的遗传上不同的变异体的动态时提出的。在个体啮齿动物宿主中相继感染的变体之间的遗传差异的基础上,测量获得新变体的频率。介绍了两种用于执行此类分析的统计技术,并使用从特定多菌株巴尔通体系统收集的一组数据说明了该方法。我们进行了共感染模式的频率分析,以及对连续混合感染时间序列的马尔可夫链分析,以根据啮齿动物种群的观察疾病数据对巴尔通体变体进行基于基因的分组进行测试。我们的分析表明,巴尔通体的 A、B 和 C 三个基因组作为独立的物种发挥作用,但每个基因组内的变体彼此之间具有一定的交叉免疫力。新开发的方法广泛适用于分析其他多菌株病原体数据,这些数据越来越多地用于各种传染病。