Abstract

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.

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