A putative bacterial ecocline inKlebsiella pneumoniae
Abstract
The genetic structure of bacterial species is most often interpreted in terms of clonal descent but can also reflect processes including natural selection, and hence give functional and ecological insight.Klebsiella pneumoniae(KP) has high recombination rates and disperses effectively around the world which should result in the species having a well-mixed gene pool. Nevertheless, phylogenies based on diverse KP strains contain a “backbone”. This structure reflects a component of variation captured by the first component, PC1, in Principal Components Analysis (PCA) which explains 16.8% of total variation. We propose that the component is generated by diversifying selection on a quantitative genetic trait. We simulated a model in which trait is influenced by many genes, and strains with the most extreme trait values have a small advantage. For high recombination rates or weak selection, the simulated gene pool is approximately randomly mixed, with low variation in trait values. For intermediate rates, trait values become continuously distributed over a wider range. We call the gradient in gene frequencies of the genes associated with the trait a bacterial ecocline. For low recombination rates or stronger selection, trait values the species splits into two separate gene pools. After fitting selection and recombination parameters, we were able recapitulate the overall genetic structure of KP, while the neutral models we investigated could not. As well as providing an explanation for the phylogenetic backbone, our results provide insight into how species such as KP can speciate, via stronger selection on a trait or a reduction in gene flow. Our hypothesis begs two questions about the putative KP bacterial ecocline, namely what the trait is underlying it and why is it under diversifying selection. The genes that are most strongly associated with PC1 provide some hints with number 1 being the fimbria locusKpa. Identification of the trait, if it exists, should facilitate insight into selection on quantitative genetic traits in natural bacterial populations, which have largely been unstudied in microbiology, except in the atypical context of antibiotic resistance.
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