Document Type

Article

Publication Title

Evolutionary Applications

Publisher

John Wiley & Sons Ltd

Publication Date

8-2014

Volume

7

Disciplines

Biology | Life Sciences

Abstract

Cross-species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological scenarios. We used a simulation model with two host species and known transmission rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phylogeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole-genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced.

Keywords

bacterial pathogens, cross-species transmission, infectious disease, molecular epidemiology, most parsimonious phylogenetic reconstruction, simulation modeling

DOI

10.1111/eva.12173

Rights

© 2014 The Authors.

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

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