期刊
EVOLUTIONARY APPLICATIONS
卷 7, 期 7, 页码 774-787出版社
WILEY
DOI: 10.1111/eva.12173
关键词
bacterial pathogens; cross-species transmission; infectious disease; molecular epidemiology; most parsimonious phylogenetic reconstruction; simulation modeling
资金
- National Science Foundation
- National Institutes of Health Ecology of Infectious Disease [DEB-1067129]
- United States Geological Survey
- WGFD
- Direct For Biological Sciences
- Division Of Environmental Biology [1067129] Funding Source: National Science Foundation
- Division Of Environmental Biology
- Direct For Biological Sciences [1067613] Funding Source: National Science Foundation
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.
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