Assessing the probability of detection of horizontal gene transfer events in bacterial populations.

Frontiers in Microbiology
Jeffrey P TownsendKaare M Nielsen

Abstract

Experimental approaches to identify horizontal gene transfer (HGT) events of non-mobile DNA in bacteria have typically relied on detection of the initial transformants or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to be detected in a short time frame. Population genetic modeling of the growth dynamics of bacterial genotypes is therefore necessary to account for natural selection and genetic drift during the time lag and to predict realistic time frames for detection with a given sampling design. Here we draw on statistical approaches to population genetic theory to construct a cohesive probabilistic framework for investigation of HGT of exogenous DNA into bacteria. In particular, the stochastic timing of rare HGT events is accounted for. Integrating over all possible event timings, we provide an equation for the probability of detection, given that HGT actually occurred. Furthermore, we identify the key variables determining the probability of detecting HGT events in four different case scenarios that are representative of bacterial populations in various environments. Our theoretical analysis provides insight into the temporal aspects of dissemination of genet...Continue Reading

Citations

Nov 20, 2013·Proceedings of the National Academy of Sciences of the United States of America·Søren Overballe-PetersenEske Willerslev
Oct 6, 2014·Nature Genetics·Leonor Sánchez-BusóFernando González-Candelas
Mar 23, 2013·Microbiology·Oliver WrightTom Ellis
Apr 4, 2013·Mobile Genetic Elements·Sara DominguesKaare M Nielsen
Mar 14, 2013·Mobile Genetic Elements·Janet L Siefert
Oct 18, 2014·Frontiers in Microbiology·Sylvie Nazaret, Rustam Aminov
Aug 20, 2017·Scientific Reports·Frances Tran, James Q Boedicker
Jan 6, 2019·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Hassan WaseemMuhammad Ishtiaq Ali

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