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Dissecting horizontal and vertical gene transfer of antibiotic resistance plasmid in bacterial community using microfluidics

Li, Bing, Qiu, Yong, Song, Yanqing, Lin, Hai, Yin, Huabing
Environment international 2019 v.131 pp. 105007
Escherichia coli, activated sludge, amoxicillin, antibiotic resistance, antibiotic resistance genes, bacterial communities, gene transfer, horizontal gene transfer, image analysis, microfluidic technology, models, plasmids, tetracycline, trimethoprim
The spread of antibiotic resistance genes (ARGs) has become an emerging threat to the global health. Although horizontal gene transfer (HGT) is regarded as one of the major pathways, more evidence has shown the significant involvement of vertical gene transfer (VGT). However, traditional cultivation-based methods cannot distinguish HGT and VGT, resulting in often contradictory conclusions. Here, single-cell microfluidics with time-lapse imaging has been successfully employed to dissect the contribution of plasmid-mediated HGT and VGT to ARG transmission in an environmental community. Using Escherichia coli with an ARG-coded plasmid pKJK5 with trimethoprim resistance as the donor, we quantified the effects of three representative antibiotics (trimethoprim, tetracycline and amoxicillin) on the ARG transfer process in an activated sludge bacterial community. It was found that HGT was influenced by the inhibitory mechanism of an antibiotic and its targets (donor, recipient alone or together), whereas VGT contributes significantly to the formation of transconjugants and consequently ARG spreading. Trimethoprim is highly resisted by the donor and transconjugants, and its presence significantly increased both the HGT and VGT rates. Although tetracycline and amoxicillin both inhibit the donor, they showed different effects on HGT rate as a result of different inhibitory mechanisms. Furthermore, we show the kinetics of HGT in a community can be described using an epidemic infection model, which in combination with quantitative measure of HGT and VGT on chip provides a promising tool to study and predict the dynamics of ARG spread in real-world communities.