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Abundant rifampin resistance genes and significant correlations of antibiotic resistance genes and plasmids in various environments revealed by metagenomic analysis

  • Environmental biotechnology
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Abstract

In the present study, a newly developed metagenomic analysis approach was applied to investigate the abundance and diversity of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) in aquaculture farm sediments, activated sludge, biofilm, anaerobic digestion sludge, and river water. BLASTX analysis against the Comprehensive Antibiotic Resistance Database was conducted for the metagenomic sequence data of each sample and then the ARG-like sequences were sorted based on structured sub-database using customized scripts. The results showed that freshwater fishpond sediment had the highest abundance (196 ppm), and anaerobic digestion sludge possessed the highest diversity (133 subtypes) of ARGs among the samples in this study. Significantly, rifampin resistance genes were universal in all the diverse samples and consistently accounted for 26.9~38.6 % of the total annotated ARG sequences. Furthermore, a significant linear correlation (R 2 = 0.924) was found between diversities (number of subtypes) of ARGs and diversities of plasmids in diverse samples. This work provided a wide spectrum scan of ARGs and MGEs in different environments and revealed the prevalence of rifampin resistance genes and the strong correlation between ARG diversity and plasmid diversity for the first time.

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Acknowledgments

The authors thank the Hong Kong GRF (HKU 7201/11E) for the financial support on this study. Liping Ma thanks The University of Hong Kong for the postgraduate studentship. Dr. Bing Li thanks The University of Hong Kong for the postdoctoral fellowship. The technical assistance of Ms. Vicky Fung is also greatly appreciated.

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Correspondence to Tong Zhang.

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Ma, L., Li, B. & Zhang, T. Abundant rifampin resistance genes and significant correlations of antibiotic resistance genes and plasmids in various environments revealed by metagenomic analysis. Appl Microbiol Biotechnol 98, 5195–5204 (2014). https://doi.org/10.1007/s00253-014-5511-3

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