Assessment of antibiotic resistance genes in dialysis water treatment processes

Highlights

• Quantitative global ARGs profile in dialysis water was investigated.

• Totally 35 ARGs were found in the dialysis treatment train.

• 29 ARGs (highest) were found in carbon filtration effluent.

• erm and mtrD-02 occurred in the final effluent.

• The effluent was associated with health risks even after RO treatment.

Abstract

Dialysis water is directly related to the safety of hemodialysis patients, thus its quality is generally ensured by a stepwise water purification cascade. To study the effect of water treatment on the presence of antibiotic resistance genes (ARGs) in dialysis water, this study used propidium monoazide (PMA) in conjunction with high throughput quantitative PCR to analyze the diversity and abundance of ARGs found in viable bacteria from water having undergone various water treatment processes. The results indicated the presence of 35 ARGs in the effluents from the different water treatment steps. Twenty-nine ARGs were found in viable bacteria from the effluent following carbon filtration, the highest among all of the treatment processes, and at 6.96 Log (copies/L) the absolute abundance of the cphA gene was the highest. Two resistance genes, erm (36) and mtrD-02, which belong to the resistance categories macrolides-lincosamides-streptogramin B (MLSB) and other/efflux pump, respectively, were detected in the effluent following reverse osmosis treatment. Both of these genes have demonstrated the potential for horizontal gene transfer. These results indicated that the treated effluent from reverse osmosis, the final treatment step in dialysis-water production, was associated with potential health risks.

Graphical abstract

Keywords

Dialysis water / Treatment process / Antibiotic resistance gene / High-throughput quantitative PCR / Horizontal gene transfer

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Acknowledgements

This study was financially supported by the Ministry of Science and Technology of China (No. 2017YFE0107300), National Natural Science Foundation of China (Grant Nos. 51478450, 51678551) and Xiamen Municipal Bureau of Science and Technology (No. 3502Z20171003).

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