Distributions and potential risks of antibiotic resistance genes in soils around Dongting Lake Basin,China
52 surface soil samples were collected around Dongting Lake basin.The distribution characteristics and potential health risks of eight typical antibiotic resistance genes(ARGs,comprising 16subtypes of ARGs)in surface soil were analyzed by real-time fluorescence quantitative PCR(qPCR)and a probability health risk assessment model based on Monte Carlo simulation.The total abundance of ARGs in surface soil of the Dongting Lake Basin ranged from 3.29×107 to 3.73×109 copies/g,which was significantly higher than the soil background value of ARGs(1.80×105 to 1.35×107 copies/g,with an average of 3.03×106 copies/g).The southern Dongting Lake Basin exhibited higher ARGs abundance in surface soil compared to the eastern and western Dongting Lake Basin.Sulfonamide,tetracycline,and aminoglycoside resistance genes were the predominant ARGs,with average abundances of 1.51×108,1.50×107,and 2.64×107 copies/g,respectively.The main subtypes of ARGs were sul1and dfrA14,both belonging to sulfonamide resistance genes.The average abundance of class I integron gene(intl1)was 6.94×108copies/g,higher than the average abundance of total ARGs in the study area.Correlation analysis showed a significant positive correlation(P＜0.05)between intl1 abundance and the abundances of dfrA14,tetR,and kan genes,indicating that intl1promotes the spread of ARGs in surface soil via horizontal gene transfer.Monte Carlo simulation revealed that there was a probability of 64.92%to 98.68%for human exposure to ARGs exceeding risk background values(adults and children were 12.56 and 38.11copies/(g·d),respectively),indicating that the potential health risks associated with soil-borne ARGs in the study area.Skin contact was identified as the main exposure pathway for ARGs,and sulfonamide resistance genes were identified as the primary contributors to potential health risks of ARGs.
Dongting Lake Basinsoilantibiotic resistance genesdistribution characteristicspotential risks
万方数据
维普
