Study on antibiotics, antibiotic resistance genes, bacterial community characteristics, and their correlation in the landfill leachates

2021 ◽  
Author(s):  
Lirong Bai ◽  
Z T ◽  
Hangyuan Gong ◽  
Min Xu ◽  
Zhiping Li ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Bacterial Community ◽  
Resistance Genes ◽  
Antibiotic Resistance Genes ◽  
Community Characteristics ◽  
Landfill Leachates

scholarly journals Analysis of Antibiotic Resistance Genes, Environmental Factors, and Microbial Community From Aquaculture Farms in Five Provinces, China

2021 ◽  
Vol 12 ◽  
Author(s):  
Xu Cheng ◽  
Yitong Lu ◽  
Yanzhen Song ◽  
Ruifang Zhang ◽  
Xinyan ShangGuan ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Environmental Factors ◽  
Bacterial Community ◽  
Correlation Analysis ◽  
Resistance Genes ◽  
Environmental Risk ◽  
Antibiotic Resistance Genes ◽  
Community Diversity ◽  
Sediment Samples ◽  
Positive Correlation

The excessive use of antibiotics speeds up the dissemination and aggregation of antibiotic resistance genes (ARGs) in the environment. The ARGs have been regarded as a contaminant of serious environmental threats on a global scale. The constant increase in aquaculture production has led to extensive use of antibiotics as a means to prevent and treat bacterial infections; there is a universal concern about the environmental risk of ARGs in the aquaculture environment. In this study, a survey was conducted to evaluate the abundance and distributions of 10 ARGs, bacterial community, and environmental factors in sediment samples from aquatic farms distributed in Anhui (AP1, AP2, and AP3), Fujian (FP1, FP2, and FP3), Guangxi (GP1, GP2, and GP3), Hainan (HP1, HP2, and HP3), and Shaanxi (SP1, SP2, and SP3) Province in China. The results showed that the relative abundance of total ARGs was higher in AP1, AP2, AP3, FP3, GP3, HP1, HP2, and HP3 than that in FP1, FP2, GP1, GP2, SP1, SP2, and SP3. The sul1 and tetW genes of all sediment samples had the highest abundance. The class 1 integron (intl1) was detected in all samples, and the result of Pearson correlation analysis showed that the intl1 has a positive correlation with the sul1, sul2, sul3, blaOXA, qnrS, tetM, tetQ, and tetW genes. Correlation analysis of the bacterial community diversity and environmental factors showed that the Ca2+ concentration has a negative correlation with richness and diversity of the bacterial community in these samples. Of the identified bacterial community, Proteobacteria, Firmicutes, Chloroflexi, and Bacteroidota were the predominant phyla in these samples. Redundancy analysis showed that environmental factors (TN, TP, Cl–, and Ca2+) have a positive correlation with the bacterial community (AP1, GP1, GP2, GP3, SP1, SP2, and SP3), and the abundance of ARGs (sul1, tetW, qnrS, and intl1) has a positive correlation with the bacterial community (AP2, AP3, HP1, HP2, and HP3). Based on the network analysis, the ARGs (sul1, sul2, blaCMY, blaOXA, qnrS, tetW, tetQ, tetM, and intl1) were found to co-occur with bacterial taxa from the phyla Chloroflexi, Euryarchaeota, Firmicutes, Halobacterota, and Proteobacteria. In conclusion, this study provides an important reference for understanding the environmental risk associated with aquaculture activities in China.

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