Next Article in Journal
Association between Precipitation and Diarrheal Disease in Mozambique
Next Article in Special Issue
Assessment of Impacts of Coal Mining in the Region of Sydney, Australia on the Aquatic Environment Using Macroinvertebrates and Chlorophyll as Indicators
Previous Article in Journal
Are Bank Employees Stressed? Job Perception and Positivity in the Banking Sector: An Italian Observational Study
Previous Article in Special Issue
Antibiotics in Crab Ponds of Lake Guchenghu Basin, China: Occurrence, Temporal Variations, and Ecological Risks
Open AccessArticle

Abundances of Clinically Relevant Antibiotic Resistance Genes and Bacterial Community Diversity in the Weihe River, China

College of Natural Resources and Environment, Agriculture Key Laboratory of Plant Nutrition and Agri-Environment in Northwest China, Northwest A&F University, Yangling 712100, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2018, 15(4), 708; https://doi.org/10.3390/ijerph15040708
Received: 3 February 2018 / Revised: 30 March 2018 / Accepted: 7 April 2018 / Published: 10 April 2018
(This article belongs to the Special Issue Aquatic Ecosystem Health)
The spread of antibiotic resistance genes in river systems is an emerging environmental issue due to their potential threat to aquatic ecosystems and public health. In this study, we used droplet digital polymerase chain reaction (ddPCR) to evaluate pollution with clinically relevant antibiotic resistance genes (ARGs) at 13 monitoring sites along the main stream of the Weihe River in China. Six clinically relevant ARGs and a class I integron-integrase (intI1) gene were analyzed using ddPCR, and the bacterial community was evaluated based on the bacterial 16S rRNA V3–V4 regions using MiSeq sequencing. The results indicated Proteobacteria, Actinobacteria, Cyanobacteria, and Bacteroidetes as the dominant phyla in the water samples from the Weihe River. Higher abundances of blaTEM, strB, aadA, and intI1 genes (103 to 105 copies/mL) were detected in the surface water samples compared with the relatively low abundances of strA, mecA, and vanA genes (0–1.94 copies/mL). Eight bacterial genera were identified as possible hosts of the intI1 gene and three ARGs (strA, strB, and aadA) based on network analysis. The results suggested that the bacterial community structure and horizontal gene transfer were associated with the variations in ARGs. View Full-Text
Keywords: antibiotic resistance gene; bacterial community; droplet digital polymerase chain reaction (ddPCR); network analysis; Weihe River antibiotic resistance gene; bacterial community; droplet digital polymerase chain reaction (ddPCR); network analysis; Weihe River
Show Figures

Graphical abstract

MDPI and ACS Style

Wang, X.; Gu, J.; Gao, H.; Qian, X.; Li, H. Abundances of Clinically Relevant Antibiotic Resistance Genes and Bacterial Community Diversity in the Weihe River, China. Int. J. Environ. Res. Public Health 2018, 15, 708.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
  • Supplementary File 1:

    Supplementary (PDF, 703 KB)

  • Externally hosted supplementary file 1
    Doi: no
    Link: http://no
    Description: Figure S1: Total relative abundances of ARGs and intI1 in water samples collected from the Weihe River; Figure S2: Venn diagrams showing the shared and distinct operational taxonomic units (OTUs) in different sites; Figure S3: Distributions of the relative abundances of the 10 most abundant bacteria in the 13 samples at different levels: (a) phylum level; (b) class level; (c) order level; and (d) family level; Table S1: Descriptions of the sampling sites; Table S2: Primers and probes for the detection of clinically relevant antibiotic genes in this study; Table S3: Raw and clean tags, OTUs, Good’s coverage, and Shannon, Chao1, ACE, and Simpson’s indices for the 13 water samples; Table S4: Environmental factors used for redundancy analysis; Table S5: Pearson’s correlation coefficients between genes and the main bacterial phyla. * Significantly different at p < 0.05. ** Significantly different at p < 0.01; Table S6: Pearson’s correlation coefficients between the relative abundances of ARGs and the intI1 gene. * Significantly different at p < 0.05; Table S7: Pearson’s correlation coefficients between genes and environmental factors. * Significantly different at p < 0.05.
Back to TopTop