High-throughput Profiling and Analysis of Shared Antibiotic Resistance Genes in Human Feces, Skin and Water Environments

doi:10.13560/j.cnki.biotech.bull.1985.2022-1430

Abstract

Abstract:

Antibiotic resistance genes（ARGs）are emerging contaminants, whose spread in the environment exacerbates antibiotic resistance issues. Little is known about the critical and shared antibiotic resistance genes（ARGs）and their potential hosts in human and water environments. Here, we characterized the ARG profile and bacterial community in human and water environments from a Chinese rural village using high-throughput quantitative polymerase chain reaction and 16S rRNA gene sequencing. A total of 70 shared ARGs, 7 shared mobile genetic elements（MGEs）, and 58 shared bacteria between human and water environments were identified. The dominant shared ARGs in feces were both tetracycline and MLSB resistance genes. Further, we identified 20 bacterial biomarkers by linear discriminant analysis effect size（LEfSe）. The network revealed a significant association among shared ARGs, MGEs, and bacteria（P < 0.05）, suggesting the potential transfer of ARGs between humans and environments via these bacteria. This study revealed the shared ARGs in drinking water, feces, skin, wastewater, and river samples. Our results may provide a better understanding of the co-occurrence of these genetic elements and identify the potential hosts of ARGs between humans and the environment in peri-urban areas. In conclusion, this study demonstrated the co-occurrence and transmission of shared ARGs and bacteria in humans and water environments.

Key words: high-throughput, antibiotic resistance gene, water environment, human, rural area

ZHOU Zhen-chao, ZHENG Ji, SHUAI Xin-yi, LIN Ze-jun, CHEN Hong. High-throughput Profiling and Analysis of Shared Antibiotic Resistance Genes in Human Feces, Skin and Water Environments[J]. Biotechnology Bulletin, 2023, 39(7): 288-297.

Figures/Tables 6

Fig. 1 Relative abundances of ARGs in humans and water samples Red points indicate commonly shared ARGs in human feces, skin and water（n =70）. Error bars indicate min/max values, and centre bars indicate median

Fig. 2 Heatmap of shared ARGs abundances

Fig. 3 Relative abundances（A）and proportions（B）of shared ARGs in different environments

Fig. 4 Taxa discriminates among human feces, skin and water microbiota as determined by LEfSe A: Kingdom- to family-level taxa were shown in the phylogenetic tree. Colored taxa are discriminative between categories（alpha value of < 0.05 for both the Kruskal-Wallis and pairwise Wilcoxon rank-sum tests, and LDA effect size of ≥ 4.0）, circle size is proportional to the taxa abundance. B, C: Relative abundances of discriminative microbial phyla（B）and families（C）in human feces, skin and water microbiota. Only taxa with a mean relative abundance of ≥ 1% in one category are shown. Error bars indicate standard deviation（s. d.）, centre bars indicate median, and black points indicate outliers

Fig. 5 Heatmap of shared bacteria abundances

Fig. 6 Network analysis of all detected ARGs, MGEs and bacteria（A）and shared ARGs, MGEs and bacteria（B） The nodes were colored according to modularity class. A connection represents a strong（Spearman's correlation coefficient（ρ）>0.7）and significant（P-value<0.01）correlation. Node size weighted according to the number of connections（that is the degree）and edges weighted according to the correlation coefficient

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