Unveiling the prevalence of metal resistance genes and their associations with antibiotic resistance genes in heavy metal-contaminated rivers

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Fang-Zhou Gao , Li-Xin Hu , You-Sheng Liu , Hai-Yan Yang , Liang-Ying He , Hong Bai , Feng Liu , Xiao-Wei Jin , Guang-Guo Ying
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Abstract

Heavy metals can drive antibiotic resistance through co-selection mechanisms. Current knowledge predominantly focuses on relationships between metal resistance genes (MRGs) and antibiotic resistance genes (ARGs) at the river reach scale. It remains unclear the links between MRGs and ARGs at the large river basin scale, as does the role of MRG-ARG colocalization in resistance dissemination. This study employed metagenomics to investigate the prevalence of MRGs in the Xiangjiang River, a historically heavy metal-contaminated river, and their connections with ARGs by combining resistome profiling with colocalization analyses. Results revealed the significant prevalence of MRGs in the river compared to nationwide rivers, but it showed weak correlations with metal concentrations in either water or sediment. The prevalence of MRGs in water was weakly driven by abiotic parameters, but was strongly influenced by microbial composition. The proportion of water MRGs attributable to sewage sources was tightly positively correlated with MRG abundances, suggesting the significant contribution of external waste input. Plasmid-originated MRGs were more abundant in water, while chromosomal MRGs dominated in sediment, indicating medium-specific transfer dynamics. The profile of MRGs were strongly correlated with that of ARGs in both media, encompassing several clinically high-risk ARGs. However, MRG-ARG colocalization events were rarely detected (eight instances in total), consistent with low frequencies in nationwide rivers (3.5 % in sediment; 2.0 % in water), implying their limited roles in resistance dissemination. Overall, the findings enhance our understanding of riverine metal resistome and its associations with antibiotic resistome, while emphasize the rare presence of MRG-ARG colocalization in riverine environments.

Abstract Image

Abstract Image

揭示重金属污染河流中金属抗性基因的流行及其与抗生素抗性基因的关系
重金属可以通过共选择机制驱动抗生素耐药性。目前的知识主要集中在河流尺度上金属抗性基因(MRGs)和抗生素抗性基因(ARGs)之间的关系。在大流域尺度上,mrg和arg之间的联系尚不清楚,MRG-ARG共定位在耐药性传播中的作用也不清楚。本研究采用宏基因组学方法,结合抵抗组分析和共定位分析,研究了湘江这条历史上重金属污染的河流中mrg的流行情况,以及它们与arg的关系。结果显示,与全国河流相比,该河中MRGs的普遍存在,但它与水或沉积物中的金属浓度相关性较弱。水中MRGs的流行受非生物参数的影响不大,但受微生物组成的影响很大。归属于污水源的水中MRG比例与MRG丰度呈紧密正相关,表明外部废物输入的贡献显著。质粒来源的MRGs在水中更丰富,而染色体MRGs在沉积物中占主导地位,表明中等特异性转移动力学。两种介质中mrg的分布与arg的分布密切相关,包括几种临床高危arg。然而,MRG-ARG共定位事件很少被检测到(总共8次),与全国河流的低频率一致(沉积物中为3.5%;在水中占2.0%),这意味着它们在耐药性传播中的作用有限。总的来说,这些发现增强了我们对河流金属抵抗组及其与抗生素抵抗组的关系的理解,同时强调了MRG-ARG共定位在河流环境中的罕见存在。
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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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