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Transfer dynamics of intracellular and extracellular last-resort antibiotic resistome in hospital wastewater

IF 11.4 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research Pub Date : 2025-05-16 DOI:10.1016/j.watres.2025.123833

Shengcen Zhang , Jingrong Li , Junzhong Lai , Qianwen Zhang , Zhichang Zhao , Bin Li

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引用次数: 0

Abstract

The increasing prevalence of last-resort antibiotic resistance genes (LARGs) has posed severe public health hazards. Previous studies focused primarily on the profiles of intracellular LARGs (iLARGs) in hospital wastewater (HWW), while largely neglecting the expression patterns of iLARGs and the presence of extracellular LARGs (eLARGs). Currently, wastewater resistomes and transfer dynamics of LARGs are still poorly characterized. This study integrates Nanopore-metagenomic and metatranscriptomic sequencing to conduct the comprehensive longitudinal analysis of both iLARGs and eLARGs in HWW. Our study firstly revealed the distinct seasonal patterns of iLARGs and eLARGs. Specifically, iLARGs showed higher abundance during colder seasons, whereas eLARGs showed higher abundance in warm seasons. Both clinical pathogens and functional bacteria of wastewater treatments were identified as important hosts of LARGs, while clinical pathogens played predominant roles in the high expression levels of LARGs. Acinetobacter spp. was identified as major host of bla_NDM-1 in HWW, which is unrestricted by plasmid host range compatibility. However, HWW treatments could not remove LARGs effectively and instead facilitated their transmission by enhancing the expression and horizontal transfer of mobile genetic element (MGE)-derived LARGs. Our study provides comprehensive insights for the atlas and transfer dynamics of LARGs in HWW for the development of control strategies under worldwide spread of antibiotic resistance.

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医院废水中细胞内和细胞外最后手段抗生素抵抗组的转移动力学

最后手段抗生素耐药基因（LARGs）的日益流行已构成严重的公共卫生危害。以往的研究主要集中在医院废水（HWW）中细胞内LARGs （iLARGs）的谱上，而很大程度上忽略了iLARGs的表达模式和细胞外LARGs （eLARGs）的存在。目前，对废水中LARGs的抗性和转移动力学的研究仍然很少。本研究结合纳米孔宏基因组和亚转录组测序对HWW中iLARGs和eLARGs进行了全面的纵向分析。本研究首次揭示了iLARGs和eLARGs具有明显的季节特征。其中，iLARGs在寒冷季节丰度较高，而eLARGs在温暖季节丰度较高。临床病原菌和废水处理中的功能菌都是LARGs的重要宿主，其中临床病原菌在LARGs高表达中起主导作用。不动杆菌属（Acinetobacter sp .）是HWW中blaNDM-1的主要寄主，不受质粒宿主范围相容性的限制。然而，HWW处理不能有效去除LARGs，而是通过增强移动遗传元件（MGE）衍生LARGs的表达和水平转移来促进其传播。我们的研究为在抗生素耐药性全球传播的情况下制定控制策略提供了全面的见解，为HWW中LARGs的图谱和转移动力学提供了依据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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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