Identifying groundwater anthropogenic disturbances and their predominant impact on microbial nitrogen cycling at a former contamination site adjacent to Baiyangdian Lake

IF 12.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2025-03-23 DOI:10.1016/j.watres.2025.123544
Sining Zhong , Bin Li , Qian Chen , Jinzheng zhang , Hetong Cai , Rui An , Guohong Liu , Shungui Zhou
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Abstract

Groundwater ecosystems face increasing threat from declining water quality due to intensified urbanization, agricultural, and industrial activities. Accurately identifying anthropogenic disturbances remains challenging, and their effects on microbial nitrogen cycling are still largely unknown. Here, by collecting 64 groundwater samples from an aquifer beneath the Tanghe sewage reservoir in the North China Plain, we conducted a full-spectrum screening of 228 physiochemical indices, 47 nitrogen cycling genes (NCGs) and 2182 metagenome-assembled genomes (MAGs) harboring NCGs. Unmix model identified antibiotic usage, industrial manufacturing, and agricultural practices as the predominant pollution sources, explaining 49.6–92.2 % (averaged 81.0 %) of the variations in aquifer attributes. These activities were primary drivers governing distributions of groundwater NCGs and NCG-hosts, with fragmented denitrification processes being prevalent. Antibiotic usage and industrial activities were probably associated with suppressed nitrogen cycling, while agriculture had a positive effect. Notably, we observed enhanced mutualistic interactions within NCG-hosts and increased enrichment of NCG-antibiotic resistance gene (ARG), NCG-mental resistance gene (MRG), and NCG-ARG-MRG co-hosts under high anthropogenic stresses, suggesting microbial adaptation to optimize nutrient and energy metabolism. This study provided new insight into how groundwater nitrogen cycling responds to anthropogenic disturbances, offering valuable information for developing groundwater management and pollution control strategies.

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白洋淀前污染场地下水人为干扰及其对微生物氮循环的主要影响
由于城市化、农业和工业活动的加剧,地下水生态系统面临着日益严重的水质下降威胁。准确识别人为干扰仍然具有挑战性,它们对微生物氮循环的影响在很大程度上仍然未知。本研究通过采集华北平原唐河污水库地下含水层64份地下水样本,对228个理化指标、47个氮循环基因(NCGs)和2182个含NCGs的宏基因组组装基因组(MAGs)进行了全谱筛选。Unmix模型确定抗生素使用、工业制造和农业实践是主要污染源,解释了49.6% - 92.2%(平均81.0%)的含水层属性变化。这些活动是地下水ncg和ncg宿主分布的主要驱动因素,分散的反硝化过程普遍存在。抗生素使用和工业活动可能与抑制氮循环有关,而农业则有积极影响。值得注意的是,我们观察到在高人为胁迫下,ncg宿主内部的互惠相互作用增强,ncg -抗生素耐药基因(ARG)、ncg -精神耐药基因(MRG)和NCG-ARG-MRG共同宿主的富集增加,表明微生物适应优化营养和能量代谢。该研究为地下水氮循环对人为干扰的响应提供了新的认识,为制定地下水管理和污染控制策略提供了有价值的信息。
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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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