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

Water Research Pub Date : 2025-04-05 DOI:10.1016/j.watres.2025.123599

Jun Li, Lili Li, Weiqiang Liang, Lingyu Li, Ruya Wang, Zhenhua Wang, Chunxia Ma

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引用次数: 0

摘要

大多数关于外源污染物生物效应的研究都集中在整个样本或细胞群上，由于技术限制，缺乏对空间异质性的考虑。蓝藻藻华中的微囊藻毒素-LR（MC-LR）威胁着生态系统和人类健康，而饮用水中的微囊藻毒素-LR消毒副产物（MCLR-DBPs）因其毒素样结构仍令人担忧。本研究采用空间多组学方法研究斑马鱼摄入 MC-LR 和 MCLR-DBPs 所造成的干扰。该方法整合了代谢组学、空间代谢组学和空间转录组学，对MC-LR和MCLR-DBPs引起的斑马鱼整体代谢变化进行表征，然后进一步深入了解MC-LR和MCLR-DBPs靶器官代谢物和基因的空间分布变化。结果表明，MC-LR和MCLR-DBPs会诱导氧化应激和代谢失衡，破坏斑马鱼的生理平衡。空间多组学分析进一步揭示，MC-LR 和 MCLR-DBPs 通过调节 gatm、gnmt、cyp2p9 和 tdo2b 等基因的表达，加剧了能量和脂质代谢、甲基化过程和免疫途径的紊乱。总之，本研究开发了一种空间多组学方法，不仅能加深对 MC-LR 和 MCLR-DBPs 生物效应的理解，还能为调查其他环境污染物提供有力的技术支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Spatial multi-omics analysis of metabolic heterogeneity in zebrafish exposed to microcystin-LR and its disinfection byproducts

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Spatial multi-omics analysis of metabolic heterogeneity in zebrafish exposed to microcystin-LR and its disinfection byproducts

Most studies on the biological effects of exogenous pollutants have focused on whole samples or cell populations, and lack spatial heterogeneity consideration due to technical limitations. Microcystin-LR (MC-LR) from cyanobacterial blooms threatens ecosystems and human health, while microcystin-LR disinfection by-products (MCLR-DBPs) in drinking water remain a concern for their toxin-like structure. This study introduces spatial multi-omics to investigate the disruptions caused by ingestion of MC-LR and MCLR-DBPs in zebrafish. The method integrates metabolomics, spatial metabolomics, and spatial transcriptomics to characterize the overall metabolic changes in whole zebrafish caused by MC-LR and MCLR-DBPs, then provides further insight into the variation of spatial distribution of metabolites and genes in MC-LR and MCLR-DBPs targeted organ. The results showed that MC-LR and MCLR-DBPs induced oxidative stress and metabolic imbalance, and disrupted the physiological homeostasis of zebrafish. Spatial multi-omics analysis further revealed that MC-LR and MCLR-DBPs exacerbate disruptions in energy and lipid metabolism, methylation processes, and immune pathways by modulating the expression of genes such as gatm, gnmt, cyp2p9, and tdo2b. In conclusion, this study developed a spatial multi-omics approach that not only enhances the understanding of the biological effects of MC-LR and MCLR-DBPs but also provides robust technical support for investigating other environmental pollutants.

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来源期刊

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.