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利用生物传感器的力量对水中农药进行环境监测。

Harnessing the power of biosensors for environmental monitoring of pesticides in water.

作者信息

Mendes Filipa, Machado Beatriz O, Castro Bruno B, Sousa Maria João, Chaves Susana R

机构信息

Centre of Molecular and Environmental Biology (CBMA) & Aquatic Research Network (ARNET), Department of Biology, School of Sciences of the University of Minho, 4710-057, Braga, Portugal.

Institute of Science and Innovation for Bio-Sustainability (IB-S), School of Sciences of the University of Minho, 4710-057, Braga, Portugal.

出版信息

Appl Microbiol Biotechnol. 2025 Apr 12;109(1):92. doi: 10.1007/s00253-025-13461-x.

DOI:10.1007/s00253-025-13461-x
PMID:40216649
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11991957/
Abstract

The current strong reliance on synthetic chemicals, namely pesticides, is far from environmentally sustainable. These xenobiotics contribute significantly to global change and to the current biodiversity crisis, but have been overlooked when compared to other agents (e.g., climate change). Aquatic ecosystems are particularly vulnerable to pesticides, making monitoring programs essential to preserve ecosystem health, safeguard biodiversity, ensure water quality, and mitigate potential human health risks associated with contaminated water sources. Biosensors show great potential as time/cost-effective and disposable systems for the high-throughput detection (and quantification) of these pollutants. In this mini-review, we provide an overview of biosensors specifically developed for environmental water monitoring, covering different pesticide classes (and active ingredients), and types of biosensors (according to the bio-recognition element) and transducers, as well as the nature of sample matrices analyzed. We highlight the variety of biosensors that have been developed and successfully applied to detection of pesticides in aqueous samples, including enzymatic biosensors, immunosensors, aptasensors, and whole cell-based biosensors. While most biosensors have been designed to detect insecticides, expanding their compound target range could significantly streamline monitoring of environmental contaminants. Despite limitations related to stability, reproducibility, and interference from environmental factors, biosensors represent a promising and sustainable technology for pesticide monitoring in the aquatic environments, offering sensitivity and specificity, as well as portability and real-time results. We propose that biosensors would be most effective as an initial screening step in a tiered assessment, complementing conventional methods. KEY POINTS: • Pesticides harm aquatic ecosystems and biodiversity, requiring better monitoring • Biosensors offer cost-effective solutions to detect pesticides in water samples • Biosensors complement conventional methods as a sustainable tool for initial screens.

摘要

目前对合成化学品(即农药)的严重依赖远非环境可持续的。这些外来生物对全球变化和当前的生物多样性危机有重大影响,但与其他因素(如气候变化)相比却被忽视了。水生生态系统对农药尤为脆弱,因此监测计划对于保护生态系统健康、维护生物多样性、确保水质以及减轻与受污染水源相关的潜在人类健康风险至关重要。生物传感器作为一种具有时间/成本效益且一次性使用的系统,在高通量检测(和定量)这些污染物方面具有巨大潜力。在本综述中,我们概述了专门为环境水监测开发的生物传感器,涵盖不同农药类别(及其活性成分)、生物传感器类型(根据生物识别元件)和换能器,以及所分析样品基质的性质。我们重点介绍了已开发并成功应用于检测水样中农药的各种生物传感器,包括酶生物传感器、免疫传感器、适配体传感器和基于全细胞的生物传感器。虽然大多数生物传感器旨在检测杀虫剂,但扩大其化合物目标范围可显著简化对环境污染物的监测。尽管存在与稳定性、重现性以及环境因素干扰相关的局限性,但生物传感器仍是一种用于水生环境中农药监测的有前景的可持续技术,具有灵敏度和特异性,以及便携性和实时结果。我们认为生物传感器作为分层评估中的初始筛选步骤最为有效,可补充传统方法。要点:• 农药危害水生生态系统和生物多样性,需要更好的监测 • 生物传感器为检测水样中的农药提供了具有成本效益的解决方案 • 生物传感器作为可持续的初始筛选工具可补充传统方法

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/941d00a3425b/253_2025_13461_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/3b37f2f0125b/253_2025_13461_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/20c3e580d5ca/253_2025_13461_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/2eb64ae74ed4/253_2025_13461_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/2385a99c2cbd/253_2025_13461_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/941d00a3425b/253_2025_13461_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/3b37f2f0125b/253_2025_13461_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/20c3e580d5ca/253_2025_13461_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/2eb64ae74ed4/253_2025_13461_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/2385a99c2cbd/253_2025_13461_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0e6/11991957/941d00a3425b/253_2025_13461_Fig5_HTML.jpg

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