Nanopore Environmental Analysis

IF 8.5 Q1 CHEMISTRY, MULTIDISCIPLINARY
Xiaofeng Lu, Xiaoyu Du, Dong Zhong, Renjie Li, Junjie Cao, Shuo Huang* and Yuqin Wang*, 
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引用次数: 0

Abstract

As global pollution continues to escalate, timely and accurate monitoring is essential for guiding pollution governance and safeguarding public health. The increasing diversity of pollutants across environmental matrices poses a significant challenge for instrumental analysis methods, which often require labor-intensive and time-consuming sample pretreatment. Nanopore technology, an emerging single-molecule technique, presents a promising solution by enabling the rapid identification of multiple targets within complex mixtures with minimal sample preparation. A wide range of pollutants have been characterized using natural biological nanopores or artificial solid-state nanopores, and their distinct advantages include simple sample preparation, high sensitivity, and rapid onsite analysis. In particular, long-read nanopore sequencing has led to dramatic improvements in the analyses of environmental microbial communities, allows species-level taxonomic assignment using amplicon sequencing, and simplifies the assembly of metagenomes. In this Perspective, we review the latest advancements in analyzing chemical and biological pollutants through nanopore sensing and sequencing techniques. We also explore the challenges that remain in this rapidly evolving field and provide an outlook on the potential for nanopore environmental analysis to transform pollution monitoring, risk assessment, and public health protection.

纳米孔环境分析
随着全球污染持续升级,及时准确的监测对指导污染治理、保障公众健康至关重要。环境基质中污染物的多样性日益增加,对仪器分析方法提出了重大挑战,这通常需要劳动密集型和耗时的样品预处理。纳米孔技术是一种新兴的单分子技术,它提供了一种很有前途的解决方案,可以在最小的样品制备中快速识别复杂混合物中的多个目标。利用天然生物纳米孔或人工固体纳米孔对多种污染物进行了表征,其独特的优点包括样品制备简单、灵敏度高、现场分析快速。特别是,长读纳米孔测序在环境微生物群落分析方面取得了巨大的进步,允许使用扩增子测序进行物种水平的分类分配,并简化了宏基因组的组装。本文综述了利用纳米孔传感和测序技术分析化学和生物污染物的最新进展。我们还探讨了在这个快速发展的领域中仍然存在的挑战,并展望了纳米孔环境分析在改变污染监测、风险评估和公共健康保护方面的潜力。
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
CiteScore
9.10
自引率
0.00%
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0
审稿时长
10 weeks
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