[Advances in molecular networking technology for discovering emerging contaminants and transformation products].

Xiao-Mei Tan, Yu-Wei Zhang, Zhao-Yu Jiao, Nan-Yang Yu, Si Wei
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Abstract

Emerging contaminants and their transformation products are widely distributed in the environment. These pollutants carry unknown risks owing to their persistence, migration, and toxicity. The wide variety and complex structures of these substances render them difficult to identify using only target analysis. Suspect screening analysis can identify more substances than target analysis in a single run. However, this analysis method is based on limited data and cannot meet the growing demand for compound identification, especially for emerging contaminants and their transformation products with unknown information. The development of high-resolution mass spectrometry technology has promoted the applications of nontarget analysis in the environmental field, especially for identifying unknown transformation products. At present, the challenges of nontarget analysis include the difficulty of finding compounds of interest and their transformation products from complex data. Molecular networking calculates the similarity between mass spectra based on an improved cosine similarity algorithm. This method can cluster molecular families with similar structures, achieve visualization and a collection of massive mass spectral datasets, and promote the annotation of pollutants through networks and communities. Molecular networking can globally organize and systematically interpret complex tandem mass spectral datasets, providing a new direction for nontarget analysis. This technology was first used in proteomics and gradually introduced into metabolomics for the discovery of new natural products. Recently, it has been introduced into the environmental field for the study of various man-made chemicals, particularly for the discovery of emerging contaminants and their transformation products. In this paper, we introduce a molecular networking analysis method based on high-resolution tandem mass spectrometry and describe its applications in the nontargeted screening of emerging contaminants, focusing on the technical principles, workflow, application status, and future development prospects. This paper discusses the applications of molecular networking technology in the detection of emerging contaminants and their transformation products such as drugs, perfluorinated compounds, and disinfection byproducts. Molecular networking technology is widely applicable to the screening of emerging contaminants in various environmental media, revealing the full range of pollutants in the environment and promoting studies on the environmental behavior and toxicological properties of these compounds.

[发现新兴污染物和转化产物的分子网络技术进展]。
新兴污染物及其转化产物在环境中分布广泛。这些污染物由于其持久性、迁移性和毒性而具有未知的风险。这些物质种类繁多,结构复杂,仅用靶分析很难识别。可疑筛选分析在单次运行中比目标分析可以识别更多的物质。然而,这种分析方法基于有限的数据,不能满足日益增长的化合物鉴定需求,特别是对于未知信息的新兴污染物及其转化产物。高分辨率质谱技术的发展促进了非目标分析在环境领域的应用,特别是在鉴定未知转化产物方面。目前,非目标分析的挑战包括难以从复杂的数据中找到感兴趣的化合物及其转化产物。分子网络基于改进的余弦相似度算法计算质谱之间的相似度。该方法可以将结构相似的分子家族聚类,实现可视化和海量质谱数据集的收集,并通过网络和社区促进污染物的标注。分子网络可以对复杂的串联质谱数据集进行全局组织和系统解释,为非目标分析提供了新的方向。该技术最初用于蛋白质组学,并逐渐引入代谢组学,用于发现新的天然产物。最近,它已被引入环境领域,用于研究各种人造化学品,特别是用于发现新出现的污染物及其转化产物。本文介绍了一种基于高分辨率串联质谱的分子网络分析方法,并阐述了其在新兴污染物非靶向筛选中的应用,重点介绍了技术原理、工作流程、应用现状及未来发展前景。本文讨论了分子网络技术在新兴污染物及其转化产物(如药物、全氟化合物和消毒副产物)检测中的应用。分子网络技术广泛应用于各种环境介质中新兴污染物的筛选,揭示环境中污染物的全貌,促进对这些化合物的环境行为和毒理学特性的研究。
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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