Exposome-Scale Investigation of Cl-/Br-Containing Chemicals Using High-Resolution Mass Spectrometry, Multistage Machine Learning, and Cloud Computing

Over 70% of organic halogens, representing chlorine- and bromine-containing disinfection byproducts (Cl-/Br-DBPs), remain unidentified after 50 years of research. This work introduces a streamlined and cloud-based exposomics workflow that integrates high-resolution mass spectrometry (HRMS) analysis, multistage machine learning, and cloud computing for efficient analysis and characterization of Cl-/Br-DBPs. In particular, the multistage machine learning structure employs progressively different heavy isotopic peaks at each layer and capture the distinct isotopic characteristics of nonhalogenated compounds and Cl-/Br-compounds at different halogenation levels. This innovative approach enables the recognition of 22 types of Cl-/Br-compounds with up to 6 Br and 8 Cl atoms. To address the data imbalance among different classes, particularly the limited number of heavily chlorinated and brominated compounds, data perturbation is performed to generate hypothetical/synthetic molecular formulas containing multiple Cl and Br atoms, facilitating data augmentation. To further benefit the environmental chemistry community with limited computational experience and hardware access, above innovations are incorporated into HalogenFinder (http://www.halogenfinder.com/), a user-friendly, web-based platform for Cl-/Br-compound characterization, with statistical analysis support via MetaboAnalyst. In the benchmarking, HalogenFinder outperformed two established tools, achieving a higher recognition rate for 277 authentic Cl-/Br-compounds and uniquely identifying the number of Cl/Br atoms. In laboratory tests of DBP mixtures, it identified 72 Cl-/Br-DBPs with proposed structures, of which eight were confirmed with chemical standards. A retrospective analysis of 2022 finished water HRMS data revealed insightful temporal trends in Cl-DBP features. These results demonstrate HalogenFinder's effectiveness in advancing Cl-/Br-compound identification for environmental science and exposomics.

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Publication Details

Journal
Analytical Chemistry
Published
2025-05-22
DOI
https://doi.org/10.1021/acs.analchem.5c00503
Citations
6
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
4.04

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article

Exposome-Scale Investigation of Cl-/Br-Containing Chemicals Using High-Resolution Mass Spectrometry, Multistage Machine Learning, and Cloud Computing

Qiming Shen, Y. Wang, Tao Huan, Tingting Zhao et al.
6 citations
Analytical Chemistry
Advanced Chemical Sensor Technologies
4.04
article

Exposome-Scale Investigation of Cl-/Br-Containing Chemicals Using High-Resolution Mass Spectrometry, Multistage Machine Learning, and Cloud Computing

Qiming Shen, Y. Wang, Tao Huan, Tingting Zhao, Brian Low, Zhiqiang Pang, Jianguo Xia, K. N. Minh Chau, Xiaoxiao Li, David Hidalgo Delgado
article en
6 citations

Abstract

Over 70% of organic halogens, representing chlorine- and bromine-containing disinfection byproducts (Cl-/Br-DBPs), remain unidentified after 50 years of research. This work introduces a streamlined and cloud-based exposomics workflow that integrates high-resolution mass spectrometry (HRMS) analysis, multistage machine learning, and cloud computing for efficient analysis and characterization of Cl-/Br-DBPs. In particular, the multistage machine learning structure employs progressively different heavy isotopic peaks at each layer and capture the distinct isotopic characteristics of nonhalogenated compounds and Cl-/Br-compounds at different halogenation levels. This innovative approach enables the recognition of 22 types of Cl-/Br-compounds with up to 6 Br and 8 Cl atoms. To address the data imbalance among different classes, particularly the limited number of heavily chlorinated and brominated compounds, data perturbation is performed to generate hypothetical/synthetic molecular formulas containing multiple Cl and Br atoms, facilitating data augmentation. To further benefit the environmental chemistry community with limited computational experience and hardware access, above innovations are incorporated into HalogenFinder (http://www.halogenfinder.com/), a user-friendly, web-based platform for Cl-/Br-compound characterization, with statistical analysis support via MetaboAnalyst. In the benchmarking, HalogenFinder outperformed two established tools, achieving a higher recognition rate for 277 authentic Cl-/Br-compounds and uniquely identifying the number of Cl/Br atoms. In laboratory tests of DBP mixtures, it identified 72 Cl-/Br-DBPs with proposed structures, of which eight were confirmed with chemical standards. A retrospective analysis of 2022 finished water HRMS data revealed insightful temporal trends in Cl-DBP features. These results demonstrate HalogenFinder's effectiveness in advancing Cl-/Br-compound identification for environmental science and exposomics.

Analytical ChemistryVol. 97(21)
University of British Columbia (CA), University of Alberta (CA), Institute of Parasitology (CZ), McGill University (CA)
Genome Canada, Canada Foundation for Innovation, Michael Smith Health Research BC, Genome British Columbia, Canada Research Chairs, Alberta Innovates, Natural Sciences and Engineering Research Council of Canada
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Advanced Chemical Sensor Technologies
4.04
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