ArticleAnalytical and bioanalytical chemistry2021
Feature-based molecular networking for identification of organic micropollutants including metabolites by non-target analysis applied to riverbank filtration.
Article in Analytical and bioanalytical chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Assessing the performance of weak and strong ion exchange solid-phase extraction and data mining tools to identify congeners and transformation products in municipal wastewaters by non-targeted analysis.Analytical and bioanalytical chemistry · 2026Article
- Molecular networking, conformal predictions and revised fingerprint-based models for discovering endocrine disruptors in mixtures.Analytical and bioanalytical chemistry · 2026Article
- A Functional Metabolomics Framework to Track Microbiome Drug Metabolism.bioRxiv : the preprint server for biology · 2026Article
- Molecular Networking in Cosmetic Analysis: A Review of Non-Targeted Profiling for Safety Hazards and Bioactive Compounds.Molecules (Basel, Switzerland) · 2025Review
- Uncovering the role of chemical pollutants in shaping biological invasions.Proceedings. Biological sciences · 2025Review
- Advancing the Spatiotemporal Dimension of Wildlife-Pollution Interactions.Environmental science & technology letters · 2025Review
- [Advances in molecular networking technology for discovering emerging contaminants and transformation products].Se pu = Chinese journal of chromatography · 2025Review
- Evaluation of Nontargeted Mass Spectral Data Acquisition Strategies for Water Analysis and Toxicity-Based Feature Prioritization by MS2Tox.Environmental science & technology · 2024Article
- The Impact of the Culture Regime on the Metabolome and Anti-Phytopathogenic Activity of Marine Fungal Co-Cultures.Marine drugs · 2024Article
- Predicting the Diagnostic Information of Tandem Mass Spectra of Environmentally Relevant Compounds Using Machine Learning.Analytical chemistry · 2023Article
- Evaluation of Data-Dependent MS/MS Acquisition Parameters for Non-Targeted Metabolomics and Molecular Networking of Environmental Samples: Focus on the Q Exactive Platform.Analytical chemistry · 2023Article
- Nontarget Analysis of Polluted Surface Waters in Bangladesh Using Open Science Workflows.Environmental science & technology · 2023Article
- Cholinesterase Inhibitors from an Endophytic FungusMolecules (Basel, Switzerland) · 2023Article
- Synthesis, Characterization and Application of a MIP-polyHIPE for Selective Extraction of Angiotensin II Receptor Antagonists Residues in Natural Waters.International journal of environmental research and public health · 2023Article
- Combining Feature-Based Molecular Networking and Contextual Mass Spectral Libraries to Decipher Nutrimetabolomics Profiles.Metabolites · 2022Article
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5 authors.
Funding
Abstract
Due to growing concern about organic micropollutants and their transformation products (TP) in surface and drinking water, reliable identification of unknowns is required. Here, we demonstrate how non-target liquid chromatography (LC)-high-resolution tandem mass spectrometry (MS/MS) and the feature-based molecular networking (FBMN) workflow provide insight into water samples from four riverbank filtration sites with different redox conditions. First, FBMN prioritized and connected drinking water relevant and seasonally dependent compounds based on a modification-aware MS/MS cosine similarity. Within the resulting molecular networks, forty-three compounds were annotated. Here, carbamazepine, sartans, and their respective TP were investigated exemplarily. With chromatographic information and spectral similarity, four additional TP (dealkylated valsartan, dealkylated irbesartan, two oxygenated irbesartan isomers) and olmesartan were identified and partly verified with an authentic standard. In this study, sartans and TP were investigated and grouped regarding their removal behavior under different redox conditions and seasons for the first time. Antihypertensives were grouped into compounds being well removed during riverbank filtration, those primarily removed under anoxic conditions, and rather persistent compounds. Observed seasonal variations were mainly limited to varying river water concentrations. FBMN is a powerful tool for identifying previously unknown or unexpected compounds and their TP in water samples by non-target analysis.
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