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Published on: December 22, 2023
Using biotransformation product profiles to rank metabolic prioritization of organic pollutants in multicomponent
Pengfei Xue1, Hao Wang1, Shipeng Dong1
1State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Chemistry and Biomedicine Innovation Center, Nanjing University, Nanjing 210023, China.
Abstract:
Assessing the metabolic prioritization of organic pollutants is crucial for environmental health evaluation. However, conventional methods relying solely on parent compound dissipation or transformation rates were difficult to capture the complexity of environmental transformation, which involved diverse transformation products (TPs), multiple metabolic pathways, and dynamic spatiotemporal distribution patterns. Here, a novel Multicomponent Pollutant Biotransformation (MPB) approach was developed, introducing a data-driven Biotransformation Index (BTI) to decode the metabolic prioritization of four distinct organic pollutants in this system. The framework was designed to integrate two key attributes, temporal product variations (BTIsingle) and pathway-dependent evolution (BTIchange), with overall extent of biotransformation quantified via time-invariant coefficients (ΔBTI/time) in multicomponent systems. A soil-microbe-earthworm (SME) system was used to evaluate the framework applicability for prothioconazole (PTC) and three PAHs: benzo[a]anthracene (BaA), benzo[a]pyrene (BaP), and dibenz[a,h]anthracene (DBA). High-resolution screening identified 34, 28, 23, and 12 biotransformation products (TPs), respectively, primarily resulting from desulfurization, hydroxylation, oxygenation, methylation, and dehydration pathways. The time-series data of these TPs were used to validate and refine the approach for the BTI. Results demonstrated that the distinct product profile patterns, characterized by BTIsingle and BTIchange, were observed. Product counts based on |ΔBTI| were well-fitted to a Gaussian distribution (0.70 < adjusted-R2 < 0.95, p < 0.05), indicating high consistency. A clear prioritization hierarchy was revealed: PTC (0.2627) > BaA (0.0560) > BaP (0.0414) > DBA (0.0010). The mechanistic linkage among pollutants was enabled through the integration of structural pathway information into quantitative metrics of metabolic level. This evaluation framework provides a reference for assessing the transport, fate, and ecological risk of organic pollutants across soil ecosystems. SYNOPSIS: A novel evaluation framework was developed to quantify metabolic level of distinct organic pollutants in multicomponent soil system, enabling predictive risk assessment and targeted remediation.
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