Randomized trial elucidates microbial pathways for dechlorination of PCBs, suggesting new bioremediation strategies.
Key Points
This research aims to understand how microbial communities dechlorinate polychlorinated biphenyls (PCBs) through advanced models and quantum chemistry.
Integrated high-throughput enzymatic assays and quantum chemical calculations.
Utilized machine learning models, specifically XGBoost, to evaluate dechlorination reactivity of all 209 PCB congeners.
Analyzed Hirshfeld charge and steric effects across diverse <i>Dehalococcoides</i> isolates.
Achieved 98.3% accuracy in predicting dechlorination pathways for PCBs.
Identified that steric effect-corrected Hirshfeld charge and PCB solubility mainly regulate microbial dechlorination potential.
Predicted that 11 out of 12 dioxin-like PCB congeners are amenable to microbial degradation under anaerobic conditions.