Abstract
Pyrethroid pesticides are of great environmental and health concern with regard to neurotoxicity and ubiquitous occurrence. Here, we reported a new bacterial strain identified as Bacillus cereus AKAD 3–1 that degraded 88.1% of 50 mg/l of cypermethrin in an aqueous medium. The biodegradation of cypermethrin was optimized by CCD (central composite design) and validated by ANN-GA (artificial neural network-genetic algorithm). Both the approaches proved to possess good performance in modeling and optimizing the growth conditions. Results indicated that the process variables have a significant (< 0.0001) impact on cypermethrin biodegradation. Moreover, the predicted CCD model had a “lack of fit p-value” of “0.9975.” The optimum CCD and ANN model had an R2 value of 0.9703 and 0.9907, indicating that the two models’ experimental and predicted values are closely fitted. The isolate successfully converted cypermethrin to CO2 and phenol without producing any toxic metabolite. Finally, a degradation pathway was proposed with the intermediate compounds identified by GC–MS. The present study highlights an important potential application of strain AKAD 3–1 for the in situ bioremediation of cypermethrin-contaminated environments.
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The datasets analyzed during the current study are available from the corresponding author on reasonable request.
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Funding
MM would like to acknowledge the University Ph.D. Fellowship for supporting this study. AK gratefully acknowledge DST-SERB for financial support obtained through project grant of (CRG/2021/003696), New Delhi, Govt of India.
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Muneer Ahmad Malla: Investigation, methodology, original draft preparation. Anamika Dubey: Visualization, editing. Dushyanth Reddy Vennapu: GC–MS analysis. Ashwani Kumar: Supervision, reviewing and editing. Niraj Upadhyay: Biochemical. Dileswar Pradhan: Software, validation. Rama Chandra Pradhan: ANN software. Shweta Yadav: Supervision.
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Malla, M.A., Dubey, A., Kumar, A. et al. Process optimization of cypermethrin biodegradation by regression analysis and parametric modeling along with biochemical degradation pathway. Environ Sci Pollut Res 29, 77418–77427 (2022). https://doi.org/10.1007/s11356-022-21191-0
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DOI: https://doi.org/10.1007/s11356-022-21191-0