Advancing the enzymatic removal of antibiotics with unspecific peroxygenase and vanadium chloroperoxidase
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Enzymatic processes for the remediation of wastewater containing organic pollutants are a promising alternative to advanced treatment processes that are often energy intensive and/or generate waste or by-products. For antibiotics, enzyme systems studied to date have been limited by substrate scope, pH tolerance, and stability. In this work, the remediation potential of two promiscuous H₂O₂-dependent enzymes is explored: the unspecific peroxygenase from Agrocybe aegerita (AaeUPO) and the chloroperoxidase from Curvularia inaequalis (CiVCPO), for the removal of four antibiotics commonly found in WWTP effluents and surface waters. While both enzymes showed a high removal potential for sulfamethoxazole (SMX) as a model antibiotic, CiVCPO was inactive in municipal wastewater, likely due to the presence of phosphate and nitrate. In contrast, AaeUPO remained active and stable within a suitable pH and temperature range. The transformation products showed decreased antibiotic activity against a susceptible strain of E. coli and decreased phytotoxicity, as indicated by the increased root length of Daucus carota. Peroxygenases are known to be sensitive to excess H₂O₂, and AaeUPO displays significant catalase activity at low substrate concentrations. To minimise H₂O₂-mediated inactivation, experiments were conducted at various H₂O₂ dosing rates in batch mode. Optimal conditions for the operation of a continuous enzymatic membrane reactor were then investigated, achieving over 95 % removal of SMX. This lays the groundwork for continuous operation and paves the way for efficient reactor design.
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de Boer, S., Sastre, D., Castillo, A., Balboa Méndez, S., Hollmann, F., Lores, M., Schäffer, A., & Moreira, M. T. (2025). Advancing the enzymatic removal of antibiotics with unspecific peroxygenase and vanadium chloroperoxidase. “Journal of Environmental Chemical Engineering”, vol. 13(2), 115795. https://doi.org/10.1016/j.jece.2025.115795
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https://doi.org/10.1016/j.jece.2025.115795Sponsors
This study was funded by the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 812880 and by CIES (PID2022–142334OB-I00) project granted by MCIN-AEI and the Spanish Ministry of Science and Innovation. The authors would like to thank Dr. Martin Krauss (UFZ) for his help provided during identification of transformation products.
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© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Attribution 4.0 International
Attribution 4.0 International








