References
[1] Ahn, C., & Jeung, E.-B. (2023). Endocrine-Disrupting Chemicals and Disease Endpoints. International Journal of Molecular Sciences, 24(6), 5342. https://doi.org/10.3390/ijms24065342
[2] Yilmaz, B., Terekeci, H., Sandal, S., & Kelestimur, F. (2020). Endocrine disrupting chemicals: Exposure, effects on human health, mechanism of action, models for testing and strategies for prevention. Reviews in Endocrine and Metabolic Disorders, 21(1), 127–147. https://doi.org/10.1007/s11154-019-09521-z
[3] Aris, A. Z., Shamsuddin, A. S., & Praveena, S. M. (2014). Occurrence of 17α-ethynylestradiol (EE2) in the environment and effect on exposed biota: A review. Environment International, 69, 104–119. https://doi.org/10.1016/j.envint.2014.04.011
[4] Klaic, M., & Jirsa, F. (2022). 17α-Ethinylestradiol (EE2): Concentrations in the environment and methods for wastewater treatment – an update. RSC Advances, 12(20), 12794–12805. https://doi.org/10.1039/d2ra00915c
[5] Lippert, C., Seeger, H., Wallwiener, D., & Mueck, A. O. (2002). Comparison of the effects of 17alpha-ethinylestradiol and 17beta-estradiol on the proliferation of human breast cancer cells and human umbilical vein endothelial cells. Clinical and Experimental Obstetrics & Gynecology, 29(2), 87–90.
[6] Gárriz, Á., del Fresno, P. S., & Miranda, L. A. (2017). Exposure to E2 and EE2 environmental concentrations affect different components of the Brain-Pituitary-Gonadal axis in pejerrey fish (Odontesthes bonariensis). Ecotoxicology and Environmental Safety, 144, 45–53. https://doi.org/10.1016/j.ecoenv.2017.06.002
[7] Parrott, J. L., & Blunt, B. R. (2005). Life-cycle exposure of fathead minnows (Pimephales promelas) to an ethinylestradiol concentration below 1 ng/L reduces egg fertilization success and demasculinizes males. Environmental Toxicology, 20(2), 131–141. https://doi.org/10.1002/tox.20087
[8] Servicios de Agua y Drenaje de Monterrey (2023) Acta 547. Retrieved from: https://pfiles.sadm.gob.mx/Pfiles/Uploads/Documentos/3026.pdf
[9] López-Velázquez, K., Guzmán-Mar, J. L., Saldarriaga-Noreña, H. A., Murillo-Tovar, M. A., Hinojosa-Reyes, L., & Villanueva-Rodríguez, M. (2021). Occurrence and seasonal distribution of five selected endocrine-disrupting compounds in wastewater treatment plants of the Metropolitan Area of Monterrey, Mexico: The role of water quality parameters. Environmental Pollution, 269, 116223. https://doi.org/10.1016/j.envpol.2020.116223
[10] European Commission, 2012. Proposal for a DIRECTIVE of the EUROPEAN PARLIAMENT and of the COUNCIL Amending Directives 2000/60/EC and 2008/105/EC as Regards Priority Substances in the Field of Water Policy. Brussels. https://ec.europa.eu/smart-regulation/impact/ia_carried_out/docs/ia_2012/com_2011_0876_en.pdf
[11] Jobling, S., & Owen, R. (2013). Ethinyl oestradiol in the aquatic environment. In European Environment Agency, Late lessons from early warnings: Science, precaution, innovation. Publications Office of the European Union. https://data.europa.eu/doi/10.2800/70282
[12] Silva, A., Delerue-Matos, C., Figueiredo, S. A., & Freitas, O. M. (2019). The use of algae and fungi for removal of pharmaceuticals by bioremediation and biosorption processes: A review. In Water (Switzerland) (Vol. 11, Issue 8). MDPI AG. https://doi.org/10.3390/w11081555
[13] Hassanien, A., Saadaoui, I., Schipper, K., Al-Marri, S., Dalgamouni, T., Aouida, M., Saeed, S., & Al-Jabri, H. M. (2023). Genetic engineering to enhance microalgal-based produced water treatment with emphasis on CRISPR/Cas9: A review. In Frontiers in Bioengineering and Biotechnology (Vol. 10). Frontiers Media S.A. https://doi.org/10.3389/fbioe.2022.1104914
[14] Mayer, A. M., & Staples, R. C. (2002). Laccase: new functions for an old enzyme. Phytochemistry, 60(6), 551–565. https://doi.org/10.1016/s0031-9422(02)00171-1
[15] Garcia-Morales, R., Rodríguez-Delgado, M., Gomez-Mariscal, K., Orona-Navar, C., Hernandez-Luna, C., Torres, E., Parra, R., Cárdenas-Chávez, D., Mahlknecht, J., & Ornelas-Soto, N. (2015). Biotransformation of Endocrine-Disrupting Compounds in Groundwater: Bisphenol A, Nonylphenol, Ethynylestradiol and Triclosan by a Laccase Cocktail from Pycnoporus sanguineus CS43. Water Air & Soil Pollution, 226(8). https://doi.org/10.1007/s11270-015-2514-3
[16] Sun, K., Hong, D., Liu, J., Latif, A., Li, S., Chu, G., Qin, W., & Si, Y. (2021). Trametes versicolor laccase-assisted oxidative coupling of estrogens: Conversion kinetics, linking mechanisms, and practical applications in water purification. Science of the Total Environment, 782, 146917. https://doi.org/10.1016/j.scitotenv.2021.146917
[17] Sun, K., Chen, H., Zhang, Q., Li, S., Liu, Q., & Si, Y. (2020). Influence of humic acids on fungal laccase-initiated 17α-ethynylestradiol oligomerization: Transformation kinetics and products distribution. Chemosphere, 258, 127371. https://doi.org/10.1016/j.chemosphere.2020.127371
[18] Madzak, C., Mimmi, M., Caminade, E., Brault, A., Baumberger, S., Briozzo, P., Mougin, C., & Jolivalt, C. (2005). Shifting the optimal pH of activity for a laccase from the fungus Trametes versicolor by structure-based mutagenesis. Protein Engineering Design and Selection, 19(2), 77–84. https://doi.org/10.1093/protein/gzj004
[19] Safi, C., Zebib, B., Merah, O., Pontalier, P.-Y., & Vaca-Garcia, C. (2014). Morphology, composition, production, processing and applications of Chlorella vulgaris: A review. Renewable and Sustainable Energy Reviews, 35, 265–278. https://doi.org/10.1016/j.rser.2014.04.007
[20] De Grahl, I., Rout, S. S., Maple-Grødem, J., & Reumann, S. (2020). Development of a constitutive and an auto-inducible high-yield expression system for recombinant protein production in the microalga Nannochloropsis oceanica. Applied Microbiology and Biotechnology, 104(20), 8747–8760. https://doi.org/10.1007/s00253-020-10789-4
[21] Ibero, J., Galán, B., & García, J. L. (2021). Identification of the EdcR Estrogen-Dependent Repressor in Caenibius tardaugens NBRC 16725: Construction of a Cellular Estradiol Biosensor. Genes, 12(12), 1846. https://doi.org/10.3390/genes12121846
[22] Dimas, R. P., Jordan, B. R., Jiang, X. L., Martini, C., Glavy, J. S., Patterson, D. P., Morcos, F., & Chan, C. T. Y. (2019). Engineering DNA recognition and allosteric response properties of TetR family proteins by using a module-swapping strategy. Nucleic Acids Research, 47(16), 8913–8925. https://doi.org/10.1093/nar/gkz666
[23] Ramos, J. L., Martínez-Bueno, M., Molina-Henares, A. J., Terán, W., Watanabe, K., Zhang, X., Gallegos, M. T., Brennan, R., & Tobes, R. (2005). The TetR Family of Transcriptional Repressors. Microbiology and Molecular Biology Reviews, 69(2), 326–356. https://doi.org/10.1128/MMBR.69.2.326-356.2005/FORMAT/EPUB
[24] Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., Bridgland, A., Meyer, C., Kohl, S. A. A., Ballard, A. J., Cowie, A., Romera-Paredes, B., Nikolov, S., Jain, R., Adler, J., ... & Hassabis, D. (2021). Highly accurate protein structure prediction with AlphaFold. Nature, 596(7873), 583-589.
[25] Trott, O., & Olson, A. J. (2010). AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455-461.
[26] Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera—a visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605-1612
[27] Leaver-Fay, A., Tyka, M., Lewis, S. M., Lange, O. F., Thompson, J., Jacak, R., Kaufman, K. W., Renfrew, P. D., Smith, C. A., Sheffler, W., Davis, I. W., Cooper, S., Treuille, A., Mandell, D. J., Richter, F., Ban, Y. E., Fleishman, S. J., Corn, J. E., Kim, D. E., ... & Kuhlman, B. (2011). Rosetta3: an object-oriented software suite for the simulation and design of macromolecules. Methods in Enzymology, 487, 545-574.
[28] Dassault Systèmes BIOVIA. (2021). BIOVIA Discovery Studio (Version 21.1) [Software]. San Diego: Dassault Systèmes. Available from https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-discovery-studio/
[29] Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindahl, E. (2015). GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1-2, 19-25.