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Findings identify native tropical fungi, particularly P. sanguineus, as promising candidates for enzyme-based wastewater treatment and environmental remediation.
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Ligninolytic macromycetes are important producers of oxidative enzymes with potential applications in the mycoremediation of synthetic dyes. However, the enzymatic potential of native tropical lignicolous fungi and the optimization of enzyme production for dye degradation remain poorly understood. This study aimed to isolate and characterize native lignicolous fungi, evaluate their ligninolytic enzyme production and dye-degrading [malachite green (MG) and phenol red (PR)] capacity, and optimize enzyme production using response surface methodology. Five fungal isolates were identified as Trametes villosa, Trametes sp., Junghuhnia sp., Pycnoporus sanguineus, and Schizophyllum commune. On PDA, T. villosa exhibited the highest mycelial growth rate (1.16 cm day−1), whereas P. sanguineus showed the highest laccase activity (18.64 U L−1). Under submerged fermentation, P. sanguineus produced the greatest H2O2 (418.9 mg L−1), laccase (398.6 U L−1), and lignin peroxidase (618.3 U L−1) activities; while Junghuhnia sp. exhibited the highest manganese peroxidase (MnP; 32.9 U L−1). Crude enzymatic extracts degraded MG and PR by 94.57% and 47.84%, respectively, within 72 hr. Box–Behnken optimization revealed that high glucose concentrations (30 g L−1) enhanced laccase production in 0.86-fold increase, whereas low yeast extract (1.25 g L−1) favored MnP synthesis in 5.10-fold increase. These findings identify native tropical fungi, particularly P. sanguineus, as promising candidates for enzyme-based wastewater treatment and environmental remediation.
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@article{ChvezRamrez2026Ligninolytic,
title = {Ligninolytic enzyme activity of macromycetes: optimization of their production and degradation of malachite green and phenol red},
author = {María Monserrat Chávez-Ramírez and Andrea Mendoza-Arceo and Wilberth Chan-Cupul},
journal = {Preparative Biochemistry & Biotechnology},
year = {2026},
doi = {10.1080/10826068.2026.2706596},
url = {https://doi.org/10.1080/10826068.2026.2706596}
}
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