RESUMO
No biodegradation methods are absolute in the treatment of all textile dyes, which leads to structure-dependent degradation. In this study, biodegradation of three azo dyes, reactive black 5 (RB5), acid blue 113 (AB113), and acid orange 7 (AO7), was investigated using an immobilized fungus, Trametes hirsuta D7. The degraded metabolites were identified using UPLC-PDA-FTICR MS and the biodegradation pathway followed was proposed. RB5 (92%) and AB113 (97%) were effectively degraded, whereas only 30% of AO7 was degraded. Molecular docking simulations were performed to determine the reason behind the poor degradation of AO7. Weak binding affinity, deficiency in H-bonding interactions, and the absence of interactions between the azo (-NN-) group and active residues of the model laccase enzyme were responsible for the low degradation efficiency of AO7. Furthermore, cytotoxicity and genotoxicity assays confirmed that the fungus-treated dye produced non-toxic metabolites. The observations of this study will be useful for understanding and further improving enzymatic dye biodegradation.
Assuntos
Compostos Azo , Trametes , Simulação de Acoplamento Molecular , Biodegradação Ambiental , Compostos Azo/toxicidade , Compostos Azo/metabolismo , Corantes/química , Lacase/químicaRESUMO
This study assessed the applicability of artificial neural networks (ANNs) as a tool to identify compounds contributing to compositional differences in coal-contaminated soils. An artificial neural network model was constructed from laser desorption ionization ultrahigh-resolution mass spectra obtained from coal contaminated soils. A good correlation (R2 = 1.00 for model and R2 = 0.99 for test) was observed between the measured and predicted values, thus validating the constructed model. To identify chemicals contributing to the coal contents of the soils, the weight values of the constructed model were evaluated. Condensed hydrocarbon and low oxygen containing compounds were found to have larger weight values and hence they were the main contributors to the coal contents of soils. In contrast, compounds identified as lignin did not contribute to the coal contents of soils. These findings were consistent with the conventional knowledge on coal and results from the conventional partial least square method. Therefore, we concluded that the weight interpretation following ANN analysis presented herein can be used to identify compounds that contribute to the compositional differences of natural organic matter (NOM) samples.
Assuntos
Poluentes do Solo , Solo , Carvão Mineral/análise , Monitoramento Ambiental , Espectrometria de Massas , Redes Neurais de Computação , Solo/química , Poluentes do Solo/análiseRESUMO
Biodegradation and metabolic pathways of three anthraquinone dyes, Reactive Blue 4 (RB4), Remazol Brilliant Blue - R (RBBR), and Acid Blue 129 (AB129) by Trametes hirsuta D7 fungus immobilized in light expanded clay aggregate (LECA) were investigated. Morphological characteristics observed with scanning electron microscope (SEM) showed successful immobilization of the fungus in LECA. Based on UV absorbance measurement, immobilized T. hirsuta D7 effectively degraded 90%, 95%, and 96% of RB4, RBBR and AB129, respectively. Metabolites were identified with high-resolution mass spectrometry (HRMS) and degradation pathway of the dyes by T. hirsuta D7 was proposed. Toxicity assay on human dermal fibroblast (HDF) showed that anthraquinone dyes exhibits significant toxicity of 35%, 40%, and 34% reduction of cell viability by RB4, RBBR, and AB129, respectively. Fungal treatment resulted in an abatement of the toxicity and cell viability was increased up to 94%. The data clearly showed the effectiveness of immobilized T. hirsuta D7 in LECA on detoxification of anthraquinone dyes. This study provides potential and fundamental understanding of wastewater treatment using the newly isolated fungus T. hirsuta D7.