The biodegradation of benzo[a]pyrene (BaP) by using Polyporus sp. S133, a white-rot fungus isolated from oil-contaminated soil was investigated. Approximately 73% of the initial concentration of BaP was degraded within 30 d of incubation. The isolation and characterization of 3 metabolites by thin layer chromatography, column chromatography, and UV-vis spectrophotometry in combination with gas chromatography-mass spectrometry, indicated that Polyporus sp. S133 transformed BaP to BaP-1,6-quinone. This quinone was further degraded in 2 ways. First, BaP-1,6-quinone was decarboxylated and oxidized to form coumarin, which was then hydroxylated to hydroxycoumarin, and finally to hydroxyphenyl acetic acid by addition of an epoxide group. Second, Polyporus sp. S133 converted BaP-1,6-quinone into a major product, 1-hydroxy-2-naphthoic acid. During degradation, free extracellular laccase was detected with reduced activity of lignin peroxidase, manganese-dependent peroxidase and 2,3-dioxygenase, suggesting that laccase and 1,2-dioxygenase might play an important role in the transformation of PAHs compounds.
Armillaria sp. F022, a white-rot fungus isolated from a tropical rain forest in Samarinda, Indonesia, was used to biodegrade benzo[a]pyrene (BaP). Transformation of BaP, a 5-ring polycyclic aromatic hydrocarbon (PAH), by Armillaria sp. F022, which uses BaP as a source of carbon and energy, was investigated. However, biodegradation of BaP has been limited because of its bioavailability and toxicity. Five cosubstrates were selected as cometabolic carbon and energy sources. The results showed that Armillaria sp. F022 used BaP with and without cosubstrates. A 2.5-fold increase in degradation efficiency was achieved after addition of glucose. Meanwhile, the use of glucose as a cosubstrate could significantly stimulate laccase production compared with other cosubstrates and not using any cosubstrate. The metabolic pathway was elucidated by identifying metabolites, conducting biotransformation studies, and monitoring enzyme activities in cell-free extracts. The degradation mechanism was determined through the identification of several metabolites: benzo[a]pyrene-1,6-quinone, 1-hydroxy-2-benzoic acid, and benzoic acid.
Benzo[a]pyrene is a high-molecular-weight polycyclic aromatic hydrocarbon highly recalcitrant in nature and thus harms the ecosystem and/or human health. Therefore, its removal from the marine environment is crucial. This research focuses on benzo[a]pyrene degradation by using enriched bacterial isolates in consortium under saline conditions. Bacterial isolates capable of using benzo[a]pyrene as sole source of carbon and energy were isolated from enriched mangrove sediment. These isolates were identified as Ochrobactrum anthropi, Stenotrophomonas acidaminiphila, and Aeromonas salmonicida ss salmonicida. Isolated O. anthropi and S. acidaminiphila degraded 26% and 20%, respectively, of an initial benzo[a]pyrene concentration of 20 mg/L after 8 days of incubation in seawater (28 ppm of NaCl). Meanwhile, the bacterial consortium decomposed 41% of an initial 50 mg/L benzo[a]pyrene concentration after 8 days of incubation in seawater (28 ppm of NaCl). The degradation efficiency of benzo[a]pyrene increased to 54%, when phenanthrene was supplemented as a co-metabolic substrate. The order of biodegradation rate by temperature was 30°C > 25°C > 35°C. Our results suggest that co-metabolism by the consortium could be a promising biodegradation strategy for benzo[a]pyrene in seawater.
This study examined the potential of artificial neural network (ANN) modeling to infer timing, route and dose of contaminant exposure from biomarkers in a freshwater fish. Hepatic glutathione S-transferase (GST) activity and biliary concentrations of BaP, 1-OH BaP, 3-OH BaP and 7,8D BaP were quantified in juvenile Clarias gariepinus injected intramuscularly or intraperitoneally with 10-50 mg/kg benzo[a]pyrene (BaP) 1-3 d earlier. A feedforward multilayer perceptron (MLP) ANN resulted in more accurate prediction of timing, route and exposure dose than a linear neural network or a radial basis function (RBF) ANN. MLP sensitivity analyses revealed contribution of all five biomarkers to predicting route of exposure but no contribution of hepatic GST activity or one of the two hydroxylated BaP metabolites to predicting time of exposure and dose of exposure. We conclude that information content of biomarkers collected from fish can be extended by judicious use of ANNs.