Fermentation optimization and characterization of the laccase from Pleurotus ostreatus strain 10969 |
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Authors: | Lihua Liu Zhiwei Lin Teng Zheng Ling Lin Chuanqi Zheng Zhanxi Lin Shihua Wang Zonghua Wang |
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Affiliation: | aThe Key Laboratory of Biopesticide and Chemical Biology, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou 350002, China;bThe School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China;cInspection and Quarantine Technique Centre of Fujian Entry-exit Inspection and Quarantine Bureau, Fuzhou 350001, PR China |
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Abstract: | Laccase is a widespread group of multi-copper enzymes which can catalyze the oxidation of a variety of organic compounds, with concomitant reduction of molecular oxygen to water. It has a wide application in industrial processes, particularly in renewable bio-energy industry. In this study, Pleurotus ostreatus strain 10969 with high yield of laccase, previously isolated from edible fungus growing on Juncao, was applied for optimization of fermentation media and growth parameters for the maximal enzyme production through response surface methodology and further characterization of the laccase activity. The results show that glucose and Mg2+ are the key ingredients for laccase production with the optimum concentration of 0.0988 g/mL and 7.3 mmol/L respectively. Compared to the initial medium, the highest laccase yield observed is approximately increased by 2.5 times under the optimized conditions. Extracellular laccase was then purified and its characters were analyzed. The molecular weight of the laccase is about 40 kDa, and the optimum pH and temperature for its activity is 4.0 and 50 °C with the corresponding Km and Vmax of 0.31 mmol/L and 303.25 mmol/min respectively. DTT, β-mercaptoethanol and NaN3 nearly inhibit all activity of the laccase, as well as the metal ions especially Ag+. In summary, our results will facilitate the utilization of plant lignin in biomass energy industry. |
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Keywords: | Pleurotus ostreatus Laccase Response surface methodology |
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