Statistical optimization for enhanced production of extracellular laccase from Aspergillus sp. HB_RZ4 isolated from bark scrapping

Abstract

Laccase enzyme has gained tremendous demand in various industries, waste water treatment, bioremediation and nano-biotechnology. This compels the availability of enzyme in greater yields that can be achieved by employing potential laccase producing cultures and statistical optimization. Use of Plackett–Burman design (PBD) that evaluates various medium components and having two level factorial design help to determine the factor and its level to increase the yield of product. Present paper reports the screening of laccase producting fungus identified as Aspergillus sp. by 18S rDNA of internal transcribed spacer regions and the large subunit. Aspergillus sp. HB_RZ4 isolated from tree bark scrapping showed enhanced production of laccase in minimal medium by applying two-stage statistical approach, as PBD and Response Surface Methodology using central composite design (CCD). In the first stage of optimization, out of 8 variables of minimal medium, glucose, yeast extract, CuSO4 and temperature were found as significant components that influenced laccase production. Aspergillus sp. HB_RZ4 produced highest amount (7.27 Uml−1) of extracellular laccase. Further optimization using CCD revealed that 34 °C temperature, 2.1 gL−1 of glucose (carbon source), 2.5 gL−1 of yeast extract (nitrogen source) and 0.0025 gL−1 CuSO4 (inducer) were the optimum values that yielded maximum laccase. The optimization by PBD statistical design studies revealed optimum laccase yield with conditions being; pH, 6.0; temperature, 34 °C; incubation, 9 days; glucose, 2.1 gL−1; yeast extract, 2.5 gL−1 and CuSO4., 0.0025 gL−1.