Production of thermostable T1 lipase using agro-industrial waste medium formulation

• Main Authors: Mohd Nooh, Hisham, Masomian, Malihe, Salleh, Abu Bakar, Mohamad, Rosfarizan, Mohamad Ali, Mohd Shukuri, Raja Abdul Rahman, Raja Noor Zaliha
• Format: Article
• Language: English
• Published: MDPI 2018
• Online Access: http://psasir.upm.edu.my/id/eprint/73650/1/Production%20of%20thermostable%20T1%20lipase%20using%20agro-industrial%20waste%20medium%20formulation.pdf; http://psasir.upm.edu.my/id/eprint/73650/; https://www.mdpi.com/2073-4344/8/11/485

Large-scale production of T1 lipase using conventional culture media is costly. To reduce the cost of production, an alternative growth medium using local resources has been developed. In this study, the growth of recombinant Escherichia coli and expression of T1 lipase were tested using different agroindustrial wastes as carbon and nitrogen sources by conventional method. Subsequently, by using central composite rotatable design (CCRD), a set of 30 experiments was generated to evaluate the effect of different parameters, including the amount of molasses (as carbon source), fish waste (as nitrogen source), NaCl, and inducer concentration on production of T1 lipase. Response surface methodology (RSM) analysis indicated that all factors had significant effects on T1 lipase production. This statistical analysis was utilised to develop a quadratic model to correlate various important variables for the growth of the recombinant strain and regulation of gene expression to the response (T1 lipase activity). Optimum conditions for T1 lipase production were observed to be 1.0 g/L of molasses, 2.29 g/L of fish waste, 3.46 g/L of NaCl, and 0.03 mM of IPTG (Isopropyl β-d-1-thiogalactopyranoside). Based on these conditions, the actual lipase activity was found to be 164.37 U/mL, which fitted well with the maximum predicted value of 172.89 U/mL. Therefore, the results demonstrated that, the statistical analysis, performed using RSM, was efficient in optimising T1 lipase production. Moreover, the optimum conditions obtained can be applied to scale up the process and minimise the cost of enzyme production.