Response Surface Methodology for Optimization of Production of Mevastatin by Solid State Fermentation Using Sesame Oil Cake

نویسندگان

  • N. HARSHA
  • CHANDANA LAKSHMI
  • V. SRIDEVI
چکیده

Mevastatin, also known as compactin or ML-236B is a member of the class of statins belonging to the polyketide group. Polyketides are rich sources of pharmaceuticals, including antibiotics, anticancer drugs, and cholesterol-lowering drugs, immunosuppressants and other therapeutics [1]. This study was performed for the production of mevastatin using sesame oil cake as substrate with Pencillium citrinum MTCC 1256 by Solid State FermentationThe present study was carriemevastatin by solid state fermentation with Pencillium citrinum MTCC 1256 using sesame oil cake. Different agro residues as substrates and different organisms were screened and various physico-chemical parameters were optimized. In this paper we explained in detail on the four significant factors i.e, fermentation time (X1, days), temperature (X2, C), pH (X3), nitrogen source (X4,%w/v), which significantly influence the production of mevastatin were selected by using Plackett-Burman statistical design. These variables were further optimized using a 2 full factorial CCD (Central Composite Design) and a second order polynomial model equation was obtained. In the present study the value of the regression coefficient R = 0.9938 which indicates that 99.38% of the variability in the response could be explained by the model. The adjusted R value is 0.9859 which is also very high to advocate the significance of the model. KEWORDS:Mevastatin, Pencillium citrinum MTCC 1256, Fermentation time, Temperature, pH, Nitrogen source, Carbon source. *Corresponding author V. SRIDEVI Associate professor, Centre for Biotechnology, Department of Chemical Engineering, Andhra University, Visakhapatnam-03, Andhra Pradesh, India Int J Pharm Bio Sci 2013 July; 4(3): (P) 392 401 This article can be downloaded from www.ijpbs.net P 393 INTRODUCTION Mevastatin, also known as compactin or ML236B is a member of the class of statins belonging to the polyketide group. Polyketides are rich sources of pharmaceuticals, including antibiotics, anticancer drugs, and cholesterollowering drugs, immune suppressants and other therapeutics [1] One of the major causes of death in developed countries is coronary heart disease. Approximately 10.8% of all deaths are caused due to this disease. Coronary heart disease actually is a wide assortment of diseases. The basic manifestation of many of them is atherosclerosis, caused when fatty deposit called plaque buildup on the inner walls of arteries. Cholesterol is a major component of the atherosclerotic plaque. Many scientists believe that a high level of cholesterol in the blood is a major contributor to the development of atherosclerosis. In humans, the greater part of the cholesterol in the body is synthesized, mostly in the liver, the search for drugs to inhibit cholesterol biosynthesis has long been pursued as a means to lower the level of plasma cholesterol and so it helps to prevent and treat atherosclerosis. Mevastatin is a specific and potent inhibitor of cholesterol biosynthesis, and also acts as an antifungal agent. Mevastatin competitively inhibits the regulatory enzyme, 3-hydroxy-3-methylglutarylcoenzymeA-reductase. Mevastatin is also a precursor of pravastatin, which is also an antihypercholesterolemic agent. Among the few commercially used microbial strains for the production of mevastatin are Penicillium citrinum, P. cyclopium and Aspergillus terreus. [3, 4, and The application of statistical experimental design techniques in fermentation process development can result in improvement of product yield, reduce process variability, give closer confirmation of the output response to nominal and reduce overall costs. Conventional practice of single factor reduce optimization by maintaining other factors involved at an unspecified constant level does not depict the combined effect of all the factors involved. This method is also time consuming and requires a number of experiments to determine optimum levels, which are unreliable. These limitations can be eliminated by optimizing all the affecting parameters collectively by RSM. RSM can be used to evaluate the relative significance of several factors even in the presence of complex interactions Statistical approach for the optimization of the media effectively tackles the problem, which involves the specific design of the experiment that effectively decreases the error in determining the effect of variables. In this paper we used the Planket Burman design to find the significant variables that influence the production of mevastatin and these variables were further optimized using an RSM, incorporating a 2 full factorial CCD. MATERIALS AND METHODS MATERIALS Microorganisms Penicillium citrinum MTCC 1256, Procured from MTCC, Institute of Microbial Technology, Chandigarh, India. Maintenance of culture The culture was maintained on potato dextrose agar (PDA) at 4C and the subculture was done for every three weeks in the laboratory. Fresh slants were prepared for running experiments. Substrate Agro industrial residues such as wheat bran, green gram husk, sesame oil cake, and coconut oil cake were brought from local market in Visakhapatnam, A.P, and grounded well and sieved to remove unwanted materials.Locally available wheat bran, green gram husk, sesame oil cake, coconut oil cake were grounded well and sieved to remove unwanted materials. Initially, all the substrates were screened to determine the potentiality of the above substrates for mevastatin production using SSF method. Int J Pharm Bio Sci 2013 July; 4(3): (P) 392 401 This article can be downloaded from www.ijpbs.net P 394 METHODS Inoculum preparation Cultures of Penicillium citrinum and Penicillium brevicompactum was grown on potato dextrose agar (PDA) slants at 30C and 25C for 5 and 7 days respectively and maintained at 4C. Distilled water was added to each slant and the spores were scrapped by using an inoculation loop. Fermentation procedure for mevastatin production Five grams of substrate in total was taken and supplement solution was added to it with initial moisture content being 60% (v/w). The pH of the supplement solution was maintained at 6 using 2N H3PO4. All media components were sterilized at 121C for 15 min and inoculated with 3ml of seed culture. The fermentation was carried out at 26C for 7 days Extraction At the end of SSF, fermented solid culture was adjusted to pH 6.5 with either diluted acid (aq.H3PO4) or alkali (aq.NaOH) and then 25 ml absolute ethyl alcohol was added to it for extraction by keeping in an orbital shaking incubator at 180 rpm for 1h.The residue was filtered with filter paper and then centrifuged at 6000 rpm for 15 min. Then the supernatant was collected and analyzed for quantitative determination of mevastatin. EXPERIMENTAL DEISGNS The Plackett-Burman experimental design (PBD, 7/8 runs) Out of the variables studied, the variables which influenced the fermentation significantly were studied by PBD. PBD is a two level factorial design which allows the investigation of ‘n-1’ variables with at least ‘n’ experiments. The main effect was calculated as the difference between the average of measurements made at the high setting (+1) and the average of measurements observed at low setting (−1) of each factor .This model describes no interaction among factors and it is used to screen and evaluate the important factors that influence production of mevastatin. The factors that have a confidence level above 95% are considered the most significant factors that affect the mevastatin production. The main effect of the fermentation components, regression coefficient, F values and P values of the factors were investigated. The design matrix generated by 7/8 runs of PBD of was shown in Table 1. Table 1 The design matrix for PBD. Runs A B C D E F G Final response

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تاریخ انتشار 2013