Sequential optimization and kinetic modeling of L‐asparaginase production by Pectobacteriumcarotovorum in submerged fermentation

Abstract

L-Asparaginase is a therapeutic enzyme widely used as an antitumor agent for the treatment of acute lymphoblastic leukemia and lymphosarcoma. Its potential applications as a therapeutic agent and food additive require production at high yields in a low-cost medium with high purity and stability. Statistical experimental designs were applied to identify and optimize the significant parameters for the fermentative production of L-asparaginase by Pectobacterium carotovorum Microbial Type Culture Collection (MTCC) 1428. Screening of different carbon sources identified galactose as the best carbon source for the production of L-asparaginase. Twelve medium components were selected and sixteen experiments were carried out based on the Plackett-Burman (PB) design for identifying the most significant medium components. Yeast extract, galactose, monosodium glutamate, MgSO 4 .7H 2 O and CaCl 2 .2H 2 O were found to be the most significant components that affected the production of L-asparaginase, and they were optimized by response surface methodology (RSM) using central composite design. This optimized medium showed maximum production rates of periplasmic and extracellular L-asparaginase of 3.25 and 0.83 U ml −1 , respectively. The periplasmic L-asparaginase production in the optimized medium was twofold higher than in the basal medium. Unstructured kinetic models were applied and satisfactorily described the cell growth, product formation and substrate utilization profile, thus providing a better understanding and prediction of the fermentation profile. This paper details the application of PB experimental design and RSM for the optimization of L-asparaginase production from Pe. carotovorum MTCC 1428 in submerged fermentation. 

Optimization ofL-asparaginase production from novelEnterobactersp., by submerged fermentation using response surface methodology

“…In the present investigation Enterobacter aerogenes MTCC 111 gave considerably high levels of L-asparaginase activity value using a single step statistical RSM optimization than E.coli ATCC 11303 [51] (1.03 IU/ml), Pseudomonas plecoglossicida RS1 [52] (3.65 IU/ml), Cladosporium sp. [53] (3.74 IU/ml), Pectobacterium carotovorum MTCC 1428 [54] (3.74 IU/ml) and Erwinia aroideae [55] (1.41 IU/ml). It took even 120 hr of fermentation time for some organisms to attain these low levels of enzyme activities.…”

Optimization of free fatty acids reduction in Calophyllum inophyllum (pinnai) oil using modified zirconia catalyst for biodiesel production

“…Response surface methodology (RSM) is an important tool to develop novel processes, optimizing their performance and improving their design and formulation of new products17. RSM shows promising results in industrial research, especially where large number of variables influences the system 18–20. The main goal of this study is to develop a two‐step process for the production of biodiesel from C. inophyllum oil with high FFA.…”

Optimization of mobile phase condition by using HCI program for extracting luteolin and apigenin from celery

“…However, selection of experiment conditions for each individual samples is not easy. An efficient optimization method should be employed during the method development process for these optimization problems 9, 10. Computers have been used mainly as an aid in HPLC methods to estimate performance efficiency in the separation and purification fields with increasing application of software 11–14…”