Analysis of the genome-scale metabolic model ofBacillus subtilisto design novel in-silico strategies for native and recombinant L-asparaginase overproduction

Abstract

L-asparaginase is an enzyme with widescale use in the food and medicine industry. It is used as a chemotherapeutic drug in the treatment of acute lymphoblastic leukemia. Limitations of side effects associated with commercially available L-asparaginase necessitate the search for alternative sources. Bacillus subtilis is an emerging host for the production of chemicals and therapeutic products. This study deals with L-asparaginase production in Bacillus subtilis using systems metabolic engineering approach. System biology offers a detailed understanding of organism metabolism at the network level unlike the conventional molecular approach of metabolic engineering allowing one to study the effects of metabolite production on growth. Metabolism of Bacillus subtilis is studied using genome-scale metabolic model iYO844 which consists of relationships between the genes and proteins present in Bacillus subtilis. Also, the model contains information about all the metabolic reactions and pathways allowing convenient metabolic engineering methods. Computational methods like flux balance analysis, flux variability analysis, robustness analysis, etc. are carried out to study the metabolic capabilities of Bacillus subtilis. The model predicted a specific growth rate of 0.6242 h-1, which was comparable to the experimental value. Further, the model is used to simulate recombinant L-asparaginase production generating a maximum production rate of 0.4028 mmol gDW-1 h-1. Flux scanning based on enforced objective flux and OptKnock design strategies are used for strain development of Bacillus subtilis for higher production of both native and recombinant L-asparaginase.