COMPARATIVE FLUX BALANCE ANALYSES OF SERINE ALKALINE PROTEASE OVERPRODUCTION IN Bacillus subtilis AT GENOME AND SMALL SCALE

Yıl 2023, Cilt 12, Sayı 1, 8 - 18, 30.01.2023

Pınar KOCABAŞ

https://doi.org/10.18036/estubtdc.1184733

Öz

This work aims to conduct flux balance analysis of serine alkaline protease overproduction in Bacillus subtilis using enzyme-constrained genome scale model and to compare the results with fluxes obtained from a smaller, bioreaction-based model. Fluxes of the enzyme constraint genome scale model were calculated using CobraToolbox v3.0 and compared with those of bioreaction-based model for the specific growth rate of zero. The active reaction number first increased and then remained constant with specific growth rate for enzyme constrained genome scale model. The SAP synthesis flux increased with a decrease in specific growth rate for both models. The TCA cycle was active for both models, but with lower fluxes for enzyme-constrained genome scale model. Anaplerotic reactions were active only for bioreaction-based model. Glycolysis pathway fluxes were active for enzyme-constrained genome scale model, meanwhile gluconeogenesis pathway fluxes were active for bioreaction-based model. Oxidative pentose phosphate pathway was inactive for both models and generally higher pentose phosphate pathway fluxes were obtained using bioreaction-based model. The fluxes toward amino acid synthesis pathways and serine alkaline protease synthesis were higher with bioreaction-based model. Since TCA cycle fluxes were lower with enzyme constrained genome scale model, ATP synthesis was lower with enzyme constrained genome scale model compared to bioreaction-based model. For both models, active pathways were the same for TCA cycle, pentose phosphate pathway, amino acid synthesis pathways except glycolysis pathway. The results showed that bioreaction-based model gave more sound results compared to enzyme constrained genome scale model since gluconeogenesis should be active with the carbon source of citrate.

Anahtar Kelimeler

Enzyme constrained genome scale metabolic model, Metabolic flux analysis, Bioreaction-based model

COMPARATIVE FLUX BALANCE ANALYSES OF SERINE ALKALINE PROTEASE OVERPRODUCTION IN Bacillus subtilis AT GENOME AND SMALL SCALE

Öz

The aim of this work is to conduct flux balance analysis of serine alkaline protease overproduction in Bacillus subtilis using enzyme-constrained genome scale model and to compare the results with fluxes obtained by a smaller, bioreaction based model. Fluxes of the enzyme constraint genome scale model were calculated using CobraToolbox v3.0 and compared with those of bioreaction based model for the specific growth rate of zero. Active reaction number first increased and then remained constant with specific growth rate for enzyme constrained genome scale model. SAP synthesis flux increased with the decrease in specific growth rate for both models. TCA cycle was active for both models, but with lower fluxes for enzyme-constrained genome scale model. Anaplerotic reactions were active only for bioreaction based model. Glycolysis pathway fluxes were active for enzyme-constrained genome scale model, meanwhile gluconeogenesis pathway fluxes were active for bioreaction based model. Oxidative pentose phosphate pathway was inactive for both models and generally higher pentose phosphate pathway fluxes were obtained with bioreaction based model. The fluxes towards amino acid synthesis pathways and serine alkaline protease synthesis were higher with bioreaction based model. Since TCA cycle fluxes were lower with enzyme constrained genome scale model, ATP synthesis was lower with enzyme constrained genome scale model compared to bioreaction based model. For both models, active pathways were the same for TCA cycle, pentose phosphate pathway, amino acid synthesis pathways except glycolysis pathway. The results showed that bioreaction based model gave more sound results compared to enzyme constrained genome scale model since gluconeogenesis should be active with the carbon source of citrate.

Anahtar Kelimeler

Enzyme constrained genome scale metabolic model, Metabolic flux analysis, Bioreaction-based model

Kaynakça

• [1] Çalık P, Takaç S, Çalık G, Özdamar TH. Serine alkaline protease overproduction capacity of Bacillus licheniformis. Enzyme Microb Tech 2000; 26: 45–60
• [2] Massaiu I, Pasotti L, Sonnenschein N, Rama E, Cavaletti M, Magni P, Calvio C, Herrgård MJ. Integration of enzymatic data in Bacillus subtilis genome scale metabolic model improves phenotype predictions and enables in silico design of poly γ glutamic acid production strains. Microb Cell Fact 2019;18:3
• [3] Oh YK, Palsson BO, Park SM, Schilling CH, Mahadevan R. Genome-scale reconstruction of metabolic network in Bacillus subtilis based on high-throughput phenotyping and gene essentiality data. J Biol Chem 2007; 282: 28791-28799
• [4] Wang H, Robinson JL, Kocabaş P, Gustafsson J, Anton M, Cholley PE, Huang S, Gobom J, Svensson T, Uhlen M et al. Genome-scale reconstruction of metabolic networks of model animals represents a platform for translational research. PNAS 2021; 118: 1-9
• [5] Çalık P, Özdamar TH. Carbon sources affect metabolic capacities of Bacillus species for the production of industrial enzymes: theoretical analyses for serine and neutral proteases and -amylase. Biochem Eng J 2001; 8: 61-81
• [6] Çalık P, Özdamar TH. Bioreaction Network Flux Analysis For Industrial Microorganisms: A Review. Reviews in Chemical Engineering 2002; 18: 553-596
• [7] Kunst F, Ogasawara N, Moszer I, Albertini AM, Alloni G, Azevedo V, Bertero MG, Bessieres P, Bolotin A, Borchert S et al. The complete genome sequence of the gram positive bacterium Bacillus subtilis. Nature 1997; 390: 249-256
• [8] Barbe V, Cruveiller S, Kunst F, Lenoble P, Meurice G, Sekowska A, Vallenet D, Wang T, Moszer I, Medigue C et al. From a consortium sequence to a unified sequence: the Bacillus subtilis 168 reference genome a decade later. Microbiol 2009; 155: 1758-1775
• [9] Belda E, Sekowska A, Le Fevre F, Morgat A, Mornico D, Ouzounis C, Vallenet D, Medigue C, Danchin A et al. An updated metabolic view of the Bacillus subtilis 168 genome. Microbiol 2013; 159: 757-770
• [10] Borriss R, Danchin A, Harwood CR, Medigue C, Rocha EPC, Sekowska A, Vallenet D. Bacillus subtilis, the model Gram-positive bacterium: 20 years of annotation refinement. Microb Biotechnol 2018; 11: 3-17
• [11] Geissler AS, Anthon C, Alkan F, González-Tortuero E, Poulsen LD, Kallehauge TB, Breüner A, Seemann SE, Vinther J, Gorodkin J. BSGatlas: a unified Bacillus subtilis genome and transcriptome annotation atlas with enhanced information access. Microb Genom 2021; 7:000524
• [12] Kocabaş P, Çalık P, Çalık G, Özdamar TH. Analyses of extracellular protein production in Bacillus subtilis-I: Genome-scale metabolic model reconstruction based on updated gene-enzyme-reaction data. Biochemical Engineering Journal 2017; 127: 229-241
• [13] Goelzer A, Brikci FB, Martin-Verstraete I, Noirot P, Bessières P, Aymerich S, Fromion V. Reconstruction and analysis of the genetic and metabolic regulatory networks of the central metabolism of Bacillus subtilis. BMC Syst Biol 2008; 2:20
• [14] Henry CS, Zinner JF, Cohoon MP, Stevens RL. iBsull03: A new genome-scale metabolic model of Bacillus subtilis based on SEED annotations. Genome Biol 2009; 10, R69
• [15] Tanaka K, Henry CS, Zinner JF, Jolivet E, Cohoon MP, Xia F, Bidnenko V, Ehrlich SD, Stevens RL, Noirot P. Building the repertoire of dispensable chromosome regions in Bacillus subtilis entails major refinement of cognate large-scale metabolic model. Nucleic Acids Res 2013; 41: 687-699
• [16] Hao T, Han B, Ma H, Fu J, Wang H, Wang Z, Tang B, Chen T, Zhao X. In silico metabolic engineering of Bacillus subtilis for improved production of riboflavin Egl-237,(R,R)-2,3-butanediol and isobutanol. Mol Biosyst 2013; 9: 2034-2044
• [17] Çalık P, Çalık G, Takaç S, Özdamar TH. Metabolic flux analysis for serinealkaline protease fermentation by Bacillus licheniformis in a defined medium: effects of oxygen transfer rate. Biotechnol Bioeng 1999; 64:151-167
• [18] Heirendt L, Arreckx S, Pfau T, Mendoza SN, Richelle A, Heinken A, Haraldsdottir HS, Wachowiak J, Keating SM, Vlasov V et al. Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0. Nat Protoc 2019; 14: 639-702
• [19] Sanchez BJ, Zhang C, Nilsson A, Lahtvee PJ, Kerkhoven EJ, Nielsen J. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constriants. Mol Syst Biol 2017;13: 935
• [20] Iacobazzi V, Infantino V. Citrate--New functions for an old metabolite. Biol Chem 2014; 395: 387-399
• [21] Özdamar TH, Şentürk B, Yılmaz ÖD, Kocabaş P, Çalık G, Çalık P. Bioreaction network flux analysis for human protein producing Bacillus subtilis based on genome-scale model. Chemical Engineering Science 2010; 65: 574-580.