Carbon sources affect metabolic capacities of Bacillus species for the production of industrial enzymes: theoretical analyses for serine and neutral proteases and α-amylase
Introduction
Serine alkaline protease (SAP, EC 3.4.21.14), neutral protease (NP, EC 3.4.24) and α-amylase (AMY, EC 3.2.1.1) produced by Bacillus sp. are the major industrial enzymes with increasing market demands, whereupon, the genus Bacillus is one of the most important group of industrial microorganisms that are, in fact, the microbioreactors within the bioreactors [1]. In the bacilli, substrate and medium design, and bioreactor operation conditions, e.g. oxygen transfer rate and pH, regulate SAP, NP, AMY formations beginning from t=0 h [2], [3]. Most studies that are aimed at improving the production of proteases [4] and α-amylase [5] by Bacillus species have investigated the effects of various carbon sources, e.g. glucose, acetate and citric acid. Nevertheless, analysis of the existing information on the effects of carbon sources is difficult, since many of the investigations performed on extracellular enzyme production that are subject to carbon repression suffer in-depth systematic comparative study in order to design the bioreactor media. Moreover, in production the ability of the bacilli to secrete other enzymes, amino acids and organic-acids as by-products besides the desired product, e.g. SAP, NP or AMY, needs to be regulated in order to fine tune bioreactor performance in relation with the physiology of the microorganism. In this context, knowing the distribution of the metabolic fluxes and further the capacity of the microorganism is helpful to determine the theoretical ultimate limit of the production capacity of the cell for successful selection and development of the industrial microorganism on a selective substrate, and further for successful application of metabolic engineering for increasing the yield and selectivity by predicting the rate limiting step(s) and the changes in the fluxes in the metabolic pathways leading to the desired enzyme synthesis.
Bioreaction network flux analysis that is the novel application of biochemical reaction engineering principles to metabolic reaction pathways achieved first by Aiba and Matsuoka [6], and understood and applied in the last decade of the 20th century, depends on the stoichiometrically-based analysis of the metabolic reactions for determining the metabolic fluxes in the cells [7], [8]. This analysis can be used to find the critical branch points and bottlenecks in the overall flux distributions, for modifying the medium composition, for improving the bioreactor operation conditions, moreover, for calculating the theoretical metabolic capacities of the microorganism and for selecting the host microorganism. Theoretical metabolic capacity (TC) analysis is used to determine the maximum theoretical yield of a product on a substrate together with the optimum metabolic flux distributions in order to predict the ultimate theoretical yield, selectivity and productivity that can be performed by the microorganism. Nevertheless, maximisation of the carbon yield of a product relative to the carbon consumed by the cell, and consequently minimisation of the by-product formations can be achieved in the first step by influencing the cellular metabolism by designing the bioreactor operation conditions, and further by altering the regulatory controls of the microorganism by using metabolic engineering techniques. The TC analysis has been successfully applied to a number of industrially important microorganisms and products [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24].
As the Bacillus species secrete a large number of extracellular enzymes and produce purine nucleosides, antibiotics, insecticides, vitamins, and are the potential hosts in the fermentation industry for the production of recombinant proteins, attracted the application of the metabolic flux analysis [1], [15], [18], [19], [20], [21], [22], [23], [24]. Çalık and Özdamar [19] and Çalık et al. [1] recently reported the application of metabolic flux analysis for an enzyme for the first time. The authors [19] reported the biochemistry of B. licheniformis and developed a detailed mass flux balance-based stoichiometric model that contains 147 reaction fluxes and 105 metabolites to obtain the intracellular metabolic flux distributions for SAP production; and they used the model for SAP production that minimises the SAP accumulation in the cell using elaborate experimental data in order to explain the metabolic behaviour of the cells throughout the batch bioprocess. The effects of oxygen transfer conditions on metabolic flux distributions and the potential metabolic bottlenecks in SAP synthesis in B. licheniformis were investigated by Çalık et al. [1]; and reported that the flux partitioning in the TCA cycle at α-ketoglutarate (α-KG) towards glutamate group and at oxalacetate (OA) towards aspartate group amino acids were dependent on the oxygen transfer rate. Çalık et al. [18] reported maximum SAP theoretical yields and optimum carbon flux distributions for SAP overproduction in B. licheniformis by using citric acid as the sole carbon source and then applied the model to the SAP fermentation by using experimental data obtained during the batch bioprocess in order to explain the performance of the bacilli. And lastly, Çalık et al. [20] reported the effects of oxygen transfer on the metabolic capacity of B. licheniformis.
The literature related with the metabolic flux analysis shows that there is not any individual published work concerning the effects of carbon sources on any enzyme or protein production with any Bacillus sp. or even with any microorganism. As the genus Bacillus has the potential to produce SAP, NP and AMY in relation to its genetic structure and regulation in response to its designed environment, in the present work, we focused on the effects of carbon sources that have different reduction degrees (γ) on the metabolic capacity of the bacilli for the production of the three enzymes. The carbon sources glucose (γ=4.0), acetate (γ=4.0), and the TCA cycle organic-acids succinate (γ=3.5), malate (γ=3.0), and citrate (γ=3.0) were selected for the theoretical analyses and comparisons, despite the fact that two of the TCA cycle organic-acids, i.e. succinate and malate, are not economic substrates for the bioprocesses. Thus, the theoretical intracellular bioreaction network flux distributions in B. licheniformis in response to each of the carbon sources for the overproduction of each of the three industrial enzymes are calculated to evaluate the effects of carbon sources on the metabolism of the bacilli, and, moreover, to predict the adequate substrate(s) for the media design. Further, depending on the optimised metabolic flux distributions, the potential metabolic bottlenecks in the synthesis of each enzyme are predicted, finally, the general conceptual framework to develop the bioprocesses for SAP, NP and AMY productions is presented.
Section snippets
Mass flux balance based theoretical capacity analysis
The metabolic reaction network of B. licheniformis [19] that contains 105 metabolites and 147 intracellular reactions is used by the addition of the following reactions:
Anaplerotic reactioncatalysed by pyruvate carboxylase is included to the model for the connection of the glycolysis pathway to the TCA cycle.
Neutral protease synthesis reaction [25]
Theoretical metabolic flux distributions for maximum biomass generation: cell growth phase
Metabolic flux distributions of the intracellular reaction network were determined by theoretical metabolic capacity (TC) analysis by using the reaction network model that was set up for B. licheniformis for the cell growth phase by maximising the biomass production (R145) in the objective function Eq. (3) of the generalised model for each of the five substrates, i.e. glucose, acetate, succinate, malate, and citrate. In the calculations, for the direct comparisons, all the biomass flux values
Discussion and conclusions
Since the synthesis of an enzyme and by-product formations in a microorganism in the bioreactor are dependent on the substrate, medium design, and bioreactor operation conditions, an in-depth insight was provided by applying the theoretical metabolic capacity (TC) analysis to determine the theoretical ultimate limits of the production capacities of the bacilli for the enzymes SAP, NP and AMY on the five carbon sources, i.e. glucose, acetate, succinate, malate and citrate, in order to predict
Acknowledgements
This work was supported by the State Planning Organisation (SPO, Turkey) Grant 97K120590. Professor Güzide Çalık (Ankara University) is gratefully acknowledged for her valuable comments and for reading the manuscript.
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