Stoichiometric growth model for riboflavin-producing Bacillus subtilis

Rate equations for measured extracellular rates and macromolecular composition data were combined with a stoichiometric model to describe riboflavin production with an industrial Bacillus subtilis strain using errors in variables regression analysis. On the basis of this combined stoichiometric growth model, we explored the topological features of the B. subtilis metabolic reaction network that was assembled from a large amount of literature. More specifically, we simulated maximum theoretical yields of biomass and riboflavin, including the associated flux regimes. Based on the developed model, the importance of experimental data on building block requirements for maximum yield and flux calculations were investigated. These analyses clearly show that verification of macromolecular composition data is important for optimum flux calculations.     

Enhancement of riboflavin production by overexpression of acetolactate synthase in a pta mutant of Bacillus subtilis

Genetic alterations of carbon flux into the acetoin biosynthesis pathway as a possible means to reduce acid accumulation were investigated in the riboflavin-producing Bacillus subtilis during growth on glucose. The lower rates of cell growth and riboflavin production were found in the pta-disrupted mutant while the rate of acetate formation was reduced. In contrast, acid accumulation was significantly reduced, to one-fifth that of the parental strain RH33::[pRB63](n), and a 50% increase in the riboflavin yield was obtained when the expression of the gene encoding acetolactate synthase was increased in the pta-disrupted mutant. Metabolic analysis, together with enzyme activity assays, indicated that the tricarboxylic acid cycle fluxes are significantly increased in response to acetolactate synthase overexpression in pta-disrupted mutant. Moreover, the intracellular ATP-to-ADP ratio also increased 5.8-fold. The high concentration of ATP could explain the increased riboflavin production.     

Metabolic flux model for an anchorage-dependent MDCK cell line: characteristic growth phases and minimum substrate consumption flux distribution

Up to now cell-culture based vaccine production processes only reach low productivities. The reasons are: (i) slow cell growth and (ii) low cell concentrations. To address these shortcomings, a quantitative analysis of the process conditions, especially the cell growth and the metabolic capabilities of the host cell line is required. For this purpose a MDCK cell based influenza vaccine production process was investigated. With a segregated growth model four distinct cell growth phases are distinguished in the batch process. In the first phase the cells attach to the surface of the microcarriers and show low metabolic activity. The second phase is characterized by exponential cell growth. In the third phase, preceded by a change in oxygen consumption, contact inhibition leads to a decrease in cell growth. Finally, the last phase before infection shows no further increase in cell numbers. To gain insight into the metabolic activity during these phases, a detailed metabolic model of MDCK cell was developed based on genome information and experimental analysis. The MDCK model was also used to calculate a theoretical flux distribution representing an optimized cell that only consumes a minimum of carbon sources. Comparing this minimum substrate consumption flux distribution to the fluxes estimated from experiments unveiled high overflow metabolism under the applied process conditions.     

Metabolic flux analysis of cultured hepatocytes exposed to plasma

Hepatic metabolism can be investigated using metabolic flux analysis (MFA), which provides a comprehensive overview of the intracellular metabolic flux distribution. The characterization of intermediary metabolism in hepatocytes is important for all biotechnological applications involving liver cells, including the development of bioartificial liver (BAL) devices. During BAL operation, hepatocytes are exposed to plasma or blood from the patient, at which time they are prone to accumulate intracellular lipids and exhibit poor liver-specific functions. In a prior study, we found that preconditioning the primary rat hepatocytes in culture medium containing physiological levels of insulin, as opposed to the typical supraphysiological levels found in standard hepatocyte culture media, reduced lipid accumulation during subsequent plasma exposure. Furthermore, supplementing the plasma with amino acids restored hepatospecific functions. In the current study, we used MFA to quantify the changes in intracellular pathway fluxes of primary rat hepatocytes in response to low-insulin preconditioning and amino acid supplementation. We found that culturing hepatocytes in medium containing lower physiological levels of insulin decreased the clearance of glucose and glycerol with a concomitant decrease in glycolysis. These findings are consistent with the general notion that low insulin, especially in the presence of high glucagon levels, downregulates glycolysis in favor of gluconeogenesis in hepatocytes. The MFA model shows that, during subsequent plasma exposure, low-insulin preconditioning upregulated gluconeogenesis, with lactate as the primary precursor in unsupplemented plasma, with a greater contribution from deaminated amino acids in amino acid-supplemented plasma. Concomitantly, low-insulin preconditioning increased fatty acid oxidation, an effect that was further enhanced by amino acid supplementation to the plasma. The increase in fatty acid oxidation reduced intracellular triglyceride accumulation. Overall, these findings are consistent with the notion that the insulin level in medium culture presets the metabolic machinery of hepatocytes such that it directly impacts on their metabolic behavior during subsequent plasma culture.     

Metabolic flux analysis in plants: coping with complexity

Theory and experience in metabolic engineering both show that metabolism operates at the network level. In plants, this complexity is compounded by a high degree of compartmentation and the synthesis of a very wide array of secondary metabolic products. A further challenge to understanding and predicting plant metabolic function is posed by our ignorance about the structure of metabolic networks even in well-studied systems. Metabolic flux analysis (MFA) provides tools to measure and model the functioning of metabolism, and is making significant contributions to coping with their complexity.
This review gives an overview of different MFA approaches, the measurements required to implement them and the information they yield. The application of MFA methods to plant systems is then illustrated by several examples from the recent literature. Next, the challenges that plant metabolism poses for MFA are discussed together with ways that these can be addressed. Lastly, new developments in MFA are described that can be expected to improve the range and reliability of plant MFA in the coming years.     

Using isotopomer path tracing to quantify metabolic fluxes in pathway models containing reversible reactions

As a more complete picture of the genetic and enzymatic composition of cells becomes available, there is a growing need to describe how cellular regulatory elements interact with the cellular environment to affect cell physiology. One means for describing intracellular regulatory mechanisms is concurrent measurement of multiple metabolic pathways and their interactions by metabolic flux analysis. Flux of carbon through a metabolic pathway responds to all cellular regulatory systems, including changes in enzyme and substrate concentrations, enzyme activation or inhibition, and ultimately genetic control. The extent to which metabolic flux analysis can describe cellular physiology depends on the number of pathways in the model and the quality of the data. Intracellular information is obtainable from isotopic tracer experiments, the most extensive being the determination of the isotopomer distribution, or specific labeling pattern, of intracellular metabolites. We present a rapid and novel solution method that determines the flux of carbon through complex pathway models using isotopomer data. This time-consuming problem was solved with the introduction of isotopomer path tracing, which drastically reduces the number of isotopomer variables to the number of isotopomers observed experimentally. We propose a partitioned solution method that takes advantage of the nearly linear relationship between fluxes and isotopomers. Whereas the stoichiometric matrix and the isotopomer matrix are invertible, simulated annealing and the Newton-Raphson method are used for the nonlinear components. Reversible reactions are described by a new parameter, the association factor, which scales hyperbolically with the rate of metabolite exchange. Automating the solution method permits a variety of models to be compared, thus enhancing the accuracy of results. A simplified example that contains all of the complexities of a comprehensive pathway model is presented. Copyright John Wiley & Sons, Inc.     

Genetic engineering of Bacillus subtilis for the commercial production of riboflavin

Recombinant DNA engineering was combined with mutant selection and fermentation improvement to develop a strain of Bacillus subtilis that produces commercially attractive levels of riboflavin. The B. subtilis riboflavin production strain contains multiple copies of a modified B. subtilis riboflavin biosynthetic operon (rib operon) integrated at two different sites in the B. subtilis chromosome. The modified rib operons are expressed constitutively from strong phage promoters located at the 5′ end and in an internal region of the operon. The engineered strain also contains purine analog-resistant mutations designed to deregulate the purine pathway (GTP is the precursor for riboflavin), and a riboflavin analog-resistant mutation in ribC that deregulates the riboflavin biosynthetic pathway. Received 22 June 1998/ Accepted in revised form 6 November 1998     

Comparative genome analysis of Bacillus cereus group genomes with Bacillus subtilis

Genome features of the Bacillus cereus group genomes (representative strains of Bacillus cereus, Bacillus anthracis and Bacillus thuringiensis sub spp. israelensis) were analyzed and compared with the Bacillus subtilis genome. A core set of 1381 protein families among the four Bacillus genomes, with an additional set of 933 families common to the B. cereus group, was identified. Differences in signal transduction pathways, membrane transporters, cell surface structures, cell wall, and S-layer proteins suggesting differences in their phenotype were identified. The B. cereus group has signal transduction systems including a tyrosine kinase related to two-component system histidine kinases from B. subtilis. A model for regulation of the stress responsive sigma factor sigmaB in the B. cereus group different from the well studied regulation in B. subtilis has been proposed. Despite a high degree of chromosomal synteny among these genomes, significant differences in cell wall and spore coat proteins that contribute to the survival and adaptation in specific hosts has been identified.     

枯草芽孢杆菌代谢工程改造的策略与工具

作为一种食品安全级的典型工业模式微生物,枯草芽孢杆菌Bacillus subtilis由于具有非致病性、胞外分泌蛋白能力强以及无明显的密码子偏爱性等特点,现已被广泛应用于代谢工程领域。近年来,随着分子生物学和基因工程技术等的迅速发展,多种研究策略和工具被用于构建枯草芽孢杆菌底盘细胞进行生物制品的高效合成。文中从启动子工程、基因编辑、基因回路、辅因子工程以及途径酶组装等方面介绍枯草芽孢杆菌在代谢工程领域的研究历程,并总结其在生物制品生产中的相关应用,最后对其未来的研究方向进行展望。     

A review on metabolic pathway analysis with emphasis on isotope labeling approach

The recent progress on metabolic systems engineering was reviewed based on our recent research results in terms of (1) metabolic signal flow diagram approach, (2) metabolic flux analysis (MFA) in particular with intracellular isotopomer distribution using NMR and/or GC-MS, (3) synthesis and optimization of metabolic flux distribution (MFD), (4) modification of MFD by gene manipulation and by controlling culture environment, (5) metabolic control analysis (MCA), (6) design of metabolic regulation structure, and (7) identification of unknown pathways with isotope tracing by NMR. The main characteristics of metabolic engineering is to treat metabolism as a network or entirety instead of individual reactions. The applications were made for poly-3-hydroxybutyrate (PHB) production usingRalstonia eutropha and recombinantEscherichia coli, lactate production by recombinantSaccharomyces cerevisiae, pyruvate production by vitamin auxotrophic yeastToluropsis glabrata, lysine production usingCorynebacterium glutamicum, and energetic analysis of photosynthesic microorganisms such as Cyanobateria. The characteristics of each approach were reviewed with their applications. The approach based on isotope labeling experiments gives reliable and quantitative results for metabolic flux analysis. It should be recognized that the next stage should be toward the investigation of metabolic flux analysis with gene and protein expressions to uncover the metabolic regulation in relation to genetic modification and/or the change in the culture condition.     

肌苷发酵过程中后期的代谢流节点分析

应用代谢流分析方法,实验测定副产物的积累速率,将数据输入计算机,应用MArllAB软件计算肌苷发酵中后期代谢流分布。通过分析代谢网络中重要的节点,提出了优化肌苷生物合成途径的建议。     

Metabolic isotopomer labeling systems. Part II: structural flux identifiability analysis

Metabolic flux analysis using carbon labeling experiments (CLEs) is an important tool in metabolic engineering where the intracellular fluxes have to be computed from the measured extracellular fluxes and the partially measured distribution of 13C labeling within the intracellular metabolite pools. The relation between unknown fluxes and measurements is described by an isotopomer labeling system (ILS) (see Part I [Math. Biosci. 169 (2001) 173]). Part II deals with the structural flux identifiability of measured ILSs in the steady state. The central question is whether the measured data contains sufficient information to determine the unknown intracellular fluxes. This question has to be decided a priori, i.e. before the CLE is carried out. In structural identifiability analysis the measurements are assumed to be noise-free. A general theory of structural flux identifiability for measured ILSs is presented and several algorithms are developed to solve the identifiability problem. In the particular case of maximal measurement information, a symbolical algorithm is presented that decides the identifiability question by means of linear methods. Several upper bounds of the number of identifiable fluxes are derived, and the influence of the chosen inputs is evaluated. By introducing integer arithmetic this algorithm can even be applied to large networks. For the general case of arbitrary measurement information, identifiability is decided by a local criterion. A new algorithm based on integer arithmetic enables an a priori local identifiability analysis to be performed for networks of arbitrary size. All algorithms have been implemented and flux identifiability is investigated for the network of the central metabolic pathways of a microorganism. Moreover, several small examples are worked out to illustrate the influence of input metabolite labeling and the paradox of information loss due to network simplification.     

Metabolic flux analysis using 13C peptide label measurements

¹³C metabolic flux analysis (MFA) has become the experimental method of choice to investigate the cellular metabolism of microbes, cell cultures and plant seeds. Conventional steady‐state MFA utilizes isotopic labeling measurements of amino acids obtained from protein hydrolysates. To retain spatial information in conventional steady‐state MFA, tissues or subcellular fractions must be dissected or biochemically purified. In contrast, peptides retain their identity in complex protein extracts, and may therefore be associated with a specific time of expression, tissue type and subcellular compartment. To enable ‘single‐sample’ spatially and temporally resolved steady‐state flux analysis, we investigated the suitability of peptide mass distributions (PMDs) as an alternative to amino acid label measurements. PMDs are the discrete convolution of the mass distributions of the constituent amino acids of a peptide. We investigated the requirements for the unique deconvolution of PMDs into amino acid mass distributions (AAMDs), the influence of peptide sequence length on parameter sensitivity, and how AAMD and flux estimates that are determined through deconvolution compare to estimates from a conventional GC–MS measurement‐based approach. Deconvolution of PMDs of the storage protein β–conglycinin of soybean (Glycine max) resulted in good AAMD and flux estimates if fluxes were directly fitted to PMDs. Unconstrained deconvolution resulted in inferior AAMD and flux estimates. PMD measurements do not include amino acid backbone fragments, which increase the information content in GC–MS‐derived analyses. Nonetheless, the resulting flux maps were of comparable quality due to the precision of Orbitrap quantification and the larger number of peptide measurements.     

一株可积累鸟苷菌株的纯培养条件研究

菌株Bacillus.subtilis.S3 68是以鸟苷生产菌株B .subtilis.A0 66为出发菌经诱变所得。对该菌株进行培养条件研究的过程中 ,发现该菌株可以在摇瓶纯培养条件下积累鸟苷。试验结果表明 :发酵过程中 ,腺嘌呤的用量 0 .3 5mg/ml时 ,发酵液中鸟苷积累量最大 ,培养基中腺嘌呤的用量高于或低于 0 .3 5mg/ml均不利于鸟苷产物的积累 ;培养基中味精、硫酸铵、硫酸镁、磷酸二氢钾及Mn2 +用量显著影响发酵液中鸟苷积累水平 ;培养基中生物素、蛋氨酸、精氨酸、组氨酸、氯化钙及Fe2 +、Zn2 +用量与鸟苷积累的相关性不显著     

Positioning Bacillus subtilis as terpenoid cell factory

Increasing demands for bioactive compounds have motivated researchers to employ micro-organisms to produce complex natural products. Currently, Bacillus subtilis has been attracting lots of attention to be developed into terpenoids cell factories due to its generally recognized safe status and high isoprene precursor biosynthesis capacity by endogenous methylerythritol phosphate (MEP) pathway. In this review, we describe the up-to-date knowledge of each enzyme in MEP pathway and the subsequent steps of isomerization and condensation of C5 isoprene precursors. In addition, several representative terpene synthases expressed in B. subtilis and the engineering steps to improve corresponding terpenoids production are systematically discussed. Furthermore, the current available genetic tools are mentioned as along with promising strategies to improve terpenoids in B. subtilis, hoping to inspire future directions in metabolic engineering of B. subtilis for further terpenoid cell factory development.     

Towards a comprehensive understanding of Bacillus subtilis cell physiology by physiological proteomics

Using Bacillus subtilis as a model system for functional genomics, this review will provide insights how proteomics can be used to bring the virtual life of genes to the real life of proteins. Physiological proteomics will generate a new and broad understanding of cellular physiology because the majority of proteins synthesized in the cell can be visualized. From a physiological point of view two major proteome fractions can be distinguished: proteomes of growing cells and proteomes of nongrowing cells. In the main analytical window almost 50% of the vegetative proteome expressed in growing cells of B. subtilis were identified. This proteomic view of growing cells can be employed for analyzing the regulation of entire metabolic pathways and thus opens the chance for a comprehensive understanding of metabolism and growth processes of bacteria. Proteomics, on the other hand, is also a useful tool for analyzing the adaptational network of nongrowing cells that consists of several partially overlapping regulation groups induced by stress/starvation stimuli. Furthermore, proteomic signatures for environmental stimuli can not only be applied to predict the physiological state of cells, but also offer various industrial applications from fermentation monitoring up to the analysis of the mode of action of drugs. Even if DNA array technologies currently provide a better overview of the gene expression profile than proteome approaches, the latter address biological problems in which they can not be replaced by mRNA profiling procedures. This proteomics of the second generation is a powerful tool for analyzing global control of protein stability, the protein interaction network, protein secretion or post-translational modifications of proteins on the way towards the elucidation of the mystery of life.     

Cloning in Bacillus subtilis of temperature-dependent promoter fragments from Bacillus stearothermophilus and Bacillus subtilis

Abstract Using promoter-probe plasmids, more than 200 promoter-containing fragments from Bacillus stearothermophilus and Bacillus subtilis were cloned in B. subtilis . Among these, 15 promoter fragments were highly temperature-dependent in activity compared to the promoter sequence (TTGAAA for the −35 region, TATAAT for the −10 region) of the amylase gene, amyT , from B. stearothermophilus . Some fragments exhibited higher promoter activities at elevated temperature (48°C), others showed higher activities at lower temperature (30°C). Active promoter fragments at higher and lower temperatures were obtained mainly from the thermophile ( B. stearothermophilus ) and the mesophile ( B. subtilis ), respectively. A promoter fragment active at high temperature was sequenced, and the feature of the putative promoter region was discussed.