Metabolic fluxes in riboflavin-producing Bacillus subtilis

Rational design of GDP‑D‑mannose mannosyl hydrolase for microbial L‑fucose production

BACKGROUND

L‑Fucose is a rare sugar that has beneficial biological activities, and its industrial production is mainly achieved with brown algae through acidic/enzymatic fucoidan hydrolysis and a cumbersome purification process. Fucoidan is synthesized through the condensation of a key substance, guanosine 5'‑diphosphate (GDP)‑L‑fucose. Therefore, a more direct approach for biomanufacturing L‑fucose could be the enzymatic degradation of GDP‑L‑fucose. However, no native enzyme is known to efficiently catalyze this reaction. Therefore, it would be a feasible solution to engineering an enzyme with similar function to hydrolyze GDP‑L‑fucose.

RESULTS

Herein, we constructed a de novo L‑fucose synthetic route in Bacillus subtilis by introducing heterologous GDP‑L‑fucose synthesis pathway and engineering GDP‑mannose mannosyl hydrolase (WcaH). WcaH displays a high binding affinity but low catalytic activity for GDP‑L‑fucose, therefore, a substrate simulation‑based structural analysis of the catalytic center was employed for the rational design and mutagenesis of selected positions on WcaH to enhance its GDP‑L‑fucose‑splitting efficiency. Enzyme mutants were evaluated in vivo by inserting them into an artificial metabolic pathway that enabled B. subtilis to yield L‑fucose. WcaH^R36Y/N38R was found to produce 1.6 g/L L‑fucose during shake‑flask growth, which was 67.3% higher than that achieved by wild‑type WcaH. The accumulated L‑fucose concentration in a 5 L bioreactor reached 6.4 g/L.

CONCLUSIONS

In this study, we established a novel microbial engineering platform for the fermentation production of L‑fucose. Additionally, we found an efficient GDP‑mannose mannosyl hydrolase mutant for L‑fucose biosynthesis that directly hydrolyzes GDP‑L‑fucose. The engineered strain system established in this study is expected to provide new solutions for L‑fucose or its high value‑added derivatives production.

Metabolic flux analysis: a comprehensive review on sample preparation, analytical techniques, data analysis, computational modelling, and main application areas

Metabolic flux analysis (MFA) quantitatively describes cellular fluxes to understand metabolic phenotypes and functional behaviour after environmental and/or genetic perturbations. In the last decade, the application of stable isotopes became extremely important to determine and integrate in vivo measurements of metabolic reactions in systems biology. 13C-MFA is one of the most informative methods used to study central metabolism of biological systems. This review aims to outline the current experimental procedure adopted in 13C-MFA, starting from the preparation of cell cultures and labelled tracers to the quenching and extraction of metabolites and their subsequent analysis performed with very powerful software. Here, the limitations and advantages of nuclear magnetic resonance spectroscopy and mass spectrometry techniques used in carbon labelled experiments are elucidated by reviewing the most recent published papers. Furthermore, we summarise the most successful approaches used for computational modelling in flux analysis and the main application areas with a particular focus in metabolic engineering.

Recent advances in metabolic engineering-integration of in silico design and experimental analysis of metabolic pathways

Microorganisms are widely used to produce valuable compounds. Because thousands of metabolic reactions occur simultaneously and many metabolic reactions are related to target production and cell growth, the development of a rational design method for metabolic pathway modification to optimize target production is needed. In this paper, recent advances in metabolic engineering are reviewed, specifically considering computational pathway modification design and experimental evaluation of metabolic fluxes by ¹³C-metabolic flux analysis. Computational tools for seeking effective gene deletion targets and recruiting heterologous genes are described in flux balance analysis approaches. A kinetic model and adaptive laboratory evolution were applied to identify and eliminate the rate-limiting step in metabolic pathways. Data science-based approaches for process monitoring and control are described to maximize the performance of engineered cells in bioreactors.

An insight to flux-balance analysis for biochemical networks

Systems biology is one of the integrated ways to study biological systems and is more favourable than the earlier used approaches. It includes metabolic pathway analysis, modelling, and regulatory as well as signal transduction for getting insights into cellular behaviour. Among the various techniques of modelling, simulation, analysis of networks and pathways, flux-based analysis (FBA) has been recognised because of its extensibility as well as simplicity. It is widely accepted because it is not like a mechanistic simulation which depends on accurate kinetic data. The study of fluxes through the network is informative and can give insights even in the absence of kinetic data. FBA is one of the widely used tools to study biochemical networks and needs information of reaction stoichiometry, growth requirements, specific measurement parameters of the biological system, in particular the reconstruction of the metabolic network for the genome-scale, many of which have already been built previously. It defines the boundaries of flux distributions which are possible and achievable with a defined set of genes. This review article gives an insight into FBA, from the extension of flux balancing to mathematical representation followed by a discussion about the formulation of flux-balance analysis problems, defining constraints for the stoichiometry of the pathways and the tools that can be used in FBA such as FASIMA, COBRA toolbox, and OptFlux. It also includes broader areas in terms of applications which can be covered by FBA as well as the queries which can be addressed through FBA.

Genomic, transcriptomic, and metabolic characterizations of Escherichia coli adapted to branched-chain higher alcohol tolerance

Microbial-produced branched-chain higher alcohols (BCHAs), such as isopropanol, isobutanol, and isopentanol in Escherichia coli, have emerged as promising alternative biofuels under development. Elucidating and improving the tolerance of E. coli to BCHAs are important issues for microbial production of BCHAs due to their physiological inhibitory effect. Previous works aimed at understanding the genetic basis of E. coli tolerance to BCHAs with a comparative genome, reverse engineering, or transcriptome approach have gained some important insights into the mechanism of tolerance. However, investigation on BCHA tolerance from the whole-genomic, transcriptomic, and metabolic levels via a systematic approach has not yet been completely elucidated. Here, in this study, genomic, transcriptomic, and ¹³C-metabolic flux analyses (¹³C-MFA) of an evolved E. coli strain adapted to BCHA tolerance were conducted. Genome mutation of negative regulation factor (rssB, acrB, and clpX) of RpoS level suggested upregulation of RpoS activity in BCHA tolerance of E. coli. From a more detailed perspective, enhanced energy metabolism was observed to be the main characteristic of E. coli strain tolerant to BCHAs. Enhanced energy metabolism has been achieved through several routes, which included redistribution of the central carbon metabolism, upregulation of the energy generation machinery, and facilitating the operation of electron transferring chain. Evidence of multiple solutions of genotype modification toward BCHA tolerance was also revealed through comparative analysis of previous works from different groups.

CRISPRi-Guided Multiplexed Fine-Tuning of Metabolic Flux for Enhanced Lacto-N-neotetraose Production in Bacillus subtilis

Lacto-N-neotetraose (LNnT), one of the oligosaccharides in human milk, has many beneficial effects on infant health. In a recent work, we have constructed a recombinant Bacillus subtilis strain for the production of LNnT. Here, we further improved LNnT production with a xylose-induced clustered regularly interspaced short palindromic repeats interference system. In particular, the expressions of pfkA and pyk genes in the Embden-Meyerhof-Parnas pathway module, zwf gene in the pentose phosphate pathway module, and mnaA gene in the teichoic acid synthesis module were downregulated. The LNnT titer was increased from 1.32 to 1.55 g/L. Furthermore, to improve the conversion efficiency of lacto-N-triose II to LNnT, we knocked out tuaD gene in branch pathway and improved the expression of lgtB gene, resulting in the further increase of LNnT titer to 2.01 g/L. Finally, the addition time and amount of inducer xylose were optimized, and LNnT titer reached 2.30 g/L in shake flask and 5.41 g/L in 3 L bioreactor.

Bacillus subtilis Regulators MntR and Zur Participate in Redox Cycling, Antibiotic Sensitivity, and Cell Wall Plasticity

The Bacillus subtilis MntR and Zur transcriptional regulators control homeostasis of manganese and zinc, two essential elements required in various cellular processes. In this work, we describe the global impact of mntR and zur deletions at the protein level. Using a comprehensive proteomic approach, we showed that 33 and 55 proteins are differentially abundant in ΔmntR and Δzur cells, respectively, including proteins involved in metal acquisition, translation, central metabolism, and cell wall homeostasis. In addition, both mutants showed modifications in intracellular metal ion pools, with significant Mg²⁺ accumulation in the ΔmntR mutant. Phenotypic and morphological analyses of ΔmntR and Δzur mutants revealed their high sensitivity to lysozyme, beta-lactam antibiotics, and external oxidative stress. Mutant strains had a modified cell wall thickness and accumulated lower levels of intracellular reactive oxygen species (ROS) than the wild-type strain. Remarkably, our results highlight an intimate connection between MntR, Zur, antibiotic sensitivity, and cell wall structure.IMPORTANCE Manganese and zinc are essential transition metals involved in many fundamental cellular processes, including protection against external oxidative stress. In Bacillus subtilis, Zur and MntR are key transcriptional regulators of zinc and manganese homeostasis, respectively. In this work, proteome analysis of B. subtilis wild-type, ΔmntR, and Δzur strains provided new insights into bacterial adaptation to deregulation of essential metal ions. Deletions of mntR and zur genes increased bacterial sensitivity to lysozyme, beta-lactam antibiotics, and external oxidative stress and impacted the cell wall thickness. Overall, these findings highlight that Zur and MntR regulatory networks are connected to antibiotic sensitivity and cell wall plasticity.

Flux Connections Between Gluconate Pathway, Glycolysis, and Pentose-Phosphate Pathway During Carbohydrate Metabolism in Bacillus megaterium QM B1551

Bacillus megaterium is a bacterium of great importance as a plant-beneficial bacterium in agricultural applications and in industrial bioproduction of proteins. Understanding intracellular processing of carbohydrates in this species is crucial to predicting natural carbon utilization as well as informing strategies in metabolic engineering. Here, we applied stable isotope-assisted metabolomics profiling and metabolic flux analysis to elucidate, at high resolution, the connections of the different catabolic routes for carbohydrate metabolism immediately following substrate uptake in B. megaterium QM B1551. We performed multiple 13C tracer experiments to obtain both kinetic and long-term 13C profiling of intracellular metabolites. In addition to the direct phosphorylation of glucose to glucose-6-phosphate (G6P) prior to oxidation to 6-phosphogluconate (6P-gluconate), the labeling data also captured glucose catabolism through the gluconate pathway involving glucose oxidation to gluconate followed by phosphorylation to 6P-gluconate. Our data further confirmed the absence of the Entner-Doudoroff pathway in B. megaterium and showed that subsequent catabolism of 6P-gluconate was instead through the oxidative pentose-phosphate (PP) pathway. Quantitative flux analysis of glucose-grown cells showed equal partition of consumed glucose from G6P to the Embden-Meyerhof-Parnas (EMP) pathway and from G6P to the PP pathway through 6P-gluconate. Growth on fructose alone or xylose alone was consistent with the ability of B. megaterium to use each substrate as a sole source of carbon. However, a detailed 13C mapping during simultaneous feeding of B. megaterium on glucose, fructose, and xylose indicated non-uniform intracellular investment of the different carbohydrate substrates. Flux of glucose-derived carbons dominated the gluconate pathway and the PP pathway, whereas carbon flux from both glucose and fructose populated the EMP pathway; there was no assimilatory flux of xylose-derived carbons. Collectively, our findings provide new quantitative insights on the contribution of the different catabolic routes involved in initiating carbohydrate catabolism in B. megaterium and related Bacillus species.

13 C metabolic flux profiling of Pichia pastoris grown in aerobic batch cultures on glucose revealed high relative anabolic use of TCA cycle and limited incorporation of provided precursors of branched-chain amino acids

Carbon metabolism of Crabtree-negative yeast Pichia pastoris was profiled using ¹³ C nuclear magnetic resonance (NMR) to delineate regulation during exponential growth and to study the import of two precursors for branched-chain amino acid biosynthesis, α-ketoisovalerate and α-ketobutyrate. Cells were grown in aerobic batch cultures containing (a) only glucose, (b) glucose along with the precursors, or (c) glucose and Val. The study provided the following new insights. First, ¹³ C flux ratio analyses of central metabolism reveal an unexpectedly high anaplerotic supply of the tricarboxylic acid cycle for a Crabtree-negative yeast, and show that a substantial fraction of glucose catabolism proceeds through the pentose phosphate pathway. A comparison with previous flux ratio analyses for batch cultures of Crabtree-negative Pichia stipitis and Crabtree-positive Saccharomyces cerevisiae indicate that the overall regulation of central carbon metabolism in P. pastoris is intermediate in between P. stipitis and S. cerevisiae. Second, excess α-ketoisovalerate in the medium is not transported into the cytoplasm indicating that P. pastoris lacks a suitable transporter. In contrast, excess Val is efficiently taken up and largely fulfills demands for both Val and Leu for protein synthesis. Third, excess α-ketobutyrate is transported into the mitochondria for Ile biosynthesis. However, the import does not efficiently inhibit the synthesis of α-ketobutyrate from pyruvate indicating that P. pastoris has not been optimized evolutionarily to take full advantage of this carbon source. These findings have direct implications for preparing uniformly ² H,¹³ C,¹⁵ N-labeled proteins containing protonated Ile, Val, and Leu methyl groups in P. pastoris for NMR-based structural biology.

ENZYMES

Acetohydroxy acid isomeroreductase (EC 1.1.1.86), branched-chain amino acid aminotransferase (BCAT, EC 2.6.1.42), fumarase (EC 4.2.1.2), malic enzyme (EC 1.1.1.39/1.1.1.40), phosphoenolpyruvate carboxykinase (EC 4.1.1.49), pyruvate carboxylase (EC 6.4.1.1), pyruvate kinase (EC 2.7.1.40), l-serine hydroxymethyltransferase (EC 2.1.2.1), threonine aldolase (EC 4.1.2.5), threonine dehydratase (EC 4.3.1.19); transketolase (EC 2.2.1.1), transaldolase (EC 2.2.1.2).

Improvement of uridine production of Bacillus subtilis by atmospheric and room temperature plasma mutagenesis and high-throughput screening

In the present study, a novel breeding strategy of atmospheric and room temperature plasma (ARTP) mutagenesis was used to improve the uridine production of engineered Bacillus subtilis TD12np. A high-throughput screening method was established using both resistant plates and 96-well microplates to select the ideal mutants with diverse phenotypes. Mutant F126 accumulated 5.7 and 30.3 g/L uridine after 30 h in shake-flask and 48 h in fed-batch fermentation, respectively, which represented a 4.4- and 8.7-fold increase over the parent strain. Sequence analysis of the pyrimidine nucleotide biosynthetic operon in the representative mutants showed that proline 1016 and glutamate 949 in the large subunit of B. subtilis carbamoyl phosphate synthetase were of importance for the allosteric regulation caused by uridine 5′-monophosphate. The proposed mutation method with efficient high-throughput screening assay was proved to be an appropriate strategy to obtain uridine-overproducing strain.

Synergizing 13C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production

Metabolic engineering of industrial microorganisms to produce chemicals, fuels, and drugs has attracted increasing interest as it provides an environment-friendly and renewable route that does not depend on depleting petroleum sources. However, the microbial metabolism is so complex that metabolic engineering efforts often have difficulty in achieving a satisfactory yield, titer, or productivity of the target chemical. To overcome this challenge, ¹³C Metabolic Flux Analysis (¹³C-MFA) has been developed to investigate rigorously the cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, ¹³C-MFA has been widely used in academic labs and the biotechnology industry to pinpoint the key issues related to microbial-based chemical production and to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this chapter we introduce the basics of ¹³C-MFA and illustrate how ¹³C-MFA has been applied to synergize with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production.

Quantification of Microbial Phenotypes

Metabolite profiling technologies have improved to generate close to quantitative metabolomics data, which can be employed to quantitatively describe the metabolic phenotype of an organism. Here, we review the current technologies available for quantitative metabolomics, present their advantages and drawbacks, and the current challenges to generate fully quantitative metabolomics data. Metabolomics data can be integrated into metabolic networks using thermodynamic principles to constrain the directionality of reactions. Here we explain how to estimate Gibbs energy under physiological conditions, including examples of the estimations, and the different methods for thermodynamics-based network analysis. The fundamentals of the methods and how to perform the analyses are described. Finally, an example applying quantitative metabolomics to a yeast model by 13C fluxomics and thermodynamics-based network analysis is presented. The example shows that (1) these two methods are complementary to each other; and (2) there is a need to take into account Gibbs energy errors. Better estimations of metabolic phenotypes will be obtained when further constraints are included in the analysis.

PFA toolbox: a MATLAB tool for Metabolic Flux Analysis

BACKGROUND

Metabolic Flux Analysis (MFA) is a methodology that has been successfully applied to estimate metabolic fluxes in living cells. However, traditional frameworks based on this approach have some limitations, particularly when measurements are scarce and imprecise. This is very common in industrial environments. The PFA Toolbox can be used to face those scenarios.

RESULTS

Here we present the PFA (Possibilistic Flux Analysis) Toolbox for MATLAB, which simplifies the use of Interval and Possibilistic Metabolic Flux Analysis. The main features of the PFA Toolbox are the following: (a) It provides reliable MFA estimations in scenarios where only a few fluxes can be measured or those available are imprecise. (b) It provides tools to easily plot the results as interval estimates or flux distributions. (c) It is composed of simple functions that MATLAB users can apply in flexible ways. (d) It includes a Graphical User Interface (GUI), which provides a visual representation of the measurements and their uncertainty. (e) It can use stoichiometric models in COBRA format. In addition, the PFA Toolbox includes a User's Guide with a thorough description of its functions and several examples.

CONCLUSIONS

The PFA Toolbox for MATLAB is a freely available Toolbox that is able to perform Interval and Possibilistic MFA estimations.

Carbon material distribution and flux analysis under varying glucose concentrations in hydrogen-producing Clostridium tyrobutyricum JM1

Anaerobic glucose metabolism in hydrogen-producing Clostridium tyrobutyricum was investigated in batch culture with varying initial glucose concentrations (27.8-333.6mM). To understand the regulation of metabolism, the carbon material and reduction balances were applied to estimate the carbon flux distribution for the first time, and metabolic flux analysis (MFA) was used to provide qualitative information and guidance for effective metabolic design. The overall flux distribution suggested that C. tyrobutyricum metabolism has a high capacity for the production of butyrate and hydrogen at an initial glucose concentration of 222.4mM, with balanced activities of NADH and ATP.

13C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production

Metabolic engineering of various industrial microorganisms to produce chemicals, fuels, and drugs has raised interest since it is environmentally friendly, sustainable, and independent of nonrenewable resources. However, microbial metabolism is so complex that only a few metabolic engineering efforts have been able to achieve a satisfactory yield, titer or productivity of the target chemicals for industrial commercialization. In order to overcome this challenge, ¹³C Metabolic Flux Analysis (¹³C-MFA) has been continuously developed and widely applied to rigorously investigate cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, many ¹³C-MFA studies have been performed in academic labs and biotechnology industries to pinpoint key issues related to microbe-based chemical production. Insightful information about the metabolic rewiring has been provided to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this review, we will introduce the basics of ¹³C-MFA and illustrate how ¹³C-MFA has been applied via integration with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production for various host microorganisms

Tracking the metabolic pulse of plant lipid production with isotopic labeling and flux analyses: Past, present and future

Metabolism is comprised of networks of chemical transformations, organized into integrated biochemical pathways that are the basis of cellular operation, and function to sustain life. Metabolism, and thus life, is not static. The rate of metabolites transitioning through biochemical pathways (i.e., flux) determines cellular phenotypes, and is constantly changing in response to genetic or environmental perturbations. Each change evokes a response in metabolic pathway flow, and the quantification of fluxes under varied conditions helps to elucidate major and minor routes, and regulatory aspects of metabolism. To measure fluxes requires experimental methods that assess the movements and transformations of metabolites without creating artifacts. Isotopic labeling fills this role and is a long-standing experimental approach to identify pathways and quantify their metabolic relevance in different tissues or under different conditions. The application of labeling techniques to plant science is however far from reaching it potential. In light of advances in genetics and molecular biology that provide a means to alter metabolism, and given recent improvements in instrumentation, computational tools and available isotopes, the use of isotopic labeling to probe metabolism is becoming more and more powerful. We review the principal analytical methods for isotopic labeling with a focus on seminal studies of pathways and fluxes in lipid metabolism and carbon partitioning through central metabolism. Central carbon metabolic steps are directly linked to lipid production by serving to generate the precursors for fatty acid biosynthesis and lipid assembly. Additionally some of the ideas for labeling techniques that may be most applicable for lipid metabolism in the future were originally developed to investigate other aspects of central metabolism. We conclude by describing recent advances that will play an important future role in quantifying flux and metabolic operation in plant tissues.

Fluxome study of Pseudomonas fluorescens reveals major reorganisation of carbon flux through central metabolic pathways in response to inactivation of the anti-sigma factor MucA

Background

The bacterium Pseudomonas fluorescens switches to an alginate-producing phenotype when the pleiotropic anti-sigma factor MucA is inactivated. The inactivation is accompanied by an increased biomass yield on carbon sources when grown under nitrogen-limited chemostat conditions. A previous metabolome study showed significant changes in the intracellular metabolite concentrations, especially of the nucleotides, in mucA deletion mutants compared to the wild-type. In this study, the P. fluorescens SBW25 wild-type and an alginate non-producing mucA- ΔalgC double-knockout mutant are investigated through model-based ¹³C-metabolic flux analysis (¹³C-MFA) to explore the physiological consequences of MucA inactivation at the metabolic flux level. Intracellular metabolite extracts from three carbon labelling experiments using fructose as the sole carbon source are analysed for ¹³C-label incorporation in primary metabolites by gas and liquid chromatography tandem mass spectrometry.

Results

From mass isotopomer distribution datasets, absolute intracellular metabolic reaction rates for the wild type and the mutant are determined, revealing extensive reorganisation of carbon flux through central metabolic pathways in response to MucA inactivation. The carbon flux through the Entner-Doudoroff pathway was reduced in the mucA- ΔalgC mutant, while flux through the pentose phosphate pathway was increased. Our findings also indicated flexibility of the anaplerotic reactions through down-regulation of the pyruvate shunt in the mucA- ΔalgC mutant and up-regulation of the glyoxylate shunt.

Conclusions

Absolute metabolic fluxes and metabolite levels give detailed, integrated insight into the physiology of this industrially, medically and agriculturally important bacterial species and suggest that the most efficient way of using a mucA- mutant as a cell factory for alginate production would be to use non-growing conditions and nitrogen deprivation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0148-0) contains supplementary material, which is available to authorized users.

Large-Scale 13C flux profiling reveals conservation of the Entner-Doudoroff pathway as a glycolytic strategy among marine bacteria that use glucose

Marine bacteria form one of the largest living surfaces on Earth, and their metabolic activity is of fundamental importance for global nutrient cycling. Here, we explored the largely unknown intracellular pathways in 25 microbes representing different classes of marine bacteria that use glucose: Alphaproteobacteria, Gammaproteobacteria, and Flavobacteriia of the Bacteriodetes phylum. We used (13)C isotope experiments to infer metabolic fluxes through their carbon core pathways. Notably, 90% of all strains studied use the Entner-Doudoroff (ED) pathway for glucose catabolism, whereas only 10% rely on the Embden-Meyerhof-Parnas (EMP) pathway. This result differed dramatically from the terrestrial model strains studied, which preferentially used the EMP pathway yielding high levels of ATP. Strains using the ED pathway exhibited a more robust resistance against the oxidative stress typically found in this environment. An important feature contributing to the preferential use of the ED pathway in the oceans could therefore be enhanced supply of NADPH through this pathway. The marine bacteria studied did not specifically rely on a distinct anaplerotic route, but the carboxylation of phosphoenolpyruvate (PEP) or pyruvate for fueling of the tricarboxylic acid (TCA) cycle was evenly distributed. The marine isolates studied belong to clades that dominate the uptake of glucose, a major carbon source for bacteria in seawater. Therefore, the ED pathway may play a significant role in the cycling of mono- and polysaccharides by bacterial communities in marine ecosystems.

Model-driven redox pathway manipulation for improved isobutanol production in Bacillus subtilis complemented with experimental validation and metabolic profiling analysis

To rationally guide the improvement of isobutanol production, metabolic network and metabolic profiling analysis were performed to provide global and profound insights into cell metabolism of isobutanol-producing Bacillus subtilis. The metabolic flux distribution of strains with different isobutanol production capacity (BSUL03, BSUL04 and BSUL05) drops a hint of the importance of NADPH on isobutanol biosynthesis. Therefore, the redox pathways were redesigned in this study. To increase NADPH concentration, glucose-6-phosphate isomerase was inactivated (BSUL06) and glucose-6-phosphate dehydrogenase was overexpressed (BSUL07) successively. As expected, NADPH pool size in BSUL07 was 4.4-fold higher than that in parental strain BSUL05. However, cell growth, isobutanol yield and production were decreased by 46%, 22%, and 80%, respectively. Metabolic profiling analysis suggested that the severely imbalanced redox status might be the primary reason. To solve this problem, gene udhA of Escherichia coli encoding transhydrogenase was further overexpressed (BSUL08), which not only well balanced the cellular ratio of NAD(P)H/NAD(P)⁺, but also increased NADH and ATP concentration. In addition, a straightforward engineering approach for improving NADPH concentrations was employed in BSUL05 by overexpressing exogenous gene pntAB and obtained BSUL09. The performance for isobutanol production by BSUL09 was poorer than BSUL08 but better than other engineered strains. Furthermore, in fed-batch fermentation the isobutanol production and yield of BSUL08 increased by 11% and 19%, up to the value of 6.12 g/L and 0.37 C-mol isobutanol/C-mol glucose (63% of the theoretical value), respectively, compared with parental strain BSUL05. These results demonstrated that model-driven complemented with metabolic profiling analysis could serve as a useful approach in the strain improvement for higher bio-productivity in further application.

Kinetic modeling of riboflavin biosynthesis in Bacillus subtilis under production conditions

To study the network dynamics of the riboflavin biosynthesis pathway and to identify potential bottlenecks in the system, an ordinary differential equation-based model was constructed using available literature data for production strains. The results confirmed that the RibA protein is rate limiting in the pathway. Under the conditions investigated, we determined a potential limiting order of the remaining enzymes under increased RibA concentration (>0.102 mM) and therefore higher riboflavin production (>0.045 mmol g(CDW)(-1) h(-1) and 0.0035 mM s(-1), respectively). The reductase activity of RibG and lumazine synthase (RibH) might be the next most limiting steps. The computational minimization of the enzyme concentrations of the pathway suggested the need for a greater RibH concentration (0.251 mM) compared with the other enzymes (RibG: 0.188 mM, RibB: 0.023 mM).

Labelling analysis for ¹³C MFA using NMR spectroscopy

NMR spectroscopy is an efficient method for analyzing (13)C labelling of cellular metabolites. The strength of it is especially the ability to provide direct quantitative positional information on the (13)C labelling status of carbon atoms in metabolites. NMR spectroscopic methods allow also for detection of contiguously (13)C-labelled fragments in the carbon backbones of the metabolites. Furthermore, the recent developments of NMR spectroscopy hardware have substantially improved the sensitivity of the methods. In this chapter we describe a method for analyzing the (13)C labelling of the biomass amino acids for metabolic flux analysis, sample preparation for NMR spectroscopy, acquiring and processing the NMR spectra, and extracting the (13)C labelling information from the NMR data. Different NMR methods are applied depending on the (13)C labelling strategy chosen. These strategies include uniform (13)C labelling, positional (13)C labelling, or a combination of both. Not only the preparation of sample for analysis of (13)C labelling in proteinogenic amino acids in biomass is described, but also the necessary modifications to the method when analysis of (13)C labelling in free metabolic intermediates is of interest. Finally the strategies for using the different NMR-detected (13)C labelling data in (13)C MFA are discussed.

¹³C-based metabolic flux analysis in yeast: the Pichia pastoris case

Metabolic flux analysis based on tracing patterns of stable isotopes, particularly (13)C, comprises a set of methodologies to experimentally quantify intracellular biochemical reaction rates, i.e., to measure carbon flux distributions through a metabolic network. This allows quantifying the response of a metabolic network to an environmental or genetic perturbation (i.e., the metabolic phenotype). Here, we describe a protocol based on growing yeast on a (13)C-labelled substrate and subsequent NMR detection of (13)C-patterns in proteinogenic amino acids. To calculate metabolic fluxes, we describe two complementary mathematical approaches using available software; namely, an approach based on the estimation of local ratios in network nodes, and a method based on a global iterative fitting approach. Furthermore, we consider specificities of these protocols for their application to the yeast Pichia pastoris growing on multicarbon substrates other than glucose (glycerol), as well as the case when methanol is used as co-substrate in combination with glucose or glycerol.

Kinetic isotope effects significantly influence intracellular metabolite (13) C labeling patterns and flux determination

Rigorous mathematical modeling of carbon-labeling experiments allows estimation of fluxes through the pathways of central carbon metabolism, yielding powerful information for basic scientific studies as well as for a wide range of applications. However, the mathematical models that have been developed for flux determination from (13) C labeling data have commonly neglected the influence of kinetic isotope effects on the distribution of (13) C label in intracellular metabolites, as these effects have often been assumed to be inconsequential. We have used measurements of the (13) C isotope effects on the pyruvate dehydrogenase enzyme from the literature to model isotopic fractionation at the pyruvate node and quantify the modeling errors expected to result from the assumption that isotope effects are negligible. We show that under some conditions kinetic isotope effects have a significant impact on the (13) C labeling patterns of intracellular metabolites, and the errors associated with neglecting isotope effects in (13) C-metabolic flux analysis models can be comparable in size to measurement errors associated with GC-MS. Thus, kinetic isotope effects must be considered in any rigorous assessment of errors in (13) C labeling data, goodness-of-fit between model and data, confidence intervals of estimated metabolic fluxes, and statistical significance of differences between estimated metabolic flux distributions.

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.

Malate metabolism in Bacillus subtilis: distinct roles for three classes of malate-oxidizing enzymes

The Gram-positive soil bacterium Bacillus subtilis uses glucose and malate as the preferred carbon sources. In the presence of either glucose or malate, the expression of genes and operons for the utilization of secondary carbon sources is subject to carbon catabolite repression. While glucose is a preferred substrate in many organisms from bacteria to man, the factors that contribute to the preference for malate have so far remained elusive. In this work, we have studied the contribution of the different malate-metabolizing enzymes in B. subtilis, and we have elucidated their distinct functions. The malate dehydrogenase and the phosphoenolpyruvate carboxykinase are both essential for malate utilization; they introduce malate into gluconeogenesis. The NADPH-generating malic enzyme YtsJ is important to establish the cellular pools of NADPH for anabolic reactions. Finally, the NADH-generating malic enzymes MaeA, MalS, and MleA are involved in keeping the ATP levels high. Together, this unique array of distinct activities makes malate a preferred carbon source for B. subtilis.

Genome-based kinetic modeling of cytosolic glucose metabolism in industrially relevant cell lines: Saccharomyces cerevisiae and Chinese hamster ovary cells

Model-based analysis of cellular metabolism can facilitate our understanding of intracellular kinetics and aid the improvement of cell growth and biological product manufacturing. In this paper, a model-based kinetic study of cytosolic glucose metabolism for two industrially relevant cell lines, Saccharomyces cerevisiae and Chinese hamster ovary (CHO) cells, based on enzyme genetic presence and expression information is described. We have reconstructed the cytosolic glucose metabolism map for S. cerevisiae and CHO cells, containing 18 metabolites and 18 enzymes using information from the Kyoto Encyclopedia of Genes and Genomes (KEGG). Based on this map, we have developed akinetic mathematical model for the pathways involved,considering regulation and/or inhibition by products orco-substrates. The values of the maximum rates of reactions(V(max)) were estimated based on kinetic parameter information and metabolic flux analysis results available in literature, and the resulting simulation results for steady-state metabolite concentrations are in good agreement with published experimental data. Finally, the model was used to analyse how the production of DHAP, an important intermediate in fine chemicals synthesis, could be increased using gene knockout.

Metabolic flexibility of d-ribose producer strain of Bacillus pumilus under environmental perturbations

The metabolic reaction rate vector is a bridge that links gene and protein expression alterations to the phenotypic endpoint. We present a simple approach for the estimation of flux distribution at key branch points in the metabolic network by using substrate uptake, metabolite secretion rate, and biomass growth rate for transketolase (tkt) deficient Bacillus pumilus ATCC 21951. We find that the glucose-6-phosphate (G6P) and pseudo catabolic/anabolic branch points are flexible in the d-ribose-producing tkt deficient strain of B. pumilus. The normalized flux through the pentose phosphate pathway (PPP) varied from 1.5 to 86 % under different growth conditions, thereby enabling substantial extracellular accumulation of d-ribose under certain conditions. Interestingly, the flux through PPP was affected by the extracellular phosphate concentration and dissolved oxygen concentration. This metabolic flexibility may have been the underlying reason for this strain being selected from thousands of others in a screening for d-ribose producers conducted in the 1970s.

13C-flux analysis reveals NADPH-balancing transhydrogenation cycles in stationary phase of nitrogen-starving Bacillus subtilis

In their natural habitat, microorganisms are typically confronted with nutritional limitations that restrict growth and force them to persevere in a stationary phase. Despite the importance of this phase, little is known about the metabolic state(s) that sustains it. Here, we investigate metabolically active but non-growing Bacillus subtilis during nitrogen starvation. In the absence of biomass formation as the major NADPH sink, the intracellular flux distribution in these resting B. subtilis reveals a large apparent catabolic NADPH overproduction of 5.0 ± 0.6 mmol g(-1)h(-1) that was partly caused by high pentose phosphate pathway fluxes. Combining transcriptome analysis, stationary (13)C-flux analysis in metabolic deletion mutants, (2)H-labeling experiments, and kinetic flux profiling, we demonstrate that about half of the catabolic excess NADPH is oxidized by two transhydrogenation cycles, i.e. isoenzyme pairs of dehydrogenases with different cofactor specificities that operate in reverse directions. These transhydrogenation cycles were constituted by the combined activities of the glyceraldehyde 3-phosphate dehydrogenases GapA/GapB and the malic enzymes MalS/YtsJ. At least an additional 6% of the overproduced NADPH is reoxidized by continuous cycling between ana- and catabolism of glutamate. Furthermore, in vitro enzyme data show that a not yet identified transhydrogenase could potentially reoxidize ∼20% of the overproduced NADPH. Overall, we demonstrate the interplay between several metabolic mechanisms that concertedly enable network-wide NADPH homeostasis under conditions of high catabolic NADPH production in the absence of cell growth in B. subtilis.

Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico

BACKGROUND

Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico.

RESULTS

A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production.

CONCLUSIONS

FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

Recent advances in engineering the central carbon metabolism of industrially important bacteria

This paper gives an overview of the recent advances in engineering the central carbon metabolism of the industrially important bacteria Escherichia coli, Bacillus subtilis, Corynobacterium glutamicum, Streptomyces spp., Lactococcus lactis and other lactic acid bacteria. All of them are established producers of important classes of products, e.g. proteins, amino acids, organic acids, antibiotics, high-value metabolites for the food industry and also, promising producers of a large number of industrially or therapeutically important chemicals. Optimization of existing or introduction of new cellular processes in these microorganisms is often achieved through manipulation of targets that reside at major points of central metabolic pathways, such as glycolysis, gluconeogenesis, the pentose phosphate pathway and the tricarboxylic acid cycle with the glyoxylate shunt. Based on the huge progress made in recent years in biochemical, genetic and regulatory studies, new fascinating engineering approaches aim at ensuring an optimal carbon and energy flow within central metabolism in order to achieve optimized metabolite production.

Malate-mediated carbon catabolite repression in Bacillus subtilis involves the HPrK/CcpA pathway

Most organisms can choose their preferred carbon source from a mixture of nutrients. This process is called carbon catabolite repression. The Gram-positive bacterium Bacillus subtilis uses glucose as the preferred source of carbon and energy. Glucose-mediated catabolite repression is caused by binding of the CcpA transcription factor to the promoter regions of catabolic operons. CcpA binds DNA upon interaction with its cofactors HPr(Ser-P) and Crh(Ser-P). The formation of the cofactors is catalyzed by the metabolite-activated HPr kinase/phosphorylase. Recently, it has been shown that malate is a second preferred carbon source for B. subtilis that also causes catabolite repression. In this work, we addressed the mechanism by which malate causes catabolite repression. Genetic analyses revealed that malate-dependent catabolite repression requires CcpA and its cofactors. Moreover, we demonstrate that HPr(Ser-P) is present in malate-grown cells and that CcpA and HPr interact in vivo in the presence of glucose or malate but not in the absence of a repressing carbon source. The formation of the cofactor HPr(Ser-P) could be attributed to the concentrations of ATP and fructose 1,6-bisphosphate in cells growing with malate. Both metabolites are available at concentrations that are sufficient to stimulate HPr kinase activity. The adaptation of cells to environmental changes requires dynamic metabolic and regulatory adjustments. The repression strength of target promoters was similar to that observed in steady-state growth conditions, although it took somewhat longer to reach the second steady-state of expression when cells were shifted to malate.

Quantification of metabolic limitations during recombinant protein production in Escherichia coli

Escherichia coli is one of the major microorganisms for recombinant protein production because it has been best characterized in terms of molecular genetics and physiology, and because of the availability of various expression vectors and strains. The synthesis of proteins is one of the most energy consuming processes in the cell, with the result that cellular energy supply may become critical. Indeed, the so called metabolic burden of recombinant protein synthesis was reported to cause alterations in the operation of the host's central carbon metabolism. To quantify these alterations in E. coli metabolism in dependence of the rate of recombinant protein production, (13)C-tracer-based metabolic flux analysis in differently induced cultures was used. To avoid dilution of the (13)C-tracer signal by the culture history, the recombinant protein produced was used as a flux probe, i.e., as a read out of intracellular flux distributions. In detail, an increase in the generation rate rising from 36 mmol(ATP)g(CDW)(-1)h(-1) for the reference strain to 45 mmol(ATP)g(CDW)(-1)h(-1) for the highest yielding strain was observed during batch cultivation. Notably, the flux through the TCA cycle was rather constant at 2.5±0.1 mmol g(CDW)(-1)h(-1), hence was independent of the induced strength for gene expression. E. coli compensated for the additional energy demand of recombinant protein synthesis by reducing the biomass formation to almost 60%, resulting in excess NADPH. Speculative, this excess NADPH was converted to NADH via the soluble transhydrogenase and subsequently used for ATP generation in the electron transport chain. In this study, the metabolic burden was quantified by the biomass yield on ATP, which constantly decreased from 11.7g(CDW)mmol(ATP)(-1) for the reference strain to 4.9g(CDW)mmol(ATP)(-1) for the highest yielding strain. The insights into the operation of the metabolism of E. coli during recombinant protein production might guide the optimization of microbial hosts and fermentation conditions.

Bridging the gap between fluxomics and industrial biotechnology

Metabolic flux analysis is a vital tool used to determine the ultimate output of cellular metabolism and thus detect biotechnologically relevant bottlenecks in productivity. ¹³C-based metabolic flux analysis (¹³C-MFA) and flux balance analysis (FBA) have many potential applications in biotechnology. However, noteworthy hurdles in fluxomics study are still present. First, several technical difficulties in both ¹³C-MFA and FBA severely limit the scope of fluxomics findings and the applicability of obtained metabolic information. Second, the complexity of metabolic regulation poses a great challenge for precise prediction and analysis of metabolic networks, as there are gaps between fluxomics results and other omics studies. Third, despite identified metabolic bottlenecks or sources of host stress from product synthesis, it remains difficult to overcome inherent metabolic robustness or to efficiently import and express nonnative pathways. Fourth, product yields often decrease as the number of enzymatic steps increases. Such decrease in yield may not be caused by rate-limiting enzymes, but rather is accumulated through each enzymatic reaction. Fifth, a high-throughput fluxomics tool hasnot been developed for characterizing nonmodel microorganisms and maximizing their application in industrial biotechnology. Refining fluxomics tools and understanding these obstacles will improve our ability to engineer highlyefficient metabolic pathways in microbial hosts.