Metabolic flux analysis of a glycerol-overproducing Saccharomyces cerevisiae strain based on GC-MS, LC-MS and NMR-derived C-labelling data

This study focuses on unravelling the carbon and redox metabolism of a previously developed glycerol-overproducing Saccharomyces cerevisiae strain with deletions in the structural genes encoding triosephosphate isomerase (TPI1), the external mitochondrial NADH dehydrogenases (NDE1 and NDE2) and the respiratory chain-linked glycerol-3-phosphate dehydrogenase (GUT2). Two methods were used for analysis of metabolic fluxes: metabolite balancing and (13)C-labelling-based metabolic flux analysis. The isotopic enrichment of intracellular primary metabolites was measured both directly (liquid chromatography-MS) and indirectly through proteinogenic amino acids (nuclear magnetic resonance and gas chromatography-MS). Because flux sensitivity around several important metabolic nodes proved to be dependent on the applied technique, the combination of the three (13)C quantification techniques generated the most accurate overall flux pattern. When combined, the measured conversion rates and (13)C-labelling data provided evidence that a combination of assimilatory metabolism and pentose phosphate pathway activity diverted some of the carbon away from glycerol formation. Metabolite balancing indicated that this results in excess cytosolic NADH, suggesting the presence of a cytosolic NADH sink in addition to those that were deleted. The exchange flux of four-carbon dicarboxylic acids across the mitochondrial membrane, as measured by the (13)C-labelling data, supports a possible role of a malate/aspartate or malate/oxaloacetate redox shuttle in the transfer of these redox equivalents from the cytosol to the mitochondrial matrix.     

Metabolic flux analysis of the sterol pathway in the yeast Saccharomyces cerevisiae

The yeast Saccharomyces cerevisiae is a useful model system for examining the biosynthesis of sterols in eukaryotic cells. To investigate underlying regulation mechanisms, a flux analysis of the ergosterol pathway was performed. A stoichiometric model was derived based on well known biochemistry of the pathway. The model was integrated in the Software COMPFlux which uses a global optimization algorithm for the estimation of intracellular fluxes. Sterol concentration patterns were determined by gas chromatography in aerobic and anaerobic batch cultivations, when the sterol metabolism was suppressed due to the absence of oxygen. In addition, the sterol concentrations were observed in a cultivation which was shifted from anaerobic to aerobic growth conditions causing the sterol pools in the cell to be filled. From time-dependent flux patterns, possible limitations in the pathway could be localized and the esterification of sterols was identified as an integral part of regulation in ergosterol biosynthesis.     

Metabolic flux network and analysis of fermentative hydrogen production

Fermentative hydrogen production (FHP) has received a great R & D interest in recent decades, as it offers a potential means of producing H₂ from a variety of renewable resources, even wastewater via a low energy continuous process. Various extracellular metabolites including ethanol, acetate, butyrate and lactate can be produced during the fermentation, building a complex metabolic network of the FHP. Except for the recognition of its complexity, the metabolic flux network has not been well understood. Studies on biochemical reactions and metabolic flux network associated with the FHP in anaerobic fermentation system have only been drawn attention in recent years. This review summarizes the biochemical reactions taking place in the metabolic network of FHP. We discuss how the key operation factors influence metabolism in the FHP process. Recently developed and applied technologies for metabolic flux analysis have been described. Future studies on the metabolic network to enhance fermentative hydrogen production by strict anaerobes are recommended. It is expected that this review can provide useful information in terms of fundamental knowledge and update technology for scientists and research engineers in the field of biological hydrogen production.     

Metabolic flux analyses for serine alkaline protease production

The intracellular metabolic fluxes through the central carbon pathways in Bacillus licheniformis in serine alkaline protease (SAP) production were calculated to predict the potential strategies for increasing the performance of the bacilli, by using two optimization approaches, i.e. the theoretical data-based (TDA) and the theoretical data-based capacity (TDC) analyses based on respectively minimum in-vivo SAP accumulation rate and maximum SAP synthesis rate assumptions, at low-, medium-, and high-oxygen transfer conditions. At all periods of low-oxygen transfer condition, in lag and early exponential periods of medium-oxygen transfer (MOT) condition, and SAP synthesis period of high-oxygen transfer (HOT) condition, the TDA and TDC analyses revealed that SAP overproduction capacity is almost equal to the observed SAP production due to the regulation effect of the oxygen transfer. In the growth and early SAP synthesis period and in SAP synthesis period at MOT condition the calculated results of the two analyses reveal that SAP synthesis rate of the microorganism can be increased 7.2 and 16.7 folds, respectively; whereas, in the growth and early SAP synthesis period at HOT condition it can be increased 12.6 folds. The diversions in the biochemical reaction network and the influence of the oxygen transfer on the performance of the bacilli were also presented. The results encourage the application of metabolic engineering for lifting the rate limitations and for improving the genetic regulations in order to increase the SAP production.     

Metabolic flux analysis for calcium dependent antibiotic (CDA) production in Streptomyces coelicolor

The calcium dependent antibiotic (CDA) is a nonribosomal lipopeptide produced by Streptomyces coelicolor. We constructed a metabolic network of more than 400 reactions for the primary and secondary metabolism of S. coelicolor and used computational metabolic flux balancing to investigate some of the factors affecting growth and production of CDA. Computational results indicated that the CDA production was concomitant with growth. Computational specific growth rates were twice as high as the experimental specific growth rates. Metabolic flux distributions and sensitivity analyses computed for various phases of the batch culture indicated that the specific CDA production rate was affected by nitrogen assimilation, pentose phosphate pathway, shikimate biosynthesis, and oxoglutarate fluxes. Consequently, these metabolic targets were tested using genetic deletions in the model which increased the in silico specific CDA production rate.     

Metabolic flux analysis ofBeijerinckia indica for PS-7 production

In order to investigate central metabolic changes inBeijerinckia indica, cells were grown on different carbon sources and intracellular flux distributions were studied under varying concentrations of nitrogen. Metabolic fluxes were estimated by combining material balances with extracellular substrate uptake rate, biomass formation rate, and exopolysaccharide (EPS) accumulation rate. Thirty-one metabolic reactions and 30 intracellular metabolites were considered for the flux analysis. The results revealed that most of the carbon source was directed into the Entner-Doudoroff pathway, followed by the recycling of triose-3-phosphate back to Hexose-6-phosphate. The pentose phosphate pathway was operated at a minimal level to supply the precursors for biomass formation. The different metabolic behaviors under varying nitrogen concentrations were observed with flux analysis.     

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 control analysis of branch points: an improved approach to obtain flux control coefficients from large perturbation data

An overview of published approaches for the metabolic flux control analysis of branch points revealed that often not all fundamental constraints on the flux control coefficients have been taken into account. This has led to contradictory statements in literature on the minimum number of large perturbation experiments required to estimate the complete set of flux control coefficients C(J) for a metabolic branch point. An improved calculation procedure, based on approximate Lin-log reaction kinetics, is proposed, providing explicit analytical solutions of steady state fluxes and metabolite concentrations as a function of large changes in enzyme levels. The obtained solutions allow direct calculation of elasticity ratios from experimental data and subsequently all C(J)-values from the unique relation between elasticity ratio's and flux control coefficients. This procedure ensures that the obtained C(J)-values satisfy all fundamental constraints. From these it follows that for a three enzyme branch point only one characterised or two uncharacterised large flux perturbations are sufficient to obtain all C(J)- values. The improved calculation procedure is illustrated with four experimental cases.     

Genetically constrained metabolic flux analysis

Significant progress has been made in using existing metabolic databases to estimate metabolic fluxes. Traditional metabolic flux analysis generally starts with a predetermined metabolic network. This approach has been employed successfully to analyze the behaviors of recombinant strains by manually adding or removing the corresponding pathway(s) in the metabolic map. The current work focuses on the development of a new framework that utilizes genomic and metabolic databases, including available genetic/regulatory network structures and gene chip expression data, to constrain metabolic flux analysis. The genetic network consisting of the sensing/regulatory circuits will activate or deactivate a specific set of genes in response to external stimulus. The activation and/or repression of this set of genes will result in different gene expression levels that will in turn change the structure of the metabolic map. Hence, the metabolic map will automatically "adapt" to the external stimulus as captured by the genetic network. This adaptation selects a subnetwork from the pool of feasible reactions and so performs what we term "environmentally driven dimensional reduction." The Escherichia coli oxygen and redox sensing/regulatory system, which controls the metabolic patterns connected to glycolysis and the TCA cycle, was used as a model system to illustrate the proposed approach.     

Metabolic flux and robustness analysis of glycerol metabolism in <Emphasis Type="Italic">Klebsiella pneumoniae</Emphasis>

The knowledge of the mechanism of flux distribution will benefit understanding cell physiology and regulation of metabolism. In this study, the measured fluxes obtained under steady-state conditions were used to estimate intracellular fluxes and identify the robustness of branch points of the anaerobic glycerol metabolism in Klebsiella pneumoniae for the production of 1,3-propanediol by metabolic flux analysis. The biomass concentration increased as NADH₂/NAD⁺ decreased at low initial concentration and inversed at high initial glycerol concentration. The flux distribution revealed that the branch points of glycerol and dihydroxyacetonephosphate were rigid to the environmental conditions. However, the pyruvate and acetyl coenzyme A metabolisms gave cells the flexibility to regulate the energy and intermediate fluxes under various environmental conditions. Additionly, it was found that the formation rate of ethanol and the ratio of pyruvate dehydrogenase to pyruvate formate lyase appeared visible fluctuations at high glycerol uptake rate.     

Metabolic flux analysis of the non-transitory starch tradeoff for lipid production in mature tobacco leaves

The metabolic plasticity of tobacco leaves has been demonstrated via the generation of transgenic plants that can accumulate over 30% dry weight as triacylglycerols. In investigating the changes in carbon partitioning in these high lipid-producing (HLP) leaves, foliar lipids accumulated stepwise over development. Interestingly, non-transient starch was observed to accumulate with plant age in WT but not HLP leaves, with a drop in foliar starch concurrent with an increase in lipid content. The metabolic carbon tradeoff between starch and lipid was studied using ¹³CO₂-labeling experiments and isotopically nonstationary metabolic flux analysis, not previously applied to the mature leaves of a crop. Fatty acid synthesis was investigated through assessment of acyl-acyl carrier proteins using a recently derived quantification method that was extended to accommodate isotopic labeling. Analysis of labeling patterns and flux modeling indicated the continued production of unlabeled starch, sucrose cycling, and a significant contribution of NADP-malic enzyme to plastidic pyruvate production for the production of lipids in HLP leaves, with the latter verified by enzyme activity assays. The results suggest an inherent capacity for a developmentally regulated carbon sink in tobacco leaves and may in part explain the uniquely successful leaf lipid engineering efforts in this crop.     

Isotopic non-stationary 13C gluconate tracer method for accurate determination of the pentose phosphate pathway split-ratio in Penicillium chrysogenum

Current (13)C labeling experiments for metabolic flux analysis (MFA) are mostly limited by either the requirement of isotopic steady state or the extremely high computational effort due to the size and complexity of large metabolic networks. The presented novel approach circumvents these limitations by applying the isotopic non-stationary approach to a local metabolic network. The procedure is demonstrated in a study of the pentose phosphate pathway (PPP) split-ratio of Penicillium chrysogenum in a penicillin-G producing chemostat-culture grown aerobically at a dilution rate of 0.06h(-1) on glucose, using a tracer amount of uniformly labeled [U-(13)C(6)] gluconate. The rate of labeling inflow can be controlled by using different cell densities and/or different fractions of the labeled tracer in the feed. Due to the simplicity of the local metabolic network structure around the 6-phosphogluconate (6pg) node, only three metabolites need to be measured for the pool size and isotopomer distribution. Furthermore, the mathematical modeling of isotopomer distributions for the flux estimation has been reduced from large scale differential equations to algebraic equations. Under the studied cultivation condition, the estimated split-ratio (41.2+/-0.6%) using the novel approach, shows statistically no difference with the split-ratio obtained from the originally proposed isotopic stationary gluconate tracing method.     

Metabolic flux analysis of CHO cell metabolism in the late non‐growth phase

Chinese hamster ovary (CHO) cell cultures are commonly used for production of recombinant human therapeutic proteins. Often the goal of such a process is to separate the growth phase of the cells, from the non‐growth phase where ideally the cells are diverting resources to produce the protein of interest. Characterizing the way that the cells use nutrients in terms of metabolic fluxes as a function of culture conditions can provide a deeper understanding of the cell biology offering guidance for process improvements. To evaluate the fluxes, metabolic flux analysis of the CHO cell culture in the non‐growth phase was performed by a combination of steady‐state isotopomer balancing and stoichiometric modeling. Analysis of the glycolytic pathway and pentose phosphate pathway (PPP) indicated that almost all of the consumed glucose is diverted towards PPP with a high NADPH production; with even recycle from PPP to G6P in some cases. Almost all of the pyruvate produced from glycolysis entered the TCA cycle with little or no lactate production. Comparison of the non‐growth phase against previously reported fluxes from growth phase cultures indicated marked differences in the fluxes, in terms of the split between glycolysis and PPP, and also around the pyruvate node. Possible reasons for the high NADPH production are also discussed. Evaluation of the fluxes indicated that the medium strength, carbon dioxide level, and temperature with dissolved oxygen have statistically significant impacts on different nodes of the flux network. Biotechnol. Bioeng. 2011; 108:82–92. © 2010 Wiley Periodicals, Inc.     

Flux analysis and metabolomics for systematic metabolic engineering of microorganisms

Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and ¹³C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering.     

Metabolic systems analysis to advance algal biotechnology

Algal fuel sources promise unsurpassed yields in a carbon neutral manner that minimizes resource competition between agriculture and fuel crops. Many challenges must be addressed before algal biofuels can be accepted as a component of the fossil fuel replacement strategy. One significant challenge is that the cost of algal fuel production must become competitive with existing fuel alternatives. Algal biofuel production presents the opportunity to fine-tune microbial metabolic machinery for an optimal blend of biomass constituents and desired fuel molecules. Genome-scale model-driven algal metabolic design promises to facilitate both goals by directing the utilization of metabolites in the complex, interconnected metabolic networks to optimize production of the compounds of interest. Network analysis can direct microbial development efforts towards successful strategies and enable quantitative fine-tuning of the network for optimal product yields while maintaining the robustness of the production microbe. Metabolic modeling yields insights into microbial function, guides experiments by generating testable hypotheses, and enables the refinement of knowledge on the specific organism. While the application of such analytical approaches to algal systems is limited to date, metabolic network analysis can improve understanding of algal metabolic systems and play an important role in expediting the adoption of new biofuel technologies.     

Effect of CO2 on succinate production in dual-phase Escherichia coli fermentations

Succinate production under different concentrations of carbon dioxide (CO₂) was studied in Escherichia coli AFP111, which contains mutations in pyruvate formate lyase (pfl), lactate dehydrogenase (ldhA) and the phosphotransferase system glucosephosphotransferase enzyme II (ptsG). A series of two-phase fermentations were conducted in which an aerobic cell growth phase was followed by an anaerobic succinate production phase using several constant concentrations of CO₂. As the concentration of CO₂ in the gas phase increased from 0% to 50%, the succinate specific productivity increased from 1.9 mg/g h to 225 mg/g h, and the succinate yield increased from 0.04 g/g to 0.75 g/g. Above 50% CO₂, succinate production did not increase further. Intracellular fluxes were determined at three different CO₂ concentrations (3%, 10%, and 50%) using ¹³C-label tracing coupled with LC–MS analysis. The fraction of carbon flux into the pentose phosphate pathway increased from 0.04 at 3% CO₂ to 0.17 at 50% CO₂. Also, the fractional flux through anaplerotic carboxylation at the phosphoenolpyruvate (PEP) node increased slightly from 0.53 at 3% CO₂ to 0.63 at 50% CO₂. The increased flux into the pentose phosphate pathway is attributed to an increased demand for reduced cofactors with elevated CO₂. A four-process explicit model to describe the CO₂ transfer and utilization was proposed. The model predicted that at CO₂ concentrations below about 30–40% the system becomes limited by gas phase CO₂, while at higher CO₂ concentrations the system is limited by PEP carboxylase enzyme kinetics.     

Metabolic flux analysis for optimizing the specific growth rate of recombinant <Emphasis Type="Italic">Aspergillus niger</Emphasis>

A comprehensive metabolic network comprising three intracellular compartments (cytoplasm, mitochondrion and peroxisome) was developed for Aspergillus niger. The metabolic flux network includes carbohydrate and amino acid metabolism in both anabolic and catabolic reactions. Linear programming was used for the optimization of the specific growth rates in combination with 37 measured input and output fluxes of the key metabolites to evaluate corresponding intracellular flux distributions throughout the batch fermentations. Logarithmic sensitivity analysis revealed that the addition of proline, alanine and glutamate benefited growth in defined media. The experimental observations and flux analysis showed that tyrosine was a potential candidate for biomass production improvement. Model predictions was verified by conducting batch and fed-batch fermentations and it was found that the addition of the four amino acids according to the predetermined schedule resulted in a 44 and 41% improvements in biomass and recombinant protein productions, respectively.     

Metabolic flux analyses of Pseudomonas aeruginosa cystic fibrosis isolates

Pseudomonas aeruginosa is a metabolically versatile wide-ranging opportunistic pathogen. In humans P. aeruginosa causes infections of the skin, urinary tract, blood, and the lungs of Cystic Fibrosis patients. In addition, P. aeruginosa's broad environmental distribution, relatedness to biotechnologically useful species, and ability to form biofilms have made it the focus of considerable interest. We used ¹³C metabolic flux analysis (MFA) and flux balance analysis to understand energy and redox production and consumption and to explore the metabolic phenotypes of one reference strain and five strains isolated from the lungs of cystic fibrosis patients. Our results highlight the importance of the oxidative pentose phosphate and Entner-Doudoroff pathways in P. aeruginosa growth. Among clinical strains we report two divergent metabolic strategies and identify changes between genetically related strains that have emerged during a chronic infection of the same patient. MFA revealed that the magnitude of fluxes through the glyoxylate cycle correlates with growth rates.     

Quantification of statin effects on hepatic cholesterol synthesis by transient C-flux analysis

The present work is the first to deal with the determination of cholesterol synthesis rates in primary rat hepatocytes using transient ¹³C-flux analysis. The effects of statins on cholesterol biosynthesis and central carbon fluxes were quantified at a therapeutic concentration of 50 nM atorvastatin using carbon-labeled glutamine. The flux through the cholesterol pathway decreased from 0.27 to 0.08 mmol/l_cv h in response to the administration of the hypolipidemic drug. Isotopic steady state was reached within 4 h in the central carbon metabolism but not in the cholesterol pathway, regardless of whether atorvastatin was administered or not. Marked channeling was observed for the symmetrical tricarboxylic acid cycle intermediates, succinate and fumarate. Non-stationary ¹³C-based flux identification delivers both intracellular fluxes and intermediate levels, which was for the first time utilized for investigating systems-level effects of the administered drug by quantifying the flux control of the 3-hydroxy-3-methylglutaryl-coenzyme A reductase.