Deoxyxylulose 5-Phosphate Synthase Does Not Play a Major Role in Regulating the Methylerythritol 4-Phosphate Pathway in Poplar.

The plastidic 2-C-methylerythritol 4-phosphate (MEP) pathway supplies the precursors of a large variety of essential plant isoprenoids, but its regulation is still not well understood. Using metabolic control analysis (MCA), we examined the first enzyme of this pathway, 1-deoxyxylulose 5-phosphate synthase (DXS), in multiple grey poplar (Populus × canescens) lines modified in their DXS activity. Single leaves were dynamically labeled with 13CO2 in an illuminated, climate-controlled gas exchange cuvette coupled to a proton transfer reaction mass spectrometer, and the carbon flux through the MEP pathway was calculated. Carbon was rapidly assimilated into MEP pathway intermediates and labeled both the isoprene released and the IDP+DMADP pool by up to 90%. DXS activity was increased by 25% in lines overexpressing the DXS gene and reduced by 50% in RNA interference lines, while the carbon flux in the MEP pathway was 25-35% greater in overexpressing lines and unchanged in RNA interference lines. Isoprene emission was also not altered in these different genetic backgrounds. By correlating absolute flux to DXS activity under different conditions of light and temperature, the flux control coefficient was found to be low. Among isoprenoid end products, isoprene itself was unchanged in DXS transgenic lines, but the levels of the chlorophylls and most carotenoids measured were 20-30% less in RNA interference lines than in overexpression lines. Our data thus demonstrate that DXS in the isoprene-emitting grey poplar plays only a minor part in controlling flux through the MEP pathway.

Increase in lysophosphatidate acyltransferase activity in oilseed rape (Brassica napus) increases seed triacylglycerol content despite its low intrinsic flux control coefficient.

Lysophosphatidate acyltransferase (LPAAT) catalyses the second step of the Kennedy pathway for triacylglycerol (TAG) synthesis. In this study we expressed Trapaeolum majus LPAAT in Brassica napus (B. napus) cv 12075 to evaluate the effects on lipid synthesis and estimate the flux control coefficient for LPAAT. We estimated the flux control coefficient of LPAAT in a whole plant context by deriving a relationship between it and overall lipid accumulation, given that this process is a exponential. Increasing LPAAT activity resulted in greater TAG accumulation in seeds of between 25% and 29%; altered fatty acid distributions in seed lipids (particularly those of the Kennedy pathway); and a redistribution of label from 14 C-glycerol between phosphoglycerides. Greater LPAAT activity in seeds led to an increase in TAG content despite its low intrinsic flux control coefficient on account of the exponential nature of lipid accumulation that amplifies the effect of the small flux increment achieved by increasing its activity. We have also developed a novel application of metabolic control analysis likely to have broad application as it determines the in planta flux control that a single component has upon accumulation of storage products.

Flux control-based design of furfural-resistance strains of Saccharomyces cerevisiae for lignocellulosic biorefinery.

We have previously developed a dynamic flux balance analysis of Saccharomyces cerevisiae for elucidation of genome-wide flux response to furfural perturbation (Unrean and Franzen, Biotechnol J 10(8):1248-1258, 2015). Herein, the dynamic flux distributions were analyzed by flux control analysis to identify target overexpressed genes for improved yeast robustness against furfural. The flux control coefficient (FCC) identified overexpressing isocitrate dehydrogenase (IDH1), a rate-controlling flux for ethanol fermentation, and dicarboxylate carrier (DIC1), a limiting flux for cell growth, as keys of furfural-resistance phenotype. Consistent with the model prediction, strain characterization showed 1.2- and 2.0-fold improvement in ethanol synthesis and furfural detoxification rates, respectively, by IDH1 overexpressed mutant compared to the control. DIC1 overexpressed mutant grew at 1.3-fold faster and reduced furfural at 1.4-fold faster than the control under the furfural challenge. This study hence demonstrated the FCC-based approach as an effective tool for guiding the design of robust yeast strains.

The Peculiar Glycolytic Pathway in Hyperthermophylic Archaea: Understanding Its Whims by Experimentation In Silico.

Mathematical models are key to systems biology where they typically describe the topology and dynamics of biological networks, listing biochemical entities and their relationships with one another. Some (hyper)thermophilic Archaea contain an enzyme, called non-phosphorylating glyceraldehyde-3-phosphate dehydrogenase (GAPN), which catalyzes the direct oxidation of glyceraldehyde-3-phosphate to 3-phosphoglycerate omitting adenosine 5'-triphosphate (ATP) formation by substrate-level-phosphorylation via phosphoglycerate kinase. In this study we formulate three hypotheses that could explain functionally why GAPN exists in these Archaea, and then construct and use mathematical models to test these three hypotheses. We used kinetic parameters of enzymes of Sulfolobus solfataricus (S. solfataricus) which is a thermo-acidophilic archaeon that grows optimally between 60 and 90 °C and between pH 2 and 4. For comparison, we used a model of Saccharomyces cerevisiae (S. cerevisiae), an organism that can live at moderate temperatures. We find that both the first hypothesis, i.e., that the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) plus phosphoglycerate kinase (PGK) route (the alternative to GAPN) is thermodynamically too much uphill and the third hypothesis, i.e., that GAPDH plus PGK are required to carry the flux in the gluconeogenic direction, are correct. The second hypothesis, i.e., that the GAPDH plus PGK route delivers less than the 1 ATP per pyruvate that is delivered by the GAPN route, is only correct when GAPDH reaction has a high rate and 1,3-bis-phosphoglycerate (BPG) spontaneously degrades to 3PG at a high rate.

Metabolic control analysis of the Trypanosoma cruzi peroxide detoxification pathway identifies tryparedoxin as a suitable drug target.

BACKGROUND: The principal oxidative-stress defense in the human parasite Trypanosoma cruzi is the tryparedoxin-dependent peroxide detoxification pathway, constituted by trypanothione reductase (TryR), tryparedoxin (TXN), tryparedoxin peroxidase (TXNPx) and tryparedoxin-dependent glutathione peroxidase A (GPxA). Here, Metabolic Control Analysis (MCA) was applied to quantitatively prioritize drug target(s) within the pathway by identifying its flux-controlling enzymes. METHODS: The recombinant enzymes were kinetically characterized at physiological pH/temperature. Further, the pathway was in vitro reconstituted using enzyme activity ratios and fluxes similar to those observed in the parasites; then, enzyme and substrate titrations were performed to determine their degree of control on flux. Also, kinetic characterization of the whole pathway was performed. RESULTS: Analyses of the kinetic properties indicated that TXN is the less efficient pathway enzyme derived from its high Kmapp for trypanothione and low Vmax values within the cell. MCA established that the TXN-TXNPx and TXN-GPxA redox pairs controlled by 90-100% the pathway flux, whereas 10% control was attained by TryR. The Kmapp values of the complete pathway for substrates suggested that the pathway flux was determined by the peroxide availability, whereas at high peroxide concentrations, flux may be limited by NADPH. CONCLUSION: These quantitative kinetic and metabolic analyses pointed out to TXN as a convenient drug target due to its low catalytic efficiency, high control on the flux of peroxide detoxification and role as provider of reducing equivalents to the two main peroxidases in the parasite. GENERAL SIGNIFICANCE: MCA studies provide rational and quantitative criteria to select enzymes for drug-target development.

Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties.

The Segway, which is a popular vehicle nowadays, is an uncertain nonlinear system and has an unknown time-varying control coefficient. Thus, we should consider the unknown time-varying control coefficient and model uncertainties to design the controller. Motivated by this observation, we propose a robust control for the Segway with unknown control coefficient and model uncertainties. To deal with the time-varying unknown control coefficient, we employ the Nussbaum gain technique. We introduce an auxiliary variable to solve the underactuated problem. Due to the prescribed performance control technique, the proposed controller does not require the adaptive technique, neural network, and fuzzy logic to compensate the uncertainties. Therefore, it can be simple. From the Lyapunov stability theory, we prove that all signals in the closed-loop system are bounded. Finally, we provide the simulation results to demonstrate the effectiveness of the proposed control scheme.

Metabolic control analysis of L-lactate synthesis pathway in Rhizopus oryzae As 3.2686.

The relationship between the metabolic flux and the activities of the pyruvate branching enzymes of Rhizopus oryzae As 3.2686 during L-lactate fermentation was investigated using the perturbation method of aeration. The control coefficients for five enzymes, pyruvate dehydrogenase (PDH), pyruvate carboxylase (PC), pyruvate decarboxylase (PDC), lactate dehydrogenase (LDH), and alcohol dehydrogenase (ADH), were calculated. Our results indicated significant correlations between PDH and PC, PDC and LDH, PDC and ADH, LDH and ADH, and PDC and PC. It also appeared that PDH, PC, and LDH strongly controlled the L-lactate flux; PDH and ADH strongly controlled the ethanol flux; while PDH and PC strongly controlled the acetyl coenzyme A flux and the oxaloacetate flux. Further, the flux control coefficient curves indicated that the control of the system gradually transferred from PDC to PC during the steady state. Therefore, PC was the key rate-limiting enzyme that controls the flux distribution.

Adaptive fuzzy tracking control for a class of time-varying output constrained nonlinear systems with non-affine nonlinear faults.

This paper investigates a tracking control issue for a class of time-varying output constrained nonlinear systems subject to non-affine nonlinear faults and virtual control coefficients. In the controller design process, the nonlinear function is approximated by fuzzy logic systems. Utilizing a feasible function to convert the system, a new transformation strategy is proposed to handle the system with time-varying output constraints or without output constraints. The mean value theorem is applied to split non-affine faults, and the Nussbaum-type function is used to eliminate the effect of the unknown directional affine variable gain of input resulted from non-affine faults. Combined with adaptive fuzzy backstepping technology and the error transformation function, a new control strategy is presented, which not only deals with the time-varying output constraint but also handles non-affine faults, effectively. Finally, all closed-loop system signals are bounded, and the tracking error can converge to a small preset set. Two simulations are performed to confirm the validity of the presented strategy.

Metabolic control analysis as a strategy to identify therapeutic targets, the case of cancer glycolysis.

The use of kinetic modeling and metabolic control analysis (MCA) to identify possible therapeutic targets and to investigate the controlling and regulatory mechanisms in cancer glycolysis is here reviewed. The glycolytic pathway has been considered a target to decrease cancer cell growth; however, its occurrence in normal cells makes it difficult to design therapeutic strategies that target this pathway in pathological cells. Notwithstanding, the over-expression of all enzymes and transporters, as well as the expression of isoenzymes with different kinetic and regulatory properties in cancer cells, suggested a different distribution of the control of glycolytic flux than that observed in normal cells. Kinetic models of glycolysis are constructed with enzyme kinetics experimental data, validated with the steady-state metabolite concentrations and glycolytic fluxes; applying MCA, permitted us to identify the steps with the highest control of glycolysis in cancer cells, but low control in normal cells. The cancer glycolysis main controlling steps under several metabolic conditions were: glucose transport, hexokinase and hexose-6-phosphate isomerase (HPI); whereas in normal cells were: the first two and phosphofructokinase-1. HPI is the best therapeutic target because it exerts high control in cancer glycolytic flux, but not in normal cells. Furthermore, kinetic modeling also contributed to identifying new feed-back and feed-forward regulatory loops in cancer cells glycolysis, and to understanding the mode of metabolic action of glycolytic inhibitors. Thus, MCA and metabolic modeling allowed to propose new strategies for inhibiting glycolysis in cancer cells.

Injection of Gelling Systems to a Layered Reservoir for Conformance Improvement.

The paper describes the introduction and estimation of performance criteria for the gelling agent injection technology based on a general approach to modeling physical and chemical enhanced oil recovery (EOR) methods. The current mathematical models do not include performance criteria for the process of gelling agent injection and do not allow for assessing the level of success of a treatment job in production wells. The paper introduces such criteria for the first time. To simulate the effect on injection wells, the mass conservation laws and the generalized flow law are used, and closing relations for the gelling rate are taken into account. A conformance control coefficient is introduced which characterizes the positive effect of well treatments and injectivity drop which characterizes the negative effect. The performance criteria allow for identifying the wells where the treatment jobs were the most successful. The model verification, based on the comparison of post-treatment injectivity estimated in the developed model, with Rosneft's field data showed a satisfactory match. The developed correlations can be used as the basis for a surrogate model that allows for avoiding building sector geological and flow simulation models of the treated zone.

A quantitative approach relating emergent features of complex traits to protein expression.

Linking complex, multigenic traits to protein activity is an important challenge in current biology, including applications in the medical sciences, agriculture, or forestry. Two simple algorithms are presented here to establish that link. The first one describes synergistic interactions of n proteins in shaping a complex trait ('weak emergence') as opposed to a simply additive 'modular' contribution of these proteins. A coefficient κ is defined that allows to quantify the degree of emergent interaction. For cases of strong emergence a separate formalism is introduced, implying that a number of n proteins at concentrations exceeding individual threshold values are required to spontaneously form a new, complex trait. Threshold concentrations are allowed to vary, depending on the concentrations of the other constitutive proteins. The experimental effort is estimated to provide a corresponding database for applying both formalisms, including high-throughput phenomics, and manipulation of protein concentrations using the molecular toolbox. Future efforts will be directed to overcome current limitations of the models that ignore the dynamics of protein-trait relationships with time, and the importance of the spatial arrangement of proteins for emergent interaction.

Supply and Demand Analysis of Autophagy.

Autophagy is an intracellular protein degradation pathway that plays a vital role in cellular homeostasis. It maintains cellular function through proteostasis and the removal of unused and harmful proteins and organelles. Moreover, it also serves as an adaptive response to metabolic perturbations. Deviation in autophagy activity has been linked to the progression of several pathologies, including neurodegenerative diseases. Preclinical trials have shown that modulating autophagy holds great promise in treating neurodegenerative diseases by clearing toxic protein aggregates. The success of autophagy modulating therapies requires extensive knowledge of the molecular machinery and, importantly, an in-depth understanding of the underlying systems properties of the autophagy system. A computational approach provides a powerful platform to interrogate and analyze the regulation, control, and behavior of reaction networks. However, the complexity of interactions involved in the autophagy pathway makes it challenging to isolate and characterize individual components. By reducing the autophagy process to a supply-demand system in which autophagosome synthesis (supply) and autophagosome degradation (demand) are linked by the autophagosomes, it is possible to determine the control of the supply and demand over the steady-state autophagosome flux and autophagosome concentration. In this chapter, we describe a methodology to perform supply and demand analysis of the autophagy system, the experimental procedure to measure the autophagy variables, and the use of the supply-demand framework to determine the distribution of flux and concentration control.

Metabolic Control Analysis for Drug Target Prioritization in Trypanosomatids.

To validate therapeutic targets in metabolic pathways of trypanosomatids, the criterion of enzyme essentiality determined by gene knockout or knockdown is usually being applied. Since, it is often found that most of the enzymes/proteins analyzed are essential, additional criteria have to be implemented for drug target prioritization. Metabolic control analysis (MCA), often in conjunction with kinetic pathway modeling, offers such possibility for prioritization. MCA is a theoretical and experimental approach to analyze how metabolic pathways are controlled. It involves strategies to perform quantitative analyses to determine the degree in which an enzyme controls a pathway flux, a value called flux control coefficient ([Formula: see text]). By determining the [Formula: see text] of individual steps in a metabolic pathway, the distribution of control of the pathway is established, that is, the identification of the main flux-controlling steps. Therefore, MCA can help in ranking pathway enzymes as drug targets from a metabolic perspective. In this chapter, three approaches to determine [Formula: see text] are reviewed: (1) In vitro pathway reconstitution, (2) manipulation of enzyme activities within parasites, and (3) in silico kinetic modeling of the metabolic pathway. To perform these methods, accurate experimental data of enzyme activities, metabolite concentrations and pathway fluxes are necessary. The methodology is illustrated with the example of trypanothione metabolism of Trypanosoma cruzi and protocols to determine such experimental data for this metabolic process are also described. However, the MCA strategy can be applied to any metabolic pathway in the parasite and general directions to perform it are provided in this chapter.

Gamma-glutamylcysteine synthetase and tryparedoxin 1 exert high control on the antioxidant system in Trypanosoma cruzi contributing to drug resistance and infectivity.

Trypanothione (T(SH)2) is the main antioxidant metabolite for peroxide reduction in Trypanosoma cruzi; therefore, its metabolism has attracted attention for therapeutic intervention against Chagas disease. To validate drug targets within the T(SH)2 metabolism, the strategies and methods of Metabolic Control Analysis and kinetic modeling of the metabolic pathway were used here, to identify the steps that mainly control the pathway fluxes and which could be appropriate sites for therapeutic intervention. For that purpose, gamma-glutamylcysteine synthetase (γECS), trypanothione synthetase (TryS), trypanothione reductase (TryR) and the tryparedoxin cytosolic isoform 1 (TXN1) were separately overexpressed to different levels in T. cruzi epimastigotes and their degrees of control on the pathway flux as well as their effect on drug resistance and infectivity determined. Both experimental in vivo as well as in silico analyses indicated that γECS and TryS control T(SH)2 synthesis by 60-74% and 15-31%, respectively. γECS overexpression prompted up to a 3.5-fold increase in T(SH)2 concentration, whereas TryS overexpression did not render an increase in T(SH)2 levels as a consequence of high T(SH)2 degradation. The peroxide reduction flux was controlled for 64-73% by TXN1, 17-20% by TXNPx and 11-16% by TryR. TXN1 and TryR overexpression increased H2O2 resistance, whereas TXN1 overexpression increased resistance to the benznidazole plus buthionine sulfoximine combination. γECS overexpression led to an increase in infectivity capacity whereas that of TXN increased trypomastigote bursting. The present data suggested that inhibition of high controlling enzymes such as γECS and TXN1 in the T(SH)2 antioxidant pathway may compromise the parasite's viability and infectivity.

Drug Target Selection for Trypanosoma cruzi Metabolism by Metabolic Control Analysis and Kinetic Modeling.

In the search for therapeutic targets in the intermediary metabolism of trypanosomatids the gene essentiality criterion as determined by using knock-out and knock-down genetic strategies is commonly applied. As most of the evaluated enzymes/transporters have turned out to be essential for parasite survival, additional criteria and approaches are clearly required for suitable drug target prioritization. The fundamentals of Metabolic Control Analysis (MCA; an approach in the study of control and regulation of metabolism) and kinetic modeling of metabolic pathways (a bottom-up systems biology approach) allow quantification of the degree of control that each enzyme exerts on the pathway flux (flux control coefficient) and metabolic intermediate concentrations (concentration control coefficient). MCA studies have demonstrated that metabolic pathways usually have two or three enzymes with the highest control of flux; their inhibition has more negative effects on the pathway function than inhibition of enzymes exerting low flux control. Therefore, the enzymes with the highest pathway control are the most convenient targets for therapeutic intervention. In this review, the fundamentals of MCA as well as experimental strategies to determine the flux control coefficients and metabolic modeling are analyzed. MCA and kinetic modeling have been applied to trypanothione metabolism in Trypanosoma cruzi and the model predictions subsequently validated in vivo. The results showed that three out of ten enzyme reactions analyzed in the T. cruzi anti-oxidant metabolism were the most controlling enzymes. Hence, MCA and metabolic modeling allow a further step in target prioritization for drug development against trypanosomatids and other parasites.

Control and regulation of the pyrophosphate-dependent glucose metabolism in Entamoeba histolytica.

Entamoeba histolytica has neither Krebs cycle nor oxidative phosphorylation activities; therefore, glycolysis is the main pathway for ATP supply and provision of carbon skeleton precursors for the synthesis of macromolecules. Glucose is metabolized through fermentative glycolysis, producing ethanol as its main end-product as well as some acetate. Amoebal glycolysis markedly differs from the typical Embden-Meyerhof-Parnas pathway present in human cells: (i) by the use of inorganic pyrophosphate, instead of ATP, as the high-energy phospho group donor; (ii) with one exception, the pathway enzymes can catalyze reversible reactions under physiological conditions; (iii) there is no allosteric regulation and sigmoidal kinetic behavior of key enzymes; and (iv) the presence of some glycolytic and fermentation enzymes similar to those of anaerobic bacteria. These peculiarities bring about alternative mechanisms of control and regulation of the PPi-dependent fermentative glycolysis in the parasite in comparison to the ATP-dependent and allosterically regulated glycolysis in many other eukaryotic cells. In this review, the current knowledge of the carbohydrate metabolism enzymes in E. histolytica is analyzed. Thermodynamics and stoichiometric analyses indicate 2 to 3.5 ATP yield per glucose metabolized, instead of the often presumed 5 ATP/glucose ratio. PPi derived from anabolism seems insufficient for PPi-glycolysis; hence, alternative ways of PPi supply are also discussed. Furthermore, the underlying mechanisms of control and regulation of the E. histolytica carbohydrate metabolism, analyzed by applying integral and systemic approaches such as Metabolic Control Analysis and kinetic modeling, contribute to unveiling alternative and promising drug targets.

A metabolic control analysis approach to introduce the study of systems in biochemistry: the glycolytic pathway in the red blood cell.

Metabolic control analysis (MCA) is a promising approach in biochemistry aimed at understanding processes in a quantitative fashion. Here the contribution of enzymes and transporters to the control of a given pathway flux and metabolite concentrations is determined and expressed quantitatively by means of numerical coefficients. Metabolic flux can be influenced by a wide variety of modulators acting on one or more metabolic steps along the pathway. We describe a laboratory exercise to study metabolic regulation of human erythrocytes (RBCs). Within the framework of MCA, students use these cells to determine the sensitivity of the glycolytic flux to two inhibitors (iodoacetic acid: IA, and iodoacetamide: IAA) known to act on the enzyme glyceraldehyde-3-phosphate-dehydrogenase. Glycolytic flux was estimated by determining the concentration of extracellular lactate, the end product of RBC glycolysis. A low-cost colorimetric assay was implemented, that takes advantage of the straightforward quantification of the absorbance signal from the photographic image of the multi-well plate taken with a standard digital camera. Students estimate flux response coefficients for each inhibitor by fitting an empirical function to the experimental data, followed by analytical derivation of this function. IA and IAA exhibit qualitatively different patterns, which are thoroughly analyzed in terms of the physicochemical properties influencing their action on the target enzyme. IA causes highest glycolytic flux inhibition at lower concentration than IAA. This work illustrates the feasibility of using the MCA approach to study key variables of a simple metabolic system, in the context of an upper level biochemistry course. © 2018 International Union of Biochemistry and Molecular Biology, 46(5):502-515, 2018.

In vivo identification of the steps that control energy metabolism and survival of Entamoeba histolytica.

The steps that control the Entamoeba histolytica glycolytic flux were here identified by elasticity analysis, an experimental approach of metabolic control analysis. The concentrations of glycolytic metabolites were gradually varied in live trophozoites by (a) feeding with different glucose concentrations and (b) inhibiting the final pathway steps; in parallel, the changes in the pathway flux were determined. From the metabolite concentration-flux relationship, the elasticity coefficients of individual or groups of pathway reactions were determined and used to calculate their respective degrees of control on the glycolytic flux (flux control coefficients). The results indicated that the pathway flux was mainly controlled (72-86%) by the glucose transport/hexokinase/glycogen degradation group of reactions and by bifunctional aldehyde-alcohol dehydrogenase (ADHE; 18%). Further, inhibition of the first pathway reactions with 2-deoxyglucose (2DOG) decreased the glycolytic flux and ATP content by 75% and 50%, respectively. Cell viability was also decreased by 2DOG (25%) and more potently (50%) by 2DOG plus the ADHE inhibitor tetraethylthiuram disulfide (disulfiram). Biosate as an alternative carbon (amino acid) source was unable to replace glucose for ATP supply, which indicated that glucose was the main nutrient for amoebal ATP synthesis and survival. These results indicated that glycolysis in the parasite is mainly controlled by the initial pathway reactions and that their inhibition can decrease the parasite energy load and survival.

Modeling cancer glycolysis under hypoglycemia, and the role played by the differential expression of glycolytic isoforms.

UNLABELLED: The effect of hypoglycemia on the contents of glycolytic proteins, activities of enzymes/transporters and flux of HeLa and MCF-7 tumor cells was experimentally analyzed and modeled in silico. After 24 h hypoglycemia (2.5 mm initial glucose), significant increases in the protein levels of glucose transporters 1 and 3 (GLUT 1 and 3) (3.4 and 2.1-fold, respectively) and hexokinase I (HKI) (2.3-fold) were observed compared to the hyperglycemic standard cell culture condition (25 mm initial glucose). However, these changes did not bring about a significant increase in the total activities (Vmax ) of GLUT and HK; instead, the affinity of these proteins for glucose increased, which may explain the twofold increased glycolytic flux under hypoglycemia. Thus, an increase in more catalytically efficient isoforms for two of the main controlling steps was sufficient to induce increased flux. Further, a previous kinetic model of tumor glycolysis was updated by including the ratios of GLUT and HK isoforms, modified pyruvate kinase kinetics and an oxidative phosphorylation reaction. The updated model was robust in terms of simulating most of the metabolite levels and fluxes of the cells exposed to various glycemic conditions. Model simulations indicated that the main controlling steps were glycogen degradation > HK > hexosephosphate isomerase under hyper- and normoglycemia, and GLUT > HK > glycogen degradation under hypoglycemia. These predictions were experimentally evaluated: the glycolytic flux of hypoglycemic cells was more sensitive to cytochalasin B (a GLUT inhibitor) than that of hyperglycemic cells. The results indicated that cancer glycolysis should be inhibited at multiple controlling sites, regardless of external glucose levels, to effectively block the pathway. DATABASE: The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.mib.ac.uk/database/achcar/index.html. [Database section added 21 July 2014 after original online publication].

Exploring metabolic engineering design principles for the photosynthetic production of lactic acid by Synechocystis sp. PCC6803.

BACKGROUND: Molecular engineering of the intermediary physiology of cyanobacteria has become important for the sustainable production of biofuels and commodity compounds from CO2 and sunlight by "designer microbes." The chemical commodity product L-lactic acid can be synthesized in one step from a key intermediary metabolite of these organisms, pyruvate, catalyzed by a lactate dehydrogenase. Synthetic biology engineering to make "designer microbes" includes the introduction and overexpression of the product-forming biochemical pathway. For further optimization of product formation, modifications in the surrounding biochemical network of intermediary metabolism have to be made. RESULTS: To improve light-driven L-lactic acid production from CO2, we explored several metabolic engineering design principles, using a previously engineered L-lactic acid producing mutant strain of Synechocystis sp. PCC6803 as the benchmark. These strategies included: (i) increasing the expression level of the relevant product-forming enzyme, lactate dehydrogenase (LDH), for example, via expression from a replicative plasmid; (ii) co-expression of a heterologous pyruvate kinase to increase the flux towards pyruvate; and (iii) knockdown of phosphoenolpyruvate carboxylase to decrease the flux through a competing pathway (from phosphoenolpyruvate to oxaloacetate). In addition, we tested selected lactate dehydrogenases, some of which were further optimized through site-directed mutagenesis to improve the enzyme's affinity for the co-factor nicotinamide adenine dinucleotide phosphate (NADPH). The carbon partitioning between biomass and lactic acid was increased from about 5% to over 50% by strain optimization. CONCLUSION: An efficient photosynthetic microbial cell factory will display a high rate and extent of conversion of substrate (CO2) into product (here: L-lactic acid). In the existing CO2-based cyanobacterial cell factories that have been described in the literature, by far most of the control over product formation resides in the genetically introduced fermentative pathway. Here we show that a strong promoter, in combination with increased gene expression, can take away a significant part of the control of this step in lactic acid production from CO2. Under these premises, modulation of the intracellular precursor, pyruvate, can significantly increase productivity. Additionally, production enhancement is achieved by protein engineering to increase co-factor specificity of the heterologously expressed LDH.