Machine learning predicts system-wide metabolic flux control in cyanobacteria.

Metabolic fluxes and their control mechanisms are fundamental in cellular metabolism, offering insights for the study of biological systems and biotechnological applications. However, quantitative and predictive understanding of controlling biochemical reactions in microbial cell factories, especially at the system level, is limited. In this work, we present ARCTICA, a computational framework that integrates constraint-based modelling with machine learning tools to address this challenge. Using the model cyanobacterium Synechocystis sp. PCC 6803 as chassis, we demonstrate that ARCTICA effectively simulates global-scale metabolic flux control. Key findings are that (i) the photosynthetic bioproduction is mainly governed by enzymes within the Calvin-Benson-Bassham (CBB) cycle, rather than by those involve in the biosynthesis of the end-product, (ii) the catalytic capacity of the CBB cycle limits the photosynthetic activity and downstream pathways and (iii) ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is a major, but not the most, limiting step within the CBB cycle. Predicted metabolic reactions qualitatively align with prior experimental observations, validating our modelling approach. ARCTICA serves as a valuable pipeline for understanding cellular physiology and predicting rate-limiting steps in genome-scale metabolic networks, and thus provides guidance for bioengineering of cyanobacteria.

Metabolic control analysis enabled the improvement of the L-cysteine production process with Escherichia coli.

L-cysteine is an amino acid with relevance to the pharmaceutical, food, feed, and cosmetic industry. The environmental and societal impact of its chemical production has led to the development of more sustainable fermentative L-cysteine production processes with engineered E. coli based on glucose and thiosulfate as sulphur source. Still, most of the published processes show low yields. For the identification of further metabolic engineering targets, engineered E. coli cells were withdrawn from a fed-batch production process, followed by in vivo metabolic control analysis (MCA) based on the data of short-term perturbation experiments, metabolomics (LC-MS), and thermodynamic flux analysis (TFA). In vivo MCA indicated that the activities of the L-cysteine synthases of the cells withdrawn from the production process might be limiting, and we hypothesised that the L-cysteine precursor O-acetylserine (OAS) might be exported from the cells faster than it took to transform OAS into L-cysteine. By increasing the expression of the L-cysteine synthases, either sulfocysteine synthase or L-cysteine synthase, which transform OAS into L-cysteine, an improvement of up to 70% in specific L-cysteine productivity and up to 47% in the final L-cysteine concentration was achieved in standardised fed-batch processes thereby increasing the yield on glucose by more than 85 to 9.2% (w/w). KEY POINTS: • Metabolic control analysis was applied to analyse L-cysteine production with E. coli • OAS export was faster than its transformation to L-cysteine • Overexpression of L-cysteine synthases improved L-cysteine productivity and yield.

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.

A dynamic kinetic model captures cell-free metabolism for improved butanol production.

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 h. We present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

Overexpression of phospholipid: diacylglycerol acyltransferase in Brassica napus results in changes in lipid metabolism and oil accumulation.

The regulation of lipid metabolism in oil seeds is still not fully understood and increasing our knowledge in this regard is of great economic, as well as intellectual, importance. Oilseed rape (Brassica napus) is a major global oil crop where increases in triacylglycerol (TAG) accumulation have been achieved by overexpression of relevant biosynthetic enzymes. In this study, we expressed Arabidopsis phospholipid: diacylglycerol acyltransferase (PDAT1), one of the two major TAG-forming plant enzymes in B. napus DH12075 to evaluate its effect on lipid metabolism in developing seeds and to estimate its flux control coefficient. Despite several-fold increase in PDAT activity, seeds of three independently generated PDAT transgenic events showed a small but consistent decrease in seed oil content and had altered fatty acid composition of phosphoglycerides and TAG, towards less unsaturation. Mass spectrometry imaging of seed sections confirmed the shift in lipid compositions and indicated that PDAT overexpression altered the distinct heterogeneous distributions of phosphatidylcholine (PC) molecular species. Similar, but less pronounced, changes in TAG molecular species distributions were observed. Our data indicate that PDAT exerts a small, negative, flux control on TAG biosynthesis and could have under-appreciated effects in fine-tuning of B. napus seed lipid composition in a tissue-specific manner. This has important implications for efforts to increase oil accumulation in similar crops.

Metabolic control analysis of hepatic glycogen synthesis in vivo.

Multiple insulin-regulated enzymes participate in hepatic glycogen synthesis, and the rate-controlling step responsible for insulin stimulation of glycogen synthesis is unknown. We demonstrate that glucokinase (GCK)-mediated glucose phosphorylation is the rate-controlling step in insulin-stimulated hepatic glycogen synthesis in vivo, by use of the somatostatin pancreatic clamp technique using [13C6]glucose with metabolic control analysis (MCA) in three rat models: 1) regular chow (RC)-fed male rats (control), 2) high fat diet (HFD)-fed rats, and 3) RC-fed rats with portal vein glucose delivery at a glucose infusion rate matched to the control. During hyperinsulinemia, hyperglycemia dose-dependently increased hepatic glycogen synthesis. At similar levels of hyperinsulinemia and hyperglycemia, HFD-fed rats exhibited a decrease and portal delivery rats exhibited an increase in hepatic glycogen synthesis via the direct pathway compared with controls. However, the strong correlation between liver glucose-6-phosphate concentration and net hepatic glycogen synthetic rate was nearly identical in these three groups, suggesting that the main difference between models is the activation of GCK. MCA yielded a high control coefficient for GCK in all three groups. We confirmed these findings in studies of hepatic GCK knockdown using an antisense oligonucleotide. Reduced liver glycogen synthesis in lipid-induced hepatic insulin resistance and increased glycogen synthesis during portal glucose infusion were explained by concordant changes in translocation of GCK. Taken together, these data indicate that the rate of insulin-stimulated hepatic glycogen synthesis is controlled chiefly through GCK translocation.

Interrogating the effect of enzyme kinetics on metabolism using differentiable constraint-based models.

Metabolic models are typically characterized by a large number of parameters. Traditionally, metabolic control analysis is applied to differential equation-based models to investigate the sensitivity of predictions to parameters. A corresponding theory for constraint-based models is lacking, due to their formulation as optimization problems. Here, we show that optimal solutions of optimization problems can be efficiently differentiated using constrained optimization duality and implicit differentiation. We use this to calculate the sensitivities of predicted reaction fluxes and enzyme concentrations to turnover numbers in an enzyme-constrained metabolic model of Escherichia coli. The sensitivities quantitatively identify rate limiting enzymes and are mathematically precise, unlike current finite difference based approaches used for sensitivity analysis. Further, efficient differentiation of constraint-based models unlocks the ability to use gradient information for parameter estimation. We demonstrate this by improving, genome-wide, the state-of-the-art turnover number estimates for E. coli. Finally, we show that this technique can be generalized to arbitrarily complex models. By differentiating the optimal solution of a model incorporating both thermodynamic and kinetic rate equations, the effect of metabolite concentrations on biomass growth can be elucidated. We benchmark these metabolite sensitivities against a large experimental gene knockdown study, and find good alignment between the predicted sensitivities and in vivo metabolome changes. In sum, we demonstrate several applications of differentiating optimal solutions of constraint-based metabolic models, and show how it connects to classic metabolic control analysis.

Metabolic control analysis enables rational improvement of E. coli L-tryptophan producers but methylglyoxal formation limits glycerol-based production.

BACKGROUND: Although efficient L-tryptophan production using engineered Escherichia coli is established from glucose, the use of alternative carbon sources is still very limited. Through the application of glycerol as an alternate, a more sustainable substrate (by-product of biodiesel preparation), the well-studied intracellular glycolytic pathways are rerouted, resulting in the activity of different intracellular control sites and regulations, which are not fully understood in detail. Metabolic analysis was applied to well-known engineered E. coli cells with 10 genetic modifications. Cells were withdrawn from a fed-batch production process with glycerol as a carbon source, followed by metabolic control analysis (MCA). This resulted in the identification of several additional enzymes controlling the carbon flux to L-tryptophan. RESULTS: These controlling enzyme activities were addressed stepwise by the targeted overexpression of 4 additional enzymes (trpC, trpB, serB, aroB). Their efficacy regarding L-tryptophan productivity was evaluated under consistent fed-batch cultivation conditions. Although process comparability was impeded by process variances related to a temporal, unpredictable break-off in L-tryptophan production, process improvements of up to 28% with respect to the L-tryptophan produced were observed using the new producer strains. The intracellular effects of these targeted genetic modifications were revealed by metabolic analysis in combination with MCA and expression analysis. Furthermore, it was discovered that the E. coli cells produced the highly toxic metabolite methylglyoxal (MGO) during the fed-batch process. A closer look at the MGO production and detoxification on the metabolome, fluxome, and transcriptome level of the engineered E. coli indicated that the highly toxic metabolite plays a critical role in the production of aromatic amino acids with glycerol as a carbon source. CONCLUSIONS: A detailed process analysis of a new L-tryptophan producer strain revealed that several of the 4 targeted genetic modifications of the E. coli L-tryptophan producer strain proved to be effective, and, for others, new engineering approaches could be derived from the results. As a starting point for further strain and process optimization, the up-regulation of MGO detoxifying enzymes and a lowering of the feeding rate during the last third of the cultivation seems reasonable.

Control of redox potential in a novel continuous bioelectrochemical system led to remarkable metabolic and energetic responses of Clostridium pasteurianum grown on glycerol.

BACKGROUND: Electro-fermentation (EF) is an emerging tool for bioprocess intensification. Benefits are especially expected for bioprocesses in which the cells are enabled to exchange electrons with electrode surfaces directly. It has also been demonstrated that the use of electrical energy in BES can increase bioprocess performance by indirect secondary effects. In this case, the electricity is used to alter process parameters and indirectly activate desired pathways. In many bioprocesses, oxidation-reduction potential (ORP) is a crucial process parameter. While C. pasteurianum fermentation of glycerol has been shown to be significantly influenced electrochemically, the underlying mechanisms are not clear. To this end, we developed a system for the electrochemical control of ORP in continuous culture to quantitatively study the effects of ORP alteration on C. pasteurianum by metabolic flux analysis (MFA), targeted metabolomics, sensitivity and regulation analysis. RESULTS: In the ORP range of -462 mV to -250 mV, the developed algorithm enabled a stable anodic electrochemical control of ORP at desired set-points and a fixed dilution rate of 0.1 h-1. An overall increase of 57% in the molar yield for 1,3-propanediol was observed by an ORP increase from -462 to -250 mV. MFA suggests that C. pasteurianum possesses and uses cellular energy generation mechanisms in addition to substrate-level phosphorylation. The sensitivity analysis showed that ORP exerted its strongest impact on the reaction of pyruvate-ferredoxin-oxidoreductase. The regulation analysis revealed that this influence is mainly of a direct nature. Hence, the observed metabolic shifts are primarily caused by direct inhibition of the enzyme upon electrochemical production of oxygen. A similar effect was observed for the enzyme pyruvate-formate-lyase at elevated ORP levels. CONCLUSIONS: The results show that electrochemical ORP alteration is a suitable tool to steer the metabolism of C. pasteurianum and increase product yield for 1,3-propanediol in continuous culture. The approach might also be useful for application with further anaerobic or anoxic bioprocesses. However, to maximize the technique's efficiency, it is essential to understand the chemistry behind the ORP change and how the microbial system responds to it by transmitted or direct effects.

The effects of model complexity and size on metabolic flux distribution and control: case study in Escherichia coli.

BACKGROUND: Significant efforts have been made in building large-scale kinetic models of cellular metabolism in the past two decades. However, most kinetic models published to date, remain focused around central carbon pathways or are built around ad hoc reduced models without clear justification on their derivation and usage. Systematic algorithms exist for reducing genome-scale metabolic reconstructions to build thermodynamically feasible and consistently reduced stoichiometric models. However, it is important to study how network complexity affects conclusions derived from large-scale kinetic models built around consistently reduced models before we can apply them to study biological systems. RESULTS: We reduced the iJO1366 Escherichia Coli genome-scale metabolic reconstruction systematically to build three stoichiometric models of different size. Since the reduced models are expansions around the core subsystems for which the reduction was performed, the models are nested. We present a method for scaling up the flux profile and the concentration vector reference steady-states from the smallest model to the larger ones, whilst preserving maximum equivalency. Populations of kinetic models, preserving similarity in kinetic parameters, were built around the reference steady-states and their metabolic sensitivity coefficients (MSCs) were computed. The MSCs were sensitive to the model complexity. We proposed a metric for measuring the sensitivity of MSCs to these structural changes. CONCLUSIONS: We proposed for the first time a workflow for scaling up the size of kinetic models while preserving equivalency between the kinetic models. Using this workflow, we demonstrate that model complexity in terms of networks size has significant impact on sensitivity characteristics of kinetic models. Therefore, it is essential to account for the effects of network complexity when constructing kinetic models. The presented metric for measuring MSC sensitivity to structural changes can guide modelers and experimentalists in improving model quality and guide synthetic biology and metabolic engineering. Our proposed workflow enables the testing of the suitability of a kinetic model for answering certain study-specific questions. We argue that the model-based metabolic design targets that are common across models of different size are of higher confidence, while those that are different could be the objective of investigations for model improvement.

Mitochondrial capacity and reactive oxygen species production during hypoxia and reoxygenation in the ocean quahog, Arctica islandica.

Oxygen fluctuations are common in marine waters, and hypoxia-reoxygenation (H-R) stress can negatively affect mitochondrial metabolism. The long-lived ocean quahog, Arctica islandica, is known for its hypoxia tolerance associated with metabolic rate depression, yet the mechanisms that sustain mitochondrial function during oxygen fluctuations are not well understood. We used top-down metabolic control analysis (MCA) to determine aerobic capacity and control over oxygen flux in the mitochondria of quahogs exposed to short-term hypoxia (24 h <0.01% O2) and subsequent reoxygenation (1.5 h 21% O2) compared with normoxic control animals (21% O2). We demonstrated that flux capacity of the substrate oxidation and proton leak subsystems were not affected by hypoxia, while the capacity of the phosphorylation subsystem was enhanced during hypoxia associated with a depolarization of the mitochondrial membrane. Reoxygenation decreased the oxygen flux capacity of all three mitochondrial subsystems. Control over oxidative phosphorylation (OXPHOS) respiration was mostly exerted by substrate oxidation regardless of H-R stress, whereas control by the proton leak subsystem of LEAK respiration increased during hypoxia and returned to normoxic levels during reoxygenation. During hypoxia, reactive oxygen species (ROS) efflux was elevated in the LEAK state, whereas it was suppressed in the OXPHOS state. Mitochondrial ROS efflux returned to normoxic control levels during reoxygenation. Thus, mitochondria of A. islandica appear robust to hypoxia by maintaining stable substrate oxidation and upregulating phosphorylation capacity, but remain sensitive to reoxygenation. This mitochondrial phenotype might reflect adaptation of A. islandica to environments with unpredictable oxygen fluctuations and its behavioural preference for low oxygen levels.

Metabolic control analysis of L-tryptophan producing Escherichia coli applying targeted perturbation with shikimate.

L-tryptophan production from glycerol with Escherichia coli was analysed by perturbation studies and metabolic control analysis. The insertion of a non-natural shikimate transporter into the genome of an Escherichia coli L-tryptophan production strain enabled targeted perturbation within the product pathway with shikimate during parallelised short-term perturbation experiments with cells withdrawn from a 15 L fed-batch production process. Expression of the shikimate/H+-symporter gene (shiA) from Corynebacterium glutamicum did not alter process performance within the estimation error. Metabolic analyses and subsequent extensive data evaluation were performed based on the data of the parallel analysis reactors and the production process. Extracellular rates and intracellular metabolite concentrations displayed evident deflections in cell metabolism and particularly in chorismate biosynthesis due to the perturbations with shikimate. Intracellular flux distributions were estimated using a thermodynamics-based flux analysis method, which integrates thermodynamic constraints and intracellular metabolite concentrations to restrain the solution space. Feasible flux distributions, Gibbs reaction energies and concentration ranges were computed simultaneously for the genome-wide metabolic model, with minimum bias in relation to the direction of metabolic reactions. Metabolic control analysis was applied to estimate elasticities and flux control coefficients, predicting controlling sites for L-tryptophan biosynthesis. The addition of shikimate led to enhanced deviations in chorismate biosynthesis, revealing a so far not observed control of 3-dehydroquinate synthase on L-tryptophan formation. The relative expression of the identified target genes was analysed with RT-qPCR. Transcriptome analysis revealed disparities in gene expression and the localisation of target genes to further improve the microbial L-tryptophan producer by metabolic engineering.

Thermodynamic constraints on the regulation of metabolic fluxes.

Nutrition and metabolism are fundamental to cellular function. Metabolic activity (i.e. rates of flow, most commonly referred to as flux) is constrained by thermodynamics and regulated by the activity of enzymes. The general principles that relate biological and physical variables to metabolic control are incompletely understood. Using metabolic control analysis and computer simulations in several models of simplified metabolic pathways, we derive analytical expressions that define relationships between thermodynamics, enzyme activity, and flux control. The relationships are further analyzed in a mathematical model of glycolysis as an example of a complex biochemical pathway. We show that metabolic pathways that are very far from equilibrium are controlled by the activity of upstream enzymes. However, in general, regulation of metabolic fluxes by an enzyme has a more adaptable pattern, which relies more on distribution of free energy among reaction steps in the pathway than on the thermodynamic properties of the given enzyme. These findings show how the control of metabolic pathways is shaped by thermodynamic constraints of the given 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.

Distribution of control in the sulfur assimilation in Arabidopsis thaliana depends on environmental conditions.

Sulfur assimilation is central to the survival of plants and has been studied under different environmental conditions. Multiple studies have been published trying to determine rate-limiting or controlling steps in this pathway. However, the picture remains inconclusive with at least two different enzymes proposed to represent such rate-limiting steps. Here, we used computational modeling to gain an integrative understanding of the distribution of control in the sulfur assimilation pathway of Arabidopsis thaliana. For this purpose, we set up a new ordinary differential equation (ODE)-based, kinetic model of sulfur assimilation encompassing all biochemical reactions directly involved in this process. We fitted the model to published experimental data and produced a model ensemble to deal with parameter uncertainties. The ensemble was validated against additional published experimental data. We used the model ensemble to subsequently analyse the control pattern and robustly identified a set of processes that share the control in this pathway under standard conditions. Interestingly, the pattern of control is dynamic and not static, that is it changes with changing environmental conditions. Therefore, while adenosine-5'-phosphosulfate reductase (APR) and sulfite reductase (SiR) share control under standard laboratory conditions, APR takes over an even more dominant role under sulfur starvation conditions.

Cell free biosynthesis of isoprenoids from isopentenol.

Cell-free systems are growing in importance for the biosynthesis of complex molecules. These systems combine the precision of traditional chemistry with the versatility of biology in creating superior overall processes. Recently, a new synthetic pathway for the biosynthesis of isoprenoids using the substrate isopentenol, dubbed the isopentenol utilization pathway (IUP), was demonstrated to be a promising alternative to the native 2C-methyl-d-erythritol-4-phosphate (MEP) and mevalonate (MVA) pathways. This simplified pathway, which contains a minimum of four enzymes to produce basic monoterpenes and only depends on ATP and isopentenol as substrates, allows for a highly flexible approach to the commercial synthesis of isoprenoid products. In this work, we use metabolic reconstitution to characterize this new pathway in vitro and demonstrate its use for the cell-free synthesis of mono-, sesquit-, and diterpenoids. Kinetic modeling and sensitivity analysis were also used to identify the most significant parameters for taxadiene productivity, and metabolic control analysis was employed to elucidate protein-level interactions within this pathway, which demonstrated that the IUP enzymatic system is primarily controlled by the concentration and kinetics of choline kinase (CK) and not regulated by any pathway intermediates. This is a significant advantage over the natural MEP or MVA pathways as it greatly simplifies future metabolic engineering efforts, both in vitro and in vivo, aiming at improving the kinetics of CK. Finally, we used the insights gathered to demonstrate an in vitro IUP system that can produce 220 mg/L of the diterpene taxadiene, in 9 hr, almost 3-fold faster than any system reported thus far.

Investigation of the methylerythritol 4-phosphate pathway for microbial terpenoid production through metabolic control analysis.

BACKGROUND: Terpenoids are of high interest as chemical building blocks and pharmaceuticals. In microbes, terpenoids can be synthesized via the methylerythritol phosphate (MEP) or mevalonate (MVA) pathways. Although the MEP pathway has a higher theoretical yield, metabolic engineering has met with little success because the regulation of the pathway is poorly understood. RESULTS: We applied metabolic control analysis to the MEP pathway in Escherichia coli expressing a heterologous isoprene synthase gene (ispS). The expression of ispS led to the accumulation of isopentenyl pyrophosphate (IPP)/dimethylallyl pyrophosphate (DMAPP) and severely impaired bacterial growth, but the coexpression of ispS and isopentenyl diphosphate isomerase (idi) restored normal growth and wild-type IPP/DMAPP levels. Targeted proteomics and metabolomics analysis provided a quantitative description of the pathway, which was perturbed by randomizing the ribosome binding site in the gene encoding 1-deoxyxylulose 5-phosphate synthase (Dxs). Dxs has a flux control coefficient of 0.35 (i.e., a 1% increase in Dxs activity resulted in a 0.35% increase in pathway flux) in the isoprene-producing strain and therefore exerted significant control over the flux though the MEP pathway. At higher dxs expression levels, the intracellular concentration of 2-C-methyl-D-erythritol-2,4-cyclopyrophosphate (MEcPP) increased substantially in contrast to the other MEP pathway intermediates, which were linearly dependent on the abundance of Dxs. This indicates that 4-hydroxy-3-methylbut-2-en-1-yl diphosphate synthase (IspG), which consumes MEcPP, became saturated and therefore limited the flux towards isoprene. The higher intracellular concentrations of MEcPP led to the efflux of this intermediate into the growth medium. DISCUSSION: These findings show the importance of Dxs, Idi and IspG and metabolite export for metabolic engineering of the MEP pathway and will facilitate further approaches for the microbial production of valuable isoprenoids.

Metabolic activation-driven mitochondrial hyperpolarization predicts insulin secretion in human pancreatic beta-cells.

Mitochondrial metabolism plays a central role in insulin secretion in pancreatic beta-cells. Generation of protonmotive force and ATP synthesis from glucose-originated pyruvate are critical steps in the canonical pathway of glucose-stimulated insulin secretion. Mitochondrial metabolism is intertwined with pathways that are thought to amplify insulin secretion with mechanisms distinct from the canonical pathway, and the relative importance of these two pathways is controversial. Here I show that glucose-induced mitochondrial membrane potential (MMP) hyperpolarization is necessary for, and predicts, the rate of insulin secretion in primary cultured human beta-cells. When glucose concentration is elevated, increased metabolism results in a substantial MMP hyperpolarization, as well as in increased rates of ATP synthesis and turnover marked by faster cell respiration. Using modular kinetic analysis I explored what properties of cellular energy metabolism enable a large glucose-induced change in MMP in human beta-cells. I found that an ATP-dependent pathway activates glucose or substrate oxidation, acting as a positive feedback in energy metabolism. This activation mechanism is essential for concomitant fast respiration and high MMP, and for a high magnitude glucose-induced MMP hyperpolarization and therefore for insulin secretion.

Comparative analysis of the bioenergetics of human adenocarcinoma Caco-2 cell line and postoperative tissue samples from colorectal cancer patients.

The aim of this work was to explore the key bioenergetic properties for mitochondrial respiration in the widely-used Caco-2 cell line and in human colorectal cancer (HCC) postoperational tissue samples. Oxygraphy and metabolic control analysis (MCA) were applied to estimate the function of oxidative phosphorylation in cultured Caco-2 cells and HCC tissue samples. The mitochondria of Caco-2 cells and HCC tissues displayed larger functional activity of respiratory complex (C)II compared with CI, whereas in normal colon tissue an inverse pattern in the ratio of CI to CII activity was observed. MCA showed that the respiration in Caco-2 and HCC tissue cells is regulated by different parts of electron transport chain. In HCC tissues, this control is performed essentially at the level of respiratory chain complexes I-IV, whereas in Caco-2 cells at the level of CIV (cytochrome c oxidase) and the ATP synthasome. The differences we found in the regulation of respiratory chain activity and glycose index could represent an adaptive response to distinct growth conditions; this highlights the importance of proper validation of results obtained from in-vitro models before their extrapolation to the more complex in-vivo systems.

Coenzyme A, protein CoAlation and redox regulation in mammalian cells.

In a diverse family of cellular cofactors, coenzyme A (CoA) has a unique design to function in various biochemical processes. The presence of a highly reactive thiol group and a nucleotide moiety offers a diversity of chemical reactions and regulatory interactions. CoA employs them to activate carbonyl-containing molecules and to produce various thioester derivatives (e.g. acetyl CoA, malonyl CoA and 3-hydroxy-3-methylglutaryl CoA), which have well-established roles in cellular metabolism, production of neurotransmitters and the regulation of gene expression. A novel unconventional function of CoA in redox regulation, involving covalent attachment of this coenzyme to cellular proteins in response to oxidative and metabolic stress, has been recently discovered and termed protein CoAlation (S-thiolation by CoA or CoAthiolation). A diverse range of proteins was found to be CoAlated in mammalian cells and tissues under various experimental conditions. Protein CoAlation alters the molecular mass, charge and activity of modified proteins, and prevents them from irreversible sulfhydryl overoxidation. This review highlights the role of a key metabolic integrator CoA in redox regulation in mammalian cells and provides a perspective of the current status and future directions of the emerging field of protein CoAlation.