A synthetic biochemistry system for the in vitro production of isoprene from glycolysis intermediates

The high yields required for the economical production of chemicals and fuels using microbes can be difficult to achieve due to the complexities of cellular metabolism. An alternative to performing biochemical transformations in microbes is to build biochemical pathways in vitro, an approach we call synthetic biochemistry. Here we test whether the full mevalonate pathway can be reconstituted in vitro and used to produce the commodity chemical isoprene. We construct an in vitro synthetic biochemical pathway that uses the carbon and ATP produced from the glycolysis intermediate phosphoenolpyruvate to run the mevalonate pathway. The system involves 12 enzymes to perform the complex transformation, while providing and balancing the ATP, NADPH, and acetyl‐CoA cofactors. The optimized system produces isoprene from phosphoenolpyruvate in ～100% molar yield. Thus, by inserting the isoprene pathway into previously developed glycolysis modules it may be possible to produce isoprene and other acetyl‐CoA derived isoprenoids from glucose in vitro.     

Rewiring and regulation of cross-compartmentalized metabolism in protists

Plastid acquisition, endosymbiotic associations, lateral gene transfer, organelle degeneracy or even organelle loss influence metabolic capabilities in many different protists. Thus, metabolic diversity is sculpted through the gain of new metabolic functions and moderation or loss of pathways that are often essential in the majority of eukaryotes. What is perhaps less apparent to the casual observer is that the sub-compartmentalization of ubiquitous pathways has been repeatedly remodelled during eukaryotic evolution, and the textbook pictures of intermediary metabolism established for animals, yeast and plants are not conserved in many protists. Moreover, metabolic remodelling can strongly influence the regulatory mechanisms that control carbon flux through the major metabolic pathways. Here, we provide an overview of how core metabolism has been reorganized in various unicellular eukaryotes, focusing in particular on one near universal catabolic pathway (glycolysis) and one ancient anabolic pathway (isoprenoid biosynthesis). For the example of isoprenoid biosynthesis, the compartmentalization of this process in protists often appears to have been influenced by plastid acquisition and loss, whereas for glycolysis several unexpected modes of compartmentalization have emerged. Significantly, the example of trypanosomatid glycolysis illustrates nicely how mathematical modelling and systems biology can be used to uncover or understand novel modes of pathway regulation.     

Multiplicity of Steady States in Glycolysis and Shift of Metabolic State in Cultured Mammalian Cells

Cultured mammalian cells exhibit elevated glycolysis flux and high lactate production. In the industrial bioprocesses for biotherapeutic protein production, glucose is supplemented to the culture medium to sustain continued cell growth resulting in the accumulation of lactate to high levels. In such fed-batch cultures, sometimes a metabolic shift from a state of high glycolysis flux and high lactate production to a state of low glycolysis flux and low lactate production or even lactate consumption is observed. While in other cases with very similar culture conditions, the same cell line and medium, cells continue to produce lactate. A metabolic shift to lactate consumption has been correlated to the productivity of the process. Cultures that exhibited the metabolic shift to lactate consumption had higher titers than those which didn’t. However, the cues that trigger the metabolic shift to lactate consumption state (or low lactate production state) are yet to be identified. Metabolic control of cells is tightly linked to growth control through signaling pathways such as the AKT pathway. We have previously shown that the glycolysis of proliferating cells can exhibit bistability with well-segregated high flux and low flux states. Low lactate production (or lactate consumption) is possible only at a low glycolysis flux state. In this study, we use mathematical modeling to demonstrate that lactate inhibition together with AKT regulation on glycolysis enzymes can profoundly influence the bistable behavior, resulting in a complex steady-state topology. The transition from the high flux state to the low flux state can only occur in certain regions of the steady state topology, and therefore the metabolic fate of the cells depends on their metabolic trajectory encountering the region that allows such a metabolic state switch. Insights from such switch behavior present us with new means to control the metabolism of mammalian cells in fed-batch cultures.     

Development of bifunctional biosensors for sensing and dynamic control of glycolysis flux in metabolic engineering

Glycolysis is the primary metabolic pathway in all living organisms. Maintaining the balance of glycolysis flux and biosynthetic pathways is the crucial matter involved in the microbial cell factory. Few regulation systems can address the issue of metabolic flux imbalance in glycolysis. Here, we designed and constructed a bifunctional glycolysis flux biosensor that can dynamically regulate glycolysis flux for overproduction of desired biochemicals. A series of positive-and negative-response biosensors were created and modified for varied thresholds and dynamic ranges. These engineered glycolysis flux biosensors were verified to be able to characterize in vivo fructose-1,6-diphosphate concentration. Subsequently, the biosensors were applied for fine-tuning glycolysis flux to effectively balance the biosynthesis of two chemicals: mevalonate and N-acetylglucosamine. A glycolysis flux-dynamically controlled Escherichia coli strain achieved a 111.3 g/L mevalonate titer in a 1L fermenter.     

Recovering metabolic pathways via optimization

A metabolic pathway is a coherent set of enzyme catalysed biochemical reactions by which a living organism transforms an initial (source) compound into a final (target) compound. Some of the different metabolic pathways adopted within organisms have been experimentally determined. In this paper, we show that a number of experimentally determined metabolic pathways can be recovered by a mathematical optimization model.     

Engineering primary metabolic pathways of industrial micro-organisms

Metabolic engineering is a powerful tool for the optimisation and the introduction of new cellular processes. This is mostly done by genetic engineering. Since the introduction of this multidisciplinary approach, the success stories keep accumulating. The primary metabolism of industrial micro-organisms has been studied for long time and most biochemical pathways and reaction networks have been elucidated. This large pool of biochemical information, together with data from proteomics, metabolomics and genomics underpins the strategies for design of experiments and choice of targets for manipulation by metabolic engineers. These targets are often located in the primary metabolic pathways, such as glycolysis, pentose phosphate pathway, the TCA cycle and amino acid biosynthesis and mostly at major branch points within these pathways. This paper describes approaches taken for metabolic engineering of these pathways in bacteria, yeast and filamentous fungi.     

Bionics and Structural Biology： A Novel Approach for Bio-energy Production

Cellular metabolism is a very complex process. The biochemical pathways are fundamental structures of biology. These pathways possess a number of regeneration steps which facilitate energy shuttling on a massive scale. This facilitates the biochemical pathways to sustain the energy currency of the cells. This concept has been mimicked using electronic circuit components and it has been used to increase the efficiency of bio-energy generation. Six of the carbohydrate biochemical pathways have been chosen in which glycolysis is the principle pathway. All the six pathways are interrelated and coordinated in a complex manner. Mimic circuits have been designed for all the six biochemical pathways. The components of the metabolic pathways such as enzymes, cofactors etc., are substituted by appropriate electronic circuit components. Enzymes are related to the gain of transistors by the bond dissociation energies of enzyme-substrate molecules under consideration. Cofactors and coenzymes are represented by switches and capacitors respectively. Resistors are used for proper orientation of the circuits. The energy obtained from the current methods employed for the decomposition of organic matter is used to trigger the mimic circuits. A similar energy shuttle is observed in the mimic circuits and the percentage rise for each cycle of circuit functioning is found to be 78.90. The theoretical calculations have been made using a sample of domestic waste weighing 1.182 kg. The calculations arrived at finally speak of the efficiency of the novel methodology employed.     

Functional relationships between capacitation-dependent cell signaling and compartmentalized metabolic pathways in murine spermatozoa

Spermatozoa are highly polarized cells with specific metabolic pathways compartmentalized in different regions. Previously, we hypothesized that glycolysis is organized in the fibrous sheath of the flagellum to provide ATP to dynein ATPases that generate motility and to protein kinases that regulate motility. Although a recent report suggested that glucose is not essential for murine sperm capacitation, we demonstrated that glucose (but not lactate or pyruvate) was necessary and sufficient to support the protein tyrosine phosphorylation events associated with capacitation. The effect of glucose on this signaling pathway was downstream of cAMP, and appeared to arise indirectly as a consequence of metabolism as opposed to a direct signaling effect. Moreover, the phosphorylation events were not affected by uncouplers of oxidative respiration, inhibitors of electron transfer, or by a lack of substrates for oxidative respiration in the medium. Further experiments aimed at identifying potential regulators of sperm glycolysis focused on a germ cell-specific isoform of hexokinase, HK1-SC, which localizes to the fibrous sheath. HK1-SC activity and biochemical localization did not change during sperm capacitation, suggesting that glycolysis in sperm is regulated either at the level of substrate availability or by downstream enzymes. These data support the hypothesis that ATP specifically produced by a compartmentalized glycolytic pathway in the principal piece of the flagellum, as opposed to ATP generated by mitochondria in the mid-piece, is strictly required for protein tyrosine phosphorylation events that take place during sperm capacitation. The relationship between these pathways suggests that spermatozoa offer a model system for the study of integration of compartmentalized metabolic and signaling pathways.     

Integrating thermodynamic and enzymatic constraints into genome-scale metabolic models

Stoichiometric genome-scale metabolic network models (GEMs) have been widely used to predict metabolic phenotypes. In addition to stoichiometric ratios, other constraints such as enzyme availability and thermodynamic feasibility can also limit the phenotype solution space. Extended GEM models considering either enzymatic or thermodynamic constraints have been shown to improve prediction accuracy. In this paper, we propose a novel method that integrates both enzymatic and thermodynamic constraints in a single Pyomo modeling framework (ETGEMs). We applied this method to construct the EcoETM (E. coli metabolic model with enzymatic and thermodynamic constraints). Using this model, we calculated the optimal pathways for cellular growth and the production of 22 metabolites. When comparing the results with those of iML1515 and models with one of the two constraints, we observed that many thermodynamically unfavorable and/or high enzyme cost pathways were excluded from EcoETM. For example, the synthesis pathway of carbamoyl-phosphate (Cbp) from iML1515 is both thermodynamically unfavorable and enzymatically costly. After introducing the new constraints, the production pathways and yields of several Cbp-derived products (e.g. L-arginine, orotate) calculated using EcoETM were more realistic. The results of this study demonstrate the great application potential of metabolic models with multiple constraints for pathway analysis and phenotype prediction.     

Influence of uncertainties in pH,pMg, activity coefficients,metabolite concentrations,and other factors on the analysis of the thermodynamic feasibility of metabolic pathways

Thermodynamic feasibility analysis (TFA) has been used as a tool capable of providing additional constraints to the mass balance‐based methods of analysis of metabolic networks (e.g., flux balance analysis). Several publications have recently appeared in which TFA of different metabolic pathways from relatively simple to the genome‐scale networks was described as a means of detecting the possible metabolic control steps. However, in order to perform TFA, many simplifying assumptions were necessary. On the other hand, it has been shown by applying TFA to the well‐known pathway of glycolysis that erroneous simplifying assumptions may seriously bias the results of the analysis. A quantitative analysis of the influence of non‐ideality of the biochemical system, pH, temperature, and complexation of the metabolites with Mg²⁺ ions as well as a number of other factors on the TFA is reported. It is shown that the feasibility of glycolysis is very seriously limited by the reaction of oxidative phosphorylation of glyceraldehyde phosphate, and that the intracellular concentration of the main product of this reaction, biphosphoglycerate, must be anywhere from 10 to 100 times lower than published values. In addition, the driving force for this reaction, and consequently the feasibility of the entire pathway depend strongly on the intracellular pH and ionic strength and to a lesser extent on pMg and temperature. The analysis may also be influenced by uncertainties of the dissociation and magnesium complexation constants of glyceraldehyde phosphate. The analysis demonstrates the crucial importance of taking such factors into account when performing TFA. It also suggests an urgent need for experimental determinations of such factors as a prerequisite for sensible thermodynamic analysis of metabolism on a genome‐wide scale. Biotechnol. Bioeng. 2009;103: 780–795. © 2009 Wiley Periodicals, Inc.     

Cardiac metabolism as a driver and therapeutic target of myocardial infarction

Reducing infarct size during a cardiac ischaemic-reperfusion episode is still of paramount importance, because the extension of myocardial necrosis is an important risk factor for developing heart failure. Cardiac ischaemia-reperfusion injury (IRI) is in principle a metabolic pathology as it is caused by abruptly halted metabolism during the ischaemic episode and exacerbated by sudden restart of specific metabolic pathways at reperfusion. It should therefore not come as a surprise that therapy directed at metabolic pathways can modulate IRI. Here, we summarize the current knowledge of important metabolic pathways as therapeutic targets to combat cardiac IRI. Activating metabolic pathways such as glycolysis (eg AMPK activators), glucose oxidation (activating pyruvate dehydrogenase complex), ketone oxidation (increasing ketone plasma levels), hexosamine biosynthesis pathway (O-GlcNAcylation; administration of glucosamine/glutamine) and deacetylation (activating sirtuins 1 or 3; administration of NAD⁺-boosting compounds) all seem to hold promise to reduce acute IRI. In contrast, some metabolic pathways may offer protection through diminished activity. These pathways comprise the malate-aspartate shuttle (in need of novel specific reversible inhibitors), mitochondrial oxygen consumption, fatty acid oxidation (CD36 inhibitors, malonyl-CoA decarboxylase inhibitors) and mitochondrial succinate metabolism (malonate). Additionally, protecting the cristae structure of the mitochondria during IR, by maintaining the association of hexokinase II or creatine kinase with mitochondria, or inhibiting destabilization of F_OF₁-ATPase dimers, prevents mitochondrial damage and thereby reduces cardiac IRI. Currently, the most promising and druggable metabolic therapy against cardiac IRI seems to be the singular or combined targeting of glycolysis, O-GlcNAcylation and metabolism of ketones, fatty acids and succinate.     

High salt diet induces metabolic alterations in multiple biological processes of Dahl salt-sensitive rats

High salt induced renal disease is a condition resulting from the interactions of genetic and dietary factors causing multiple complications. To understand the metabolic alterations associated with renal disease, we comprehensively analyzed the metabonomic changes induced by high salt intake in Dahl salt-sensitive (SS) rats using GC-MS technology and biochemical analyses. Physiological features, serum chemistry, and histopathological data were obtained as complementary information. Our results showed that high salt (HS) intake for 16 weeks caused significant metabolic alterations in both the renal medulla and cortex involving a variety pathways involved in the metabolism of organic acids, amino acids, fatty acids, and purines. In addition, HS enhanced glycolysis (hexokinase, phosphofructokinase and pyruvate kinase) and amino acid metabolism and suppressed the TCA (citrate synthase and aconitase) cycle. Finally, HS intake caused up-regulation of the pentose phosphate pathway (glucose 6-phosphate dehydrogenase and 6-phosphogluconate dehydrogenase), the ratio of NADPH/NADP⁺, NADPH oxidase activity and ROS production, suggesting that increased oxidative stress was associated with an altered PPP pathway. The metabolic pathways identified may serve as potential targets for the treatment of renal damage. Our findings provide comprehensive biochemical details about the metabolic responses to a high salt diet, which may contribute to the understanding of renal disease and salt-induced hypertension in SS rats.     

Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective

Cellular metabolism is most often described and interpreted in terms of the biochemical reactions that make up the metabolic network. Genomics is providing near complete information regarding the genes/gene products participating in cellular metabolism for a growing number of organisms. As the true functional units of metabolic systems are its pathways, the time has arrived to define metabolic pathways in the context of whole-cell metabolism for the analysis of the structural design and capabilities of the metabolic network. In this study, we present the theoretical foundations for the identification of the unique set of systemically independent biochemical pathways, termed extreme pathways, based on system stochiometry and limited thermodynamics. These pathways represent the edges of the steady-state flux cone derived from convex analysis, and they can be used to represent any flux distribution achievable by the metabolic network. An algorithm is presented to determine the set of extreme pathways for a system of any complexity and a classification scheme is introduced for the characterization of these pathways. The property of systemic independence is discussed along with its implications for issues related to metabolic regulation and the evolution of cellular metabolic networks. The underlying pathway structure that is determined from the set of extreme pathways now provides us with the ability to analyse, interpret, and perhaps predict metabolic function from a pathway-based perspective in addition to the traditional reaction-based perspective. The algorithm and classification scheme developed can be used to describe the pathway structure in annotated genomes to explore the capabilities of an organism.     

Thermodynamically based profiling of drug metabolism and drug-drug metabolic interactions: a case study of acetaminophen and ethanol toxic interaction

Drug-drug metabolic interactions can result in unwanted side effects, including reduced drug efficacy and formation of toxic metabolic intermediates. In this work, thermodynamic constraints on non-equilibrium metabolite concentrations are used to reveal the biochemical interactions between the metabolic pathways of ethanol and acetaminophen (N-acetyl-p-aminophenol), two drugs known to interact unfavorably. It is known that many reactions of these pathways are coupled to the central energy metabolic reactions through a number of metabolites and the cellular redox potential. Based on these observations, a metabolic network model has been constructed and a database of thermodynamic properties for all participating metabolites and reactions has been compiled. Constraint-based computational analysis of the feasible metabolite concentrations reveals that the non-toxic pathways for APAP metabolism and the pathway for detoxifying N-acetyl-p-benzoquinoneimine (NAPQI) are inhibited by network interactions with ethanol metabolism. These results point to the potential utility of thermodynamically based profiling of metabolic network interactions in screening of drug candidates and analysis of potential toxicity.     

PathMiner: predicting metabolic pathways by heuristic search

MOTIVATION: Automated methods for biochemical pathway inference are becoming increasingly important for understanding biological processes in living and synthetic systems. With the availability of data on complete genomes and increasing information about enzyme-catalyzed biochemistry it is becoming feasible to approach this problem computationally. In this paper we present PathMiner, a system for automatic metabolic pathway inference. PathMiner predicts metabolic routes by reasoning over transformations using chemical and biological information. RESULTS: We build a biochemical state-space using data from known enzyme-catalyzed transformations in Ligand, including, 2917 unique transformations between 3890 different compounds. To predict metabolic pathways we explore this state-space by developing an informed search algorithm. For this purpose we develop a chemically motivated heuristic to guide the search. Since the algorithm does not depend on predefined pathways, it can efficiently identify plausible routes using known biochemical transformations.     

Rapid simulation and analysis of isotopomer distributions using constraints based on enzyme mechanisms: an example from HT29 cancer cells

MOTIVATION: Addition of labeled substrates and the measurement of the subsequent distribution of the labels in isotopomers in reaction networks provide a unique method for assessing metabolic fluxes in whole cells. However, owing to insufficiency of information, attempts to quantify the fluxes often yield multiple possible sets of solutions that are consistent with a given experimental pattern of isotopomers. In the study of the pentose phosphate pathways, the need to consider isotope exchange reactions of transketolase (TK) and transaldolase (TA) (which in past analyses have often been ignored) magnifies this problem; but accounting for the interrelation between the fluxes known from biochemical studies and kinetic modeling solves it. The mathematical relationships between kinetic and equilibrium constants restrict the domain of estimated fluxes to the ones compatible not only with a given set of experimental data, but also with other biochemical information. METHOD: We present software that integrates kinetic modeling with isotopomer distribution analysis. It solves the ordinary differential equations for total concentrations (accounting for the kinetic mechanisms) as well as for all isotopomers in glycolysis and the pentose phosphate pathway (PPP). In the PPP the fluxes created in the TK and TA reactions are expressed through unitary rate constants. The algorithms that account for all the kinetic and equilbrium constant constraints are integrated with the previously developed algorithms, which have been further optimized. The most time-consuming calculations were programmed directly in assembly language; this gave an order of magnitude decrease in the computation time, thus allowing analysis of more complex systems. The software was developed as C-code linked to a program written in Mathematica (Wolfram Research, Champaign, IL), and also as a C++ program independent from Mathematica. RESULTS: Implementing constraints imposed by kinetic and equilibrium constants in the isotopomer distribution analysis in the data from the cancer cells eliminated estimates of fluxes that were inconsistent with the kinetic mechanisms of TK and TA. Fluxes measured experimentally in cells can be used to estimate better the kinetics of TK and TA as they operate in situ. Thus, our approach of integrating various methods for in situ flux analysis opens up the possibility of designing new types of experiments to probe metabolic interrelationships, including the incorporation of additional biochemical information. AVAILABILITY: Software is available freely at: http://www.bq.ub.es/bioqint/selivanov.htm CONTACT: martacascante@ub.edu