The danger of metabolic pathways with turbo design

Visualizing Metabolism in Biotechnologically Important Yeasts with dDNP NMR Reveals Evolutionary Strategies and Glycolytic Logic

Saccharomyces cerevisiae has long been a pillar of biotechnological production and basic research. More recently, strides to exploit the functional repertoire of nonconventional yeasts for biotechnological production have been made. Genomes and genetic tools for these yeasts are not always available, and yeast genomics alone may be insufficient to determine the functional features in yeast metabolism. Hence, functional assays of metabolism, ideally in the living cell, are best suited to characterize the cellular biochemistry of such yeasts. Advanced in cell NMR methods can allow the direct observation of carbohydrate influx into central metabolism on a seconds time scale: dDNP NMR spectroscopy temporarily enhances the nuclear spin polarization of substrates by more than 4 orders of magnitude prior to functional assays probing central metabolism. We use various dDNP enhanced carbohydrates for in-cell NMR to compare the metabolism of S. cerevisiae and nonconventional yeasts, with an emphasis on the wine yeast Hanseniaspora uvarum. In-cell observations indicated more rapid exhaustion of free cytosolic NAD+ in H. uvarum and alternative routes for pyruvate conversion, in particular, rapid amination to alanine. In-cell observations indicated that S. cerevisiae outcompetes other biotechnologically relevant yeasts by rapid ethanol formation due to the efficient adaptation of cofactor pools and the removal of competing reactions from the cytosol. By contrast, other yeasts were better poised to use redox neutral processes that avoided CO2-emission. Beyond visualizing the different cellular strategies for arriving at redox neutral end points, in-cell dDNP NMR probing showed that glycolytic logic is more conserved: nontoxic precursors of cellular building blocks formed high-population intermediates in the influx of glucose into the central metabolism of eight different biotechnologically important yeasts. Unsupervised clustering validated that the observation of rapid intracellular chemistry is a viable means to functionally classify biotechnologically important organisms.

Metabolic Tug-of-War between Glycolysis and Translation Revealed by Biochemical Reconstitution

Inside cells, various biological systems work cooperatively for homeostasis and self-replication. These systems do not work independently as they compete for shared elements like ATP and NADH. However, it has been believed that such competition is not a problem in codependent biological systems such as the energy-supplying glycolysis and the energy-consuming translation system. In this study, we biochemically reconstituted the coupling system of glycolysis and translation using purified elements and found that the competition for ATP between glycolysis and protein synthesis interferes with their coupling. Both experiments and simulations revealed that this interference is derived from a metabolic tug-of-war between glycolysis and translation based on their reaction rates, which changes the threshold of the initial substrate concentration for the success coupling. By the metabolic tug-of-war, translation energized by strong glycolysis is facilitated by an exogenous ATPase, which normally inhibits translation. These findings provide chemical insights into the mechanism of competition among biological systems in living cells and provide a framework for the construction of synthetic metabolism in vitro.

The Imidazolium Ionic Liquids Toxicity is Due to Their Effect on the Plasma Membrane

Ionic liquids (ILs) are organic salts with a low melting point. This is due to the fact that their alkyl side chains, which are covalently connected to the ion, hinder the crystallization of ILs. The low melting point of ILs has led to their widespread use as relatively harmless solvents. However, ILs do have toxic properties, the mechanism of which is largely unknown, so identifying the cellular targets of ILs is of practical importance. In our work, we showed that imidazolium ILs are not able to penetrate model membranes without damaging them. We also found that inactivation of multidrug resistance (MDR) pumps in yeast cells does not increase their sensitivity to imidazolium ILs. The latter indicates that the target of toxicity of imidazolium ILs is not in the cytoplasm. Thus, it can be assumed that the disruption of the barrier properties of the plasma membrane is the main reason for the toxicity of low concentrations of imidazolium ILs. We also showed that supplementation with imidazolium ILs restores the growth of cells with kinetically blocked glycolysis. Apparently, a slight disruption of the plasma membrane caused by ILs can, in some cases, be beneficial for the cell.

The impact of metabolism on the adaptation of organisms to environmental change

Since Jacob and Monod's discovery of the lac operon ∼1960, the explanations offered for most metabolic adaptations have been genetic. The focus has been on the adaptive changes in gene expression that occur, which are often referred to as "metabolic reprogramming." The contributions metabolism makes to adaptation have been largely ignored. Here we point out that metabolic adaptations, including the associated changes in gene expression, are highly dependent on the metabolic state of an organism prior to the environmental change to which it is adapting, and on the plasticity of that state. In support of this hypothesis, we examine the paradigmatic example of a genetically driven adaptation, the adaptation of E. coli to growth on lactose, and the paradigmatic example of a metabolic driven adaptation, the Crabtree effect in yeast. Using a framework based on metabolic control analysis, we have reevaluated what is known about both adaptations, and conclude that knowledge of the metabolic properties of these organisms prior to environmental change is critical for understanding not only how they survive long enough to adapt, but also how the ensuing changes in gene expression occur, and their phenotypes post-adaptation. It would be useful if future explanations for metabolic adaptations acknowledged the contributions made to them by metabolism, and described the complex interplay between metabolic systems and genetic systems that make these adaptations possible.

Dynamics of co-substrate pools can constrain and regulate metabolic fluxes

Cycling of co-substrates, whereby a metabolite is converted among alternate forms via different reactions, is ubiquitous in metabolism. Several cycled co-substrates are well known as energy and electron carriers (e.g. ATP and NAD(P)H), but there are also other metabolites that act as cycled co-substrates in different parts of central metabolism. Here, we develop a mathematical framework to analyse the effect of co-substrate cycling on metabolic flux. In the cases of a single reaction and linear pathways, we find that co-substrate cycling imposes an additional flux limit on a reaction, distinct to the limit imposed by the kinetics of the primary enzyme catalysing that reaction. Using analytical methods, we show that this additional limit is a function of the total pool size and turnover rate of the cycled co-substrate. Expanding from this insight and using simulations, we show that regulation of these two parameters can allow regulation of flux dynamics in branched and coupled pathways. To support these theoretical insights, we analysed existing flux measurements and enzyme levels from the central carbon metabolism and identified several reactions that could be limited by the dynamics of co-substrate cycling. We discuss how the limitations imposed by co-substrate cycling provide experimentally testable hypotheses on specific metabolic phenotypes. We conclude that measuring and controlling co-substrate dynamics is crucial for understanding and engineering metabolic fluxes in cells.

Structural Thermokinetic Modelling

To translate metabolic networks into dynamic models, the Structural Kinetic Modelling framework (SKM) assumes a given reference state and replaces the reaction elasticities in this state by random numbers. A new variant, called Structural Thermokinetic Modelling (STM), accounts for reversible reactions and thermodynamics. STM relies on a dependence schema in which some basic variables are sampled, fitted to data, or optimised, while all other variables can be easily computed. Correlated elasticities follow from enzyme saturation values and thermodynamic forces, which are physically independent. Probability distributions in the dependence schema define a model ensemble, which allows for probabilistic predictions even if data are scarce. STM highlights the importance of variabilities, dependencies, and covariances of biological variables. By varying network structure, fluxes, thermodynamic forces, regulation, or types of rate laws, the effects of these model features can be assessed. By choosing the basic variables, metabolic networks can be converted into kinetic models with consistent reversible rate laws. Metabolic control coefficients obtained from these models can tell us about metabolic dynamics, including responses and optimal adaptations to perturbations, enzyme synergies and metabolite correlations, as well as metabolic fluctuations arising from chemical noise. To showcase STM, I study metabolic control, metabolic fluctuations, and enzyme synergies, and how they are shaped by thermodynamic forces. Considering thermodynamics can improve predictions of flux control, enzyme synergies, correlated flux and metabolite variations, and the emergence and propagation of metabolic noise.

Kinetic Modeling of Saccharomyces cerevisiae Central Carbon Metabolism: Achievements, Limitations, and Opportunities

Central carbon metabolism comprises the metabolic pathways in the cell that process nutrients into energy, building blocks and byproducts. To unravel the regulation of this network upon glucose perturbation, several metabolic models have been developed for the microorganism Saccharomyces cerevisiae. These dynamic representations have focused on glycolysis and answered multiple research questions, but no commonly applicable model has been presented. This review systematically evaluates the literature to describe the current advances, limitations, and opportunities. Different kinetic models have unraveled key kinetic glycolytic mechanisms. Nevertheless, some uncertainties regarding model topology and parameter values still limit the application to specific cases. Progressive improvements in experimental measurement technologies as well as advances in computational tools create new opportunities to further extend the model scale. Notably, models need to be made more complex to consider the multiple layers of glycolytic regulation and external physiological variables regulating the bioprocess, opening new possibilities for extrapolation and validation. Finally, the onset of new data representative of individual cells will cause these models to evolve from depicting an average cell in an industrial fermenter, to characterizing the heterogeneity of the population, opening new and unseen possibilities for industrial fermentation improvement.

Gene expression regulates metabolite homeostasis during the Crabtree effect: Implications for the adaptation and evolution of Metabolism

A key issue in both molecular and evolutionary biology has been to define the roles of genes and phenotypes in the adaptation of organisms to environmental changes. The dominant view has been that an organism's metabolic adaptations are driven by gene expression and that gene mutations, independent of the starting phenotype, are responsible for the evolution of new metabolic phenotypes. We propose an alternate hypothesis, in which the phenotype and genotype together determine metabolic adaptation both in the lifetime of the organism and in the evolutionary selection of adaptive metabolic traits. We tested this hypothesis by flux-balance and metabolic-control analysis of the relative roles of the starting phenotype and gene expression in regulating the metabolic adaptations during the Crabtree effect in yeast, when they are switched from a low- to high-glucose environment. Critical for successful short-term adaptation was the ability of the glycogen/trehalose shunt to balance the glycolytic pathway. The role of later gene expression of new isoforms of glycolytic enzymes, rather than flux control, was to provide additional homeostatic mechanisms allowing an increase in the amount and efficiency of adenosine triphosphate and product formation while maintaining glycolytic balance. We further showed that homeostatic mechanisms, by allowing increased phenotypic plasticity, could have played an important role in guiding the evolution of the Crabtree effect. Although our findings are specific to Crabtree yeast, they are likely to be broadly found because of the well-recognized similarities in glucose metabolism across kingdoms and phyla from yeast to humans.

Metabolomic analysis of antimicrobial mechanism of polysaccharides from Sparassis crispa based on HPLC-Q-TOF/MS

Abuse of antibiotics makes antibiotic-resistance become a huge challenge in bacterial infection treatment. The discovery of new antibiotics is of great significance to human health. In this study, the antibacterial mechanism of Sparassis crispa polysaccharides (SCPs) was explored. The SCPs isolated from Sparassis crispa was composed of fucose, glucose and galactose with a molar ratio of 0.043 : 0.652: 0.305. Bacteriostatic tests showed SCPs inhibited the growth of Staphylococcus aureus better than Escherichia coli's, and damage to bacteria was observed under scanning electron microscopy. Metabolomic analysis based on HPLC-Q-TOF/MS indicated that SCPs disrupted metabolism of the glycolysis and tricarboxylic acid cycle pathways in S. aureus. The variations of fructose-1,6-diphosphate, 1,3-diphosphoglycerol, succinate and oxaloacetate were significant, whose systematic changes accompanied with decrease of ATP in cells indicated that SCPs could exert antibacterial effects by inducing dysfunction of catabolism and energy metabolism. Our research confirmed the antibacterial properties of SCPs and provided a perspective for understanding antibacterial mechanism of polysaccharides from natural products through metabolomics technology.

Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes

A virtual metabolic human model is a valuable complement to experimental biology and clinical studies, because in vivo research involves serious ethical and technical problems. I have proposed a multi-organ and multi-scale kinetic model that formulates the reactions of enzymes and transporters with the regulation of hormonal actions at postprandial and postabsorptive states. The computational model consists of 202 ordinary differential equations for metabolites with 217 reaction rates and 1,140 kinetic parameter constants. It is the most comprehensive, largest, and highly predictive model of the whole-body metabolism. Use of the model revealed the mechanisms by which individual disorders, such as steatosis, β cell dysfunction, and insulin resistance, were combined to cause diabetes. The model predicted a glycerol kinase inhibitor to be an effective medicine for type 2 diabetes, which not only decreased hepatic triglyceride but also reduced plasma glucose. The model also enabled us to rationally design combination therapy.

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A standard of virtual metabolic human dynamic models is proposed

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It integrates the three scales of molecules, organs, and whole body

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It gets insight into pathological mechanisms of type 1 and type 2 diabetes

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It enables the computer-aided design of medication treatment for diabetes

Selection for rapid uptake of scarce or fluctuating resource explains vulnerability of glycolysis to imbalance

Glycolysis is a conserved central pathway in energy metabolism that converts glucose to pyruvate with net production of two ATP molecules. Because ATP is produced only in the lower part of glycolysis (LG), preceded by an initial investment of ATP in the upper glycolysis (UG), achieving robust start-up of the pathway upon activation presents a challenge: a sudden increase in glucose concentration can throw a cell into a self-sustaining imbalanced state in which UG outpaces LG, glycolytic intermediates accumulate and the cell is unable to maintain high ATP concentration needed to support cellular functions. Such metabolic imbalance can result in "substrate-accelerated death", a phenomenon observed in prokaryotes and eukaryotes when cells are exposed to an excess of substrate that previously limited growth. Here, we address why evolution has apparently not eliminated such a costly vulnerability and propose that it is a manifestation of an evolutionary trade-off, whereby the glycolysis pathway is adapted to quickly secure scarce or fluctuating resource at the expense of vulnerability in an environment with ample resource. To corroborate this idea, we perform individual-based eco-evolutionary simulations of a simplified yeast glycolysis pathway consisting of UG, LG, phosphate transport between a vacuole and a cytosol, and a general ATP demand reaction. The pathway is evolved in constant or fluctuating resource environments by allowing mutations that affect the (maximum) reaction rate constants, reflecting changing expression levels of different glycolytic enzymes. We demonstrate that under limited constant resource, populations evolve to a genotype that exhibits balanced dynamics in the environment it evolved in, but strongly imbalanced dynamics under ample resource conditions. Furthermore, when resource availability is fluctuating, imbalanced dynamics confers a fitness advantage over balanced dynamics: when glucose is abundant, imbalanced pathways can quickly accumulate the glycolytic intermediate FBP as intracellular storage that is used during periods of starvation to maintain high ATP concentration needed for growth. Our model further predicts that in fluctuating environments, competition for glucose can result in stable coexistence of balanced and imbalanced cells, as well as repeated cycles of population crashes and recoveries that depend on such polymorphism. Overall, we demonstrate the importance of ecological and evolutionary arguments for understanding seemingly maladaptive aspects of cellular metabolism.

Impact of Altered Trehalose Metabolism on Physiological Response of Penicillium chrysogenum Chemostat Cultures during Industrially Relevant Rapid Feast/Famine Conditions

Due to insufficient mass transfer and mixing issues, cells in the industrial-scale bioreactor are often forced to experience glucose feast/famine cycles, mostly resulting in reduced commercial metrics (titer, yield and productivity). Trehalose cycling has been confirmed as a double-edged sword in the Penicillium chrysogenum strain, which facilitates the maintenance of a metabolically balanced state, but it consumes extra amounts of the ATP responsible for the repeated breakdown and formation of trehalose molecules in response to extracellular glucose perturbations. This loss of ATP would be in competition with the high ATP-demanding penicillin biosynthesis. In this work, the role of trehalose metabolism was further explored under industrially relevant conditions by cultivating a high-yielding Penicillium chrysogenum strain, and the derived trehalose-null strains in the glucose-limited chemostat system where the glucose feast/famine condition was imposed. This dynamic feast/famine regime with a block-wise feed/no feed regime (36 s on, 324 s off) allows one to generate repetitive cycles of moderate changes in glucose availability. The results obtained using quantitative metabolomics and stoichiometric analysis revealed that the intact trehalose metabolism is vitally important for maintaining penicillin production capacity in the Penicillium chrysogenum strain under both steady state and dynamic conditions. Additionally, cells lacking such a key metabolic regulator would become more sensitive to industrially relevant conditions, and are more able to sustain metabolic rearrangements, which manifests in the shrinkage of the central metabolite pool size and the formation of ATP-consuming futile cycles.

Microbial metabolic noise

From the time a cell was first placed under the microscope, it became apparent that identifying two clonal cells that "look" identical is extremely challenging. Since then, cell-to-cell differences in shape, size, and protein content have been carefully examined, informing us of the ultimate limits that hinder two cells from occupying an identical phenotypic state. Here, we present recent experimental and computational evidence that similar limits emerge also in cellular metabolism. These limits pertain to stochastic metabolic dynamics and, thus, cell-to-cell metabolic variability, including the resulting adapting benefits. We review these phenomena with a focus on microbial metabolism and conclude with a brief outlook on the potential relationship between metabolic noise and adaptive evolution. This article is categorized under: Metabolic Diseases > Computational Models Metabolic Diseases > Biomedical Engineering.

Aberrant Intracellular pH Regulation Limiting Glyceraldehyde-3-Phosphate Dehydrogenase Activity in the Glucose-Sensitive Yeast tps1Δ Mutant

Glucose catabolism is the backbone of metabolism in most organisms. In spite of numerous studies and extensive knowledge, major controls on glycolysis and its connections to the other metabolic pathways remain to be discovered. A striking example is provided by the extreme glucose sensitivity of the yeast tps1Δ mutant, which undergoes apoptosis in the presence of just a few millimolar glucose. Previous work has shown that the conspicuous glucose-induced hyperaccumulation of the glycolytic metabolite fructose-1,6-bisphosphate (Fru1,6bisP) in tps1Δ cells triggers apoptosis through activation of the Ras-cAMP-protein kinase A (PKA) signaling pathway. However, the molecular cause of this Fru1,6bisP hyperaccumulation has remained unclear. We now provide evidence that the persistent drop in intracellular pH upon glucose addition to tps1Δ cells likely compromises the activity of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), a major glycolytic enzyme downstream of Fru1,6bisP, due to its unusually high pH optimum. Our work highlights the potential importance of intracellular pH fluctuations for control of major metabolic pathways.

Whereas the yeast Saccharomyces cerevisiae shows great preference for glucose as a carbon source, a deletion mutant in trehalose-6-phosphate synthase, tps1Δ, is highly sensitive to even a few millimolar glucose, which triggers apoptosis and cell death. Glucose addition to tps1Δ cells causes deregulation of glycolysis with hyperaccumulation of metabolites upstream and depletion downstream of glyceraldehyde-3-phosphate dehydrogenase (GAPDH). The apparent metabolic barrier at the level of GAPDH has been difficult to explain. We show that GAPDH isozyme deletion, especially Tdh3, further aggravates glucose sensitivity and metabolic deregulation of tps1Δ cells, but overexpression does not rescue glucose sensitivity. GAPDH has an unusually high pH optimum of 8.0 to 8.5, which is not altered by tps1Δ. Whereas glucose causes short, transient intracellular acidification in wild-type cells, in tps1Δ cells, it causes permanent intracellular acidification. The hxk2Δ and snf1Δ suppressors of tps1Δ restore the transient acidification. These results suggest that GAPDH activity in the tps1Δ mutant may be compromised by the persistently low intracellular pH. Addition of NH₄Cl together with glucose at high extracellular pH to tps1Δ cells abolishes the pH drop and reduces glucose-6-phosphate (Glu6P) and fructose-1,6-bisphosphate (Fru1,6bisP) hyperaccumulation. It also reduces the glucose uptake rate, but a similar reduction in glucose uptake rate in a tps1Δ hxt2,4,5,6,7Δ strain does not prevent glucose sensitivity and Fru1,6bisP hyperaccumulation. Hence, our results suggest that the glucose-induced intracellular acidification in tps1Δ cells may explain, at least in part, the apparent glycolytic bottleneck at GAPDH but does not appear to fully explain the extreme glucose sensitivity of the tps1Δ mutant.

Lipophilic Cations Rescue the Growth of Yeast under the Conditions of Glycolysis Overflow

Chemicals inducing a mild decrease in the ATP/ADP ratio are considered as caloric restriction mimetics as well as treatments against obesity. Screening for such chemicals in animal model systems requires a lot of time and labor. Here, we present a system for the rapid screening of non-toxic substances causing such a de-energization of cells. We looked for chemicals allowing the growth of yeast lacking trehalose phosphate synthase on a non-fermentable carbon source in the presence of glucose. Under such conditions, the cells cannot grow because the cellular phosphate is mostly being used to phosphorylate the sugars in upper glycolysis, while the biosynthesis of bisphosphoglycerate is blocked. We reasoned that by decreasing the ATP/ADP ratio, one might prevent the phosphorylation of the sugars and also boost bisphosphoglycerate synthesis by providing the substrate, i.e., inorganic phosphate. We confirmed that a complete inhibition of oxidative phosphorylation alleviates the block. As our system includes a non-fermentable carbon source, only the chemicals that did not cause a complete block of mitochondrial ATP synthesis allowed the initial depletion of glucose followed by respiratory growth. Using this system, we found two novel compounds, dodecylmethyl diphenylamine (FS1) and diethyl (tetradecyl) phenyl ammonium bromide (Kor105), which possess a mild membrane-depolarizing activity.

An Improved ATP FRET Sensor For Yeast Shows Heterogeneity During Nutrient Transitions

Adenosine 5-triphosphate (ATP) is the main free energy carrier in metabolism. In budding yeast, shifts to glucose-rich conditions cause dynamic changes in ATP levels, but it is unclear how heterogeneous these dynamics are at a single-cell level. Furthermore, pH also changes and affects readout of fluorescence-based biosensors for single-cell measurements. To measure ATP changes reliably in single yeast cells, we developed yAT1.03, an adapted version of the AT1.03 ATP biosensor, that is pH-insensitive. We show that pregrowth conditions largely affect ATP dynamics during transitions. Moreover, single-cell analyses showed a large variety in ATP responses, which implies large differences of glycolytic startup between individual cells. We found three clusters of dynamic responses, and we show that a small subpopulation of wild-type cells reached an imbalanced state during glycolytic startup, characterized by low ATP levels. These results confirm the need for new tools to study dynamic responses of individual cells in dynamic environments.

Regulation of trehalose, a typical stress protectant, on central metabolisms, cell growth and division of Saccharomyces cerevisiae CEN.PK113-7D

Trehalose could protect the typical food microorganism Saccharomyces cerevisiae cell against environmental stresses; however, the other regulation effects of trehalose on yeast cells during the fermentation are still poorly understood. In this manuscript, different concentrations (i.e., 0, 2 and 5% g/v) of trehalose were respectively added into the medium to evaluate the effect of trehalose on growth, central metabolisms and division of S. cerevisiae CEN.PK113-7D strain that could uptake exogenous trehalose. Results indicated that addition of trehalose could inhibit yeast cell growth in the presence or absence of 8% v/v ethanol stress. Exogenous trehalose inhibited the glucose transporting efficiency and reduced intracellular glucose content. Simultaneously, increased intracellular trehalose content destroyed the steady state of trehalose cycle and caused the imbalance between the upper glycolysis part and the lower part, thereby leading to the dysfunction of glycolysis and further inhibiting the normal yeast cell growth. Moreover, energy metabolisms were impaired and the ATP production was reduced by addition of trehalose. Finally, exogenous trehalose-associated inhibition on yeast cell growth and metabolisms delayed cell cycle. These results also highlighted our knowledge about relationship between trehalose and growth, metabolisms and division of S. cerevisiae cells during fermentation.

The plastid phosphorylase as a multiple-role player in plant metabolism

The physiological roles of the plastidial phosphorylase in starch metabolism of higher plants have been debated for decades. While estimated physiological substrate levels favor a degradative role, genetic evidence indicates that the plastidial phosphorylase (Pho1) plays an essential role in starch initiation and maturation of the starch granule in developing rice grains. The plastidial enzyme contains a unique peptide domain, up to 82 residues in length depending on the plant species, not found in its cytosolic counterpart or glycogen phosphorylases. The role of this extra peptide domain is perplexing, as its complete removal does not significantly affect the in vitro catalytic or enzymatic regulatory properties of rice Pho1. This peptide domain may have a regulatory function as it contains potential phosphorylation sites and, in some plant Pho1s, a PEST motif, a substrate for proteasome-mediated degradation. We discuss the potential roles of Pho1 and its L80 domain in starch biosynthesis and photosynthesis.

Self-replenishment cycles generate a threshold response

Many metabolic cycles, including the tricarboxylic acid cycle, glyoxylate cycle, Calvin cycle, urea cycle, coenzyme recycling, and substrate cycles, are well known to catabolize and anabolize different metabolites for efficient energy and mass conversion. In terms of stoichiometric structure, this study explicitly identifies two types of metabolic cycles. One is the well-known, elementary cycle that converts multiple substrates into different products and recycles one of the products as a substrate, where the recycled substrate is supplied from the outside to run the cycle. The other is the self-replenishment cycle that merges multiple substrates into two or multiple identical products and reuses one of the products as a substrate. The substrates are autonomously supplied within the cycle. This study first defines the self-replenishment cycles that many scientists have overlooked despite its functional importance. Theoretical analysis has revealed the design principle of the self-replenishment cycle that presents a threshold response without any bistability nor cooperativity. To verify the principle, three detailed kinetic models of self-replenishment cycles embedded in an E. coli metabolic system were simulated. They presented the threshold response or digital switch-like function that steeply shift metabolic status.

Yeast Systems Biology: Model Organism and Cell Factory

For thousands of years, the yeast Saccharomyces cerevisiae (S. cerevisiae) has served as a cell factory for the production of bread, beer, and wine. In more recent years, this yeast has also served as a cell factory for producing many different fuels, chemicals, food ingredients, and pharmaceuticals. S. cerevisiae, however, has also served as a very important model organism for studying eukaryal biology, and even today many new discoveries, important for the treatment of human diseases, are made using this yeast as a model organism. Here a brief review of the use of S. cerevisiae as a model organism for studying eukaryal biology, its use as a cell factory, and how advances in systems biology underpin developments in both these areas, is provided.

Systems Biology - A Guide for Understanding and Developing Improved Strains of Lactic Acid Bacteria

Lactic Acid Bacteria (LAB) are extensively employed in the production of various fermented foods, due to their safe status, ability to affect texture and flavor and finally due to the beneficial effect they have on shelf-life. More recently, LAB have also gained interest as production hosts for various useful compounds, particularly compounds with sensitive applications, such as food ingredients and therapeutics. As for all industrial microorganisms, it is important to have a good understanding of the physiology and metabolism of LAB in order to fully exploit their potential, and for this purpose, many systems biology approaches are available. Systems metabolic engineering, an approach that combines optimization of metabolic enzymes/pathways at the systems level, synthetic biology as well as in silico model simulation, has been used to build microbial cell factories for production of biofuels, food ingredients and biochemicals. When developing LAB for use in foods, genetic engineering is in general not an accepted approach. An alternative is to screen mutant libraries for candidates with desirable traits using high-throughput screening technologies or to use adaptive laboratory evolution to select for mutants with special properties. In both cases, by using omics data and data-driven technologies to scrutinize these, it is possible to find the underlying cause for the desired attributes of such mutants. This review aims to describe how systems biology tools can be used for obtaining both engineered as well as non-engineered LAB with novel and desired properties.

Glycolytic flux in Saccharomyces cerevisiae is dependent on RNA polymerase III and its negative regulator Maf1

Protein biosynthesis is energetically costly, is tightly regulated and is coupled to stress conditions including glucose deprivation. RNA polymerase III (RNAP III)-driven transcription of tDNA genes for production of tRNAs is a key element in efficient protein biosynthesis. Here we present an analysis of the effects of altered RNAP III activity on the Saccharomyces cerevisiae proteome and metabolism under glucose-rich conditions. We show for the first time that RNAP III is tightly coupled to the glycolytic system at the molecular systems level. Decreased RNAP III activity or the absence of the RNAP III negative regulator, Maf1 elicit broad changes in the abundance profiles of enzymes engaged in fundamental metabolism in S. cerevisiae In a mutant compromised in RNAP III activity, there is a repartitioning towards amino acids synthesis de novo at the expense of glycolytic throughput. Conversely, cells lacking Maf1 protein have greater potential for glycolytic flux.

Combined In-Cell NMR and Simulation Approach to Probe Redox-Dependent Pathway Control

Dynamic response of intracellular reaction cascades to changing environments is a hallmark of living systems. As metabolism is complex, mechanistic models have gained popularity for describing the dynamic response of cellular metabolism and for identifying target genes for engineering. At the same time, the detailed tracking of transient metabolism in living cells on the subminute time scale has become amenable using dynamic nuclear polarization-enhanced ¹³C NMR. Here, we suggest an approach combining in-cell NMR spectroscopy with perturbation experiments and modeling to obtain evidence that the bottlenecks of yeast glycolysis depend on intracellular redox state. In pre-steady-state glycolysis, pathway bottlenecks shift from downstream to upstream reactions within a few seconds, consistent with a rapid decline in the NAD⁺/NADH ratio. Simulations using mechanistic models reproduce the experimentally observed response and help identify unforeseen biochemical events. Remaining inaccuracies in the computational models can be identified experimentally. The combined use of rapid injection NMR spectroscopy and in silico simulations provides a promising method for characterizing cellular reactions with increasing mechanistic detail.

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.

Understanding start-up problems in yeast glycolysis

Yeast glycolysis has been the focus of research for decades, yet a number of dynamical aspects of yeast glycolysis remain poorly understood at present. If nutrients are scarce, yeast will provide its catabolic and energetic needs with other pathways, but the enzymes catalysing upper glycolytic fluxes are still expressed. We conjecture that this overexpression facilitates the rapid transition to glycolysis in case of a sudden increase in nutrient concentration. However, if starved yeast is presented with abundant glucose, it can enter into an imbalanced state where glycolytic intermediates keep accumulating, leading to arrested growth and cell death. The bistability between regularly functioning and imbalanced phenotypes has been shown to depend on redox balance. We shed new light on these phenomena with a mathematical analysis of an ordinary differential equation model, including NADH to account for the redox balance. In order to gain qualitative insight, most of the analysis is parameter-free, i.e., without assigning a numerical value to any of the parameters. The model has a subtle bifurcation at the switch between an inviable equilibrium state and stable flux through glycolysis. This switch occurs if the ratio between the flux through upper glycolysis and ATP consumption rate of the cell exceeds a fixed threshold. If the enzymes of upper glycolysis would be barely expressed, our model predicts that there will be no glycolytic flux, even if external glucose would be at growth-permissable levels. The existence of the imbalanced state can be found for certain parameter conditions independent of the mentioned bifurcation. The parameter-free analysis proved too complex to directly gain insight into the imbalanced states, but the starting point of a branch of imbalanced states can be shown to exist in detail. Moreover, the analysis offers the key ingredients necessary for successful numerical continuation, which highlight the existence of this bistability and the influence of the redox balance.

Metabolic dynamics restricted by conserved carriers: Jamming and feedback

To uncover the processes and mechanisms of cellular physiology, it first necessary to gain an understanding of the underlying metabolic dynamics. Recent studies using a constraint-based approach succeeded in predicting the steady states of cellular metabolic systems by utilizing conserved quantities in the metabolic networks such as carriers such as ATP/ADP as an energy carrier or NADH/NAD+ as a hydrogen carrier. Although such conservation quantities restrict not only the steady state but also the dynamics themselves, the latter aspect has not yet been completely understood. Here, to study the dynamics of metabolic systems, we propose adopting a carrier cycling cascade (CCC), which includes the dynamics of both substrates and carriers, a commonly observed motif in metabolic systems such as the glycolytic and fermentation pathways. We demonstrate that the conservation laws lead to the jamming of the flux and feedback. The CCC can show slow relaxation, with a longer timescale than that of elementary reactions, and is accompanied by both robustness against small environmental fluctuations and responsiveness against large environmental changes. Moreover, the CCC demonstrates robustness against internal fluctuations due to the feedback based on the moiety conservation. We identified the key parameters underlying the robustness of this model against external and internal fluctuations and estimated it in several metabolic systems.

The Glycogen Shunt Maintains Glycolytic Homeostasis and the Warburg Effect in Cancer

Despite many decades of study there is a lack of a quantitative explanation for the Warburg effect in cancer. We propose that the glycogen shunt, a pathway recently shown to be critical for cancer cell survival, may explain the excess lactate generation under aerobic conditions characteristic of the Warburg effect. The proposal is based on research on yeast and mammalian muscle and brain that demonstrates that the glycogen shunt functions to maintain homeostasis of glycolytic intermediates and ATP during large shifts in glucose supply or demand. Loss of the glycogen shunt leads to cell death under substrate stress. Similarities between the glycogen shunt in yeast and cancer cells lead us here to propose a parallel explanation of the lactate produced by cancer cells in the Warburg effect. The model also explains the need for the active tetramer and inactive dimer forms of pyruvate kinase (PKM2) in cancer cells, similar to the two forms of Pyk2p in yeast, as critical for regulating the glycogen shunt flux. The novel role proposed for the glycogen shunt implicates the high activities of glycogen synthase and fructose bisphosphatase in tumors as potential targets for therapy.

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.

Systems Biology of Metabolism

Metabolism is highly complex and involves thousands of different connected reactions; it is therefore necessary to use mathematical models for holistic studies. The use of mathematical models in biology is referred to as systems biology. In this review, the principles of systems biology are described, and two different types of mathematical models used for studying metabolism are discussed: kinetic models and genome-scale metabolic models. The use of different omics technologies, including transcriptomics, proteomics, metabolomics, and fluxomics, for studying metabolism is presented. Finally, the application of systems biology for analyzing global regulatory structures, engineering the metabolism of cell factories, and analyzing human diseases is discussed.

Design principles of autocatalytic cycles constrain enzyme kinetics and force low substrate saturation at flux branch points

A set of chemical reactions that require a metabolite to synthesize more of that metabolite is an autocatalytic cycle. Here, we show that most of the reactions in the core of central carbon metabolism are part of compact autocatalytic cycles. Such metabolic designs must meet specific conditions to support stable fluxes, hence avoiding depletion of intermediate metabolites. As such, they are subjected to constraints that may seem counter-intuitive: the enzymes of branch reactions out of the cycle must be overexpressed and the affinity of these enzymes to their substrates must be relatively weak. We use recent quantitative proteomics and fluxomics measurements to show that the above conditions hold for functioning cycles in central carbon metabolism of E. coli. This work demonstrates that the topology of a metabolic network can shape kinetic parameters of enzymes and lead to seemingly wasteful enzyme usage.

DOI:http://dx.doi.org/10.7554/eLife.20667.001

Many bacteria are able to produce all the molecules they need to survive from a limited supply of nutrients. This allows the bacteria to thrive even in harsh environments where other organisms struggle to live. The bacteria act as miniature chemical factories to convert nutrients into the desired molecules via a series of chemical reactions. Some molecules are made in sets of reactions termed autocatalytic cycles. These reaction sets require a molecule to be present in the cell in order to produce more of that molecule; like how a savings account needs to contain some money before it can generate more via interest.

Bacteria have many different enzymes that each drive specific chemical reactions. In order for an autocatalytic cycle to work properly, the cell needs to maintain adequate supplies of the molecule it is trying to make and all of the “intermediate” molecules in the cycle. If less of an intermediate molecule is produced, for example, the cell needs to reduce the demand for that molecule by controlling later chemical reactions in the cycle. Bacteria control chemical reactions by regulating the activities of the enzymes involved, but it is not clear exactly how they regulate the enzymes that drive autocatalytic cycles.

Barenholz et al. combined two approaches called proteomics and fluxomics to study autocatalytic cycles in a bacterium known as E. coli. The experiments suggest several core principles allow autocatalytic cycles to work smoothly in the bacteria. The next step is to apply these principles to different kinds of molecules produced in bacterial cells. A future challenge is to search for other structures that regulate chemical reactions in E. coli and other bacteria. Extending our understanding of autocatalytic cycles and other pathways of chemical reactions is essential for designing and engineering new reactions in bacteria. Such knowledge can be used to modify bacteria to produce valuable chemicals in environmentally friendly ways.

DOI:http://dx.doi.org/10.7554/eLife.20667.002

Ongoing resolution of duplicate gene functions shapes the diversification of a metabolic network

The evolutionary mechanisms leading to duplicate gene retention are well understood, but the long-term impacts of paralog differentiation on the regulation of metabolism remain underappreciated. Here we experimentally dissect the functions of two pairs of ancient paralogs of the GALactose sugar utilization network in two yeast species. We show that the Saccharomyces uvarum network is more active, even as over-induction is prevented by a second co-repressor that the model yeast Saccharomyces cerevisiae lacks. Surprisingly, removal of this repression system leads to a strong growth arrest, likely due to overly rapid galactose catabolism and metabolic overload. Alternative sugars, such as fructose, circumvent metabolic control systems and exacerbate this phenotype. We further show that S. cerevisiae experiences homologous metabolic constraints that are subtler due to how the paralogs have diversified. These results show how the functional differentiation of paralogs continues to shape regulatory network architectures and metabolic strategies long after initial preservation.

Engineering levoglucosan metabolic pathway in Rhodococcus jostii RHA1 for lipid production

Oleaginous strains of Rhodococcus including R. jostii RHA1 have attracted considerable attention due to their ability to accumulate triacylglycerols (TAGs), robust growth properties and genetic tractability. In this study, a novel metabolic pathway was introduced into R. jostii by heterogenous expression of the well-characterized gene, lgk encoding levoglucosan kinase from Lipomyces starkeyi YZ-215. This enables the recombinant R. jostii RHA1 to produce TAGs from the anhydrous sugar, levoglucosan, which can be generated efficiently as the major molecule from the pyrolysis of cellulose. The recombinant R. jostii RHA1 could grow on levoglucosan as the sole carbon source, and the consumption rate of levoglucosan was determined. Furthermore, expression of one more copy of lgk increased the enzymatic activity of LGK in the recombinant. However, the growth performance of the recombinant bearing two copies of lgk on levoglucosan was not improved. Although expression of lgk in the recombinants was not repressed by the glucose present in the media, glucose in the sugar mixture still affected consumption of levoglucosan. Under nitrogen limiting conditions, lipid produced from levoglucosan by the recombinant bearing lgk was up to 43.54 % of the cell dry weight, which was comparable to the content of lipid accumulated from glucose. This work demonstrated the technical feasibility of producing lipid from levoglucosan, an anhydrosugar derived from the pyrolysis of lignocellulosic materials, by the genetically modified rhodococci strains.

Type 2 Diabetes Dysregulates Glucose Metabolism in Cardiac Progenitor Cells

Type 2 diabetes is associated with increased mortality and progression to heart failure. Recent studies suggest that diabetes also impairs reparative responses after cell therapy. In this study, we examined potential mechanisms by which diabetes affects cardiac progenitor cells (CPCs). CPCs isolated from the diabetic heart showed diminished proliferation, a propensity for cell death, and a pro-adipogenic phenotype. The diabetic CPCs were insulin-resistant, and they showed higher energetic reliance on glycolysis, which was associated with up-regulation of the pro-glycolytic enzyme 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3). In WT CPCs, expression of a mutant form of PFKFB, which mimics PFKFB3 activity and increases glycolytic rate, was sufficient to phenocopy the mitochondrial and proliferative deficiencies found in diabetic cells. Consistent with activation of phosphofructokinase in diabetic cells, stable isotope carbon tracing in diabetic CPCs showed dysregulation of the pentose phosphate and glycero(phospho)lipid synthesis pathways. We describe diabetes-induced dysregulation of carbon partitioning using stable isotope metabolomics-based coupling quotients, which relate relative flux values between metabolic pathways. These findings suggest that diabetes causes an imbalance in glucose carbon allocation by uncoupling biosynthetic pathway activity, which could diminish the efficacy of CPCs for myocardial repair.

Cellular Growth Arrest and Persistence from Enzyme Saturation

Metabolic efficiency depends on the balance between supply and demand of metabolites, which is sensitive to environmental and physiological fluctuations, or noise, causing shortages or surpluses in the metabolic pipeline. How cells can reliably optimize biomass production in the presence of metabolic fluctuations is a fundamental question that has not been fully answered. Here we use mathematical models to predict that enzyme saturation creates distinct regimes of cellular growth, including a phase of growth arrest resulting from toxicity of the metabolic process. Noise can drive entry of single cells into growth arrest while a fast-growing majority sustains the population. We confirmed these predictions by measuring the growth dynamics of Escherichia coli utilizing lactose as a sole carbon source. The predicted heterogeneous growth emerged at high lactose concentrations, and was associated with cell death and production of antibiotic-tolerant persister cells. These results suggest how metabolic networks may balance costs and benefits, with important implications for drug tolerance.

In bacteria, changes in gene expression, with resulting changes in protein concentration, can drastically change how fast cells and cellular populations grow. This fact has big implications for how we treat infectious disease, which types of organisms make up our microbiomes, and what patterns of gene regulation have undergone evolutionary selection. Here, we show how, in principle, the expression level of a single enzyme can affect bacterial population growth by creating a threshold where cells grow optimally fast just below it, but rapidly reach a state of no growth just above it because metabolic byproducts build up and halt growth. The narrow margin between these two states makes entering either of them possible for the same bacterium because of intrinsic uncertainty, or "noise", in gene expression. The predicted result is a variety of growth rates in a single population of genetically identical cells, manifested as a mix of fast- and slow-growing cells. We created laboratory conditions that reproduce the effect in the model organism E. coli, and showed that there may be a benefit to having slower growing cells, because they can survive antibiotic exposure for longer.

Sugar and Glycerol Transport in Saccharomyces cerevisiae

In Saccharomyces cerevisiae the process of transport of sugar substrates into the cell comprises a complex network of transporters and interacting regulatory mechanisms. Members of the large family of hexose (HXT) transporters display uptake efficiencies consistent with their environmental expression and play physiological roles in addition to feeding the glycolytic pathway. Multiple glucose-inducing and glucose-independent mechanisms serve to regulate expression of the sugar transporters in yeast assuring that expression levels and transporter activity are coordinated with cellular metabolism and energy needs. The expression of sugar transport activity is modulated by other nutritional and environmental factors that may override glucose-generated signals. Transporter expression and activity is regulated transcriptionally, post-transcriptionally and post-translationally. Recent studies have expanded upon this suite of regulatory mechanisms to include transcriptional expression fine tuning mediated by antisense RNA and prion-based regulation of transcription. Much remains to be learned about cell biology from the continued analysis of this dynamic process of substrate acquisition.

Synthetic Biology for Cell-Free Biosynthesis: Fundamentals of Designing Novel In Vitro Multi-Enzyme Reaction Networks

Cell-free biosynthesis in the form of in vitro multi-enzyme reaction networks or enzyme cascade reactions emerges as a promising tool to carry out complex catalysis in one-step, one-vessel settings. It combines the advantages of well-established in vitro biocatalysis with the power of multi-step in vivo pathways. Such cascades have been successfully applied to the synthesis of fine and bulk chemicals, monomers and complex polymers of chemical importance, and energy molecules from renewable resources as well as electricity. The scale of these initial attempts remains small, suggesting that more robust control of such systems and more efficient optimization are currently major bottlenecks. To this end, the very nature of enzyme cascade reactions as multi-membered systems requires novel approaches for implementation and optimization, some of which can be obtained from in vivo disciplines (such as pathway refactoring and DNA assembly), and some of which can be built on the unique, cell-free properties of cascade reactions (such as easy analytical access to all system intermediates to facilitate modeling).

Homeostasis and the glycogen shunt explains aerobic ethanol production in yeast

Aerobic glycolysis in yeast and cancer cells produces pyruvate beyond oxidative needs, a paradox noted by Warburg almost a century ago. To address this question, we reanalyzed extensive measurements from (13)C magnetic resonance spectroscopy of yeast glycolysis and the coupled pathways of futile cycling and glycogen and trehalose synthesis (which we refer to as the glycogen shunt). When yeast are given a large glucose load under aerobic conditions, the fluxes of these pathways adapt to maintain homeostasis of glycolytic intermediates and ATP. The glycogen shunt uses glycolytic ATP to store glycolytic intermediates as glycogen and trehalose, generating pyruvate and ethanol as byproducts. This conclusion is supported by studies of yeast with a partial block in the glycogen shunt due to the cif mutation, which found that when challenged with glucose, the yeast cells accumulate glycolytic intermediates and ATP, which ultimately leads to cell death. The control of the relative fluxes, which is critical to maintain homeostasis, is most likely exerted by the enzymes pyruvate kinase and fructose bisphosphatase. The kinetic properties of yeast PK and mammalian PKM2, the isoform found in cancer, are similar, suggesting that the same mechanism may exist in cancer cells, which, under these conditions, could explain their excess lactate generation. The general principle that homeostasis of metabolite and ATP concentrations is a critical requirement for metabolic function suggests that enzymes and pathways that perform this critical role could be effective drug targets in cancer and other diseases.

A fast sensor for in vivo quantification of cytosolic phosphate in Saccharomyces cerevisiae

Eukaryotic metabolism consists of a complex network of enzymatic reactions and transport processes which are distributed over different subcellular compartments. Currently, available metabolite measurement protocols allow to measure metabolite whole cell amounts which hinder progress to describe the in vivo dynamics in different compartments, which are driven by compartment specific concentrations. Phosphate (Pi) is an essential component for: (1) the metabolic balance of upper and lower glycolytic flux; (2) Together with ATP and ADP determines the phosphorylation energy. Especially, the cytosolic Pi has a critical role in disregulation of glycolysis in tps1 knockout. Here we developed a method that enables us to monitor the cytosolic Pi concentration in S. cerevisiae using an equilibrium sensor reaction: maltose + Pi < = > glucose + glucose-1-phosphate. The required enzyme, maltose phosphorylase from L. sanfranciscensis was overexpressed in S. cerevisiae. With this reaction in place, the cytosolic Pi concentration was obtained from intracellular glucose, G1P and maltose concentrations. The cytosolic Pi concentration was determined in batch and chemostat (D = 0.1 h(-1) ) conditions, which was 17.88 µmol/gDW and 25.02 µmol/gDW, respectively under Pi-excess conditions. Under Pi-limited steady state (D = 0.1 h(-1) ) conditions, the cytosolic Pi concentration dropped to only 17.7% of the cytosolic Pi in Pi-excess condition (4.42 µmol/gDW vs. 25.02 µmol/gDW). In response to a Pi pulse, the cytosolic Pi increased very rapidly, together with the concentration of sugar phosphates. Main sources of the rapid Pi increase are vacuolar Pi (and not the polyPi), as well as Pi uptake from the extracellular space. The temporal increase of cytosolic Pi increases the driving force of GAPDH reaction of the lower glycolytic reactions. The novel cytosol specific Pi concentration measurements provide new insight into the thermodynamic driving force for ATP hydrolysis, GAPDH reaction, and Pi transport over the plasma and vacuolar membranes.

Understanding bistability in yeast glycolysis using general properties of metabolic pathways

Glycolysis is the central pathway in energy metabolism in the majority of organisms. In a recent paper, van Heerden et al. showed experimentally and computationally that glycolysis can exist in two states, a global steady state and a so-called imbalanced state. In the imbalanced state, intermediary metabolites accumulate at low levels of ATP and inorganic phosphate. It was shown that Baker's yeast uses a peculiar regulatory mechanism--via trehalose metabolism--to ensure that most yeast cells reach the steady state and not the imbalanced state.

RESULTS

Here we explore the apparent bistable behaviour in a core model of glycolysis that is based on a well-established detailed model, and study in great detail the bifurcation behaviour of solutions, without using any numerical information on parameter values.

CONCLUSION

We uncover a rich suite of solutions, including so-called imbalanced states, bistability, and oscillatory behaviour. The techniques employed are generic, directly suitable for a wide class of biochemical pathways, and could lead to better analytical treatments of more detailed models.

Remarkable reproducibility of enzyme activity profiles in tomato fruits grown under contrasting environments provides a roadmap for studies of fruit metabolism

To assess the influence of the environment on fruit metabolism, tomato (Solanum lycopersicum 'Moneymaker') plants were grown under contrasting conditions (optimal for commercial, water limited, or shaded production) and locations. Samples were harvested at nine stages of development, and 36 enzyme activities of central metabolism were measured as well as protein, starch, and major metabolites, such as hexoses, sucrose, organic acids, and amino acids. The most remarkable result was the high reproducibility of enzyme activities throughout development, irrespective of conditions or location. Hierarchical clustering of enzyme activities also revealed tight relationships between metabolic pathways and phases of development. Thus, cell division was characterized by high activities of fructokinase, glucokinase, pyruvate kinase, and tricarboxylic acid cycle enzymes, indicating ATP production as a priority, whereas cell expansion was characterized by enzymes involved in the lower part of glycolysis, suggesting a metabolic reprogramming to anaplerosis. As expected, enzymes involved in the accumulation of sugars, citrate, and glutamate were strongly increased during ripening. However, a group of enzymes involved in ATP production, which is probably fueled by starch degradation, was also increased. Metabolites levels seemed more sensitive than enzymes to the environment, although such differences tended to decrease at ripening. The integration of enzyme and metabolite data obtained under contrasting growth conditions using principal component analysis suggests that, with the exceptions of alanine amino transferase and glutamate and malate dehydrogenase and malate, there are no links between single enzyme activities and metabolite time courses or levels.

Lost in transition: start-up of glycolysis yields subpopulations of nongrowing cells

Cells need to adapt to dynamic environments. Yeast that fail to cope with dynamic changes in the abundance of glucose can undergo growth arrest. We show that this failure is caused by imbalanced reactions in glycolysis, the essential pathway in energy metabolism in most organisms. The imbalance arises largely from the fundamental design of glycolysis, making this state of glycolysis a generic risk. Cells with unbalanced glycolysis coexisted with vital cells. Spontaneous, nongenetic metabolic variability among individual cells determines which state is reached and, consequently, which cells survive. Transient ATP (adenosine 5'-triphosphate) hydrolysis through futile cycling reduces the probability of reaching the imbalanced state. Our results reveal dynamic behavior of glycolysis and indicate that cell fate can be determined by heterogeneity purely at the metabolic level.

Handling uncertainty in dynamic models: the pentose phosphate pathway in Trypanosoma brucei

Dynamic models of metabolism can be useful in identifying potential drug targets, especially in unicellular organisms. A model of glycolysis in the causative agent of human African trypanosomiasis, Trypanosoma brucei, has already shown the utility of this approach. Here we add the pentose phosphate pathway (PPP) of T. brucei to the glycolytic model. The PPP is localized to both the cytosol and the glycosome and adding it to the glycolytic model without further adjustments leads to a draining of the essential bound-phosphate moiety within the glycosome. This phosphate “leak” must be resolved for the model to be a reasonable representation of parasite physiology. Two main types of theoretical solution to the problem could be identified: (i) including additional enzymatic reactions in the glycosome, or (ii) adding a mechanism to transfer bound phosphates between cytosol and glycosome. One example of the first type of solution would be the presence of a glycosomal ribokinase to regenerate ATP from ribose 5-phosphate and ADP. Experimental characterization of ribokinase in T. brucei showed that very low enzyme levels are sufficient for parasite survival, indicating that other mechanisms are required in controlling the phosphate leak. Examples of the second type would involve the presence of an ATP:ADP exchanger or recently described permeability pores in the glycosomal membrane, although the current absence of identified genes encoding such molecules impedes experimental testing by genetic manipulation. Confronted with this uncertainty, we present a modeling strategy that identifies robust predictions in the context of incomplete system characterization. We illustrate this strategy by exploring the mechanism underlying the essential function of one of the PPP enzymes, and validate it by confirming the model predictions experimentally.

Mathematical models have been valuable tools for investigating the complex behaviors of metabolism. Due to incomplete knowledge of biological systems, these models contain inevitable uncertainty. This uncertainty is present in the measured or estimated parameter values, but also in the structure of the metabolic network. In this paper we increase the coverage of a particularly well studied model of glucose metabolism in Trypanosoma brucei, a tropical parasite that causes African sleeping sickness, by extending it with an additional pathway in two compartments. During this modeling process we highlighted uncertainties in parameter values and network structure and used these to formulate new hypotheses which were subsequently tested experimentally. The models were improved with the experimentally derived data, but uncertainty remained concerning the exact topology of the system. These models allowed us to investigate the effects of the loss of one enzyme, 6-phosphogluconate dehydrogenase. By taking uncertainty into account, the models demonstrated that the loss of this enzyme is lethal to the parasite by a mechanism different than that in other organisms. Our methodology shows how formally introducing uncertainty into model building provides robust model behavior that is independent of the network structure or parameter values.

Nitrogen assimilation in Escherichia coli: putting molecular data into a systems perspective

We present a comprehensive overview of the hierarchical network of intracellular processes revolving around central nitrogen metabolism in Escherichia coli. The hierarchy intertwines transport, metabolism, signaling leading to posttranslational modification, and transcription. The protein components of the network include an ammonium transporter (AmtB), a glutamine transporter (GlnHPQ), two ammonium assimilation pathways (glutamine synthetase [GS]-glutamate synthase [glutamine 2-oxoglutarate amidotransferase {GOGAT}] and glutamate dehydrogenase [GDH]), the two bifunctional enzymes adenylyl transferase/adenylyl-removing enzyme (ATase) and uridylyl transferase/uridylyl-removing enzyme (UTase), the two trimeric signal transduction proteins (GlnB and GlnK), the two-component regulatory system composed of the histidine protein kinase nitrogen regulator II (NRII) and the response nitrogen regulator I (NRI), three global transcriptional regulators called nitrogen assimilation control (Nac) protein, leucine-responsive regulatory protein (Lrp), and cyclic AMP (cAMP) receptor protein (Crp), the glutaminases, and the nitrogen-phosphotransferase system. First, the structural and molecular knowledge on these proteins is reviewed. Thereafter, the activities of the components as they engage together in transport, metabolism, signal transduction, and transcription and their regulation are discussed. Next, old and new molecular data and physiological data are put into a common perspective on integral cellular functioning, especially with the aim of resolving counterintuitive or paradoxical processes featured in nitrogen assimilation. Finally, we articulate what still remains to be discovered and what general lessons can be learned from the vast amounts of data that are available now.

Systematic construction of kinetic models from genome-scale metabolic networks

The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.

Firmicutes dominate the bacterial taxa within sugar-cane processing plants

Sugar cane processing sites are characterised by high sugar/hemicellulose levels, available moisture and warm conditions, and are relatively unexplored unique microbial environments. The PhyloChip microarray was used to investigate bacterial diversity and community composition in three Australian sugar cane processing plants. These ecosystems were highly complex and dominated by four main Phyla, Firmicutes (the most dominant), followed by Proteobacteria, Bacteroidetes, and Chloroflexi. Significant variation (p < 0.05) in community structure occurred between samples collected from 'floor dump sediment', 'cooling tower water', and 'bagasse leachate'. Many bacterial Classes contributed to these differences, however most were of low numerical abundance. Separation in community composition was also linked to Classes of Firmicutes, particularly Bacillales, Lactobacillales and Clostridiales, whose dominance is likely to be linked to their physiology as 'lactic acid bacteria', capable of fermenting the sugars present. This process may help displace other bacterial taxa, providing a competitive advantage for Firmicutes bacteria.