Cellular concentrations of enzymes and their substrates

Environmental systems biology of cold-tolerant phenotype in Saccharomyces species adapted to grow at different temperatures

Temperature is one of the leading factors that drive adaptation of organisms and ecosystems. Remarkably, many closely related species share the same habitat because of their different temporal or micro-spatial thermal adaptation. In this study, we seek to find the underlying molecular mechanisms of the cold-tolerant phenotype of closely related yeast species adapted to grow at different temperatures, namely S. kudriavzevii CA111 (cryo-tolerant) and S. cerevisiae 96.2 (thermo-tolerant). Using two different systems approaches, i. thermodynamic-based analysis of a genome-scale metabolic model of S. cerevisiae and ii. large-scale competition experiment of the yeast heterozygote mutant collection, genes and pathways important for the growth at low temperature were identified. In particular, defects in lipid metabolism, oxidoreductase and vitamin pathways affected yeast fitness at cold. Combining the data from both studies, a list of candidate genes was generated and mutants for two predicted cold-favouring genes, GUT2 and ADH3, were created in two natural isolates. Compared with the parental strains, these mutants showed lower fitness at cold temperatures, with S. kudriavzevii displaying the strongest defect. Strikingly, in S. kudriavzevii, these mutations also significantly improve the growth at warm temperatures. In addition, overexpression of ADH3 in S. cerevisiae increased its fitness at cold. These results suggest that temperature-induced redox imbalances could be compensated by increased glycerol accumulation or production of cytosolic acetaldehyde through the deletion of GUT2 or ADH3, respectively.

Sites of superoxide and hydrogen peroxide production by muscle mitochondria assessed ex vivo under conditions mimicking rest and exercise

The sites and rates of mitochondrial production of superoxide and H2O2 in vivo are not yet defined. At least 10 different mitochondrial sites can generate these species. Each site has a different maximum capacity (e.g. the outer quinol site in complex III (site IIIQo) has a very high capacity in rat skeletal muscle mitochondria, whereas the flavin site in complex I (site IF) has a very low capacity). The maximum capacities can greatly exceed the actual rates observed in the absence of electron transport chain inhibitors, so maximum capacities are a poor guide to actual rates. Here, we use new approaches to measure the rates at which different mitochondrial sites produce superoxide/H2O2 using isolated muscle mitochondria incubated in media mimicking the cytoplasmic substrate and effector mix of skeletal muscle during rest and exercise. We find that four or five sites dominate during rest in this ex vivo system. Remarkably, the quinol site in complex I (site IQ) and the flavin site in complex II (site IIF) each account for about a quarter of the total measured rate of H2O2 production. Site IF, site IIIQo, and perhaps site EF in the β-oxidation pathway account for most of the remainder. Under conditions mimicking mild and intense aerobic exercise, total production is much less, and the low capacity site IF dominates. These results give novel insights into which mitochondrial sites may produce superoxide/H2O2 in vivo.

Cellular metabolites enhance the light sensitivity of Arabidopsis cryptochrome through alternate electron transfer pathways

Cryptochromes are blue light receptors with multiple signaling roles in plants and animals. Plant cryptochrome (cry1 and cry2) biological activity has been linked to flavin photoreduction via an electron transport chain comprising three evolutionarily conserved tryptophan residues known as the Trp triad. Recently, it has been reported that cry2 Trp triad mutants, which fail to undergo photoreduction in vitro, nonetheless show biological activity in vivo, raising the possibility of alternate signaling pathways. Here, we show that Arabidopsis thaliana cry2 proteins containing Trp triad mutations indeed undergo robust photoreduction in living cultured insect cells. UV/Vis and electron paramagnetic resonance spectroscopy resolves the discrepancy between in vivo and in vitro photochemical activity, as small metabolites, including NADPH, NADH, and ATP, were found to promote cry photoreduction even in mutants lacking the classic Trp triad electron transfer chain. These metabolites facilitate alternate electron transfer pathways and increase light-induced radical pair formation. We conclude that cryptochrome activation is consistent with a mechanism of light-induced electron transfer followed by flavin photoreduction in vivo. We further conclude that in vivo modulation by cellular compounds represents a feature of the cryptochrome signaling mechanism that has important consequences for light responsivity and activation.

The structural and functional coordination of glycolytic enzymes in muscle: evidence of a metabolon?

Metabolism sustains life through enzyme-catalyzed chemical reactions within the cells of all organisms. The coupling of catalytic function to the structural organization of enzymes contributes to the kinetic optimization important to tissue-specific and whole-body function. This coupling is of paramount importance in the role that muscle plays in the success of Animalia. The structure and function of glycolytic enzyme complexes in anaerobic metabolism have long been regarded as a major regulatory element necessary for muscle activity and whole-body homeostasis. While the details of this complex remain to be elucidated through in vivo studies, this review will touch on recent studies that suggest the existence of such a complex and its structure. A potential model for glycolytic complexes and related subcomplexes is introduced.

Theory on the dynamics of oscillatory loops in the transcription factor networks

We develop a detailed theoretical framework for various types of transcription factor gene oscillators. We further demonstrate that one can build genetic-oscillators which are tunable and robust against perturbations in the critical control parameters by coupling two or more independent Goodwin-Griffith oscillators through either -OR- or -AND- type logic. Most of the coupled oscillators constructed in the literature so far seem to be of -OR- type. When there are transient perturbations in one of the -OR- type coupled-oscillators, then the overall period of the system remains constant (period-buffering) whereas in case of -AND- type coupling the overall period of the system moves towards the perturbed oscillator. Though there is a period-buffering, the amplitudes of oscillators coupled through -OR- type logic are more sensitive to perturbations in the parameters associated with the promoter state dynamics than -AND- type. Further analysis shows that the period of -AND- type coupled dual-feedback oscillators can be tuned without conceding on the amplitudes. Using these results we derive the basic design principles governing the robust and tunable synthetic gene oscillators without compromising on their amplitudes.

Bistability in glycolysis pathway as a physiological switch in energy metabolism

The flux of glycolysis is tightly controlled by feed-back and feed-forward allosteric regulations to maintain the body's glucose homeostasis and to respond to cell's growth and energetic needs. Using a mathematical model based on reported mechanisms for the allosteric regulations of the enzymes, we demonstrate that glycolysis exhibits multiple steady state behavior segregating glucose metabolism into high flux and low flux states. Two regulatory loops centering on phosphofructokinase and on pyruvate kinase each gives rise to the bistable behavior, and together impose more complex flux control. Steady state multiplicity endows glycolysis with a robust switch to transit between the two flux states. Under physiological glucose concentrations the glycolysis flux does not move between the states easily without an external stimulus such as hormonal, signaling or oncogenic cues. Distinct combination of isozymes in glycolysis gives different cell types the versatility in their response to different biosynthetic and energetic needs. Insights from the switch behavior of glycolysis may reveal new means of metabolic intervention in the treatment of cancer and other metabolic disorders through suppression of glycolysis.

Mitochondrial MTHFD2L is a dual redox cofactor-specific methylenetetrahydrofolate dehydrogenase/methenyltetrahydrofolate cyclohydrolase expressed in both adult and embryonic tissues

Mammalian mitochondria are able to produce formate from one-carbon donors such as serine, glycine, and sarcosine. This pathway relies on the mitochondrial pool of tetrahydrofolate (THF) and several folate-interconverting enzymes in the mitochondrial matrix. We recently identified MTHFD2L as the enzyme that catalyzes the oxidation of 5,10-methylenetetrahydrofolate (CH2-THF) in adult mammalian mitochondria. We show here that the MTHFD2L enzyme is bifunctional, possessing both CH2-THF dehydrogenase and 5,10-methenyl-THF cyclohydrolase activities. The dehydrogenase activity can use either NAD(+) or NADP(+) but requires both phosphate and Mg(2+) when using NAD(+). The NADP(+)-dependent dehydrogenase activity is inhibited by inorganic phosphate. MTHFD2L uses the mono- and polyglutamylated forms of CH2-THF with similar catalytic efficiencies. Expression of the MTHFD2L transcript is low in early mouse embryos but begins to increase at embryonic day 10.5 and remains elevated through birth. In adults, MTHFD2L is expressed in all tissues examined, with the highest levels observed in brain and lung.

Who controls the ATP supply in cancer cells? Biochemistry lessons to understand cancer energy metabolism

Applying basic biochemical principles, this review analyzes data that contrasts with the Warburg hypothesis that glycolysis is the exclusive ATP provider in cancer cells. Although disregarded for many years, there is increasing experimental evidence demonstrating that oxidative phosphorylation (OxPhos) makes a significant contribution to ATP supply in many cancer cell types and under a variety of conditions. Substrates oxidized by normal mitochondria such as amino acids and fatty acids are also avidly consumed by cancer cells. In this regard, the proposal that cancer cells metabolize glutamine for anabolic purposes without the need for a functional respiratory chain and OxPhos is analyzed considering thermodynamic and kinetic aspects for the reductive carboxylation of 2-oxoglutarate catalyzed by isocitrate dehydrogenase. In addition, metabolic control analysis (MCA) studies applied to energy metabolism of cancer cells are reevaluated. Regardless of the experimental/environmental conditions and the rate of lactate production, the flux-control of cancer glycolysis is robust in the sense that it involves the same steps: glucose transport, hexokinase, hexosephosphate isomerase and glycogen degradation, all at the beginning of the pathway; these steps together with phosphofructokinase 1 also control glycolysis in normal cells. The respiratory chain complexes exert significantly higher flux-control on OxPhos in cancer cells than in normal cells. Thus, determination of the contribution of each pathway to ATP supply and/or the flux-control distribution of both pathways in cancer cells is necessary in order to identify differences from normal cells which may lead to the design of rational alternative therapies that selectively target cancer energy metabolism.

Regulatory and functional diversity of methylmercaptopropionate coenzyme A ligases from the dimethylsulfoniopropionate demethylation pathway in Ruegeria pomeroyi DSS-3 and other proteobacteria

The organosulfur compound dimethylsulfoniopropionate (DMSP) is produced by phytoplankton and is ubiquitous in the surface ocean. Once released from phytoplankton, marine bacteria degrade DMSP by either the cleavage pathway to form the volatile gas dimethylsulfide (DMS) or the demethylation pathway, yielding methanethiol (MeSH), which is readily assimilated or oxidized. The enzyme DmdB, a methylmercaptopropionate (MMPA)-coenzyme A (CoA) ligase, catalyzes the second step in the demethylation pathway and is a major regulatory point. The two forms of DmdB present in the marine roseobacter Ruegeria pomeroyi DSS-3, RPO_DmdB1 and RPO_DmdB2, and the single form in the SAR11 clade bacterium "Candidatus Pelagibacter ubique" HTCC1062, PU_DmdB1, were characterized in detail. DmdB enzymes were also examined from Ruegeria lacuscaerulensis ITI-1157, Pseudomonas aeruginosa PAO1, and Burkholderia thailandensis E264. The DmdB enzymes separated into two phylogenetic clades. All enzymes had activity with MMPA and were sensitive to inhibition by salts, but there was no correlation between the clades and substrate specificity or salt sensitivity. All Ruegeria species enzymes were inhibited by physiological concentrations (70 mM) of DMSP. However, ADP reversed the inhibition of RPO_DmdB1, suggesting that this enzyme was responsive to cellular energy charge. MMPA reversed the inhibition of RPO_DmdB2 as well as both R. lacuscaerulensis ITI-1157 DmdB enzymes, suggesting that a complex regulatory system exists in marine bacteria. In contrast, the DmdBs of the non-DMSP-metabolizing P. aeruginosa PAO1 and B. thailandensis E264 were not inhibited by DMSP, suggesting that DMSP inhibition is a specific adaptation of DmdBs from marine bacteria.

Analysis of Chinese hamster ovary cell metabolism through a combined computational and experimental approach

Optimization of cell culture processes can benefit from the systematic analysis of experimental data and their organization in mathematical models, which can be used to decipher the effect of individual process variables on multiple outputs of interest. Towards this goal, a kinetic model of cytosolic glucose metabolism coupled with a population-level model of Chinese hamster ovary cells was used to analyse metabolic behavior under batch and fed-batch cell culture conditions. The model was parameterized using experimental data for cell growth dynamics, extracellular and intracellular metabolite profiles. The results highlight significant differences between the two culture conditions in terms of metabolic efficiency and motivate the exploration of lactate as a secondary carbon source. Finally, the application of global sensitivity analysis to the model parameters highlights the need for additional experimental information on cell cycle distribution to complement metabolomic analyses with a view to parameterize kinetic models.

What is the total number of protein molecules per cell volume? A call to rethink some published values

Novel methods such as mass-spectrometry enable a view of the proteomes of cells in unprecedented detail. Recently, these efforts have culminated in quantitative measurements of the number of copies per cell for most expressed proteins in organisms ranging from bacteria to mammalian cells. Here, we estimate the expected total number of proteins per unit of cell volume using known parameters related to the composition of cells such as the fraction of cell mass that is protein, and the average protein length. Using simple arguments, we estimate a range of 2–4 million proteins per cubic micron (i.e. 1 fL) in bacteria, yeast, and mammalian cells. Interestingly, we find that measured values that are reported for fission yeast and mammalian cells are often about 3–10 times lower. We discuss this apparent discrepancy and how to use the estimate as benchmark to recalibrate proteome-wide quantitative censuses or to revisit assumptions about cell composition.

We estimate the expected total number of proteins per unit cell volume as 2–4 million proteins per cubic micron. Some reported values for fission yeast and mammalian cells using mass spectrometry are 3–10 times lower than these estimates. We discuss this apparent discrepancy and how to recalibrate proteome-wide quantitative censuses.

Proteomic data from human cell cultures refine mechanisms of chaperone-mediated protein homeostasis

In the crowded environment of human cells, folding of nascent polypeptides and refolding of stress-unfolded proteins is error prone. Accumulation of cytotoxic misfolded and aggregated species may cause cell death, tissue loss, degenerative conformational diseases, and aging. Nevertheless, young cells effectively express a network of molecular chaperones and folding enzymes, termed here "the chaperome," which can prevent formation of potentially harmful misfolded protein conformers and use the energy of adenosine triphosphate (ATP) to rehabilitate already formed toxic aggregates into native functional proteins. In an attempt to extend knowledge of chaperome mechanisms in cellular proteostasis, we performed a meta-analysis of human chaperome using high-throughput proteomic data from 11 immortalized human cell lines. Chaperome polypeptides were about 10% of total protein mass of human cells, half of which were Hsp90s and Hsp70s. Knowledge of cellular concentrations and ratios among chaperome polypeptides provided a novel basis to understand mechanisms by which the Hsp60, Hsp70, Hsp90, and small heat shock proteins (HSPs), in collaboration with cochaperones and folding enzymes, assist de novo protein folding, import polypeptides into organelles, unfold stress-destabilized toxic conformers, and control the conformal activity of native proteins in the crowded environment of the cell. Proteomic data also provided means to distinguish between stable components of chaperone core machineries and dynamic regulatory cochaperones.

Towards kinetic modeling of genome-scale metabolic networks without sacrificing stoichiometric, thermodynamic and physiological constraints

Mathematical modeling is an essential tool for the comprehensive understanding of cell metabolism and its interactions with the environmental and process conditions. Recent developments in the construction and analysis of stoichiometric models made it possible to define limits on steady-state metabolic behavior using flux balance analysis. However, detailed information on enzyme kinetics and enzyme regulation is needed to formulate kinetic models that can accurately capture the dynamic metabolic responses. The use of mechanistic enzyme kinetics is a difficult task due to uncertainty in the kinetic properties of enzymes. Therefore, the majority of recent works considered only mass action kinetics for reactions in metabolic networks. Herein, we applied the optimization and risk analysis of complex living entities (ORACLE) framework and constructed a large-scale mechanistic kinetic model of optimally grown Escherichia coli. We investigated the complex interplay between stoichiometry, thermodynamics, and kinetics in determining the flexibility and capabilities of metabolism. Our results indicate that enzyme saturation is a necessary consideration in modeling metabolic networks and it extends the feasible ranges of metabolic fluxes and metabolite concentrations. Our results further suggest that enzymes in metabolic networks have evolved to function at different saturation states to ensure greater flexibility and robustness of cellular metabolism.

IcmQ in the Type 4b secretion system contains an NAD+ binding domain

A Type 4b secretion system (T4bSS) is required for Legionella growth in alveolar macrophages. IcmQ associates with IcmR, binds to membranes, and has a critical role in the T4bSS. We have now solved a crystal structure of IcmR-IcmQ to further our understanding of this complex. This structure revealed an amphipathic four-helix bundle, formed by IcmR and the N-terminal domain of IcmQ, which is linked to a novel C-terminal domain of IcmQ (Qc) by a linker helix. The Qc domain has structural homology with ADP ribosyltransferase domains in certain bacterial toxins and binds NAD(+) with a dissociation constant in the physiological range. Structural homology and molecular dynamics were used to identify an extended NAD(+) binding site on Qc, and the resulting model was tested by mutagenesis and binding assays. Based on the data, we suggest that IcmR-IcmQ binds to membranes, where it may interact with, or perhaps modify, a protein in the T4bSS when NAD(+) is bound.

CREPE: mathematical model for crosstalking of endothelial cells and hepatocyte metabolism

The liver shows a close coexistence between endothelial cells and hepatocytes (HepG2). Endothelial cells' main purpose is to protect (HepG2) from blood vessel shear stress, acting as a barrier, but experimental evidence suggests that they could also play a role in regulating (HepG2) glucose metabolism. A well-known singular effect in hepatocyte-endothelial co-cultures is the reduction of glucose consumption respect to (HepG2) in single culture. (HepG2) were shown to reduce their glucose consumption supporting energy needs of endothelial cells. Monti have studied the effects of endothelin-1 (Et-1) on Glucokinase activity in adult rat (HepG2). They observed a reduction in hepatocytes Glucokinase catalytic rate, which is dependent on Et-1 concentration. We developed crosstalking of endothelial cells and hepatocyte metabolism (CREPE) that is a mathematical model of the endothelin-1 mediated crosstalk between HepG2 and endothelial cells (human umbilical vein endothelial cells) in a traditional static co-culture system. CREPE was validated against experimental data, showing good agreement with them. CREPE can be a starting point to develop predictive tools on complex and highly interconnected environments.

Generation of circularly permuted fluorescent-protein-based indicators for in vitro and in vivo detection of citrate

Indicators for citrate, particularly those applicable to its in vivo detection and quantitation, have attracted much interest in both biochemical studies and industrial applications since citrate is a key metabolic intermediate playing important roles in living cells. We generated novel fluorescence indicators for citrate by fusing the circularly permuted fluorescent protein (cpFP) and the periplasmic domain of the bacterial histidine kinase CitA, which can bind to citrate with high specificity. The ratiometric fluorescent signal change was observed with one of these cpFP-based indicators, named CF98: upon addition of citrate, the excitation peak at 504 nm increased proportionally to the decrease in the peak at 413 nm, suitable for build-in quantitative estimation of the binding compound. We confirmed that CF98 can be used for detecting citrate in vitro at millimolar levels in the range of 0.1 to 50 mM with high selectivity; even in the presence of other organic acids such as isocitrate and malate, the fluorescence intensity of CF98 remains unaffected. We finally demonstrated the in vivo applicability of CF98 to estimation of the intracellular citrate concentration in Escherichia coli co-expressing the genes encoding CF98 and the citrate carrier CitT. The novel indicator CF98 can be a specific and simple detection tool for citrate in vitro and a non-invasive tool for real-time estimation of intracellular concentrations of the compound in vivo.

Understanding metabolic regulation and its influence on cell physiology

Metabolism impacts all cellular functions and plays a fundamental role in biology. In the last century, our knowledge of metabolic pathway architecture and the genomic landscape of disease has increased exponentially. Combined with these insights, advances in analytical methods for quantifying metabolites and systems approaches to analyze these data now provide powerful tools to study metabolic regulation. Here we review the diverse mechanisms cells use to adapt metabolism to specific physiological states and discuss how metabolic flux analyses can be applied to identify important regulatory nodes to understand normal and pathological cell physiology.

Structural basis for enzyme I inhibition by α-ketoglutarate

Creating new bacterial strains in which carbon and nitrogen metabolism are uncoupled is potentially very useful for optimizing yields of microbial produced chemicals from renewable carbon sources. However, the mechanisms that balance carbon and nitrogen consumption in bacteria are poorly understood. Recently, α-ketoglutarate (αKG), the carbon substrate for ammonia assimilation, has been observed to inhibit Escherichia coli enzyme I (EI), the first component of the bacterial phosphotransferase system (PTS), thereby providing a direct biochemical link between central carbon and nitrogen metabolism. Here we investigate the EI-αKG interaction by NMR and enzymatic assays. We show that αKG binds with a KD of ∼2.2 mM at the active site of EI, acting as a competitive inhibitor. In addition, we use molecular docking simulations to derive a structural model of the enzyme-inhibitor complex that is fully consistent with NMR and analytical ultracentrifugation data. We expect that the EI-αKG structure presented here will provide a starting point for structure-based design of EI mutants resistant to αKG.

Genome-based kinetic modeling of cytosolic glucose metabolism in industrially relevant cell lines: Saccharomyces cerevisiae and Chinese hamster ovary cells

Model-based analysis of cellular metabolism can facilitate our understanding of intracellular kinetics and aid the improvement of cell growth and biological product manufacturing. In this paper, a model-based kinetic study of cytosolic glucose metabolism for two industrially relevant cell lines, Saccharomyces cerevisiae and Chinese hamster ovary (CHO) cells, based on enzyme genetic presence and expression information is described. We have reconstructed the cytosolic glucose metabolism map for S. cerevisiae and CHO cells, containing 18 metabolites and 18 enzymes using information from the Kyoto Encyclopedia of Genes and Genomes (KEGG). Based on this map, we have developed akinetic mathematical model for the pathways involved,considering regulation and/or inhibition by products orco-substrates. The values of the maximum rates of reactions(V(max)) were estimated based on kinetic parameter information and metabolic flux analysis results available in literature, and the resulting simulation results for steady-state metabolite concentrations are in good agreement with published experimental data. Finally, the model was used to analyse how the production of DHAP, an important intermediate in fine chemicals synthesis, could be increased using gene knockout.

Different designs of kinase-phosphatase interactions and phosphatase sequestration shapes the robustness and signal flow in the MAPK cascade

Background

The three layer mitogen activated protein kinase (MAPK) signaling cascade exhibits different designs of interactions between its kinases and phosphatases. While the sequential interactions between the three kinases of the cascade are tightly preserved, the phosphatases of the cascade, such as MKP3 and PP2A, exhibit relatively diverse interactions with their substrate kinases. Additionally, the kinases of the MAPK cascade can also sequester their phosphatases. Thus, each topologically distinct interaction design of kinases and phosphatases could exhibit unique signal processing characteristics, and the presence of phosphatase sequestration may lead to further fine tuning of the propagated signal.

Results

We have built four architecturally distinct types of models of the MAPK cascade, each model with identical kinase-kinase interactions but unique kinases-phosphatases interactions. Our simulations unravelled that MAPK cascade’s robustness to external perturbations is a function of nature of interaction between its kinases and phosphatases. The cascade’s output robustness was enhanced when phosphatases were sequestrated by their target kinases. We uncovered a novel implicit/hidden negative feedback loop from the phosphatase MKP3 to its upstream kinase Raf-1, in a cascade resembling the B cell MAPK cascade. Notably, strength of the feedback loop was reciprocal to the strength of phosphatases’ sequestration and stronger sequestration abolished the feedback loop completely. An experimental method to verify the presence of the feedback loop is also proposed. We further showed, when the models were activated by transient signal, memory (total time taken by the cascade output to reach its unstimulated level after removal of signal) of a cascade was determined by the specific designs of interaction among its kinases and phosphatases.

Conclusions

Differences in interaction designs among the kinases and phosphatases can differentially shape the robustness and signal response behaviour of the MAPK cascade and phosphatase sequestration dramatically enhances the robustness to perturbations in each of the cascade. An implicit negative feedback loop was uncovered from our analysis and we found that strength of the negative feedback loop is reciprocally related to the strength of phosphatase sequestration. Duration of output phosphorylation in response to a transient signal was also found to be determined by the individual cascade’s kinase-phosphatase interaction design.

Cancer-associated isocitrate dehydrogenase mutations inactivate NADPH-dependent reductive carboxylation

Isocitrate dehydrogenase (IDH) is a reversible enzyme that catalyzes the NADP(+)-dependent oxidative decarboxylation of isocitrate (ICT) to α-ketoglutarate (αKG) and the NADPH/CO(2)-dependent reductive carboxylation of αKG to ICT. Reductive carboxylation by IDH1 was potently inhibited by NADP(+) and, to a lesser extent, by ICT. IDH1 and IDH2 with cancer-associated mutations at the active site arginines were unable to carry out the reductive carboxylation of αKG. These mutants were also defective in ICT decarboxylation and converted αKG to 2-hydroxyglutarate using NADPH. These mutant proteins were thus defective in both of the normal reactions of IDH. Biochemical analysis of heterodimers between wild-type and mutant IDH1 subunits showed that the mutant subunit did not inactivate reductive carboxylation by the wild-type subunit. Cells expressing the mutant IDH are thus deficient in their capacity for reductive carboxylation and may be compromised in their ability to produce acetyl-CoA under hypoxia or when mitochondrial function is otherwise impaired.

NADPH inhibits [2Fe-2S] cluster protein transfer from diabetes drug target MitoNEET to an apo-acceptor protein

MitoNEET (mNT) is the founding member of the recently discovered CDGSH family of [2Fe-2S] proteins capable of [2Fe-2S] cluster transfer to apo-acceptor proteins. It is a target of the thiazolidinedione (TZD) class of anti-diabetes drugs whose binding modulate both electron transfer and cluster transfer properties. The [2Fe-2S] cluster in mNT is destabilized upon binding of NADPH, which leads to loss of the [2Fe-2S] cluster to the solution environment. Because mNT is capable of transferring [2Fe-2S] clusters to apo-acceptor proteins, we sought to determine whether NADPH binding also affects cluster transfer. We show that NADPH inhibits transfer of the [2Fe-2S] cluster to an apo-acceptor protein with an inhibition constant (K(i)) of 200 μm, which reflects that of NADPH concentrations expected under physiological conditions. In addition, we determined that the strictly conserved cluster interacting residue Asp-84 in the CDGSH domain is necessary for the NADPH-dependent inhibition of [2Fe-2S] cluster transfer. The most critical cellular function of NADPH is in the maintenance of a pool of reducing equivalents, which is essential to counteract oxidative damage. Taken together, our findings suggest that NADPH can regulate both mNT [2Fe-2S] cluster levels in the cell as well as the ability of the protein to transfer [2Fe-2S] clusters to cytosolic or mitochondrial acceptors.

Generic pathways to stability in concentrated protein mixtures

We present a series of experimental results that disclose the crucial role of ionic strength and partial volume fractions in the control of the phase behaviour of binary protein mixtures. Our findings can be understood as that the ionic strength determines the relative contribution of the entropy of the protein counter-ions to the overall thermodynamics of the system. Associative phase separation and crystallization observed at, respectively, low and high ionic strength are suppressed at intermediate salt concentrations, where the entropy gain upon releasing the counter-ions from the double layer of the proteins is negligible and the entropy loss upon confining the counter-ions within the protein crystal phase significant. Moreover, we find that the partial volume fraction of the protein prone to crystallize determines the crystallization boundary and that the presence of other proteins strongly delays crystallization, leading to temporarily stable mixtures. These findings suggest that stability in more complex protein mixtures, such as the cytosol, relates to the ionic strength and protein composition rather than to protein specific properties.

Nonrenewal statistics in the catalytic activity of enzyme molecules at mesoscopic concentrations

Recent fluorescence spectroscopy measurements of single-enzyme kinetics have shown that enzymatic turnovers form a renewal stochastic process in which the inverse of the mean waiting time between turnovers follows the Michaelis-Menten equation. We study enzyme kinetics at physiologically relevant mesoscopic concentrations using a master equation. From the exact solution of the master equation we find that the waiting times are neither independent nor identically distributed, implying that enzymatic turnovers form a nonrenewal stochastic process. The inverse of the mean waiting time shows strong departure from the Michaelis-Menten equation. The waiting times between consecutive turnovers are anticorrelated, where short intervals are more likely to be followed by long intervals and vice versa. Correlations persist beyond consecutive turnovers indicating that multiscale fluctuations govern enzyme kinetics.

Strong glucose dependence of electron current in human monocytes

Reactive oxygen species (ROS) production by human monocytes differs profoundly from that by neutrophils and eosinophils in its dependence on external media glucose. Activated granulocytes produce vast amounts of ROS, even in the absence of glucose. Human peripheral blood monocytes (PBM), in contrast, are suspected not to be able to produce any ROS if glucose is absent from the media. Here we compare ROS production by monocytes and neutrophils, measured electrophysiologically on a single-cell level. Perforated-patch-clamp measurements revealed that electron current appeared after stimulation of PBM with phorbol myristate acetate. Electron current reflects the translocation of electrons through the NADPH oxidase, the main source of ROS production. The electron current was nearly abolished by omitting glucose from the media. Furthermore, in preactivated glucose-deprived cells, electron current appeared immediately with the addition of glucose to the bath. To characterize glucose dependence of PBM further, NADPH oxidase activity was assessed as hydrogen peroxide (H(2)O(2)) production and was recorded fluorometrically. H(2)O(2) production exhibited similar glucose dependence as did electron current. We show fundamental differences in the glucose dependence of ROS in human monocytes compared with human neutrophils.

A new view of the bacterial cytosol environment

The cytosol is the major environment in all bacterial cells. The true physical and dynamical nature of the cytosol solution is not fully understood and here a modeling approach is applied. Using recent and detailed data on metabolite concentrations, we have created a molecular mechanical model of the prokaryotic cytosol environment of Escherichia coli, containing proteins, metabolites and monatomic ions. We use 200 ns molecular dynamics simulations to compute diffusion rates, the extent of contact between molecules and dielectric constants. Large metabolites spend ∼80% of their time in contact with other molecules while small metabolites vary with some only spending 20% of time in contact. Large non-covalently interacting metabolite structures mediated by hydrogen-bonds, ionic and π stacking interactions are common and often associate with proteins. Mg²⁺ ions were prominent in NIMS and almost absent free in solution. Κ⁺ is generally not involved in NIMSs and populates the solvent fairly uniformly, hence its important role as an osmolyte. In simulations containing ubiquitin, to represent a protein component, metabolite diffusion was reduced owing to long lasting protein-metabolite interactions. Hence, it is likely that with larger proteins metabolites would diffuse even more slowly. The dielectric constant of these simulations was found to differ from that of pure water only through a large contribution from ubiquitin as metabolite and monatomic ion effects cancel. These findings suggest regions of influence specific to particular proteins affecting metabolite diffusion and electrostatics. Also some proteins may have a higher propensity for associations with metabolites owing to their larger electrostatic fields. We hope that future studies may be able to accurately predict how binding interactions differ in the cytosol relative to dilute aqueous solution.

The cytosol is the major cellular environment housing the majority of cellular activity. Although the cytosol is an aqueous environment, it contains high concentrations of ions, metabolites, and proteins, making it very different from dilute aqueous solution, which is frequently used for in vitro biochemistry. Recent advances in metabolomics have provided detailed concentration data for metabolites in E.coli. We used this information to construct accurate atomistic models of the cytosol solution. We find that, unlike the situation in dilute solutions, most metabolites spend the majority of their time in contact with other metabolites, or in contact with proteins. Furthermore, we find large non-covalently interacting metabolite structures are common and often associated with proteins. The presence of proteins reduced metabolite diffusion owing to long lasting correlations of motion. The dielectric constant of these simulations was found to differ from that of pure water only through a large contribution from proteins as metabolite and monatomic ion effects largely cancel. These findings suggest specific protein spheres of influence affecting metabolite diffusion and the electrostatic environment.

Kinetic challenges facing oxalate, malonate, acetoacetate, and oxaloacetate decarboxylases

To compare the powers of the corresponding enzymes as catalysts, the rates of uncatalyzed decarboxylation of several aliphatic acids (oxalate, malonate, acetoacetate, and oxaloacetate) were determined at elevated temperatures and extrapolated to 25 °C. In the extreme case of oxalate, the rate of the uncatalyzed reaction at pH 4.2 was 1.1 × 10(-12) s(-1), implying a 2.5 × 10(13)-fold rate enhancement by oxalate decarboxylase. Whereas the enzymatic decarboxylation of oxalate requires O(2) and Mn(II), the uncatalyzed reaction is unaffected by the presence of these cofactors and appears to proceed by heterolytic elimination of CO(2).

The glmS riboswitch integrates signals from activating and inhibitory metabolites in vivo

The glmS riboswitch belongs to the family of regulatory RNAs that provide feedback regulation of metabolic genes. It is also a ribozyme that self-cleaves upon binding glucosamine-6-phosphate, the product of the enzyme encoded by glmS. The ligand concentration dependence of intracellular self-cleavage kinetics was measured for the first time in a yeast model system and unexpectedly revealed that this riboswitch is subject to inhibition as well as activation by hexose metabolites. Reporter gene experiments in Bacillus subtilis confirmed that this riboswitch integrates positive and negative chemical signals in its natural biological context. Contrary to the conventional view that a riboswitch responds to just a single cognate metabolite, our new model proposes that a single riboswitch integrates information from an array of chemical signals to modulate gene expression based on the overall metabolic state of the cell.

2-hydroxyglutarate production, but not dominant negative function, is conferred by glioma-derived NADP-dependent isocitrate dehydrogenase mutations

BACKGROUND

Gliomas frequently contain mutations in the cytoplasmic NADP(+)-dependent isocitrate dehydrogenase (IDH1) or the mitochondrial NADP(+)-dependent isocitrate dehydrogenase (IDH2). Several different amino acid substitutions recur at either IDH1 R132 or IDH2 R172 in glioma patients. Genetic evidence indicates that these mutations share a common gain of function, but it is unclear whether the shared function is dominant negative activity, neomorphic production of (R)-2-hydroxyglutarate (2HG), or both.

METHODOLOGY/PRINCIPAL FINDINGS

We show by coprecipitation that five cancer-derived IDH1 R132 mutants bind IDH1-WT but that three cancer-derived IDH2 R172 mutants exert minimal binding to IDH2-WT. None of the mutants dominant-negatively lower isocitrate dehydrogenase activity at physiological (40 µM) isocitrate concentrations in mammalian cell lysates. In contrast to this, all of these mutants confer 10- to 100-fold higher 2HG production to cells, and glioma tissues containing IDH1 R132 or IDH2 R172 mutations contain high levels of 2HG compared to glioma tissues without IDH mutations (54.4 vs. 0.1 mg 2HG/g protein).

CONCLUSIONS

Binding to, or dominant inhibition of, WT IDH1 or IDH2 is not a shared feature of the IDH1 and IDH2 mutations, and thus is not likely to be important in cancer. The fact that the gain of the enzymatic activity to produce 2HG is a shared feature of the IDH1 and IDH2 mutations suggests that this is an important function for these mutants in driving cancer pathogenesis.

Parameter balancing in kinetic models of cell metabolism

Kinetic modeling of metabolic pathways has become a major field of systems biology. It combines structural information about metabolic pathways with quantitative enzymatic rate laws. Some of the kinetic constants needed for a model could be collected from ever-growing literature and public web resources, but they are often incomplete, incompatible, or simply not available. We address this lack of information by parameter balancing, a method to complete given sets of kinetic constants. Based on Bayesian parameter estimation, it exploits the thermodynamic dependencies among different biochemical quantities to guess realistic model parameters from available kinetic data. Our algorithm accounts for varying measurement conditions in the input data (pH value and temperature). It can process kinetic constants and state-dependent quantities such as metabolite concentrations or chemical potentials, and uses prior distributions and data augmentation to keep the estimated quantities within plausible ranges. An online service and free software for parameter balancing with models provided in SBML format (Systems Biology Markup Language) is accessible at www.semanticsbml.org. We demonstrate its practical use with a small model of the phosphofructokinase reaction and discuss its possible applications and limitations. In the future, parameter balancing could become an important routine step in the kinetic modeling of large metabolic networks.

Mass action stoichiometric simulation models: incorporating kinetics and regulation into stoichiometric models

The ability to characterize biological dynamics is important for understanding the integrated molecular processes that underlie normal and abnormal cellular states. The availability of metabolomic data, in addition to new developments in the formal description of dynamic states of networks, has enabled a new data integration approach for building large-scale kinetic networks. We show that dynamic network models can be constructed in a scalable manner using metabolomic data mapped onto stoichiometric models, resulting in mass action stoichiometric simulation (MASS) models. Enzymes and their various functional states are represented explicitly as compounds, or nodes in a stoichiometric network, within this formalism. Analyses and simulations of MASS models explicitly show that regulatory enzymes can control dynamic states of networks in part by binding numerous metabolites at multiple sites. Thus, network functional states are reflected in the fractional states of a regulatory enzyme, such as the fraction of the total enzyme concentration that is in a catalytically active versus inactive state. The feasible construction of MASS models represents a practical means to increase the size, scope, and predictive capabilities of dynamic network models in cell and molecular biology.

Phosphorylation is switch of L-type pyruvate kinase allostery

Among four pyruvate kinase isoenzymes, M1, M2, R and L, only M1 is considered as a nonallosteric enzyme. However, here we show that the non-phosphorylated L-type pyruvate kinase (L-PK) is also a non-allosteric enzyme with respect to its substrate phosphoenolpyruvate (PEP). The allosteric catalytic properties of L-PK are switched on through phosphorylation by cAMP-dependent protein kinase. The non-phosphorylated enzyme was produced by expressing the rat L-PK in E. coli, as the bacterium does not have mammalian-type protein kinases. The resulting tetrameric protein was phosphorylated with a stoichiometric ratio of one mole of phosphate per one L-PK monomer. Activity of the phosphorylated enzyme was allosterically regulated by PEP with the Hill coefficient n=2.5. It was observed that allostery was engaged by phosphorylation of the first subunit in the tetrameric enzyme, while further phosphorylation only modulated this effect. The discovered switching between non-allosteric and allosteric forms of L-PK and the possibility of modulating the allostery by phosphorylation are important for understanding of the interrelationship between allostery and the regulatory phosphorylation in general, and may have implication for further analysis of glycolysis regulation in the liver.

Inhibition kinetics of catabolic dehydrogenases by elevated moieties of ATP and ADP--implication for a new regulation mechanism in Lactococcus lactis

ATP and ADP inhibit, in varying degrees, several dehydrogenases of the central carbon metabolism of Lactococcus lactis ATCC 19435 in vitro, i.e. glyceraldehyde-3-phosphate dehydrogenase (GAPDH), lactate dehydrogenase (LDH) and alcohol dehydrogenase (ADH). Here we demonstrate mixed inhibition for GAPDH and competitive inhibition for LDH and ADH by adenine nucleotides in single inhibition studies. The nonlinear negative co-operativity was best modelled with Hill-type kinetics, showing greater flexibility than the usual parabolic inhibition equation. Because these natural inhibitors are present simultaneously in the cytoplasm, multiple inhibition kinetics was determined for each dehydrogenase. For ADH and LDH, the inhibitor combinations ATP plus NAD and ADP plus NAD are indifferent to each other. Model discrimination suggested that the weak allosteric inhibition of GAPDH had no relevance when multiple inhibitors are present. Interestingly, with ADH and GAPDH the combination of ATP and ADP exhibits lower dissociation constants than with either inhibitor alone. Moreover, the concerted inhibition of ADH and GAPDH, but not of LDH, shows synergy between the two nucleotides. Similar kinetics, but without synergies, were found for horse liver and yeast ADHs, indicating that dehydrogenases can be modulated by these nucleotides in a nonlinear manner in many organisms. The action of an elevated pool of ATP and ADP may effectively inactivate lactococcal ADH, but not GAPDH and LDH, providing leverage for the observed metabolic shift to homolactic acid formation in lactococcal resting cells on maltose. Therefore, we interpret these results as a regulation mechanism contributing to readjusting the flux of ATP production in L. lactis.

In silico feasibility of novel biodegradation pathways for 1,2,4-trichlorobenzene

Background

Bioremediation offers a promising pollution treatment method in the reduction and elimination of man-made compounds in the environment. Computational tools to predict novel biodegradation pathways for pollutants allow one to explore the capabilities of microorganisms in cleaning up the environment. However, given the wealth of novel pathways obtained using these prediction methods, it is necessary to evaluate their relative feasibility, particularly within the context of the cellular environment.

Results

We have utilized a computational framework called BNICE to generate novel biodegradation routes for 1,2,4-trichlorobenzene (1,2,4-TCB) and incorporated the pathways into a metabolic model for Pseudomonas putida. We studied the cellular feasibility of the pathways by applying metabolic flux analysis (MFA) and thermodynamic constraints. We found that the novel pathways generated by BNICE enabled the cell to produce more biomass than the known pathway. Evaluation of the flux distribution profiles revealed that several properties influenced biomass production: 1) reducing power required, 2) reactions required to generate biomass precursors, 3) oxygen utilization, and 4) thermodynamic topology of the pathway. Based on pathway analysis, MFA, and thermodynamic properties, we identified several promising pathways that can be engineered into a host organism to accomplish bioremediation.

Conclusions

This work was aimed at understanding how novel biodegradation pathways influence the existing metabolism of a host organism. We have identified attractive targets for metabolic engineers interested in constructing a microorganism that can be used for bioremediation. Through this work, computational tools are shown to be useful in the design and evaluation of novel xenobiotic biodegradation pathways, identifying cellularly feasible degradation routes.

Packaging effects on site-specific DNA-protein interactions

We show that the rate of site-specific association of a protein molecule of interest with the DNA chain can be approximately 10(2) times higher than that of the three-dimensional diffusion-controlled collision rate limit approximately 10(8) mol(-1) s(-1) only when the protein molecule of interest searches for its specific site on the DNA chain in a reduced dimensional space with a dimensionality dr of dr<1. Upon considering the concurrent dynamics of the linear DNA chain that is embedded in a d-dimensional space along with the one-dimensional diffusion dynamics of the nonspecifically bound protein molecule on the DNA chain, we derive the generalized scaling law epsilon approximately 2(3(2-d)+3), where epsilon is the number of times by which the rate of site-specific association of the protein molecule with the DNA chain can be enhanced over the three-dimensional diffusion-controlled collision rate limit and d is the dimensionality of the reduced search space. Using the analogy between the self-intersection loop length in the theory of random walks and the ring-closure events in the theory of site specific interactions of a protein molecule with the DNA chain, we further show that the extent of packaging and volume compression of the genomic DNA inside the living cell is designed in such a way that the efficiency of the protein molecule in the process of searching for its specific site on the genomic DNA is a maximum. Our simulation results suggest that the volume compression factor theta which is the ratio between the total volume of the living cell and the volume occupied by the DNA chain along with all the other bound protein molecules should be such that theta>or=100 for an efficient site specific interaction of a protein molecule of interest with the linear DNA chain that is embedded in a three-dimensional space. Our theoretical and simulation results agree well with the E. coli cellular system.

In silico strategy to rationally engineer metabolite production: A case study for threonine in Escherichia coli

Genetic engineering of metabolic pathways is a standard strategy to increase the production of metabolites of economic interest. However, such flux increases could very likely lead to undesirable changes in metabolite concentrations, producing deleterious perturbations on other cellular processes. These negative effects could be avoided by implementing a balanced increase of enzyme concentrations according to the Universal Method [Kacser and Acerenza (1993) Eur J Biochem 216:361-367]. Exact application of the method usually requires modification of many reactions, which is difficult to achieve in practice. Here, improvement of threonine production via pyruvate kinase deletion in Escherichia coli is used as a case study to demonstrate a partial application of the Universal Method, which includes performing sensitivity analysis. Our analysis predicts that manipulating a few reactions is sufficient to obtain an important increase in threonine production without major perturbations of metabolite concentrations.

Glioma-derived mutations in IDH1 dominantly inhibit IDH1 catalytic activity and induce HIF-1alpha

Heterozygous mutations in the gene encoding isocitrate dehydrogenase-1 (IDH1) occur in certain human brain tumors, but their mechanistic role in tumor development is unknown. We have shown that tumor-derived IDH1 mutations impair the enzyme's affinity for its substrate and dominantly inhibit wild-type IDH1 activity through the formation of catalytically inactive heterodimers. Forced expression of mutant IDH1 in cultured cells reduces formation of the enzyme product, alpha-ketoglutarate (alpha-KG), and increases the levels of hypoxia-inducible factor subunit HIF-1alpha, a transcription factor that facilitates tumor growth when oxygen is low and whose stability is regulated by alpha-KG. The rise in HIF-1alpha levels was reversible by an alpha-KG derivative. HIF-1alpha levels were higher in human gliomas harboring an IDH1 mutation than in tumors without a mutation. Thus, IDH1 appears to function as a tumor suppressor that, when mutationally inactivated, contributes to tumorigenesis in part through induction of the HIF-1 pathway.

In silico Geobacter sulfurreducens metabolism and its representation in reactive transport models

Microbial activity governs elemental cycling and the transformation of many anthropogenic substances in aqueous environments. Through the development of a dynamic cell model of the well-characterized, versatile, and abundant Geobacter sulfurreducens, we showed that a kinetic representation of key components of cell metabolism matched microbial growth dynamics observed in chemostat experiments under various environmental conditions and led to results similar to those from a comprehensive flux balance model. Coupling the kinetic cell model to its environment by expressing substrate uptake rates depending on intra- and extracellular substrate concentrations, two-dimensional reactive transport simulations of an aquifer were performed. They illustrated that a proper representation of growth efficiency as a function of substrate availability is a determining factor for the spatial distribution of microbial populations in a porous medium. It was shown that simplified model representations of microbial dynamics in the subsurface that only depended on extracellular conditions could be derived by properly parameterizing emerging properties of the kinetic cell model.

Modeling cellular metabolism and energetics in skeletal muscle: large-scale parameter estimation and sensitivity analysis

Skeletal muscle plays a major role in the regulation of whole-body energy metabolism during physiological stresses such as ischemia, hypoxia, and exercise. Current experimental techniques provide relatively little in vivo data on dynamic responses of metabolite concentrations and metabolic fluxes in skeletal muscle to such physiological stimuli. As a complementary approach to experimental measurements and as a framework for quantitatively analyzing available in vivo data, a physiologically based model of skeletal muscle cellular metabolism and energetics is developed. This model, which incorporates key transport and reaction processes, is based on dynamic mass balances of 30 chemical species in capillary (blood) and tissue (cell) domains. The reaction fluxes in the cellular domain are expressed in terms of a generalized Michaelis?Menten equation involving energy controller ratios ATP/ADP and ATP/ADP and NADH/NAD+ . This formalism introduces a large number of unknown parameters ( approximately 90). Estimating these parameters from in vivo sparse data and evaluating dynamic sensitivities of the model outputs with respect to these parameters is a challenging problem. Parameter estimation is accomplished using an efficient, nonlinear, constraint-based, optimization algorithm that minimizes differences between available experimental data and corresponding model outputs by explicitly utilizing equality constraints on resting fluxes and concentrations. With the estimated parameter values, the model is able to simulate dynamic responses to reduced blood flow (ischemia) of key metabolite concentrations and metabolic fluxes, both measured and nonmeasured. A general parameter sensitivity analysis is carried out to determine and characterize the parameters having the most and least effects on the measured outputs.