Short-term metabolome dynamics and carbon, electron, and ATP balances in chemostat-grown Saccharomyces cerevisiae CEN.PK 113-7D following a glucose pulse

Improved 2,3-Butanediol Production Rate of Metabolically Engineered Saccharomyces cerevisiae by Deletion of RIM15 and Activation of Pyruvate Consumption Pathway

Saccharomyces cerevisiae is a promising host for the bioproduction of higher alcohols, such as 2,3-butanediol (2,3-BDO). Metabolically engineered S. cerevisiae strains that produce 2,3-BDO via glycolysis have been constructed. However, the specific 2,3-BDO production rates of engineered strains must be improved. To identify approaches to improving the 2,3-BDO production rate, we investigated the factors contributing to higher ethanol production rates in certain industrial strains of S. cerevisiae compared to laboratory strains. Sequence analysis of 11 industrial strains revealed the accumulation of many nonsynonymous substitutions in RIM15, a negative regulator of high fermentation capability. Comparative metabolome analysis suggested a positive correlation between the rate of ethanol production and the activity of the pyruvate-consuming pathway. Based on these findings, RIM15 was deleted, and the pyruvate-consuming pathway was activated in YHI030, a metabolically engineered S. cerevisiae strain that produces 2,3-BDO. The titer, specific production rate, and yield of 2,3-BDO in the test tube-scale culture using the YMS106 strain reached 66.4 ± 4.4 mM, 1.17 ± 0.017 mmol (g dry cell weight h)-1, and 0.70 ± 0.03 mol (mol glucose consumed)-1. These values were 2.14-, 2.92-, and 1.81-fold higher than those of the vector control, respectively. These results suggest that bioalcohol production via glycolysis can be enhanced in a metabolically engineered S. cerevisiae strain by deleting RIM15 and activating the pyruvate-consuming pathway.

Using Kinetic Modelling to Infer Adaptations in Saccharomyces cerevisiae Carbohydrate Storage Metabolism to Dynamic Substrate Conditions

Microbial metabolism is strongly dependent on the environmental conditions. While these can be well controlled under laboratory conditions, large-scale bioreactors are characterized by inhomogeneities and consequently dynamic conditions for the organisms. How Saccharomyces cerevisiae response to frequent perturbations in industrial bioreactors is still not understood mechanistically. To study the adjustments to prolonged dynamic conditions, we used published repeated substrate perturbation regime experimental data, extended it with proteomic measurements and used both for modelling approaches. Multiple types of data were combined; including quantitative metabolome, ¹³C enrichment and flux quantification data. Kinetic metabolic modelling was applied to study the relevant intracellular metabolic response dynamics. An existing model of yeast central carbon metabolism was extended, and different subsets of enzymatic kinetic constants were estimated. A novel parameter estimation pipeline based on combinatorial enzyme selection supplemented by regularization was developed to identify and predict the minimum enzyme and parameter adjustments from steady-state to dynamic substrate conditions. This approach predicted proteomic changes in hexose transport and phosphorylation reactions, which were additionally confirmed by proteome measurements. Nevertheless, the modelling also hints at a yet unknown kinetic or regulation phenomenon. Some intracellular fluxes could not be reproduced by mechanistic rate laws, including hexose transport and intracellular trehalase activity during substrate perturbation cycles.

An excess of glycolytic enzymes under glucose-limited conditions may enable Saccharomyces cerevisiae to adapt to nutrient availability

Microorganisms, including the budding yeast Saccharomyces cerevisiae, express glycolytic proteins to a maximal capacity that (largely) exceeds the actual flux through the enzymes, especially at low growth rates. An open question is if this apparent expression level is really an overcapacity, or maintains the (optimal) enzyme capacity needed to carry flux at (very) low substrate availability. Here, we use computational modelling to suggest that yeast maintains a genuine excess of glycolytic enzymes at low specific growth rates. During fast fermentative growth at high glucose levels, the observed expression of the glycolytic enzymes matched the predicted optimal levels. We suggest that the excess glycolytic capacity at low glucose levels is a preparatory strategy in the adaptation to sugar fluctuations in the environment.

Predicting Metabolic Adaptation Under Dynamic Substrate Conditions Using a Resource-Dependent Kinetic Model: A Case Study Using Saccharomyces cerevisiae

Exposed to changes in their environment, microorganisms will adapt their phenotype, including metabolism, to ensure survival. To understand the adaptation principles, resource allocation-based approaches were successfully applied to predict an optimal proteome allocation under (quasi) steady-state conditions. Nevertheless, for a general, dynamic environment, enzyme kinetics will have to be taken into account which was not included in the linear resource allocation models. To this end, a resource-dependent kinetic model was developed and applied to the model organism Saccharomyces cerevisiae by combining published kinetic models and calibrating the model parameters to published proteomics and fluxomics datasets. Using this approach, we were able to predict specific proteomes at different dilution rates under chemostat conditions. Interestingly, the approach suggests that the occurrence of aerobic fermentation (Crabtree effect) in S. cerevisiae is not caused by space limitation in the total proteome but rather an effect of constraints on the mitochondria. When exposing the approach to repetitive, dynamic substrate conditions, the proteome space was allocated differently. Less space was predicted to be available for non-essential enzymes (reserve space). This could indicate that the perceived “overcapacity” present in experimentally measured proteomes may very likely serve a purpose in increasing the robustness of a cell to dynamic conditions, especially an increase of proteome space for the growth reaction as well as of the trehalose cycle that was shown to be essential in providing robustness upon stronger substrate perturbations. The model predictions of proteome adaptation to dynamic conditions were additionally evaluated against respective experimentally measured proteomes, which highlighted the model’s ability to accurately predict major proteome adaptation trends. This proof of principle for the approach can be extended to production organisms and applied for both understanding metabolic adaptation and improving industrial process design.

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.

LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism

BACKGROUND

The systems-scale analysis of cellular metabolites, "metabolomics," provides data ideal for applications in metabolic engineering. However, many of the computational tools for strain design are built around Flux Balance Analysis (FBA), which makes assumptions that preclude direct integration of metabolomics data into the underlying models. Finding a way to retain the advantages of FBA's linear structure while relaxing some of its assumptions could allow us to account for metabolite levels and metabolite-dependent regulation in strain design tools built from FBA, improving the accuracy of predictions made by these tools. We designed, implemented, and characterized a modeling strategy based on Dynamic FBA (DFBA), called Linear Kinetics-Dynamic Flux Balance Analysis (LK-DFBA), to satisfy these specifications. Our strategy adds constraints describing the dynamics and regulation of metabolism that are strictly linear. We evaluated LK-DFBA against alternative modeling frameworks using simulated noisy data from a small in silico model and a larger model of central carbon metabolism in E. coli, and compared each framework's ability to recapitulate the original system.

RESULTS

In the smaller model, we found that we could use regression from a dynamic flux estimation (DFE) with an optional non-linear parameter optimization to reproduce metabolite concentration dynamic trends more effectively than an ordinary differential equation model with generalized mass action rate laws when tested under realistic data sampling frequency and noise levels. We observed detrimental effects across all tested modeling approaches when metabolite time course data were missing, but found these effects to be smaller for LK-DFBA in most cases. With the E. coli model, we produced qualitatively reasonable results with similar properties to the smaller model and explored two different parameterization structures that yield trade-offs in computation time and accuracy.

CONCLUSIONS

LK-DFBA allows for calculation of metabolite concentrations and considers metabolite-dependent regulation while still retaining many computational advantages of FBA. This provides the proof-of-principle for a new metabolic modeling framework with the potential to create genome-scale dynamic models and the potential to be applied in strain engineering tools that currently use FBA.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

Quantitative Flow Cytometry to Understand Population Heterogeneity in Response to Changes in Substrate Availability in Escherichia coli and Saccharomyces cerevisiae Chemostats

Microbial cells in bioprocesses are usually described with averaged parameters. But in fact, single cells within populations vary greatly in characteristics such as stress resistance, especially in response to carbon source gradients. Our aim was to introduce tools to quantify population heterogeneity in bioprocesses using a combination of reporter strains, flow cytometry, and easily comprehensible parameters. We calculated mean, mode, peak width, and coefficient of variance to describe distribution characteristics and temporal shifts in fluorescence intensity. The skewness and the slope of cumulative distribution function plots illustrated differences in distribution shape. These parameters are person-independent and precise. We demonstrated this by quantifying growth-related population heterogeneity of Saccharomyces cerevisiae and Escherichia coli reporter strains in steady-state of aerobic glucose-limited chemostat cultures at different dilution rates and in response to glucose pulses. Generally, slow-growing cells showed stronger responses to glucose excess than fast-growing cells. Cell robustness, measured as membrane integrity after exposure to freeze-thaw treatment, of fast-growing cells was strongly affected in subpopulations of low membrane robustness. Glucose pulses protected subpopulations of fast-growing but not slower-growing yeast cells against membrane damage. Our parameters could successfully describe population heterogeneity, thereby revealing physiological characteristics that might have been overlooked during traditional averaged analysis.

Trehalose-6-phosphate promotes fermentation and glucose repression in Saccharomyces cerevisiae

The yeast trehalose-6-phosphate synthase (Tps1) catalyzes the formation of trehalose-6-phosphate (T6P) in trehalose synthesis. Besides, Tps1 plays a key role in carbon and energy homeostasis in this microbial cell, as shown by the well documented loss of ATP and hyper accumulation of sugar phosphates in response to glucose addition in a mutant defective in this protein. The inability of a Saccharomyces cerevisiae tps1 mutant to cope with fermentable sugars is still a matter of debate. We reexamined this question through a quantitative analysis of the capability of TPS1 homologues from different origins to complement phenotypic defects of this mutant. Our results allowed to classify this complementation in three groups. A first group enclosed TPS1 of Klyveromyces lactis with that of S. cerevisiae as their expression in Sctps1 cells fully recovered wild type metabolic patterns and fermentation capacity in response to glucose. At the opposite was the group with TPS1 homologues from the bacteria Escherichia coli and Ralstonia solanacearum, the plant Arabidopsis thaliana and the insect Drosophila melanogaster whose metabolic profiles were comparable to those of a tps1 mutant, notably with almost no accumulation of T6P, strong impairment of ATP recovery and potent reduction of fermentation capacity, albeit these homologous genes were able to rescue growth of Sctps1 on glucose. In between was a group consisting of TPS1 homologues from other yeast species and filamentous fungi characterized by 5 to 10 times lower accumulation of T6P, a weaker recovery of ATP and a 3-times lower fermentation capacity than wild type. Finally, we found that glucose repression of gluconeogenic genes was strongly dependent on T6P. Altogether, our results suggest that the TPS protein is indispensable for growth on fermentable sugars, and points to a critical role of T6P as a sensing molecule that promotes sugar fermentation and glucose repression.

Advances in bio-based production of dicarboxylic acids longer than C4

Growing concerns of environmental pollution and fossil resource shortage are major driving forces for bio-based production of chemicals traditionally from petrochemical industry. Dicarboxylic acids (DCAs) are important platform chemicals with large market and wide applications, and here the recent advances in bio-based production of straight-chain DCAs longer than C4 from biological approaches, especially by synthetic biology, are reviewed. A couple of pathways were recently designed and demonstrated for producing DCAs, even those ranging from C5 to C15, by employing respective starting units, extending units, and appropriate enzymes. Furthermore, in order to achieve higher production of DCAs, enormous efforts were made in engineering microbial hosts that harbored the biosynthetic pathways and in improving properties of biocatalytic elements to enhance metabolic fluxes toward target DCAs. Here we summarize and discuss the current advantages and limitations of related pathways, and also provide perspectives on synthetic pathway design and optimization for hyper-production of DCAs.

High recycling efficiency and elemental sulfur purity achieved in a biofilm formed membrane filtration reactor

Elemental sulfur (S⁰) is always produced during bio-denitrification and desulfurization process, but the S⁰ yield and purification quality are too low. Till now, no feasible approach has been carried out to efficiently recover S⁰. In this study, we report the S⁰ generation and recovery by a newly designed, compact, biofilm formed membrane filtration reactor (BfMFR), where S⁰ was generated within a Thauera sp. strain HDD-formed biofilm on membrane surface, and then timely separated from the biofilm through membrane filtration. The high S⁰ generation efficiency (98% in average) was stably maintained under the operation conditions with the influent acetate, nitrate and sulfide concentration of 115, 120 and 100 mg/L, respectively, an initial inoculum volume of approximate 2.4 × 10⁸ cells, and a membrane pore size of 0.45 μm. Under this condition, the sulfide loading approached 62.5 kg/m³·d, one of the highest compared with the previous reports, demonstrating an efficient sulfide removal and S⁰ generation capacity. Particular important, a solid analysis of the effluent revealed that the recovered S⁰ was adulterated with barely microorganisms, extracellular polymeric substances (EPSs), or inorganic chemicals, indicating a fairly high S⁰ recovery purity. Membrane biofilm analysis revealed that 80.7% of the generated S⁰ was accomplished within 45-80 μm of biofilm from the membrane surface and while, the complete membrane fouling due to bacteria and EPSs was generally observed after 14-16 days. The in situ generation and timely separation of S⁰ from the bacterial group by BfMFR, effectively avoids the sulfur circulation (S^2- to S⁰, S⁰ to SO₄^2-, SO₄^2- to HS^-) and guarantees the high S⁰ recovery efficiency and purity, is considered as a feasible approach for S⁰ recovery from sulfide- and nitrate-contaminated wastewater.

Beyond topology: coevolution of structure and flux in metabolic networks

Interactions between the structure of a metabolic network and its functional properties underlie its evolutionary diversification, but the mechanism by which such interactions arise remains elusive. Particularly unclear is whether metabolic fluxes that determine the concentrations of compounds produced by a metabolic network, are causally linked to a network's structure or emerge independently of it. A direct empirical study of populations where both structural and functional properties vary among individuals' metabolic networks is required to establish whether changes in structure affect the distribution of metabolic flux. In a population of house finches (Haemorhous mexicanus), we reconstructed full carotenoid metabolic networks for 442 individuals and uncovered 11 structural variants of this network with different compounds and reactions. We examined the consequences of this structural diversity for the concentrations of plumage-bound carotenoids produced by flux in these networks. We found that concentrations of metabolically derived, but not dietary carotenoids, depended on network structure. Flux was partitioned similarly among compounds in individuals of the same network structure: within each network, compound concentrations were closely correlated. The highest among-individual variation in flux occurred in networks with the strongest among-compound correlations, suggesting that changes in the magnitude, but not the distribution of flux, underlie individual differences in compound concentrations on a static network structure. These findings indicate that the distribution of flux in carotenoid metabolism closely follows network structure. Thus, evolutionary diversification and local adaptations in carotenoid metabolism may depend more on the gain or loss of enzymatic reactions than on changes in flux within a network structure.

Influence of an Alkaline Zeolite on the Carbon Flow in Anaerobiosis of Three Strains of Saccharomyces cerevisiae

Nowadays ethanol is considered an alternative to liquid fossil fuels, as a product of fermentation of sugars by Saccharomyces cerevisiae and other microorganisms. It is very important in the food, pharmaceutical and chemical industries. Prior studies show that the addition of certain amount of zeolite induces an increase in the ethanol/glucose yield. In this work, the effect of zeolite on the carbon flux of S. cerevisiae in different culture conditions is reported. An explanation for the effect of the zeolite on the yeast metabolism is offered. Results show a 20 % increase in yield, thus lowering production costs and improving the use of raw materials, which would increase the possibilities of using alcohol as biofuel.

The Landscape of Evolution: Reconciling Structural and Dynamic Properties of Metabolic Networks in Adaptive Diversifications

The network of the interactions among genes, proteins, and metabolites delineates a range of potential phenotypic diversifications in a lineage, and realized phenotypic changes are the result of differences in the dynamics of the expression of the elements and interactions in this deterministic network. Regulatory mechanisms, such as hormones, mediate the relationship between the structural and dynamic properties of networks by determining how and when the elements are expressed and form a functional unit or state. Changes in regulatory mechanisms lead to variable expression of functional states of a network within and among generations. Functional properties of network elements, and the magnitude and direction of evolutionary change they determine, depend on their location within a network. Here, we examine the relationship between network structure and the dynamic mechanisms that regulate flux through a metabolic network. We review the mechanisms that control metabolic flux in enzymatic reactions and examine structural properties of the network locations that are targets of flux control. We aim to establish a predictive framework to test the contributions of structural and dynamic properties of deterministic networks to evolutionary diversifications.

Adenosine diphosphate restricts the protein remodeling activity of the Hsp104 chaperone to Hsp70 assisted disaggregation

Hsp104 disaggregase provides thermotolerance in yeast by recovering proteins from aggregates in cooperation with the Hsp70 chaperone. Protein disaggregation involves polypeptide extraction from aggregates and its translocation through the central channel of the Hsp104 hexamer. This process relies on adenosine triphosphate (ATP) hydrolysis. Considering that Hsp104 is characterized by low affinity towards ATP and is strongly inhibited by adenosine diphosphate (ADP), we asked how Hsp104 functions at the physiological levels of adenine nucleotides. We demonstrate that physiological levels of ADP highly limit Hsp104 activity. This inhibition, however, is moderated by the Hsp70 chaperone, which allows efficient disaggregation by supporting Hsp104 binding to aggregates but not to non-aggregated, disordered protein substrates. Our results point to an additional level of Hsp104 regulation by Hsp70, which restricts the potentially toxic protein unfolding activity of Hsp104 to the disaggregation process, providing the yeast protein-recovery system with substrate specificity and efficiency in ATP consumption.

DOI:http://dx.doi.org/10.7554/eLife.15159.001

Under stressful conditions, such as high temperatures, many proteins lose their proper structure and clump together to form large irregular aggregates. To combat this effect, living organisms exposed to stress produce specialized proteins called chaperones, which can rescue the damaged proteins from aggregates.

Studies into this “disaggregation” process often use budding yeast as a model organism. The protein-recovery machinery in this yeast is composed of a ring-shaped enzyme called Hsp104, together with a chaperone called Hsp70 and its partner Hsp40. The Hsp104 enzyme converts molecules of ATP into ADP and uses the energy released from the reaction to move, or “translocate”, damaged proteins through its central channel and release them from the aggregates.

Previous studies had reported that ADP negatively affects Hsp104. Now, Kłosowska et al show that Hsp104 is almost inactive in a test-tube if the concentration of ADP is as high as that found inside a cell. This raises a question: how can Hsp104 efficiently remove proteins from aggregates in cells if the conditions are so unfavorable?

Using purified proteins, Kłosowska et al. go on to show that Hsp104 is able to tolerate the level of ADP found inside cells thanks to the Hsp70 chaperone. The experiments show that ADP weakens Hsp104’s ability to bind proteins while Hsp70 supports this ability and counteracts the negative effect of ADP. Further experiments demonstrate that Hsp104 is less affected by ADP, and binds more readily to ATP, when it is translocating proteins. These findings explain how the yeast disaggregating machinery can work even at relatively high concentrations of ADP, and reveal a new control mechanism in the disaggregation process.

Many important proteins have poorly organized fragments that can be recognized by Hsp104, and if Hsp104 was to bind to and translocate these proteins it could harm the cell. The findings of Kłosowska et al. suggest that Hsp70 helps Hsp104 to specifically bind to and act upon proteins in aggregates, while binding to partly unstructured proteins is limited by the high ADP concentration. Further studies are now needed to understand how the protein-recovery machinery can discriminate between aggregated and non-aggregated proteins.

DOI:http://dx.doi.org/10.7554/eLife.15159.002

Determination of the Cytosolic NADPH/NADP Ratio in Saccharomyces cerevisiae using Shikimate Dehydrogenase as Sensor Reaction

Eukaryotic metabolism is organised in complex networks of enzyme catalysed reactions which are distributed over different organelles. To quantify the compartmentalised reactions, quantitative measurements of relevant physiological variables in different compartments are needed, especially of cofactors. NADP(H) are critical components in cellular redox metabolism. Currently, available metabolite measurement methods allow whole cell measurements. Here a metabolite sensor based on a fast equilibrium reaction is introduced to monitor the cytosolic NADPH/NADP ratio in Saccharomyces cerevisiae: NADP + shikimate ⇄ NADPH + H(+) + dehydroshikimate. The cytosolic NADPH/NADP ratio was determined by measuring the shikimate and dehydroshikimate concentrations (by GC-MS/MS). The cytosolic NADPH/NADP ratio was determined under batch and chemostat (aerobic, glucose-limited, D = 0.1 h(-1)) conditions, to be 22.0 ± 2.6 and 15.6 ± 0.6, respectively. These ratios were much higher than the whole cell NADPH/NADP ratio (1.05 ± 0.08). In response to a glucose pulse, the cytosolic NADPH/NADP ratio first increased very rapidly and restored the steady state ratio after 3 minutes. In contrast to this dynamic observation, the whole cell NADPH/NADP ratio remained nearly constant. The novel cytosol NADPH/NADP measurements provide new insights into the thermodynamic driving forces for NADP(H)-dependent reactions, like amino acid synthesis, product pathways like fatty acid production or the mevalonate pathway.

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.

In scarcity and abundance: metabolic signals regulating cell growth

Although nutrient availability is a major driver of cell growth, and continuous adaptation to nutrient supply is critical for the development and survival of all organisms, the molecular mechanisms of nutrient sensing are only beginning to emerge. Here, we highlight recent advances in the field of nutrient sensing and discuss arising principles governing how metabolism might regulate growth-promoting pathways. In addition, we discuss signaling functions of metabolic enzymes not directly related to their metabolic activity.

Changes in substrate availability in Escherichia coli lead to rapid metabolite, flux and growth rate responses

The interactions between the intracellular metabolome, fluxome and growth rate of Escherichia coli after sudden glycolytic/gluconeogenic substrate shifts are studied based on pulses of different substrates to an aerobic glucose-limited steady-state (dilution rate=0.1h(-1)). After each added glycolytic (glucose) and gluconeogenic (pyruvate and succinate) substrate pulse, no by-products were secreted and a pseudo steady state in flux and metabolites was achieved in about 30-40s. In the pulse experiments a large oxygen uptake capacity of the cells was observed. The in vivo dynamic responses showed massive reorganization and flexibility (1/100-14-fold change) of extra/intracellular metabolic fluxes, matching with large changes in the concentrations of intracellular metabolites, including reversal of reaction rate for pseudo/near equilibrium reactions. The coupling of metabolome and fluxome could be described by Q-linear kinetics. Remarkably, the three different substrate pulses resulted in a very similar increase in growth rate (0.13-0.3h(-1)). Data analysis showed that there must exist as yet unknown mechanisms which couple the protein synthesis rate to changes in central metabolites.

Systematic applications of metabolomics in metabolic engineering

The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.

Testing biochemistry revisited: how in vivo metabolism can be understood from in vitro enzyme kinetics

A decade ago, a team of biochemists including two of us, modeled yeast glycolysis and showed that one of the most studied biochemical pathways could not be quite understood in terms of the kinetic properties of the constituent enzymes as measured in cell extract. Moreover, when the same model was later applied to different experimental steady-state conditions, it often exhibited unrestrained metabolite accumulation.

Here we resolve this issue by showing that the results of such ab initio modeling are improved substantially by (i) including appropriate allosteric regulation and (ii) measuring the enzyme kinetic parameters under conditions that resemble the intracellular environment. The following modifications proved crucial: (i) implementation of allosteric regulation of hexokinase and pyruvate kinase, (ii) implementation of V_max values measured under conditions that resembled the yeast cytosol, and (iii) redetermination of the kinetic parameters of glyceraldehyde-3-phosphate dehydrogenase under physiological conditions.

Model predictions and experiments were compared under five different conditions of yeast growth and starvation. When either the original model was used (which lacked important allosteric regulation), or the enzyme parameters were measured under conditions that were, as usual, optimal for high enzyme activity, fructose 1,6-bisphosphate and some other glycolytic intermediates tended to accumulate to unrealistically high concentrations. Combining all adjustments yielded an accurate correspondence between model and experiments for all five steady-state and dynamic conditions. This enhances our understanding of in vivo metabolism in terms of in vitro biochemistry.

Baker's yeast is widely applied in modern biotechnology, for instance for production of heterologous protein or biofuel. For such applications a thorough understanding of the central energy metabolism of the bug is crucial. Nevertheless, even for this well-known organism, attempts to build models ab initio, based on independently measured characteristics of the catalysts (the enzymes), seldom gives reliable results. A key problem in this field is that enzyme characteristics are often studied under non-physiological conditions that do not resemble the environment inside the cell. In this study we measured the enzyme characteristics under physiological conditions and assembled the results into a computational model of yeast energy metabolism. We show that this simple trick greatly improves the predictive value of the computational model. This allowed us to predict correctly how yeast cells adapt to nitrogen starvation, an industrially relevant situation, in which remodeling of the proteome strongly affects cellular energy metabolism.

Escherichia coli responds with a rapid and large change in growth rate upon a shift from glucose-limited to glucose-excess conditions

Glucose pulse experiments at seconds time scale resolution were performed in aerobic glucose-limited Escherichia coli chemostat cultures. The dynamic responses of oxygen-uptake and growth rate at seconds time scale were determined using a new method based on the dynamic liquid-phase mass balance for oxygen and the pseudo-steady-state ATP balance. Significant fold changes in metabolites (10-1/10) and fluxes (4-1/4) were observed during the short (200 s) period of glucose excess. During glucose excess there was no secretion of by-products and the increased glucose uptake rate led within 40s to a 3.7 fold increase in growth rate. Also within 40-60s a new pseudo-steady-state was reached for both metabolite levels and fluxes. Flux changes of reactions were strongly correlated to the concentrations of involved compounds. Surprisingly the 3.7 fold increase in growth rate and hence protein synthesis rate was not matched by a significant increase in amino acid concentrations. This poses interesting questions for the kinetic factors, which drive protein synthesis by ribosomes.

Metabolomics in systems microbiology

Because of the importance of microbes as model organisms, biotechnology tools, and contributors to mammalian and ecosystem metabolism, there has been longstanding interest in measuring their metabolite levels. Current metabolomic methods, involving mass spectrometry-based measurement of cell extracts, enable routine quantitation of most central metabolites. Metabolomics alone, however, is inadequate to understand cellular metabolic activity: Flux measurement and proteomic, genetic, and biochemical approaches with a metabolomics bent are all needed. Here we highlight examples where these integrated methods have contributed to discovery of metabolic pathways, regulatory interactions, and homeostasis mechanisms. We also indicate enduring challenges concerning unstable and low abundance compounds, subcellular compartmentalization, and quantitative amalgamation of different data types.

Catching prompt metabolite dynamics in Escherichia coli with the BioScope at oxygen rich conditions

The design and application of a BioScope, a mini plug-flow reactor for carrying out pulse response experiments, specifically designed for Escherichia coli is presented. Main differences with the previous design are an increased volume-specific membrane surface for oxygen transfer and significantly decreased sampling intervals. The characteristics of the new device (pressure drop, residence time distribution, plug-flow behavior and O2 mass transfer) were determined and evaluated. Subsequently, 2.8 mM glucose perturbation experiments on glucose-limited aerobic E. coli chemostat cultures were carried out directly in the chemostat as well as in the BioScope (for two time frames: 8 and 40 s). It was ensured that fully aerobic conditions were maintained during the perturbation experiments. To avoid metabolite leakage during quenching, metabolite quantification (glycolytic and TCA-cycle intermediates and nucleotides) was carried out with a differential method, whereby the amounts measured in the filtrate were subtracted from the amounts measured in total broth. The dynamic metabolite profiles obtained from the BioScope perturbations were very comparable with the profiles obtained from the chemostat perturbation. This agreement demonstrates that the BioScope is a promising device for studying in vivo kinetics in E. coli that shows much faster response (< 10 s) in comparison with eukaryotes.

Mass spectrometry-based metabolomics of yeast

Driven by the advent of metabolomics, recent years have seen renewed interest in the investigation of yeast metabolism. Here we provide a practical guide to metabolomic analysis of yeast using liquid chromatography-mass spectrometry (LC-MS). We begin with background on LC-MS and its utility in studying yeast metabolism. We then describe key issues involved at each step of a typical yeast metabolomics experiment: in experimental design, cell culture, metabolite extraction, LC-MS, and data processing and analysis. Throughout, we highlight interdependencies between the steps that are relevant to developing an integrated workflow which effectively leverages LC-MS to reveal yeast biology.

Impact of thermodynamic principles in systems biology

It is shown that properties of biological systems which are relevant for systems biology motivated mathematical modelling are strongly shaped by general thermodynamic principles such as osmotic limit, Gibbs energy dissipation, near equilibria and thermodynamic driving force. Each of these aspects will be demonstrated both theoretically and experimentally.

High-throughput quantitative metabolomics: workflow for cultivation, quenching, and analysis of yeast in a multiwell format

Metabolomics is a founding pillar of quantitative biology and a valuable tool for studying metabolism and its regulation. Here we present a workflow for metabolomics in microplate format which affords high-throughput and yet quantitative monitoring of primary metabolism in microorganisms and in particular yeast. First, the most critical step of rapid sampling was adapted to a multiplex format by using fritted 96-well plates for cultivation, which ensure fast sample transfer and permit us to use well-established quenching in cold solvents. Second, extensive optimization of large-volume injection on a GC/TOF instrument provided the sensitivity necessary for robust quantification of 30 primary metabolites in 0.6 mg of yeast biomass. The metabolome profiles of baker's yeast cultivated in fritted well plates or in shake flasks were equivalent. Standard deviations of measured metabolites were between 10% and 50% within one plate. As a proof of principle we compared the metabolome of wild-type Saccharomyces cerevisiae and the single-deletion mutant Delta sdh1, which were clearly distinguishable by a 10-fold increase of the intracellular succinate concentration in the mutant. The described workflow allows the production of large amounts of metabolome samples within a day, is compatible with virtually all liquid extraction protocols, and paves the road to quantitative screens.

Energetic and metabolic transient response of Saccharomyces cerevisiae to benzoic acid

Saccharomyces cerevisiae is known to be able to adapt to the presence of the commonly used food preservative benzoic acid with a large energy expenditure. Some mechanisms for the adaptation process have been suggested, but its quantitative energetic and metabolic aspects have rarely been discussed. This study discusses use of the stimulus response approach to quantitatively study the energetic and metabolic aspects of the transient adaptation of S. cerevisiae to a shift in benzoic acid concentration, from 0 to 0.8 mM. The information obtained also serves as the basis for further utilization of benzoic acid as a tool for targeted perturbation of the energy system, which is important in studying the kinetics and regulation of central carbon metabolism in S. cerevisiae. Using this experimental set-up, we found significant fast-transient (< 3000 s) increases in O(2) consumption and CO(2) production rates, of approximately 50%, which reflect a high energy requirement for the adaptation process. We also found that with a longer exposure time to benzoic acid, S. cerevisiae decreases the cell membrane permeability for this weak acid by a factor of 10 and decreases the cell size to approximately 80% of the initial value. The intracellular metabolite profile in the new steady-state indicates increases in the glycolytic and tricarboxylic acid cycle fluxes, which are in agreement with the observed increases in specific glucose and O(2) uptake rates.

Development and application of a differential method for reliable metabolome analysis in Escherichia coli

Quantitative metabolomics of microbial cultures requires well-designed sampling and quenching procedures. We successfully developed and applied a differential method to obtain a reliable set of metabolome data for Escherichia coli K12 MG1655 grown in steady-state, aerobic, glucose-limited chemostat cultures. From a rigorous analysis of the commonly applied quenching procedure based on cold aqueous methanol, it was concluded that it was not applicable because of release of a major part of the metabolites from the cells. No positive effect of buffering or increasing the ionic strength of the quenching solution was observed. Application of a differential method in principle requires metabolite measurements in total broth and filtrate for each measurement. Different methods for sampling of culture filtrate were examined, and it was found that direct filtration without cooling of the sample was the most appropriate. Analysis of culture filtrates revealed that most of the central metabolites and amino acids were present in significant amounts outside the cells. Because the turnover time of the pools of extracellular metabolites is much larger than that of the intracellular pools, the differential method should also be applicable to short-term pulse response experiments without requiring measurement of metabolites in the supernatant during the dynamic period.

Determination of the cytosolic free NAD/NADH ratio in Saccharomyces cerevisiae under steady-state and highly dynamic conditions

The coenzyme NAD plays a major role in metabolism as a key redox carrier and signaling molecule but current measurement techniques cannot distinguish between different compartment pools, between free and protein-bound forms and/or between NAD(H) and NADP(H). Local free NAD/NADH ratios can be determined from product/substrate ratios of suitable near-equilibrium redox reactions but the application of this principle is often precluded by uncertainties regarding enzyme activity, localization and coenzyme specificity of dehydrogenases. In Saccharomyces cerevisiae, we circumvented these issues by expressing a bacterial mannitol-1-phosphate 5-dehydrogenase and determining the cytosolic free NAD/NADH ratio from the measured [fructose-6-phosphate]/[mannitol-1-phosphate] ratio. Under aerobic glucose-limited conditions we estimated a cytosolic free NAD/NADH ratio between 101(+/-14) and 320(+/-45), assuming the cytosolic pH is between 7.0 and 6.5, respectively. These values are more than 10-fold higher than the measured whole-cell total NAD/NADH ratio of 7.5(+/-2.5). Using a thermodynamic analysis of central glycolysis we demonstrate that the former are thermodynamically feasible, while the latter is not. Furthermore, we applied this novel system to study the short-term metabolic responses to perturbations. We found that the cytosolic free NAD-NADH couple became more reduced rapidly (timescale of seconds) upon a pulse of glucose (electron-donor) and that this could be reversed by the addition of acetaldehyde (electron-acceptor). In addition, these dynamics occurred without significant changes in whole-cell total NAD and NADH. This approach provides a new experimental tool for quantitative physiology and opens new possibilities in the study of energy and redox metabolism in S. cerevisiae. The same strategy should also be applicable to other microorganisms.

Quantitative analysis of the high temperature-induced glycolytic flux increase in Saccharomyces cerevisiae reveals dominant metabolic regulation

A major challenge in systems biology lies in the integration of processes occurring at different levels, such as transcription, translation, and metabolism, to understand the functioning of a living cell in its environment. We studied the high temperature-induced glycolytic flux increase in Saccharomyces cerevisiae and investigated the regulatory mechanisms underlying this increase. We used glucose-limited chemostat cultures to separate regulatory effects of temperature from effects on growth rate. Growth at increased temperature (38 degrees C versus 30 degrees C) resulted in a strongly increased glycolytic flux, accompanied by a switch from respiration to a partially fermentative metabolism. We observed an increased flux through all enzymes, ranging from 5- to 10-fold. We quantified the contributions of direct temperature effects on enzyme activities, the gene expression cascade and shifts in the metabolic network, to the increased flux through each enzyme. To do this we adapted flux regulation analysis. We show that the direct effect of temperature on enzyme kinetics can be included as a separate term. Together with hierarchical regulation and metabolic regulation, this term explains the total flux change between two steady states. Surprisingly, the effect of the cultivation temperature on enzyme catalytic capacity, both directly through the Arrhenius effect and indirectly through adapted gene expression, is only a moderate contribution to the increased glycolytic flux for most enzymes. The changes in flux are therefore largely caused by changes in the interaction of the enzymes with substrates, products, and effectors.

Dynamic in vivo metabolome response of Saccharomyces cerevisiae to a stepwise perturbation of the ATP requirement for benzoate export

Although much information is available on in vitro role of ATP in regulation, the in vivo kinetics of reactions in which ATP plays a role are only partly known. In order to study such reactions, it is therefore necessary to study the role of ATP in vivo. This study presents an in vivo, targeted perturbation of the ATP flux in aerobic glucose-limited chemostat cultures of Saccharomyces cerevisiae, which was accomplished by transiently (20 min) changing the extracellular undissociated benzoic acid concentration via the pH of the culture. The performed pH shifts resulted in, within about 20 s, a 40% decrease (pH upshift) or a 23% increase (pH downshift) of the calculated ATP consumption rate while the specific glucose uptake rate did not change because of the glucose-limited condition. The pH upshift resulted in a strong decrease in the glycolytic and TCA cycle fluxes; carbon and energy balances indicated an increased flux toward storage carbohydrates. As expected, the pH downshift leads to the opposite effects. Overall, consistent responses were observed in the metabolic fluxes, the off gas concentrations of O(2) and CO(2) and intracellular metabolite concentrations, except for the concentrations of adenosine nucleotides which unexpectedly only showed minor dynamics. This demonstrates that our knowledge of the regulation of the ATP level, the storage metabolism, and central carbon metabolism of yeast is still incomplete. The new dynamic metabolite datasets obtained in this study will prove of great value in developing kinetic models.

Quantitative physiological study of the fast dynamics in the intracellular pH of Saccharomyces cerevisiae in response to glucose and ethanol pulses

Considering the effects of pH on many aspects of cell metabolism, such as its role in signaling processes and enzyme kinetics, it is indispensable to include the measurement of the dynamics of the intracellular pH, when studying the fast dynamic response of cells to perturbations. It has been shown previously that the intracellular pH rapidly drops following an increase in external glucose concentration [Kresnowati, M.T.A.P., Suarez-Mendez, C., Groothuizen, M.K., Van Winden, W.A., Heijnen, J.J., 2007. Measurement of fast dynamic intracellular pH in Saccharomyces cerevisiae using benzoic acid pulse. Biotechnol. Bioeng. 97, 86-98; Ramos, S., Balbin, M., Raposo, M., Valle, E., Pardo, L.A., 1989. The mechanism of intracellular acidification induced by glucose in Saccharomyces cerevisiae. J. Gen. Microbiol. 135, 2413-2422; Van Urk, H., Schipper, D., Breedveld, G.J., Mak, P.R., Scheffers, W.A., Van Dijken, J.P., 1989. Localization and kinetics of pyruvate-metabolizing enzymes in relation to aerobic alcoholic fermentation in Saccharomyces cerevisiae CBS 8066 and Candida utilis CBS 621. Biochim. Biophys. Acta 992(1), 78-86]. The mechanism for this fast intracellular acidification, however, has not been elucidated yet. This paper presents a metabolome-based analysis to reveal the physiological phenomena that cause the fast intracellular acidification following either a glucose pulse or an ethanol pulse to carbon-limited chemostat cultures of Saccharomyces cerevisiae. This quantitative study, which includes the determination of intracellular buffering capacity, the calculation of electric charge balance and the quantification of weak organic acid transport shows that none of the previously suggested mechanisms, i.e. increase in glucose phosphorylation and accumulation of CO(2), is sufficient to explain the measured decrease in intracellular pH following a glucose pulse.

A metabolome study of the steady-state relation between central metabolism, amino acid biosynthesis and penicillin production in Penicillium chrysogenum

The relation between central metabolism and the penicillin biosynthesis pathway in Penicillium chrysogenum was studied by manipulating the steady-state flux in both pathways. A high producing industrial strain was cultivated at a growth rate mu=0.05 h(-1) in glucose-limited chemostat cultures, both under penicillin-G producing and non-producing conditions. Non-producing conditions were accomplished in two ways: (1) by cultivation without addition of the side chain precursor phenylacetic acid and (2) by cultivation of a mutant strain which lost all copies of the gene cluster coding for the penicillin biosynthesis pathway. Manipulation of the fluxes through central metabolism was obtained by cultivation on either glucose or ethanol as sole carbon source. A positive relation was observed between metabolite concentrations and carbon flux in central metabolism. Furthermore, in many cases a positive relation was found between the concentrations of free amino acids and their direct precursors in central metabolism. This corresponds with control of the biosynthesis of these amino acids via feed back inhibition by the end product. With respect to the penicillin production pathway, the flux seems not influenced by two of the three precursor amino acids, namely alphaAAA and valine but is only influenced by cysteine, which requires a large NADPH supply, and the ATP level. An interesting observation is that the absence of penicillin production seems to stimulate storage metabolism (trehalose metabolism). This leads to the final conclusion that the penicillin production flux appears to be mostly influenced by the availability of energy and redox cofactors, where ATP is supposed to exert its influence at ACV-synthetase and NADPH at the cysteine level.

Measurement of fast dynamic intracellular pH in Saccharomyces cerevisiae using benzoic acid pulse

pH affects many processes on cell metabolism, such as enzyme kinetics. To enhance the understanding of the living cells, it is therefore indispensable to have a method to monitor the pH in living cells. To accomplish this, a dynamic intracellular pH measurement method applying low concentration benzoic acid pulse was developed. The method was thoroughly validated and successfully implemented for measuring fast dynamic intracellular pH of Saccharomyces cerevisiae in response to a glucose pulse perturbation performed in the BioSCOPE set-up. Fast drop in intracellular pH followed by partial alkalinization was observed following the pulse. The low concentration benzoic acid pulse which was implemented in the method avoids the undesirable effects that may be introduced by benzoic acid to cell metabolism.

Bioengineering novel in vitro metabolic pathways using synthetic biology

Huge numbers of enzymes have evolved in nature to function in aqueous environments at moderate temperatures and neutral pH. This gives us, in principle, the unique opportunity to construct multistep reaction systems of considerable catalytic complexity in vitro. However, this opportunity is rarely exploited beyond research scale, because such systems are difficult to assemble and to operate productively. Recent advances in DNA synthesis, genome engineering, high-throughput analytics, model-based analysis of biochemical systems and (semi-)rational protein engineering suggest that we have all the tools available to rationally design and efficiently operate such systems of enzymes, and finally harvest their potential for preparative syntheses.

Metabolome dynamic responses of Saccharomyces cerevisiae to simultaneous rapid perturbations in external electron acceptor and electron donor

Rapid perturbation experiments are highly relevant to elaborate the in vivo kinetics for mathematical models of metabolism, which are needed for selecting gene targets for metabolic engineering. Perturbations were applied to chemostat-cultivated biomass (D=0.05 h(-1), aerobic glucose/ethanol-limited) using the BioScope of Saccharomyces cerevisiae CEN. PK 113-7D over time span of 90 and 180 s. The availability of the external electron acceptor oxygen was decreased from fully aerobic to anaerobic conditions. It was observed that the changes in metabolome response under these conditions were limited to the pyruvate node. Acetaldehyde supply was used as an extra external electron acceptor during glucose perturbation under fully aerobic conditions. This had a strong effect on the metabolome dynamics and resulted in a significantly higher initial glycolytic flux. Dynamic response of the adenine nucleotides indicated that their behavior is not dictated by the glycolytic flux but is much more coupled to the cytosolic NADH/NAD(+) ratio through the equilibrium pool of fructose 1,6-bisphosphate and 2/3-phosphoglycerate. Also, the electron donor availability (glucose) was decreased. This did not result in significant changes in the concentrations of the glycolytic and tricarboxylic acid cycle metabolites, whereas the adenine nucleotides, especially ADP and AMP, showed the opposite response to that observed in a glucose pulse experiment. Surprisingly, trehalose was not mobilized in the time frame of 180 s.

13C-Labeled metabolic flux analysis of a fed-batch culture of elutriated Saccharomyces cerevisiae

This study addresses the question of whether observable changes in fluxes in the primary carbon metabolism of Saccharomyces cerevisiae occur between the different phases of the cell division cycle. To detect such changes by metabolic flux analysis, a 13C-labeling experiment was performed with a fed-batch culture inoculated with a partially synchronized cell population obtained through centrifugal elutriation. Such a culture exhibits dynamic changes in the fractions of cells in different cell cycle phases over time. The mass isotopomer distributions of free intracellular metabolites in central carbon metabolism were measured by liquid chromatography-mass spectrometry. For four time points during the culture, these distributions were used to obtain the best estimates for the metabolic fluxes. The obtained flux fits suggested that the optimally fitted split ratio for the pentose phosphate pathway changed by almost a factor of 2 up and down around a value of 0.27 during the experiment. Statistical analysis revealed that some of the fitted flux distributions for different time points were significantly different from each other, indicating that cell cycle-dependent variations in cytosolic metabolic fluxes indeed occurred.

Simultaneous determination of multiple intracellular metabolites in glycolysis, pentose phosphate pathway and tricarboxylic acid cycle by liquid chromatography-mass spectrometry

A highly selective and sensitive method for identification and quantification of intracellular metabolites involved in central carbon metabolism (including glycolysis, pentose phosphate pathway and tricarboxylic acid cycle) by means of liquid chromatography-tandem quadrupole mass spectrometry (LC-MS/MS) was developed. The volatile ion pair modifier tributylammonium acetate (TBAA) was employed in the mobile phase for simultaneously separation of 29 negatively charged compounds including sugar phosphates, nucleotides, and carboxylic acids on a common C18 reversed-phase column. Method validation results displayed that limits of detection (LODs) calculated according to DIN (German Institute for Standardization) 32645 are mostly below 60 nM, only with the exception of pyruvate and malate. The calibration curves showed excellent linearity mainly over three orders of magnitude with correlation coefficients R(2)>0.9982. This LC-MS/MS method was successfully applied to determine these metabolites in cell extracts of Escherichia coli. Most of the intracellular metabolites were found within the detection range and the relative standard deviations of the measurements were smaller than 5.65% (n=5) for a cell extract sample.