Biomedical subjects

Joseph J Heijnen

Publications and source records attributed to Joseph J Heijnen.

At least 19 recordsLinked to original sources

PubMed2006

A method for estimation of elasticities in metabolic networks using steady state and dynamic metabolomics data and linlog kinetics.

BACKGROUND: Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (dis)functioning of living cells. So far dynamic metabolic models generally have been based on mechanistic rate equations which often contain so many parameters that their identifiability from experimental data forms a serious problem. Recently, approximative rate equations, based on the linear logarithmic (linlog) format have been proposed as a suitable alternative with fewer parameters. RESULTS: In this paper we present a method for estimation of the kinetic model parameters, which are equal to the elasticities defined in Metabolic Control Analysis, from metabolite data obtained from dynamic as well as steady state perturbations, using the linlog kinetic format. Additionally, we address the question of parameter identifiability from dynamic perturbation data in the presence of noise. The method is illustrated using metabolite data generated with a dynamic model of the glycolytic pathway of Saccharomyces cerevisiae based on mechanistic rate equations. Elasticities are estimated from the generated data, which define the complete linlog kinetic model of the glycolysis. The effect of data noise on the accuracy of the estimated elasticities is presented. Finally, identifiable subset of parameters is determined using information on the standard deviations of the estimated elasticities through Monte Carlo (MC) simulations. CONCLUSION: The parameter estimation within the linlog kinetic framework as presented here allows the determination of the elasticities directly from experimental data from typical dynamic and/or steady state experiments. These elasticities allow the reconstruction of the full kinetic model of Saccharomyces cerevisiae, and the determination of the control coefficients. MC simulations revealed that certain elasticities are potentially unidentifiable from dynamic data only. Addition of steady state perturbation of enzyme activities solved this problem.

Algorithms↗

PubMed2006

Characterization of an experimental miniature bioreactor for cellular perturbation studies.

A mini bioreactor (3.0 mL volume) has been developed and shown to be a versatile tool for rapidly screening and quantifying the response of organisms on environmental perturbations. The mini bioreactor is essentially a plug flow device transformed into a well-mixed reactor by a recycle flow of the broth. The gas and liquid phases are separated by a silicone membrane. Dynamic mass transfer experiments were performed to determine the mass transfer capacities for oxygen and carbon dioxide. The mass transfer coefficients for oxygen and carbon dioxide were found to be 1.55 +/- 0.17 x 10(-5) m/s and 4.52 +/- 0.60 x 10(-6) m/s, respectively. Cultivation experiments with the 3.0 mL bioreactor show that (i) it can maintain biomass in the same physiological state as the 4.0 L lab scale bioreactor, (ii) reproducible perturbation experiments such as changing substrate uptake rate can be readily performed and the physiological response monitored quantitatively in terms of the O2 and CO2 uptake and production rates.

Biodegradation, Environmental↗

PubMed2006

Metabolic flux analysis of a glycerol-overproducing Saccharomyces cerevisiae strain based on GC-MS, LC-MS and NMR-derived C-labelling data.

This study focuses on unravelling the carbon and redox metabolism of a previously developed glycerol-overproducing Saccharomyces cerevisiae strain with deletions in the structural genes encoding triosephosphate isomerase (TPI1), the external mitochondrial NADH dehydrogenases (NDE1 and NDE2) and the respiratory chain-linked glycerol-3-phosphate dehydrogenase (GUT2). Two methods were used for analysis of metabolic fluxes: metabolite balancing and (13)C-labelling-based metabolic flux analysis. The isotopic enrichment of intracellular primary metabolites was measured both directly (liquid chromatography-MS) and indirectly through proteinogenic amino acids (nuclear magnetic resonance and gas chromatography-MS). Because flux sensitivity around several important metabolic nodes proved to be dependent on the applied technique, the combination of the three (13)C quantification techniques generated the most accurate overall flux pattern. When combined, the measured conversion rates and (13)C-labelling data provided evidence that a combination of assimilatory metabolism and pentose phosphate pathway activity diverted some of the carbon away from glycerol formation. Metabolite balancing indicated that this results in excess cytosolic NADH, suggesting the presence of a cytosolic NADH sink in addition to those that were deleted. The exchange flux of four-carbon dicarboxylic acids across the mitochondrial membrane, as measured by the (13)C-labelling data, supports a possible role of a malate/aspartate or malate/oxaloacetate redox shuttle in the transfer of these redox equivalents from the cytosol to the mitochondrial matrix.

Carbon↗

PubMed2006

Microbial metabolomics: past, present and future methodologies.

Microbial metabolomics has received much attention in recent years mainly because it supports and complements a wide range of microbial research areas from new drug discovery efforts to metabolic engineering. Broadly, the term metabolomics refers to the comprehensive (qualitative and quantitative) analysis of the complete set of all low molecular weight metabolites present in and around growing cells at a given time during their growth or production cycle. This review focuses on the past, current and future development of various experimental protocols in the rapid developing area of metabolomics in the ongoing quest to reliably quantify microbial metabolites formed under defined physiological conditions. These developments range from rapid sample collection, instant quenching of microbial metabolic activity, extraction of the relevant intracellular metabolites as well as quantification of these metabolites using enzyme based and or modern high tech hyphenated analytical protocols, mainly chromatographic techniques coupled to mass spectrometry (LC-MS(n), GC-MS(n), CE-MS(n)), where n indicates the number of tandem mass spectrometry, and nuclear magnetic resonance spectroscopy (NMR).

Bacteria↗

PubMed2006

Cytosolic NADPH metabolism in penicillin-G producing and non-producing chemostat cultures of Penicillium chrysogenum.

This study addresses the relation between NADPH supply and penicillin synthesis, by comparing the flux through the oxidative branch of the pentose phosphate pathway (PPP; the main source of cytosolic NADPH) in penicillin-G producing and non-producing chemostat cultures of Penicillium chrysogenum. The fluxes through the oxidative part of the PPP were determined using the recently introduced gluconate-tracer method. Significantly higher oxidative PPP fluxes were observed in penicillin-G producing chemostat cultures, indicating that penicillin production puts a major burden on the supply of cytosolic NADPH. To our knowledge this is the first time direct experimental proof is presented for the causal relationship between penicillin production and NADPH supply. Additional insight in the metabolism of P. chrysogenum was obtained by comparing the PPP fluxes from the gluconate-tracer experiment to oxidative PPP fluxes derived via metabolic flux analysis, using different assumptions for the stoichiometry of NADPH consumption and production.

Anti-Bacterial Agents↗

PubMed2006

In vivo kinetics with rapid perturbation experiments in Saccharomyces cerevisiae using a second-generation BioScope.

We present a robust second-generation BioScope: a system for continuous perturbation experiments. Firstly, the BioScope design parameters (i.e., pressure drop, overall oxygen (O2) and carbon dioxide (CO2) mass transfer, mean residence time distribution and plug flow characteristics) were evaluated. The average overall mass transfer coefficients were estimated to be 1.8E-5 m s(-1) for O2 and 0.34E-5 m s(-1) for CO2. It was determined that the O2/CO2 permeable membrane accounted for 75% and 95% of the overall resistance for O2 and CO2, respectively. The Peclet number (Pe) of the system was found to be >500 for liquid flow rates between 1 and 4 ml min(-1), ensuring plug flow characteristics. Secondly, steady-state intracellular metabolite concentrations obtained using direct rapid sampling from the fermentor were compared with those obtained by rapid sampling via the pre-perturbation sample port of the BioScope. With both methods the same metabolite levels were obtained. Thirdly, glucose perturbation experiments were carried out directly in the fermentor as well as in the BioScope, whereby steady-state Saccharomyces cerevisiae cells from a glucose/ethanol limited chemostat were perturbed by increasing the extracellular glucose concentration from 0.11 to 2.8 mM. Intracellular and extracellular metabolite levels were measured within a time window of 180 s. It was observed that the dynamic metabolite concentration profiles obtained from both perturbations were nearly the same, with the exception of the C4 metabolites of the TCA cycle, which might be due to differences in culture age.

Bioreactors↗

PubMed2006

In situ product recovery (ISPR) by crystallization: basic principles, design, and potential applications in whole-cell biocatalysis.

The removal of inhibiting or degrading product from a bioreactor as soon as the product is formed is an important issue in industrial bioprocess development. In this review, the potential of crystallization as an in situ product removal (ISPR) technique for the biocatalytic production of crystalline compounds is discussed. The emphasis of this review is on the current status of crystalline product formation by metabolically active cells for application in fine-chemicals production. Examples of relevant biocatalytic conversions are summarized, and some basic process options are discussed. Furthermore, a case study is presented in which two conceptual process designs are compared. In one process, product formation and crystallization are integrated by applying ISPR, whereas a second, nonintegrated process is based on a known conventional process equivalent for the production of 6R-dihydro-oxoisophorone. The comparison indicates that employing ISPR leads to significant advantages over the nonintegrated case in terms of increased productivity and yield with a corresponding decrease in the number of downstream processing steps, as well as in the quantity of waste streams. This leads to an economically more interesting process alternative. Finally, a general outlook on the various research aspects of ISPR by crystallization is given.

Biological Products↗

PubMed2006

13C-labeled gluconate tracing as a direct and accurate method for determining the pentose phosphate pathway split ratio in Penicillium chrysogenum.

In this study we developed a new method for accurately determining the pentose phosphate pathway (PPP) split ratio, an important metabolic parameter in the primary metabolism of a cell. This method is based on simultaneous feeding of unlabeled glucose and trace amounts of [U-13C]gluconate, followed by measurement of the mass isotopomers of the intracellular metabolites surrounding the 6-phosphogluconate node. The gluconate tracer method was used with a penicillin G-producing chemostat culture of the filamentous fungus Penicillium chrysogenum. For comparison, a 13C-labeling-based metabolic flux analysis (MFA) was performed for glycolysis and the PPP of P. chrysogenum. For the first time mass isotopomer measurements of 13C-labeled primary metabolites are reported for P. chrysogenum and used for a 13C-based MFA. Estimation of the PPP split ratio of P. chrysogenum at a growth rate of 0.02 h(-1) yielded comparable values for the gluconate tracer method and the 13C-based MFA method, 51.8% and 51.1%, respectively. A sensitivity analysis of the estimated PPP split ratios showed that the 95% confidence interval was almost threefold smaller for the gluconate tracer method than for the 13C-based MFA method (40.0 to 63.5% and 46.0 to 56.5%, respectively). From these results we concluded that the gluconate tracer method permits accurate determination of the PPP split ratio but provides no information about the remaining cellular metabolism, while the 13C-based MFA method permits estimation of multiple fluxes but provides a less accurate estimate of the PPP split ratio.

Carbon Isotopes↗

PubMed2006

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

The in vivo kinetics in Saccharomyces cerevisiae CEN.PK 113-7D was evaluated during a 300-second transient period after applying a glucose pulse to an aerobic, carbon-limited chemostat culture. We quantified the responses of extracellular metabolites, intracellular intermediates in primary metabolism, intracellular free amino acids, and in vivo rates of O(2) uptake and CO(2) evolution. With these measurements, dynamic carbon, electron, and ATP balances were set up to identify major carbon, electron, and energy sinks during the postpulse period. There were three distinct metabolic phases during this time. In phase I (0 to 50 seconds after the pulse), the carbon/electron balances closed up to 85%. The accumulation of glycolytic and storage compounds accounted for 60% of the consumed glucose, caused an energy depletion, and may have led to a temporary decrease in the anabolic flux. In phase II (50 to 150 seconds), the fermentative metabolism gradually became the most important carbon/electron sink. In phase III (150 to 300 seconds), 29% of the carbon uptake was not identified in the measurements, and the ATP balance had a large surplus. These results indicate an increase in the anabolic flux, which is consistent with macroscopic balances of extracellular fluxes and the observed increase in CO(2) evolution associated with nonfermentative metabolism. The identified metabolic processes involving major carbon, electron, and energy sinks must be taken into account in in vivo kinetic models based on short-term dynamic metabolome responses.

Adenosine Triphosphate↗

PubMed2005

In vivo kinetics of primary metabolism in Saccharomyces cerevisiae studied through prolonged chemostat cultivation.

In this study, prolonged chemostat cultivation is applied to investigate in vivo enzyme kinetics of Saccharomyces cerevisiae. S. cerevisiae was grown in carbon-limited aerobic chemostats for 70-95 generations, during which multiple steady states were observed, characterized by constant intracellular fluxes but significant changes in intracellular metabolite concentrations and enzyme capacities. We provide evidence for two relevant kinetic mechanisms for sustaining constant fluxes: in vivo near-equilibrium of reversible reactions and tight regulation of irreversible reactions by coordinated changes of metabolic effectors. Using linear-logarithmic kinetics, we illustrate that these multiple steady-state measurements provide linear constraints between elasticity parameters instead of their absolute values. Upon perturbation by a glucose pulse, glucose uptake and ethanol excretion in prolonged cultures were remarkably lower, compared to a reference culture perturbed at 10 generations. Metabolome measurements during the transient indicate that the differences might be due to a reduced ATP regeneration capacity in prolonged cultures.

Adaptation, Physiological↗

PubMed2005

Approximative kinetic formats used in metabolic network modeling.

An overview is presented of the different approximative enzyme kinetic formats that have been proposed for use in metabolic modeling studies. It is considered that the following four general properties are relevant for approximative kinetics: the rate must be proportional to enzyme level; at high metabolite concentrations, there is downward concave behavior of rate versus concentration; the number of kinetic parameters should be as small as possible; analytical solutions of steady-state network balances are desirable. Six different approximative kinetic formats are evaluated (linear, logarithmic-linear, power law GMA, power law S-systems, thermokinetic, linear-logarithmic) and it is concluded that only the recently proposed linear-logarithmic approach combines all desired properties and therefore seems a most appropriate approximate kinetic format.

Algorithms↗

PubMed2005

Dynamics of intracellular metabolites of glycolysis and TCA cycle during cell-cycle-related oscillation in Saccharomyces cerevisiae.

In the present work LC-MS/MS was applied to measure the concentrations of intermediates of glycolysis and TCA cycle during autonomous, cell-cycle synchronized oscillations in aerobic, glucose-limited chemostat cultures of Saccharomyces cerevisiae. This study complements previously reported oscillations in carbon dioxide production rate, intracellular concentrations of trehalose and various free amino acids, and extracellular acetate and pyruvate in the same culture. Of the glycolytic intermediates, fructose 1,6-bisphosphate, 2- and 3-phosphoglycerate, and phosphoenolpyruvate show the most pronounced oscillatory behavior, the latter three compounds oscillating out of phase with the former. This agrees with previously observed metabolic control by phosphofructokinase and pyruvate kinase. Although individually not clearly oscillating, several intermediates of the TCA cycle, i.e., alpha-ketoglutarate, succinate, fumarate, and malate, exhibited increasing concentration during the cell cycle phase with high carbon flux through glycolysis and TCA cycle. The average mass action ratios of beta-phosphoglucomutase and fumarase agreed well with previously determined in vitro equilibrium constants. Minor differences resulted for phosphoglucose isomerase and enolase. Together with the observed close correlation of the pool sizes of the involved metabolites, this might indicate that, in vivo, these reactions are operating close to equilibrium, whereby care must be taken due to possible differences between in vivo and in vitro conditions. Combining the data with previously determined intracellular amino acid levels from the same culture, a few clear correlations between catabolism and anabolism could be identified: phosphoglycerate/serine and alpha-ketoglutarate/lysine exhibited correlated oscillatory behavior, albeit with different phase shifts. Oscillations in intracellular amino acids might therefore be, at least partly, following oscillations of their anabolic precursors.

Cell Cycle↗

PubMed2005

Quantitative analysis of the microbial metabolome by isotope dilution mass spectrometry using uniformly 13C-labeled cell extracts as internal standards.

A novel method was developed for the quantitative analysis of the microbial metabolome using a mixture of fully uniformly (U) (13)C-labeled metabolites as internal standard (IS) in the metabolite extraction procedure the subsequent liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) analysis. This mixture of fully U (13)C-labeled metabolites was extracted from biomass of Saccharomyces cerevisiae cultivated in a fed-batch fermentation on fully U (13)C-labeled substrates. The obtained labeled cell extract contained, in principle, the whole yeast metabolome, allowing the quantification of any intracellular metabolite of interest in S. cerevisiae. We have applied the labeled cell extract as IS in the analysis of glycolytic and tricarboxylic acid (TCA) cycle intermediates in S. cerevisiae sampled in both steady-state and transient conditions following a glucose pulse. The use of labeled IS effectively reduced errors due to variations occurring in the analysis and sample processing. As a result, the linearity of calibration lines and the precision of measurements were significantly improved. Coextraction of the labeled cell extract with the samples also eliminates the need to perform elaborate recovery checks for each metabolite to be analyzed. In conclusion, the method presented leads to less workload, more robustness, and a higher precision in metabolome analysis.

Carbon Isotopes↗

PubMed2005

Metabolic-flux analysis of Saccharomyces cerevisiae CEN.PK113-7D based on mass isotopomer measurements of (13)C-labeled primary metabolites.

Metabolic-flux analyses in microorganisms are increasingly based on (13)C-labeling data. In this paper a new approach for the measurement of (13)C-label distributions is presented: rapid sampling and quenching of microorganisms from a cultivation, followed by extraction and detection by liquid chromatography-mass spectrometry of free intracellular metabolites. This approach allows the direct assessment of mass isotopomer distributions of primary metabolites. The method is applied to the glycolytic and pentose phosphate pathways of Saccharomyces cerevisiae strain CEN.PK113-7D grown in an aerobic, glucose-limited chemostat culture. Detailed investigations of the measured mass isotopomer distributions demonstrate the accuracy and information-richness of the obtained data. The mass fractions are fitted with a cumomer model to yield the metabolic fluxes. It is estimated that 24% of the consumed glucose is catabolized via the pentose phosphate pathway. Furthermore, it is found that turnover of storage carbohydrates occurs. Inclusion of this turnover in the model leads to a large confidence interval of the estimated split ratio.

Carbon Isotopes↗

PubMed2005

Changes in the metabolome of Saccharomyces cerevisiae associated with evolution in aerobic glucose-limited chemostats.

The effect of culture age on intra- and extracellular metabolite levels as well as on in vitro determined specific activities of enzymes of central carbon metabolism was investigated during evolution for over 90 generations of Saccharomyces cerevisiae CEN.PK 113-7D in an aerobic glucose/ethanol-limited chemostat at a specific dilution rate of 0.052 h(-1). It was found that the fluxes of consumed (O2, glucose/ethanol) and secreted compounds (CO2) did not change significantly during the entire cultivation period. However, morphological changes were observed, leading to an increased cellular surface area. During 90 generations of chemostat growth not only the residual glucose concentration decreased, also the intracellular concentrations of trehalose, glycolytic intermediates, TCA cycle intermediates and amino acids were found to have decreased with a factor 5-10. The only exception was glyoxylate which showed a fivefold increase in concentration. In addition to this the specific activities of most glycolytic enzymes also decreased by a factor 5-10 during long-term cultivation. Exceptions to this were hexokinase, phosphofructokinase, pyruvate kinase and 6-phosphogluconate dehydrogenase of which the activities remained unchanged. Furthermore, the concentrations of the adenylate nucleotides as well as the energy charge of the cells did not change in a significant manner. Surprisingly, the specific activities of glucose-6-phosphate dehydrogenase (G6PDH), malate synthase (MS) and isocitrate lyase (ICL) increased significantly during 90 generations of chemostat cultivation. These changes seem to indicate a pattern where metabolic overcapacities (for reversible reactions) and storage pools (trehalose, high levels of amino acids and excess protein in enzymes) are lost during the evolution period. The driving force is proposed to be a growth advantage in the absence of these metabolic overcapacities.

Adaptation, Physiological↗

PubMed2005

Determination of elasticities, concentration and flux control coefficients from transient metabolite data using linlog kinetics.

This paper presents a practical approach to estimate the kinetic parameters of a metabolic network from in vivo kinetics experiments. This method is based on the linlog kinetics format (Visser and Heijnen, 2003, Metab. Eng. 5(3), 164-176; Wu et al., 2004, Eur. J. Biochem. 271, 3348-3359), of which the kinetic parameters, called elasticities, are estimated by an iterative linear optimization followed by non-linear optimization, from transient metabolite concentration data which are directly obtainable from rapid pulse experiments. In this way, not only the parameters are estimated but also a full kinetic model, based on linlog kinetics, is developed. The obtained elasticities also allow immediate calculation of all control coefficients. As an in silico case study, the estimation of elasticities of a linear pathway is presented. The method is shown to be able to estimate the elasticities quite accurately and to be robust toward errors in the metabolite data originating from sampling and measurement inaccuracy. The method allows experimental redesign to get more accurate estimated parameters and accommodates various types of experimentally applied disturbances in the pathway: changes in independent metabolites, dependent metabolites or enzyme levels/activities.

Computer Simulation↗

PubMed2005

Application of metabolome data in functional genomics: a conceptual strategy.

A gene with yet unknown physiological function can be studied by changing its expression level followed by analysis of the resulting phenotype. This type of functional genomics study can be complicated by the occurrence of 'silent mutations', the phenotypes of which are not easily observable in terms of metabolic fluxes (e.g., the growth rate). Nevertheless, genetic alteration may give rise to significant yet complicated changes in the metabolome. We propose here a conceptual functional genomics strategy based on microbial metabolome data, which identifies changes in in vivo enzyme activities in the mutants. These predicted changes are used to formulate hypotheses to infer unknown gene functions. The required metabolome data can be obtained solely from high-throughput mass spectrometry analysis, which provides the following in vivo information: (1) the metabolite concentrations in the reference and the mutant strain; (2) the metabolic fluxes in both strains and (3) the enzyme kinetic parameters of the reference strain. We demonstrate in silico that changes in enzyme activities can be accurately predicted by this approach, even in 'silent mutants'.

Genome, Fungal↗

PubMed2005

Revisiting the 13C-label distribution of the non-oxidative branch of the pentose phosphate pathway based upon kinetic and genetic evidence.

The currently applied reaction structure in stoichiometric flux balance models for the nonoxidative branch of the pentose phosphate pathway is not in accordance with the established ping-pong kinetic mechanism of the enzymes transketolase (EC 2.2.1.1) and transaldolase (EC 2.2.1.2). Based upon the ping-pong mechanism, the traditional reactions of the nonoxidative branch of the pentose phosphate pathway are replaced by metabolite specific, reversible, glycolaldehyde moiety (C(2)) and dihydroxyacetone moiety (C(3)) fragments producing and consuming half-reactions. It is shown that a stoichiometric model based upon these half-reactions is fundamentally different from the currently applied stoichiometric models with respect to the number of independent C(2) and C(3) fragment pools in the pentose phosphate pathway and can lead to different label distributions for (13)C-tracer experiments. To investigate the actual impact of the new reaction structure on the estimated flux patterns within a cell, mass isotopomer measurements from a previously published (13)C-based metabolic flux analysis of Saccharomyces cerevisiae were used. Different flux patterns were found. From a genetic point of view, it is well known that several micro-organisms, including Escherichia coli and S. cerevisiae, contain multiple genes encoding isoenzymes of transketolase and transaldolase. However, the extent to which these gene products are also actively expressed remains unknown. It is shown that the newly proposed stoichiometric model allows study of the effect of isoenzymes on the (13)C-label distribution in the nonoxidative branch of the pentose phosphate pathway by extending the half-reaction based stoichiometric model with two distinct transketolase enzymes instead of one. Results show that the inclusion of isoenzymes affects the ensuing flux estimates.

Carbon Isotopes↗