Network identification and flux quantification in the central metabolism of Saccharomyces cerevisiae under different conditions of glucose repression

Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks

BACKGROUND

Uncovering the operating principles underlying cellular processes by using 'omics' data is often a difficult task due to the high-dimensionality of the solution space that spans all interactions among the bio-molecules under consideration. A rational way to overcome this problem is to use the topology of bio-molecular interaction networks in order to constrain the solution space. Such approaches systematically integrate the existing biological knowledge with the 'omics' data.

RESULTS

Here we introduce a hypothesis-driven method that integrates bio-molecular network topology with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription Factors, Reporter Proteins and Reporter Complexes, and use this to decipher the logic of regulatory circuits playing a key role in yeast glucose repression and human diabetes.

CONCLUSION

Reporter Features offer the opportunity to identify regulatory hot-spots in bio-molecular interaction networks that are significantly affected between or across conditions. Results of the Reporter Feature analysis not only provide a snapshot of the transcriptional regulatory program but also are biologically easy to interpret and provide a powerful way to generate new hypotheses. Our Reporter Features analyses of yeast glucose repression and human diabetes data brings hints towards the understanding of the principles of transcriptional regulation controlling these two important and potentially closely related systems.

Elucidation of an alternate isoleucine biosynthesis pathway in Geobacter sulfurreducens

The central metabolic model for Geobacter sulfurreducens included a single pathway for the biosynthesis of isoleucine that was analogous to that of Escherichia coli, in which the isoleucine precursor 2-oxobutanoate is generated from threonine. 13C labeling studies performed in G. sulfurreducens indicated that this pathway accounted for a minor fraction of isoleucine biosynthesis and that the majority of isoleucine was instead derived from acetyl-coenzyme A and pyruvate, possibly via the citramalate pathway. Genes encoding citramalate synthase (GSU1798), which catalyzes the first dedicated step in the citramalate pathway, and threonine ammonia-lyase (GSU0486), which catalyzes the conversion of threonine to 2-oxobutanoate, were identified and knocked out. Mutants lacking both of these enzymes were auxotrophs for isoleucine, whereas single mutants were capable of growth in the absence of isoleucine. Biochemical characterization of the single mutants revealed deficiencies in citramalate synthase and threonine ammonia-lyase activity. Thus, in G. sulfurreducens, 2-oxobutanoate can be synthesized either from citramalate or threonine, with the former being the main pathway for isoleucine biosynthesis. The citramalate synthase of G. sulfurreducens constitutes the first characterized member of a phylogenetically distinct clade of citramalate synthases, which contains representatives from a wide variety of microorganisms.

Impact of systems biology on metabolic engineering ofSaccharomyces cerevisiae

Industrial biotechnology is a rapidly growing field. With the increasing shift towards a bio-based economy, there is rising demand for developing efficient cell factories that can produce fuels, chemicals, pharmaceuticals, materials, nutraceuticals, and even food ingredients. The yeast Saccharomyces cerevisiae is extremely well suited for this objective. As one of the most intensely studied eukaryotic model organisms, a rich density of knowledge detailing its genetics, biochemistry, physiology, and large-scale fermentation performance can be capitalized upon to enable a substantial increase in the industrial application of this yeast. Developments in genomics and high-throughput systems biology tools are enhancing one's ability to rapidly characterize cellular behaviour, which is valuable in the field of metabolic engineering where strain characterization is often the bottleneck in strain development programmes. Here, the impact of systems biology on metabolic engineering is reviewed and perspectives on the role of systems biology in the design of cell factories are given.

Predicting biological system objectives de novo from internal state measurements

Background

Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For example, methods are emerging to engineer cells to optimally produce byproducts of commercial value, such as bioethanol, as well as molecular compounds for disease therapy. Flux balance analysis (FBA) is an optimization framework that aids in this interrogation by generating predictions of optimal flux distributions in cellular networks. Critical features of FBA are the definition of a biologically relevant objective function (e.g., maximizing the rate of synthesis of biomass, a unit of measurement of cellular growth) and the subsequent application of linear programming (LP) to identify fluxes through a reaction network. Despite the success of FBA, a central remaining challenge is the definition of a network objective with biological meaning.

Results

We present a novel method called Biological Objective Solution Search (BOSS) for the inference of an objective function of a biological system from its underlying network stoichiometry as well as experimentally-measured state variables. Specifically, BOSS identifies a system objective by defining a putative stoichiometric "objective reaction," adding this reaction to the existing set of stoichiometric constraints arising from known interactions within a network, and maximizing the putative objective reaction via LP, all the while minimizing the difference between the resultant in silico flux distribution and available experimental (e.g., isotopomer) flux data. This new approach allows for discovery of objectives with previously unknown stoichiometry, thus extending the biological relevance from earlier methods. We verify our approach on the well-characterized central metabolic network of Saccharomyces cerevisiae.

Conclusion

We illustrate how BOSS offers insight into the functional organization of biochemical networks, facilitating the interrogation of cellular design principles and development of cellular engineering applications. Furthermore, we describe how growth is the best-fit objective function for the yeast metabolic network given experimentally-measured fluxes.

An elementary metabolite unit (EMU) based method of isotopically nonstationary flux analysis

Nonstationary metabolic flux analysis (NMFA) is at present a very computationally intensive exercise, especially for large reaction networks. We applied elementary metabolite unit (EMU) theory to NMFA, dramatically reducing computational difficulty. We also introduced block decoupling, a new method that systematically and comprehensively divides EMU systems of equations into smaller subproblems to further reduce computational difficulty. These improvements led to a 5000-fold reduction in simulation times, enabling an entirely new and more complicated set of problems to be analyzed with NMFA. We simulated a series of nonstationary and stationary GC/MS measurements for a large E. coli network that was then used to estimate parameters and their associated confidence intervals. We found that fluxes could be successfully estimated using only nonstationary labeling data and external flux measurements. Addition of near-stationary and stationary time points increased the precision of most parameters. Contrary to prior reports, the precision of nonstationary estimates proved to be comparable to the precision of estimates based solely on stationary data. Finally, we applied EMU-based NMFA to experimental nonstationary measurements taken from brown adipocytes and successfully estimated fluxes and some metabolite concentrations. By using NFMA instead of traditional MFA, the experiment required only 6 h instead of 50 (the time necessary for most metabolite labeling to reach 99% of isotopic steady state).

Oleic acid delays and modulates the transition from respiratory to fermentative metabolism in Saccharomyces cerevisiae after exposure to glucose excess

This work aimed to study the transition from respiratory to fermentative metabolism in Saccharomyces cerevisiae CEN.PK 113-7D and more specifically to evaluate the implication of the acetyl-coenzymeA-derived carbon transport from cytosol to mitochondria in the onset of the metabolic shift. The strategy consisted in introducing, during aerobic glucose-limited chemostat (D = 0.16 h(-1)), [corrected] a local perturbation around the step to be studied by the addition of cosubstrate and in analyzing the consequences of such a perturbation on the metabolic transition. Oleic acid and L: -carnitine were among the tested cosubstrates because they were known to stimulate enzymes implicated in the acetyl-coenzymeA transport between the different cell compartments, such as the carnitine acetyl transferases. The metabolic transition was then comparatively quantified in sole glucose and in glucose/oleic acid chemostats in presence/absence of L: -carnitine after a pulse of glucose. Feeding the culture with oleic acid (D (ole) = 0.0041 and 0.0073 h(-1)) [corrected] led to a delay in the onset of the metabolic shift (up to 15 min), a 33% decrease in the ethanol production and a redirection of the carbon flux toward biomass production. The data clearly showed a modulation of the carbon distribution among respiration and fermentation, in favor of a decrease in the "short-term" Crabtree effect by the oleic acid.

Identification of flux regulation coefficients from elementary flux modes: A systems biology tool for analysis of metabolic networks

Within a metabolic network, the elementary flux modes enables a unique description of different operations of the network. Thus, the metabolic fluxes can be specified as convex combinations of the elementary flux modes. Here, we describe an approach to identify the set of elementary flux modes that operates in a given metabolic network through the use of measurements of macroscopic fluxes, that is, fluxes in and out of the cell. Besides enabling estimation of the metabolic fluxes, the parameters of the linear combinations of the elementary flux modes provide valuable physiological information; we call these parameters flux regulation coefficients (FRCs). These coefficients indicate which enzyme subsets are important at different growth conditions. We demonstrate how FRCs can be used to map the operation of the metabolic network of the yeast Saccharomyces sp. under different growth conditions.

The topology of metabolic isotope labeling networks

Background

Metabolic Flux Analysis (MFA) based on isotope labeling experiments (ILEs) is a widely established tool for determining fluxes in metabolic pathways. Isotope labeling networks (ILNs) contain all essential information required to describe the flow of labeled material in an ILE. Whereas recent experimental progress paves the way for high-throughput MFA, large network investigations and exact statistical methods, these developments are still limited by the poor performance of computational routines used for the evaluation and design of ILEs. In this context, the global analysis of ILN topology turns out to be a clue for realizing large speedup factors in all required computational procedures.

Results

With a strong focus on the speedup of algorithms the topology of ILNs is investigated using graph theoretic concepts and algorithms. A rigorous determination of all cyclic and isomorphic subnetworks, accompanied by the global analysis of ILN connectivity is performed. Particularly, it is proven that ILNs always brake up into a large number of small strongly connected components (SCCs) and, moreover, there are natural isomorphisms between many of these SCCs. All presented techniques are universal, i.e. they do not require special assumptions on the network structure, bidirectionality of fluxes, measurement configuration, or label input. The general results are exemplified with a practically relevant metabolic network which describes the central metabolism of E. coli comprising 10390 isotopomer pools.

Conclusion

Exploiting the topological features of ILNs leads to a significant speedup of all universal algorithms for ILE evaluation. It is proven in theory and exemplified with the E. coli example that a speedup factor of about 1000 compared to standard algorithms is achieved. This widely opens the door for new high performance algorithms suitable for high throughput applications and large ILNs. Moreover, for the first time the global topological analysis of ILNs allows to comprehensively describe and understand the general patterns of label flow in complex networks. This is an invaluable tool for the structural design of new experiments and the interpretation of measured data.

Bacillus megaterium—from simple soil bacterium to industrial protein production host

Bacillus megaterium has been industrially employed for more than 50 years, as it possesses some very useful and unusual enzymes and a high capacity for the production of exoenzymes. It is also a desirable cloning host for the production of intact proteins, as it does not possess external alkaline proteases and can stably maintain a variety of plasmid vectors. Genetic tools for this species include transducing phages and several hundred mutants covering the processes of biosynthesis, catabolism, division, sporulation, germination, antibiotic resistance, and recombination. The seven plasmids of B. megaterium strain QM B1551 contain several unusual metabolic genes that may be useful in bioremediation. Recently, several recombinant shuttle vectors carrying different strong inducible promoters and various combinations of affinity tags for simple protein purification have been constructed. Leader sequences-mediated export of affinity-tagged proteins into the growth medium was made possible. These plasmids are commercially available. For a broader application of B. megaterium in industry, sporulation and protease-deficient as well as UV-sensitive mutants were constructed. The genome sequence of two different strains, plasmidless DSM319 and QM B1551 carrying seven natural plasmids, is now available. These sequences allow for a systems biotechnology optimization of the production host B. megaterium. Altogether, a "toolbox" of hundreds of genetically characterized strains, genetic methods, vectors, hosts, and genomic sequences make B. megaterium an ideal organism for industrial, environmental, and experimental applications.

Biological impacts and context of network theory

Many complex systems can be represented and analyzed as networks, and examples that have benefited from this approach span the natural sciences. For instance, we now know that systems as disparate as the World Wide Web, the Internet, scientific collaborations, food webs, protein interactions and metabolism all have common features in their organization, the most salient of which are their scale-free connectivity distributions and their small-world behavior. The recent availability of large-scale datasets that span the proteome or metabolome of an organism have made it possible to elucidate some of the organizational principles and rules that govern their function,robustness and evolution. We expect that combining the currently separate layers of information from gene regulatory networks, signal transduction networks, protein interaction networks and metabolic networks will dramatically enhance our understanding of cellular function and dynamics.

Physiology of the yeastKluyveromyces marxianusduring batch and chemostat cultures with glucose as the sole carbon source

Growth, substrate consumption, metabolite formation, biomass composition and respiratory parameters of Kluyveromyces marxianus ATCC 26548 were determined during aerobic batch and chemostat cultivations, using mineral medium with glucose as the sole carbon source, at 30 degrees C and pH 5.0. Carbon balances closed within 95-101% in all experiments. A maximum specific growth rate of 0.56 h(-1), a biomass yield on glucose of 0.51 g g(-1), and a maximum specific consumption of oxygen of 11.1 mmol g(-1) h(-1) were obtained during batch cultures. The concentration of excreted metabolites was very low at the culture conditions applied, representing 6% of the consumed carbon at most. Acetate and pyruvate were excreted to a larger extent than ethanol under the batch conditions, and the protein content accounted for 54.6% of the biomass dry weight. Steady states were obtained during chemostats at dilution rates of 0.1, 0.25 and 0.5 h(-1). At the two former dilution rates, cells grew at carbon limitation and the biomass yield on glucose was similar to that obtained under the batch conditions. Metabolite formation was rather low, accounting for a total of 0.005 C-mol C-mol(-1) substrate. At 0.5 h(-1), although the biomass yield on glucose was similar to the value obtained under the above-mentioned conditions, the cultivation was not under carbon limitation. Under this condition, 2-oxoglutarate, acetate, pyruvate and ethanol were the prevalent metabolites excreted. Total metabolite formation only accounted to 0.056 C-mol C-mol(-1) of substrate. A very high protein and a low carbohydrate content (71.9% and 9.6% of biomass dry weight, respectively) were measured in cells under this condition. It is concluded that K. marxianus aligns with the so-called aerobic-respiring or Crabtree-negative yeasts. Furthermore, it has one of the highest growth rates among yeasts, and a high capacity of converting sugar into biomass, even when carbon is not the limiting nutrient. These results provide useful data regarding the future application of K. marxianus in processes aimed at the production of biomass-linked compounds, with high yields and productivities.

Central carbon metabolism of Saccharomyces cerevisiae in anaerobic, oxygen-limited and fully aerobic steady-state conditions and following a shift to anaerobic conditions

Saccharomyces cerevisiae CEN.PK113-1A was grown in glucose-limited chemostat culture with 0%, 0.5%, 1.0%, 2.8% or 20.9% O2 in the inlet gas (D=0.10 h(-1), pH 5, 30 degrees C) to determine the effects of oxygen on 17 metabolites and 69 genes related to central carbon metabolism. The concentrations of tricarboxylic acid cycle (TCA) metabolites and all glycolytic metabolites except 2-phosphoglycerate+3-phosphoglycerate and phosphoenolpyruvate were higher in anaerobic than in fully aerobic conditions. Provision of only 0.5-1% O2 reduced the concentrations of most metabolites, as compared with anaerobic conditions. Transcription of most genes analyzed was reduced in 0%, 0.5% or 1.0% O2 relative to cells grown in 2.8% or 20.9% O2. Ethanol production was observed with 2.8% or less O2. After steady-state analysis in defined oxygen concentrations, the conditions were switched from aerobic to anaerobic. Metabolite and transcript levels were monitored for up to 96 h after the transition, and this showed that more than 30 h was required for the cells to fully adapt to anaerobiosis. Levels of metabolites of upper glycolysis and the TCA cycle increased following the transition to anaerobic conditions, whereas those of metabolites of lower glycolysis generally decreased. Gene regulation was more complex, with some genes showing transient upregulation or downregulation during the adaptation to anaerobic conditions.

Effect of carbon source perturbations on transcriptional regulation of metabolic fluxes in Saccharomyces cerevisiae

BACKGROUND

Control effective flux (CEF) of a reaction is the weighted sum of all fluxes through that reaction, derived from elementary flux modes (EFM) of a metabolic network. Change in CEFs under different environmental conditions has earlier been proven to be correlated with the corresponding changes in the transcriptome. Here we use this to investigate the degree of transcriptional regulation of fluxes in the metabolism of Saccharomyces cerevisiae. We do this by quantifying correlations between changes in CEFs and changes in transcript levels for shifts in carbon source, i.e. between the fermentative carbon source glucose and nonfermentative carbon sources like ethanol, acetate, and lactate. The CEF analysis is based on a simple stoichiometric model that includes reactions of the central carbon metabolism and the amino acid metabolism.

RESULTS

The effect of the carbon shift on the metabolic fluxes was investigated for both batch and chemostat cultures. For growth on glucose in batch (respiro-fermentative) cultures, EFMs with no by-product formation were removed from the analysis of the CEFs, whereas those including any by-products (ethanol, glycerol, acetate, succinate) were omitted in the analysis of growth on glucose in chemostat (respiratory) cultures. This resulted in improved correlations between CEF changes and transcript levels. A regression correlation coefficient of 0.60 was obtained between CEF changes and gene expression changes in the central carbon metabolism for the analysis of 5 different perturbations. Out of 45 data points there were no more than 6 data points deviating from the correlation. Additionally, up- or down-regulation of at least 75% of the genes were in qualitative agreement with the CEF changes for all perturbations studied.

CONCLUSION

The analysis indicates that changes in carbon source are associated with a high degree of hierarchical regulation of metabolic fluxes in the central carbon metabolism as the change in fluxes are correlating directly with the change in transcript levels of genes encoding their corresponding enzymes. For amino acid biosynthesis there was, however, not found to exist a similar correlation, and this may point to either post-transcriptional and/or metabolic regulation, or be due to the absence of a direct perturbation on the amino acid pathways in these experiments.

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.

Improving metabolic flux estimation via evolutionary optimization for convex solution space

MOTIVATION

Flux estimation by using (13) C-labeling pattern information of metabolites is currently the only method that can give accurate, detailed quantification of all intracellular fluxes in the central metabolism of a microorganism. In essence, it corresponds to a constrained optimization problem which minimizes a weighted distance between measured and simulated results. Characteristics, such as existence of multiple local minima, non-linear and non-differentiable make this problem a special difficulty.

RESULTS

In the present work, we propose an evolutionary-based global optimization algorithm taking advantage of the convex feature of the problem's solution space. Based on the characteristics of convex spaces, specialized initial population and evolutionary operators are designed to solve (13)C-based metabolic flux estimation problem robustly and efficiently. The algorithm was applied to estimate the central metabolic fluxes in Escherichia coli and compared with conventional optimization technique. Experimental results illustrated that our algorithm is capable of achieving fast convergence to good near-optima and maintaining the robust nature of evolutionary algorithms at the same time.

AVAILABILITY

Available from the authors upon request.

A systems biology approach to study glucose repression in the yeast Saccharomyces cerevisiae

Glucose repression in the yeast Saccharomyces cerevisiae has evolved as a complex regulatory system involving several different pathways. There are two main pathways involved in signal transduction. One has a role in glucose sensing and regulation of glucose transport, while another takes part in repression of a wide range of genes involved in utilization of alternative carbon sources. In this work, we applied a systems biology approach to study the interaction between these two pathways. Through genome-wide transcription analysis of strains with disruption of HXK2, GRR1, MIG1, the combination of MIG1 and MIG2, and the parental strain, we identified 393 genes to have significantly changed expression levels. To identify co-regulation patterns in the different strains we applied principal component analysis. Disruption of either GRR1 or HXK2 were both found to have profound effects on transcription of genes related to TCA cycle and respiration, as well as ATP synthesis coupled proton transport, all displaying an increased expression. The hxk2Delta strain showed reduced overflow metabolism towards ethanol relative to the parental strain. We also used a genome-scale metabolic model to identify reporter metabolites, and found that there is a high degree of consistency between the identified reporter metabolites and the physiological effects observed in the different mutants. Our systems biology approach points to close interaction between the two pathways, and our metabolism driven analysis of transcription data may find a wider application for analysis of cross-talk between different pathways involved in regulation of metabolism.

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.

Fluxome analysis using GC-MS

Fluxome analysis aims at the quantitative analysis of in vivo carbon fluxes in metabolic networks, i. e. intracellular activities of enzymes and pathways. It allows investigating the effects of genetic or environmental modifications and thus precisely provides a global perspective on the integrated genetic and metabolic regulation within the intact metabolic network. The experimental and computational approaches developed in this area have revealed fascinating insights into metabolic properties of various biological systems. Most of the comprehensive approaches for metabolic flux studies today involve isotopic tracer studies and GC-MS for measurement of the labeling pattern of metabolites. Initially developed and applied mainly in the field of biomedicine these GC-MS based metabolic flux approaches have been substantially extended and optimized during recent years and today display a key technology in metabolic physiology and biotechnology.

A rare sugar xylitol. Part I: the biochemistry and biosynthesis of xylitol

The rare sugar xylitol is a five-carbon polyol (pentitol) that has beneficial health effects. Xylitol has global markets and, therefore, it represents an alternative to current dominant sweeteners. The research on microbial reduction of D-xylose to xylitol has been focused on metabolically engineered Saccharomycess cerevisiae and Candida strains. The Candida strains have an advantage over the metabolically engineered S. cerevisiae in terms of D-xylose uptake and maintenance of the intracellular redox balance. Due to the current industrial scale production of xylitol, it has become an inexpensive starting material for the production of other rare sugar. The first part of this mini-review concentrates on the biochemistry of xylitol biosynthesis and the problems related to intracellular redox balance.

Metabolic analysis of adaptive evolution for in silico-designed lactate-producing strains

Experimental evolution is now frequently applied to many biological systems to achieve desired objectives. To obtain optimized performance for metabolite production, a successful strategy has been recently developed that couples metabolic engineering techniques with laboratory evolution of microorganisms. Previously, we reported the growth characteristics of three lactate-producing, adaptively evolved Escherichia coli mutant strains designed by the OptKnock computational algorithm. Here, we describe the use of (13)C-labeled experiments and mass distribution measurements to study the evolutionary effects on the fluxome of these differently designed strains. Metabolic flux ratios and intracellular flux distributions as well as physiological data were used to elucidate metabolic responses over the course of adaptive evolution and metabolic differences among strains. The study of 3 unevolved and 12 evolved engineered strains as well as a wild-type strain suggests that evolution resulted in remarkable improvements in both substrate utilization rate and the proportion of glycolytic flux to total glucose utilization flux. Among three strain designs, the most significant increases in the fraction of glucose catabolized through glycolysis (>50%) and the glycolytic fluxes (>twofold) were observed in phosphotransacetylase and phosphofructokinase 1 (PFK1) double deletion (pta- pfkA) strains, which were likely attributed to the dramatic evolutionary increase in gene expression and catalytic activity of the minor PFK encoded by pfkB. These fluxomic studies also revealed the important role of acetate synthetic pathway in anaerobic lactate production. Moreover, flux analysis suggested that independent of genetic background, optimal relative flux distributions in cells could be achieved faster than physiological parameters such as nutrient utilization rate.

Isotopomer analysis of myocardial substrate metabolism: a systems biology approach

The increasing accessibility of mass isotopomer data via GC-MS and NMR technology has necessitated the use of a systematic and reliable method to take advantage of such data for flux analysis. Here we applied a nonlinear, optimization-based method to study substrate metabolism in cardiomyocytes using (13)C data from perfused mouse hearts. The myocardial metabolic network used in this study accounts for 257 reactions and 240 metabolites, which are further compartmentalized into extracellular space, cytosol, and mitochondrial matrix. Analysis of the perfused mouse heart showed that the steady-state ATP production rate was 16.6 +/- 2.3 micromol/min . gww, with 30% of the ATP coming from glycolysis. Of the four substrates available in the perfusate (glucose, pyruvate, lactate, and oleate), exogenous glucose forms the majority of cytosolic pyruvate. Pyruvate decaboxylation is significantly higher than carboxylation, suggesting that anaplerosis is low in the perfused heart. Exchange fluxes were predicted to be high for reversible enzymes in the citric acid cycle (CAC), but low in the glycolytic pathway. Pseudoketogenesis amounted to approximately 50% of the net ketone body uptake. Sensitivity analysis showed that the estimated flux distributions were relatively insensitive to experimental errors. The application of isotopomer data drastically improved the estimation of reaction fluxes compared to results computed with respect to reaction stoichiometry alone. Further study of 12 commonly used (13)C glucose mixtures showed that the mixtures of 20% [U-(13)C(6)] glucose, 80% [3 (13)C] glucose and 20% [U-(13)C(6)] glucose, 80% [4 (13)C] were best for resolving fluxes in the current network.

Increased TCA cycle activity and reduced oxygen consumption during cytochrome P450-dependent biotransformation in fission yeast

Cytochrome P450s are haem-containing monooxygenases that catalyse a variety of oxidations utilizing a large substrate spectrum and are therefore of interest for biotechnological applications. We expressed human CYP21 in fission yeast Schizosaccharomyces pombe as a eukaryotic model for P450-dependent whole-cell biotransformation. The resulting strain displayed strong steroid hydroxylase activity that was accompanied by contrary effects on respiration and non-respiratory oxygen consumption, which combined to a significant decline in total oxygen consumption of the cells. While production of ROS (reactive oxygen species) decreased, the TCA cycle activity increased, as was shown by metabolic flux (METAFoR) analysis. Pentose phosphate pathway (PPP) activity was found to be negligible, regardless of growth phase, CYP21 expression or biocatalytic activity, indicating that NADPH levels in Sz. pombe are sufficiently high to support an exogenous P450 without adaptations of central carbon metabolism. We conclude from these data that neither oxygen supply nor NADPH availability are limiting factors in P450-dependent biocatalysis in Sz. pombe.

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.

Metabolic networks in motion: 13C-based flux analysis

Many properties of complex networks cannot be understood from monitoring the components—not even when comprehensively monitoring all protein or metabolite concentrations—unless such information is connected and integrated through mathematical models. The reason is that static component concentrations, albeit extremely informative, do not contain functional information per se. The functional behavior of a network emerges only through the nonlinear gene, protein, and metabolite interactions across multiple metabolic and regulatory layers. I argue here that intracellular reaction rates are the functional end points of these interactions in metabolic networks, hence are highly relevant for systems biology. Methods for experimental determination of metabolic fluxes differ fundamentally from component concentration measurements; that is, intracellular reaction rates cannot be detected directly, but must be estimated through computer model-based interpretation of stable isotope patterns in products of metabolism.

Metabolic flux analysis of the two astaxanthin-producing microorganismsHaematococcus pluvialis andPhaffia rhodozyma in the pure and mixed cultures

The two major astaxanthin-producing microorganisms Phaffia rhodozyma and Haematococcus pluvialis exhibited elevated astaxanthin yields under the mixed culture regime, and the changes in flux distribution were investigated by means of metabolic flux analysis (MFA). In the mixed culture of the two strains, the carbon flux towards astaxanthin formation in P. rhodozyma increased by 20%, which may be due to the enriched oxygen evolved through the photosynthesis of H. pluvialis. On the other hand, the uptake of pyruvate and CO(2) excreted by P. rhodozyma also facilitated astaxanthin synthesis in H. pluvialis, which reduced 33% of the carbon flux exported from Calvin cycle to the catabolic pathway, and in turn raised the carbon flux to glyceraldehyde-3-phosphate by 25%. As a result, the carbon flux diverted to astaxanthin synthesis increased 2.8-fold in comparison with that in the pure culture.

When transcriptome meets metabolome: fast cellular responses of yeast to sudden relief of glucose limitation

Within the first 5 min after a sudden relief from glucose limitation, Saccharomyces cerevisiae exhibited fast changes of intracellular metabolite levels and a major transcriptional reprogramming. Integration of transcriptome and metabolome data revealed tight relationships between the changes at these two levels. Transcriptome as well as metabolite changes reflected a major investment in two processes: adaptation from fully respiratory to respiro-fermentative metabolism and preparation for growth acceleration. At the metabolite level, a severe drop of the AXP pools directly after glucose addition was not accompanied by any of the other three NXP. To counterbalance this loss, purine biosynthesis and salvage pathways were transcriptionally upregulated in a concerted manner, reflecting a sudden increase of the purine demand. The short-term dynamics of the transcriptome revealed a remarkably fast decrease in the average half-life of downregulated genes. This acceleration of mRNA decay can be interpreted both as an additional nucleotide salvage pathway and an additional level of glucose-induced regulation of gene expression.

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.

Engineering of the redox imbalance of Fusarium oxysporum enables anaerobic growth on xylose

Dissimilatory nitrate reduction metabolism, of the natural xylose-fermenting fungus Fusarium oxysporum, was used as a strategy to achieve anaerobic growth and ethanol production from xylose. Beneficial alterations of the redox fluxes and thereby of the xylose metabolism were obtained by taking advantage of the regeneration of the cofactor NAD(+) during the denitrification process. In batch cultivations, nitrate sustained growth under anaerobic conditions (1.21 g L(-1) biomass) and simultaneously a maximum yield of 0.55 moles of ethanol per mole of xylose was achieved, whereas substitution of nitrate with ammonium limited the growth significantly (0.15 g L(-1) biomass). Using nitrate, the maximum acetate yield was 0.21 moles per mole of xylose and no xylitol excretion was observed. Furthermore, the network structure in the central carbon metabolism of F. oxysporum was characterized in steady state. F. oxysporum grew anaerobically on [1-(13)C] labelled glucose and unlabelled xylose in chemostat cultivation with nitrate as nitrogen source. The use of labelled substrate allowed the precise determination of the glucose and xylose contribution to the carbon fluxes in the central metabolism of this poorly described microorganism. It was demonstrated that dissimilatory nitrate reduction allows F. oxysporum to exhibit typical respiratory metabolic behaviour with a highly active TCA cycle and a large demand for NADPH.

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.

Development of a kinetic metabolic model: application to Catharanthus roseus hairy root

A kinetic metabolic model describing Catharanthus roseus hairy root growth and nutrition was developed. The metabolic network includes glycolysis, pentose-phosphate pathway, TCA cycle and the catabolic reactions leading to cell building blocks such as amino acids, organic acids, organic phosphates, lipids and structural hexoses. The central primary metabolic network was taken at pseudo-steady state and metabolic flux analysis technique allowed reducing from 31 metabolic fluxes to 20 independent pathways. Hairy root specific growth rate was described as a function of intracellular concentration in cell building blocks. Intracellular transport and accumulation kinetics for major nutrients were included. The model uses intracellular nutrients as well as energy shuttles to describe metabolic regulation. Model calibration was performed using experimental data obtained from batch and medium exchange liquid cultures of C. roseus hairy root using a minimal medium in Petri dish. The model is efficient in estimating the growth rate.

Hap4 is not essential for activation of respiration at low specific growth rates in Saccharomyces cerevisiae

In Saccharomyces cerevisiae, the heme-activated protein complex Hap2/3/4/5 plays a major role in the transcription of genes involved in respiration. Thus, overexpression of HAP4 has been shown to result in a 10% increase in the respiratory capacity. Here the physiology of a HAP4-deleted S. cerevisiae strain was investigated, and we found that the hap4delta S. cerevisiae exhibited poor growth on ethanol, although the growth rate on glucose was indifferent from the wild type in aerobic as well as anaerobic cultures. Moreover, it exhibited a large (75%) reduction in the critical glucose uptake rate at which fermentative metabolism is onset, indicating a substantial reduction in respiratory capacity. We also performed whole genome transcription analysis for the hap4delta and the wild type, grown in carbon-limited chemostat cultures operated at a dilution rate of 0.05 h(-1). Although both strains exhibited respiratory metabolism, there was significant change in expression of many genes in the hap4delta strain. These genes are involved in several different parts of the metabolism, including oxidative stress response, peroxisomal functions, and energy generation. This study strongly indicates that Hap4 activation only occurs at intermediate specific growth rates, below which the transcription of genes responsible for respiration is dependent on the Hap2/3/5 complex and above which the Hap4 protein augments the transcription. Furthermore, statistical analysis of the transcription data and integration of the data with a genome scale metabolic network provided new insight and evidence for the role of Hap4 in transcriptional regulation of mitochondrial respiration.

Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes

MOTIVATION

Flux estimation using isotopomer information of metabolites is currently the most reliable method to obtain quantitative estimates of the activity of metabolic pathways. However, the development of isotopomer measurement techniques for intermediate metabolites is a demanding task. Careful planning of isotopomer measurements is thus needed to maximize the available flux information while minimizing the experimental effort.

RESULTS

In this paper we study the question of finding the smallest subset of metabolites to measure that ensure the same level of isotopomer information as the measurement of every metabolite in the metabolic network. We study the computational complexity of this optimization problem in the case of the so-called positional enrichment data, give methods for obtaining exact and fast approximate solutions, and evaluate empirically the efficacy of the proposed methods by analyzing a metabolic network that models the central carbon metabolism of Saccharomyces cerevisiae.

Energy metabolism and its compartmentation in Trypanosoma brucei

African trypanosomes are parasitic protozoa of the order of Kinetoplastida, which cause sleeping sickness and nagana. Trypanosomes are not only of scientific interest because of their clinical importance, but also because these protozoa contain several very unusual biological features, such as their special energy metabolism. The energy metabolism of Trypanosoma brucei differs significantly from that of its host, not only because it comprises distinct enzymes and metabolic pathways, but also because some of the glycolytic enzymes are localized in organelles called glycosomes. Furthermore, the energy metabolism changes drastically during the complex life cycle of this parasite. This review will focus on the recent advances made in understanding the process of ATP production in T. brucei during its life cycle and the consequences of the special subcellular compartmentation.

Metabolic functions of duplicate genes in Saccharomyces cerevisiae

The roles of duplicate genes and their contribution to the phenomenon of enzyme dispensability are a central issue in molecular and genome evolution. A comprehensive classification of the mechanisms that may have led to their preservation, however, is currently lacking. In a systems biology approach, we classify here back-up, regulatory, and gene dosage functions for the 105 duplicate gene families of Saccharomyces cerevisiae metabolism. The key tool was the reconciled genome-scale metabolic model iLL672, which was based on the older iFF708. Computational predictions of all metabolic gene knockouts were validated with the experimentally determined phenotypes of the entire singleton yeast library of 4658 mutants under five environmental conditions. iLL672 correctly identified 96%-98% and 73%-80% of the viable and lethal singleton phenotypes, respectively. Functional roles for each duplicate family were identified by integrating the iLL672-predicted in silico duplicate knockout phenotypes, genome-scale carbon-flux distributions, singleton mutant phenotypes, and network topology analysis. The results provide no evidence for a particular dominant function that maintains duplicate genes in the genome. In particular, the back-up function is not favored by evolutionary selection because duplicates do not occur more frequently in essential reactions than singleton genes. Instead of a prevailing role, multigene-encoded enzymes cover different functions. Thus, at least for metabolism, persistence of the paralog fraction in the genome can be better explained with an array of different, often overlapping functional roles.

Biotechnology, physiology and genetics of the yeastPichia anomala

The ascomycetous yeast Pichia anomala is frequently associated with food and feed products, either as a production organism or as a spoilage yeast. It belongs to the nonSaccharomyces wine yeasts and contributes to the wine aroma by the production of volatile compounds. The ability to grow in preserved food and feed environments is due to its capacity to grow under low pH, high osmotic pressure and low oxygen tension. A new application of P. anomala is its use as a biocontrol agent, which is based on the potential to inhibit a variety of moulds in different environments. Although classified as a biosafety class-1 organism, cases of P. anomala infections have been reported in immunocompromised patients. On the other hand, P. anomala killer toxins have a potential as antimicrobial agents. The yeast can use a broad range of nitrogen and phosphor sources, which makes it a potential agent to decrease environmental pollution by organic residues from agriculture. However, present knowledge of the physiological basis of its performance is limited. Recently, the first studies have been published dealing with the global regulation of the metabolism of P. anomala under different conditions of oxygenation.

CreA influences the metabolic fluxes of Aspergillus nidulans during growth on glucose and xylose

The physiological phenotype of Aspergillus nidulans was investigated for different genetic and environmental conditions of glucose repression through the quantification of in vivo fluxes in the central carbon metabolism using (13)C-metabolic-flux analysis. The particular focus was the role of the carbon repressor CreA, which is the major regulatory protein mediating carbon repression in many fungal species, in the primary metabolism of A. nidulans. Batch cultivations were performed with a reference strain and a deletion mutant strain (creADelta4) using [1-(13)C]glucose as carbon source. The mutant strain was also grown on a mixture of [1-(13)C]glucose and unlabelled xylose. Fractional enrichment data were measured by gas chromatography-mass spectrometry. A model describing the central metabolism of A. nidulans was used in combination with fractional enrichment data, and measurements of extracellular rates and biomass composition for the estimation of the in vivo metabolic fluxes. The creA-mutant strain showed a lower maximum specific growth rate than the reference strain when grown on glucose (0.11 and 0.25 h(-1), respectively), whereas the specific growth rate of the mutant strain grown on the glucose/xylose mixture was identical to that on glucose (0.11 h(-1)). Different patterns and increased levels of extracellular polyols were observed both upon deletion of the creA gene and upon addition of xylose to the growth medium of the mutant strain. Concerning metabolic fluxes, the major change observed in the flux distribution of A. nidulans upon deletion of the creA gene was a 20 % decrease in the flux through the oxidative part of the pentose-phosphate pathway. Addition of xylose to the growth medium of the mutant resulted in an increase of about 40 % in the activity of the oxidative part of the pentose-phosphate pathway, as well as decreases in the fluxes through the Embden-Meyerhof-Parnas pathway and the tricarboxylic acid cycle (in the range of 20-30 %). The derepression of key pathways leads to alterations in the demands for cofactors, thereby imposing changes in the central metabolism due to the coupling of the many different reactions via the redox and energy metabolism of the cells.

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.

Characterization of the metabolic shift between oxidative and fermentative growth in Saccharomyces cerevisiae by comparative 13C flux analysis

Background

One of the most fascinating properties of the biotechnologically important organism Saccharomyces cerevisiae is its ability to perform simultaneous respiration and fermentation at high growth rate even under fully aerobic conditions. In the present work, this Crabtree effect called phenomenon was investigated in detail by comparative ¹³C metabolic flux analysis of S. cerevisiae growing under purely oxidative, respiro-fermentative and predominantly fermentative conditions.

Results

The metabolic shift from oxidative to fermentative growth was accompanied by complex changes of carbon flux throughout the whole central metabolism. This involved a flux redirection from the pentose phosphate pathway (PPP) towards glycolysis, an increased flux through pyruvate carboxylase, the fermentative pathways and malic enzyme, a flux decrease through the TCA cycle, and a partial relocation of alanine biosynthesis from the mitochondrion to the cytosol. S. cerevisiae exhibited a by-pass of pyruvate dehydrogenase in all physiological regimes. During oxidative growth this by-pass was mainly provided via pyruvate decarboxylase, acetaldehyde dehydrogenase, acetyl-CoA synthase and transport of acetyl-CoA into the mitochondrion. During fermentative growth this route, however, was saturated due to limited enzyme capacity. Under these conditions the cells exhibited high carbon flux through a chain of reactions involving pyruvate carboxylase, the oxaloacetate transporter and malic enzyme. During purely oxidative growth the PPP alone was sufficient to completely supply NADPH for anabolism. During fermentation, it provided only 60 % of the required NADPH.

Conclusion

We conclude that, in order to overcome the limited capacity of pyruvate dehydrogenase, S. cerevisiae possesses different metabolic by-passes to channel carbon into the mitochondrion. This involves the conversion of cytosolic pyruvate either into acetyl CoA or oxaloacetate followed by intercompartmental transport of these metabolites. During oxidative growth mainly the NAD specific isoforms of acetaldehyde dehydrogenase and isocitrate dehydrogenase catalyze the corresponding reactions in S. cerevisiae, whereas NADPH supply under fermentative conditions involves significant contribution of sources other than the PPP such as e. g. NADPH specific acetaldehyde dehydrogenase or isocitrate dehydrogenase.

Insights on the evolution of metabolic networks of unicellular translationally biased organisms from transcriptomic data and sequence analysis

Codon bias is related to metabolic functions in translationally biased organisms, and two facts are argued about. First, genes with high codon bias describe in meaningful ways the metabolic characteristics of the organism; important metabolic pathways corresponding to crucial characteristics of the lifestyle of an organism, such as photosynthesis, nitrification, anaerobic versus aerobic respiration, sulfate reduction, methanogenesis, and others, happen to involve especially biased genes. Second, gene transcriptional levels of sets of experiments representing a significant variation of biological conditions strikingly confirm, in the case of Saccharomyces cerevisiae, that metabolic preferences are detectable by purely statistical analysis: the high metabolic activity of yeast during fermentation is encoded in the high bias of enzymes involved in the associated pathways, suggesting that this genome was affected by a strong evolutionary pressure that favored a predominantly fermentative metabolism of yeast in the wild. The ensemble of metabolic pathways involving enzymes with high codon bias is rather well defined and remains consistent across many species, even those that have not been considered as translationally biased, such as Helicobacter pylori, for instance, reveal some weak form of translational bias for this genome. We provide numerical evidence, supported by experimental data, of these facts and conclude that the metabolic networks of translationally biased genomes, observable today as projections of eons of evolutionary pressure, can be analyzed numerically and predictions of the role of specific pathways during evolution can be derived. The new concepts of Comparative Pathway Index, used to compare organisms with respect to their metabolic networks, and Evolutionary Pathway Index, used to detect evolutionarily meaningful bias in the genetic code from transcriptional data, are introduced.

Contribution of the Saccharomyces cerevisiae transcriptional regulator Leu3p to physiology and gene expression in nitrogen- and carbon-limited chemostat cultures

Transcriptional regulation of branched-chain amino-acid metabolism in Saccharomyces cerevisiae involves two key regulator proteins, Leu3p and Gcn4p. Leu3p is a pathway-specific regulator, known to regulate six genes involved in branched-chain amino-acid metabolism and one gene in nitrogen assimilation. Gcn4p is a global regulator, involved in the general response to amino-acid and purine starvation. To investigate the contribution of Leu3p in regulation of gene expression, a leu3Delta strain was compared to an isogenic reference strain using DNA-microarray analysis. This comparison was performed for both glucose-grown/ammonium-limited and ethanol-limited/ammonium-excess chemostat cultures. In ethanol-limited cultures, absence of Leu3p led to reduced transcript levels of six of the seven established Leu3p target genes, but did not affect key physiological parameters. In ammonium-limited cultures, absence of Leu3p caused a drastic decrease in storage carbohydrate content. mRNA levels of genes involved in storage carbohydrate metabolism were also found reduced. Under N-limited conditions, the leu3Delta genotype elicited an amino-acid starvation response, leading to increased transcript levels of many amino-acid biosynthesis genes. By combining the transcriptome data with data from earlier studies that measured DNA binding of Leu3p both in vitro and in vivo, BAT1, GAT1 and OAC1 were identified as additional Leu3p-regulated genes. This study demonstrates that unravelling of transcriptional regulation networks should preferably include several cultivation conditions and requires a combination of experimental approaches.

Comparative metabolic network analysis of two xylose fermenting recombinant Saccharomyces cerevisiae strains

The recombinant xylose fermenting strain Saccharomyces cerevisiae TMB3001 can grow on xylose, but the xylose utilisation rate is low. One important reason for the inefficient fermentation of xylose to ethanol is believed to be the imbalance of redox co-factors. In the present study, a metabolic flux model was constructed for two recombinant S. cerevisiae strains: TMB3001 and CPB.CR4 which in addition to xylose metabolism have a modulated redox metabolism, i.e. ammonia assimilation was shifted from being NADPH to NADH dependent by deletion of gdh1 and over-expression of GDH2. The intracellular fluxes were estimated for both strains in anaerobic continuous cultivations when the growth limiting feed consisted of glucose (2.5 g L-1) and xylose (13 g L-1). The metabolic network analysis with 13C labelled glucose showed that there was a shift in the specific xylose reductase activity towards use of NADH as co-factor rather than NADPH. This shift is beneficial for solving the redox imbalance and it can therefore partly explain the 25% increase in the ethanol yield observed for CPB.CR4. Furthermore, the analysis indicated that the glyoxylate cycle was activated in CPB.CR4.

Mass spectrometry in metabolome analysis

In the post-genomic era, increasing efforts have been made to describe the relationship between the genome and the phenotype in cells and organisms. It has become clear that even a complete understanding of the state of the genes, messages, and proteins in a living system does not reveal its phenotype. Therefore, researchers have started to study the metabolome (or the metabolic complement of functional genomics). Within this context, mass spectrometry (MS) has increasingly occupied a central position in the methodologies developed for determination of the metabolic state. This review is mainly focused on the status of MS in the metabolome field, trying to direct the reader to the main approaches for analysis of metabolites, reviewing basic methodologies in sample preparation, and the most recent MS techniques introduced. Apart from the description of the different methods, this review will try to state a general comparison between the several different techniques that involve MS and metabolite analysis, and will highlight their limitations and preferred applicability.

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'.

Transient expression and flux changes during a shift from high to low riboflavin production in continuous cultures of Bacillus subtilis

At the onset of glucose-limited continuous cultures, riboflavin production in recombinant Bacillus subtilis declines significantly within 3 generations. This phenomenon was specific to riboflavin production and was not correlated with any other physiological parameter. Physiological analyses excluded genetic degeneration or co-metabolism of previously generated overflow metabolites as possible causes for the riboflavin transients. By developing a novel method for (13)C-based metabolic flux analysis under non-steady-state conditions, we showed that the pentose precursors of riboflavin were exclusively synthesized via the non-oxidative pentose-phosphate (PP) pathway as long as riboflavin production was high. The complete redirection of carbon flux to the oxidative branch of the PP pathway was achieved at unaltered PP pathway gene expression and correlated with the declining riboflavin production. With the possible exception of a slight down-regulation of the purine biosynthesis pathway, genome-wide expression analysis indicated that transcriptional regulation was not responsible for the production decline.