In vivo dynamics of galactose metabolism in Saccharomyces cerevisiae: metabolic fluxes and metabolite levels

The Metabolism of Respiring Carbon Sources by Dekkera bruxellensis and Its Relation with the Production of Acetate

Dekkera bruxellensis has been studied for several aspects of its metabolism over the past years, which has expanded our comprehension on its importance to industrial fermentation processes and uncovered its industrial relevance. Acetate is a metabolite often found in D. bruxellensis aerobic cultivations, whereas its production is linked to decreased ethanol yields. In a previous work, we aimed to understand how acetate metabolism affected the fermentation capacity of D. bruxellensis. In the present work, we evaluated the role of acetate metabolism in respiring cells using ammonium or nitrate as nitrogen sources. Our results showed that galactose is a strictly respiratory sugar and that a relevant part of its carbon is lost, while the remaining is metabolised through the Pdh bypass pathway before being assimilated into biomass. When this pathway was blocked, yeast growth was reduced while more carbon was assimilated to the biomass. In nitrate, more acetate was produced as expected, which increased carbon assimilation, although less galactose was uptaken from the medium. This scenario was not affected by the Pdh bypass inhibition. The confirmation that acetate production was crucial for carbon assimilation was brought by cultivations in pyruvate. All physiological data were connected to the expression patterns of PFK1, PDC1, ADH1, ALD3, ALD5 and ATP1 genes. Other respiring carbon sources could only be properly used by the cells when some external acetate was supplied. Therefore, the results reported herein helped in providing valuable contributions to the understanding of the oxidative metabolism in this potential industrial yeast.

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

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

Multi-OMICS study of a CHCHD10 variant causing ALS demonstrates metabolic rewiring and activation of endoplasmic reticulum and mitochondrial unfolded protein responses

Mutations in CHCHD10, coding for a mitochondrial intermembrane space protein, are a rare cause of autosomal dominant amyotrophic lateral sclerosis. Mutation-specific toxic gain of function or haploinsufficiency models have been proposed to explain pathogenicity. To decipher the metabolic dysfunction associated with the haploinsufficient p.R15L variant, we integrated transcriptomic, metabolomic and proteomic data sets in patient cells subjected to an energetic stress that forces the cells to rely on oxidative phosphorylation for ATP production. Patient cells had a complex I deficiency that resulted in an increased NADH/NAD+ ratio, diminished TCA cycle activity, a reorganization of one carbon metabolism and an increased AMP/ATP ratio leading to phosphorylation of AMPK and inhibition of mTORC1. These metabolic changes activated the unfolded protein response (UPR) in the ER through the IRE1/XBP1 pathway, upregulating downstream targets including ATF3, ATF4, CHOP and EGLN3, and two cytokine markers of mitochondrial disease, GDF15 and FGF21. Activation of the mitochondrial UPR was mediated through an upregulation of the transcription factors ATF4 and ATF5, leading to increased expression of mitochondrial proteases and heat shock proteins. There was a striking transcriptional up regulation of at least seven dual specific phosphatases, associated with an almost complete dephosphorylation of JNK isoforms, suggesting a concerted deactivation of MAP kinase pathways. This study demonstrates that loss of CHCHD10 function elicits an energy deficit that activates unique responses to nutrient stress in both the mitochondria and ER, which may contribute to the selective vulnerability of motor neurons.

Enhancement of Galactose Uptake from Kappaphycus alvarezii Hydrolysate Using Saccharomyces cerevisiae Through Overexpression of Leloir Pathway Genes

A total 42.68 g/L monosaccharide with 0.10 g/L HMF was obtained from 10% (w/v) Kappaphycus alvarezii with thermal acid hydrolysis using 350 mM HNO₃ at 121 °C for 60 min and enzymatic saccharification with a 1:1 mixture of Viscozyme L and Celluclast 1.5 L for 72 h. To enhance the galactose utilization rate, fermentation was performed with overexpression of GAL1 (galactokinase), GAL7 (galactose-1-phosphate uridyltransferase), GAL10 (UDP-glucose-4-epimerase), and PGM2 (phosphoglucomutase 2) in Saccharomyces cerevisiae CEN.PK2 using CCW12 as a strong promoter. Among the strains, the overexpression of PGM2 showed twofold high galactose utilization rate (UR_gal) and produced ethanol 1.4-fold more than that of the control. Transcriptional analysis revealed the increase of PGM2 transcription level leading to enhance glucose-6-phosphate and fructose-6-phosphate and plays a key role in ensuring a higher glycolytic flux in the PGM2 strain. This finding shows particular importance in biofuel production from seaweed because galactose is one of the major monosaccharides in seaweeds such as K. alvarezii.

Synchronization of stochastic expressions drives the clustering of functionally related genes

Functionally related genes tend to be chromosomally clustered in eukaryotic genomes even after the exclusion of tandem duplicates, but the biological significance of this widespread phenomenon is unclear. We propose that stochastic expression fluctuations of neighboring genes resulting from chromatin dynamics are more or less synchronized such that their expression ratio is more stable than that for unlinked genes. Consequently, chromosomal clustering could be advantageous when the expression ratio of the clustered genes needs to stay constant, for example, because of the accumulation of toxic compounds when this ratio is altered. Evidence from manipulative experiments on the yeast GAL cluster, comprising three chromosomally adjacent genes encoding enzymes catalyzing consecutive reactions in galactose catabolism, unequivocally supports this hypothesis and elucidates how disorder in one biological phenomenon-gene expression noise-could prompt the emergence of order in another-genome organization.

Physiological growth and galactose utilization by dairy yeast Kluyveromyces marxianus in mixed sugars and whey during fermentation

The dairy yeast Kluyveromyces marxianus represents a promising industrial strain useful for the production of bioethanol from cheese whey. Physiology of the five K. marxianus strains on galactose was examined during batch cultivation under controlled aerobic conditions on minimal media and one of the strains designated K. marxianus strain 6C17 which presented the highest specific galactose consumption rate. A maximum specific growth rate of 0.34 and 0.37 h^-1, respectively, was achieved using batch cultivation in a minimal medium and a complex medium amended with galactose (50 g/L) at 37 °C. The sugar was metabolized for the production of ethanol as the chief metabolite with a maximum ethanol yield of 0.39 g/g of galactose. Different growth behaviors were observed when galactose was used with other sugar such as glucose, lactose and fructose. The growth rates on hydrolyzed cheese whey were also measured, and a maximum specific growth rate of 0.39 and 0.32 h^-1 was observed with glucose and galactose, respectively, with the maximum flux diverted toward ethanol production. This approach of studying the physiology of thermotolerant K. marxianus on hydrolyzed whey during fermentation would be helpful in achieving higher yields of ethanol.

RETRACTED:A new function for the yeast trehalose-6P synthase (Tps1) protein, as key pro-survival factor during growth, chronological ageing, and apoptotic stress

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of Marie-Ange Teste, Isabelle Léger-Silvestre, Jean M François and Jean-Luc Parrou. Marjorie Petitjean could not be reached. The corresponding author identified major issues and brought them to the attention of the Journal. These issues span from significant errors in the Material and Methods section of the article and major flaws in cytometry data analysis to data fabrication on the part of one of the authors. Given these errors, the retracting authors state that the only responsible course of action would be to retract the article, to respect scientific integrity and maintain the standards and rigor of literature from the retracting authors' group as well as the Journal. The retracting authors sincerely apologize to the readers and editors.

Rapid and efficient galactose fermentation by engineered Saccharomyces cerevisiae

In the important industrial yeast Saccharomyces cerevisiae, galactose metabolism requires energy production by respiration; therefore, this yeast cannot metabolize galactose under strict anaerobic conditions. While the respiratory dependence of galactose metabolism provides benefits in terms of cell growth and population stability, it is not advantageous for producing fuels and chemicals since a substantial fraction of consumed galactose is converted to carbon dioxide. In order to force S. cerevisiae to use galactose without respiration, a subunit (COX9) of a respiratory enzyme was deleted, but the resulting deletion mutant (Δcox9) was impaired in terms of galactose assimilation. Interestingly, after serial sub-cultures on galactose, the mutant evolved rapidly and was able to use galactose via fermentation only. The evolved strain (JQ-G1) produced ethanol from galactose with a 94% increase in yield and 6.9-fold improvement in specific productivity as compared to the wild-type strain. (13)C-metabolic flux analysis demonstrated a three-fold reduction in carbon flux through the TCA cycle of the evolved mutant with redirection of flux toward the fermentation pathway. Genome sequencing of the JQ-G1 strain revealed a loss of function mutation in a master negative regulator of the Leloir pathway (Gal80p). The mutation (Glu348*) in Gal80p was found to act synergistically with deletion of COX9 for efficient galactose fermentation, and thus the double deletion mutant Δcox9Δgal80 produced ethanol 2.4 times faster and with 35% higher yield than a single knockout mutant with deletion of GAL80 alone. When we introduced a functional COX9 cassette back into the JQ-G1 strain, the JQ-G1-COX9 strain showed a 33% reduction in specific galactose uptake rate and a 49% reduction in specific ethanol production rate as compared to JQ-G1. The wild-type strain was also subjected to serial sub-cultures on galactose but we failed to isolate a mutant capable of utilizing galactose without respiration. We concluded that the metabolic "death valley" (i.e. no galactose utilization by the Δcox9 mutant) is a necessary intermediate phenotype to facilitate galactose utilization without respiration in yeast. The results in this study demonstrate a promising approach for directing adaptive evolution toward fermentative metabolism and for generating evolved yeast strains with improved phenotypes under anaerobic conditions.

Ethanol production from galactose by a newly isolated Saccharomyces cerevisiae KL17

A wild-type yeast strain with a good galactose-utilization efficiency was newly isolated from the soil, and identified and named Saccharomyces cerevisiae KL17 by 18s RNA sequencing. Its performance of producing ethanol from galactose was investigated in flask cultures with media containing various combination and concentrations of galactose and glucose. When the initial galactose concentration was 20 g/L, it showed 2.2 g/L/h of substrate consumption rate and 0.63 g/L/h of ethanol productivity. Although they were about 70 % of those with glucose, such performance of S. cerevisiae KL17 with galactose was considered to be quite high compared with other strains reported to date. Its additional merit was that its galactose metabolism was not repressed by the existence of glucose. Its capability of ethanol production under a high ethanol concentration was demonstrated by fed-batch fermentation in a bioreactor. A high ethanol productivity of 3.03 g/L/h was obtained with an ethanol concentration and yield of 95 and 0.39 g/L, respectively, when the cells were pre-cultured on glucose. When the cells were pre-cultured on galactose instead of glucose, fermentation time could be reduced significantly, resulting in an improved ethanol productivity of 3.46 g/L/h. The inhibitory effects of two major impurities in a crude galactose solution obtained from acid hydrolysis of galactan were assessed. Only 5-Hydroxymethylfurfural (5-HMF) significantly inhibited ethanol fermentation, while levulinic acid (LA) was benign in the range up to 10 g/L.

Gene network requirements for regulation of metabolic gene expression to a desired state

Gene circuits that control metabolism should restore metabolic functions upon environmental changes. Whether gene networks are capable of steering metabolism to optimal states is an open question. Here we present a method to identify such optimal gene networks. We show that metabolic network optimisation over a range of environments results in an input-output relationship for the gene network that guarantees optimal metabolic states. Optimal control is possible if the gene network can achieve this input-output relationship. We illustrate our approach with the best-studied regulatory network in yeast, the galactose network. We find that over the entire range of external galactose concentrations, the regulatory network is able to optimally steer galactose metabolism. Only a few gene network parameters affect this optimal regulation. The other parameters can be tuned independently for optimisation of other functions, such as fast and low-noise gene expression. This study highlights gene network plasticity, evolvability, and modular functionality.

Predictive potential of flux balance analysis of Saccharomyces cerevisiae using as optimization function combinations of cell compartmental objectives

Background

The main objective of flux balance analysis (FBA) is to obtain quantitative predictions of metabolic fluxes of an organism, and it is necessary to use an appropriate objective function to guarantee a good estimation of those fluxes.

Methodology

In this study, the predictive performance of FBA was evaluated, using objective functions arising from the linear combination of different cellular objectives. This approach is most suitable for eukaryotic cells, owing to their multiplicity of cellular compartments. For this reason, Saccharomyces cerevisiae was used as model organism, and its metabolic network was represented using the genome-scale metabolic model iMM904. As the objective was to evaluate the predictive performance from the FBA using the kind of objective function previously described, substrate uptake and oxygen consumption were the only input data used for the FBA. Experimental information about microbial growth and exchange of metabolites with the environment was used to assess the quality of the predictions.

Conclusions

The quality of the predictions obtained with the FBA depends greatly on the knowledge of the oxygen uptake rate. For the most of studied classifications, the best predictions were obtained with “maximization of growth”, and with some combinations that include this objective. However, in the case of exponential growth with unknown oxygen exchange flux, the objective function “maximization of growth, plus minimization of NADH production in cytosol, plus minimization of NAD(P)H consumption in mitochondrion” gave much more accurate estimations of fluxes than the obtained with any other objective function explored in this study.

Unravelling evolutionary strategies of yeast for improving galactose utilization through integrated systems level analysis

Identification of the underlying molecular mechanisms for a derived phenotype by adaptive evolution is difficult. Here, we performed a systems-level inquiry into the metabolic changes occurring in the yeast Saccharomyces cerevisiae as a result of its adaptive evolution to increase its specific growth rate on galactose and related these changes to the acquired phenotypic properties. Three evolved mutants (62A, 62B, and 62C) with higher specific growth rates and faster specific galactose uptake were isolated. The evolved mutants were compared with a reference strain and two engineered strains, SO16 and PGM2, which also showed higher galactose uptake rate in previous studies. The profile of intermediates in galactose metabolism was similar in evolved and engineered mutants, whereas reserve carbohydrates metabolism was specifically elevated in the evolved mutants and one evolved strain showed changes in ergosterol biosynthesis. Mutations were identified in proteins involved in the global carbon sensing Ras/PKA pathway, which is known to regulate the reserve carbohydrates metabolism. We evaluated one of the identified mutations, RAS2(Tyr112), and this mutation resulted in an increased specific growth rate on galactose. These results show that adaptive evolution results in the utilization of unpredicted routes to accommodate increased galactose flux in contrast to rationally engineered strains. Our study demonstrates that adaptive evolution represents a valuable alternative to rational design in bioengineering of improved strains and, that through systems biology, it is possible to identify mutations in evolved strain that can serve as unforeseen metabolic engineering targets for improving microbial strains for production of biofuels and chemicals.

Modeling the evolution of a classic genetic switch

Background

The regulatory network underlying the yeast galactose-use pathway has emerged as a model system for the study of regulatory network evolution. Evidence has recently been provided for adaptive evolution in this network following a whole genome duplication event. An ancestral gene encoding a bi-functional galactokinase and co-inducer protein molecule has become subfunctionalized as paralogous genes (GAL1 and GAL3) in Saccharomyces cerevisiae, with most fitness gains being attributable to changes in cis-regulatory elements. However, the quantitative functional implications of the evolutionary changes in this regulatory network remain unexplored.

Results

We develop a modeling framework to examine the evolution of the GAL regulatory network. This enables us to translate molecular changes in the regulatory network to changes in quantitative network function. We computationally reconstruct an inferred ancestral version of the network and trace the evolutionary paths in the lineage leading to S. cerevisiae. We explore the evolutionary landscape of possible regulatory networks and find that the operation of intermediate networks leading to S. cerevisiae differs substantially depending on the order in which evolutionary changes accumulate; in particular, we systematically explore evolutionary paths and find that some network features cannot be optimized simultaneously.

Conclusions

We find that a computational modeling approach can be used to analyze the evolution of a well-studied regulatory network. Our results are consistent with several experimental studies of the evolutionary of the GAL regulatory network, including increased fitness in Saccharomyces due to duplication and adaptive regulatory divergence. The conceptual and computational tools that we have developed may be applicable in further studies of regulatory network evolution.

Recent developments in parameter estimation and structure identification of biochemical and genomic systems

The organization, regulation and dynamical responses of biological systems are in many cases too complex to allow intuitive predictions and require the support of mathematical modeling for quantitative assessments and a reliable understanding of system functioning. All steps of constructing mathematical models for biological systems are challenging, but arguably the most difficult task among them is the estimation of model parameters and the identification of the structure and regulation of the underlying biological networks. Recent advancements in modern high-throughput techniques have been allowing the generation of time series data that characterize the dynamics of genomic, proteomic, metabolic, and physiological responses and enable us, at least in principle, to tackle estimation and identification tasks using 'top-down' or 'inverse' approaches. While the rewards of a successful inverse estimation or identification are great, the process of extracting structural and regulatory information is technically difficult. The challenges can generally be categorized into four areas, namely, issues related to the data, the model, the mathematical structure of the system, and the optimization and support algorithms. Many recent articles have addressed inverse problems within the modeling framework of Biochemical Systems Theory (BST). BST was chosen for these tasks because of its unique structural flexibility and the fact that the structure and regulation of a biological system are mapped essentially one-to-one onto the parameters of the describing model. The proposed methods mainly focused on various optimization algorithms, but also on support techniques, including methods for circumventing the time consuming numerical integration of systems of differential equations, smoothing overly noisy data, estimating slopes of time series, reducing the complexity of the inference task, and constraining the parameter search space. Other methods targeted issues of data preprocessing, detection and amelioration of model redundancy, and model-free or model-based structure identification. The total number of proposed methods and their applications has by now exceeded one hundred, which makes it difficult for the newcomer, as well as the expert, to gain a comprehensive overview of available algorithmic options and limitations. To facilitate the entry into the field of inverse modeling within BST and related modeling areas, the article presented here reviews the field and proposes an operational 'work-flow' that guides the user through the estimation process, identifies possibly problematic steps, and suggests corresponding solutions based on the specific characteristics of the various available algorithms. The article concludes with a discussion of the present state of the art and with a description of open questions.

Energetic limits to metabolic flexibility: responses of Saccharomyces cerevisiae to glucose-galactose transitions

Glucose is the favoured carbon source for Saccharomyces cerevisiae, and the Leloir pathway for galactose utilization is only induced in the presence of galactose during glucose-derepressed conditions. The goal of this study was to investigate the dynamics of glucose-galactose transitions. To this end, well-controlled, glucose-limited chemostat cultures were switched to galactose-excess conditions. Surprisingly, galactose was not consumed upon a switch to galactose excess under anaerobic conditions. However, the transcripts of the Leloir pathway were highly increased upon galactose excess under both aerobic and anaerobic conditions. Protein and enzyme-activity assays showed that impaired galactose consumption under anaerobiosis coincided with the absence of the Leloir-pathway proteins. Further results showed that absence of protein synthesis was not caused by glucose-mediated translation inhibition. Analysis of adenosine nucleotide pools revealed a fast decrease of the energy charge after the switch from glucose to galactose under anaerobic conditions. Similar results were obtained when glucose-galactose transitions were analysed under aerobic conditions with a respiratory-deficient strain. It is concluded that under fermentative conditions, the energy charge was too low to allow synthesis of the Leloir proteins. Hence, this study conclusively shows that the intracellular energy status is an important factor in the metabolic flexibility of S. cerevisiae upon changes in its environment.

Transcriptomic analysis of Saccharomyces cerevisiae physiology in the context of galactose assimilation perturbations

Despite being extensively studied in various organisms due to scientific, industrial and medical interest, the galactose assimilation function and regulation, and especially its interaction with other parts of cellular physiology, have not been fully elucidated yet. The post-genomic era holistic techniques ("omics") could assist towards this goal. In this paper, we holistically analyzed full-genome Saccharomyces cerevisiae transcriptional profiling data concerning its glucose- and galactose-grown wild-type (WT) physiology and its glucose-grown gal7-deficient (GAL7Delta) physiology, as these were obtained in the experiment described in Lai and Elsas (Biochem. Biophys. Res. Commun. 2000, 271, 392-400). The gal7 gene encodes for the second enzyme of the galactose assimilation, Leloir, pathway, and its deficiency in humans causes a potentially lethal disease, named "classic galactosemia". Analysis of the galactose-grown compared to the glucose-grown WT physiology indicated a significant increase in the transcriptional expression of the ribosomal machinery and decrease in the transcriptional activity of the fatty acids' beta-oxidation at the peroxisomes. Comparison of GAL7Delta to WT physiology in glucose indicated a significant transcriptional increase in the mitochondrial activity and the rate of catabolism of disaccharides, including sucrose, mannose and trehalose, towards amplified biosynthesis of the main cell wall components. Comparison with other physiological conditions indicated strong correlation between the glucose-grown GAL7Delta transcriptional physiology and the WT growth under glucose derepression conditions. Finally, the acquired results and the large number of still unknown genes that were related to the galactose assimilation regulation indicated the need for further, specifically designed, perturbations and integrated analyses of multiple levels of cellular function.

Sample preparation for chromatography: An African perspective

Africa as a continent has its unique challenges for analytical chemists in sample preparation for chromatographic analyses. The areas of agriculture, environment, food and health provide formidable challenges when it comes to method development, for example, drought can result in inadequate supplies of good quality water. The testing of water quality necessitates the development of assay methods that can be employed to not only determine the quantities of pesticides associated with malaria and tsetse fly eradication programmes, but also to monitor mycotoxins or neurotoxins. Urbanisation has also meant that endocrine disruptors such as phthalate esters need to be monitored. This review will profile some of the activities by analytical chemists practising in the African continent, who seek to address some of the challenges in sample preparation for chromatographic analyses.

An automated procedure for the extraction of metabolic network information from time series data

Novel high-throughput measurement techniques in vivo are beginning to produce dense high-quality time series which can be used to investigate the structure and regulation of biochemical networks. We propose an automated information extraction procedure which takes advantage of the unique S-system structure and supports model building from time traces, curve fitting, model selection, and structure identification based on parameter estimation. The procedure comprises of three modules: model Generation, parameter estimation or model Fitting, and model Selection (GFS algorithm). The GFS algorithm has been implemented in MATLAB and returns a list of candidate S-systems which adequately explain the data and guides the search to the most plausible model for the time series under study. By combining two strategies (namely decoupling and limiting connectivity) with methods of data smoothing, the proposed algorithm is scalable up to realistic situations of moderate size. We illustrate the proposed methodology with a didactic example.

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.

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.

A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles

BACKGROUND

In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law modelling of metabolic pathways from the Jacobian of the targeted system and the steady-state flux profiles by linearization of S-systems.

RESULTS

The results of two case studies modelling a straight and a branched pathway, respectively, showed that our method reduced the number of unknown parameters needing to be estimated. The time-courses simulated by conventional kinetic models and those described by our method behaved similarly under a wide range of perturbations of metabolite concentrations.

CONCLUSION

The proposed method reduces calculation complexity and facilitates the construction of large-scale S-system models of metabolic pathways, realizing a practical application of reverse engineering of dynamic simulation models from the Jacobian of the targeted system and steady-state flux profiles.

Tolerance and adaptation of ethanologenic yeasts to lignocellulosic inhibitory compounds

Synthetic mixtures of predominant lignocellulosic hexose sugars were supplemented with separate aliquots of three inhibitory compounds (furfural, hydroxymethylfurfural (HMF), and acetic acid) in a series of concentrations and fermented by the spent sulfite liquor (SSL)-adapted yeast strain Tembec T1 and the natural isolate Saccharomyces cerevisiae (S. cerevisiae) Y-1528 to compare tolerance and assess fermentative efficacy. The performance of Y-1528 exceeded that of Tembec T1 by a significant margin, with faster hexose sugar consumption, higher ethanol productivity, and in the case of furfural and HMF, faster inhibitor consumption. Nevertheless, furfural had a dose-proportionate effect on sugar consumption rate and ethanol productivity in both strains, but did not substantially affect ethanol yield. HMF had a similar effect on sugar consumption rate and ethanol productivity, and also lowered ethanol yield. Surprisingly, acetic acid had the least impact on sugar consumption rate and ethanol productivity, and stimulated ethanol yield at moderate concentrations. Sequential iterations of softwood (SW) and hardwood (HW) SSL were subsequently inoculated with the two yeast strains in order to compare adaptation to, and performance in lignocellulosic substrates in a cell recycle batch fermentation (CRBF) regime. Both strains were severely affected by the HW SSL, which was attributed to specific syringyl lignin-derived degradation products and synergistic interactions between inhibitors. Though ethanologenic capacity was preserved, a net loss of performance was evident from both strains, indicating the absence of adaptation to the substrates, regardless of the sequence in which the SSL types were employed.

A data integration methodology for systems biology: experimental verification

The integration of data from multiple global assays is essential to understanding dynamic spatiotemporal interactions within cells. In a companion paper, we reported a data integration methodology, designated Pointillist, that can handle multiple data types from technologies with different noise characteristics. Here we demonstrate its application to the integration of 18 data sets relating to galactose utilization in yeast. These data include global changes in mRNA and protein abundance, genome-wide protein-DNA interaction data, database information, and computational predictions of protein-DNA and protein-protein interactions. We divided the integration task to determine three network components: key system elements (genes and proteins), protein-protein interactions, and protein-DNA interactions. Results indicate that the reconstructed network efficiently focuses on and recapitulates the known biology of galactose utilization. It also provided new insights, some of which were verified experimentally. The methodology described here, addresses a critical need across all domains of molecular and cell biology, to effectively integrate large and disparate data sets.

Role of cultivation media in the development of yeast strains for large scale industrial use

The composition of cultivation media in relation to strain development for industrial application is reviewed. Heterologous protein production and pentose utilization by Saccharomyces cerevisiae are used to illustrate the influence of media composition at different stages of strain construction and strain development. The effects of complex, defined and industrial media are compared. Auxotrophic strains and strain stability are discussed. Media for heterologous protein production and for bulk bio-commodity production are summarized.

Is the regulation of galactose 1-phosphate tuned against gene expression noise?

The average number of mRNA molecules per active gene in yeast can be remarkably low. Consequently, the relative number of copies of each transcript per cell can vary greatly from moment to moment. When these transcripts are encoding metabolic enzymes, how do the resulting variations in enzyme concentrations affect the regulation of metabolic intermediates? Using a kinetic model of galactose utilization in yeast, we analysed the transmission of noise from transcription and translation on metabolic intermediate regulation. In particular, the effect of the kinetic properties of the galactose-1-phosphate uridylyltransferase reaction on the transmission of noise was analysed.

Microbial Isoprenoid Production: An Example of Green Chemistry through Metabolic Engineering

Saving energy, cost efficiency, producing less waste, improving the biodegradability of products, potential for producing novel and complex molecules with improved properties, and reducing the dependency on fossil fuels as raw materials are the main advantages of using biotechnological processes to produce chemicals. Such processes are often referred to as green chemistry or white biotechnology. Metabolic engineering, which permits the rational design of cell factories using directed genetic modifications, is an indispensable strategy for expanding green chemistry. In this chapter, the benefits of using metabolic engineering approaches for the development of green chemistry are illustrated by the recent advances in microbial production of isoprenoids, a diverse and important group of natural compounds with numerous existing and potential commercial applications. Accumulated knowledge on the metabolic pathways leading to the synthesis of the principal precursors of isoprenoids is reviewed, and recent investigations into isoprenoid production using engineered cell factories are described.

Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae

Background

The yeast Saccharomyces cerevisiae is an important microorganism for both industrial processes and scientific research. Consequently, there have been extensive efforts to characterize its cellular processes. In order to fully understand the relationship between yeast's genome and its physiology, the stockpiles of diverse biological data sets that describe its cellular components and phenotypic behavior must be integrated at the genome-scale. Genome-scale metabolic networks have been reconstructed for several microorganisms, including S. cerevisiae, and the properties of these networks have been successfully analyzed using a variety of constraint-based methods. Phenotypic phase plane analysis is a constraint-based method which provides a global view of how optimal growth rates are affected by changes in two environmental variables such as a carbon and an oxygen uptake rate. Some applications of phenotypic phase plane analysis include the study of optimal growth rates and of network capacity and function.

Results

In this study, the Saccharomyces cerevisiae genome-scale metabolic network was used to formulate a phenotypic phase plane that displays the maximum allowable growth rate and distinct patterns of metabolic pathway utilization for all combinations of glucose and oxygen uptake rates. In silico predictions of growth rate and secretion rates and in vivo data for three separate growth conditions (aerobic glucose-limited, oxidative-fermentative, and microaerobic) were concordant.

Conclusions

Taken together, this study examines the function and capacity of yeast's metabolic machinery and shows that the phenotypic phase plane can be used to accurately predict metabolic phenotypes and to interpret experimental data in the context of a genome-scale model.

Alternative pathways of galactose assimilation: could inverse metabolic engineering provide an alternative to galactosemic patients?

The galactose assimilation pathway has been extensively studied as an example of a genetic regulatory switch. Besides the importance of this pathway as a tool in basic biological research, unraveling its structure and regulation is also of major medical importance. Impairment of galactose assimilation is the cause of the genetic metabolic disease known as "galactosemia", while the in vivo activity of the pathway affects the production of glycans. The latter have been connected to tumor metastasis, anti-cancer drug resistance and various cardiovascular diseases. Despite the vast amount of studies, however, galactose assimilation and its interaction with other parts of the metabolic network have not been fully elucidated yet. In yeast and higher eukaryotes, it is still being studied as comprising only the linear Leloir pathway. Recent observations, however, indicate that alternative pathways of galactose assimilation identified in prokaryotes and fungi might also be present in yeast. Such a result is valuable per se, because it could lead to the discovery of these pathways in humans. Even more importantly, these pathways provide alternative phenotypes with known genetic fingerprints that can be used in the context of classical and inverse metabolic engineering to examine and treat the mechanisms of defects of galactose assimilation.

An ethanologenic yeast exhibiting unusual metabolism in the fermentation of lignocellulosic hexose sugars

Three lignocellulosic substrate mixtures [liquid fraction of acid-catalyzed steam-exploded softwood, softwood spent sulfite liquor (SSL) and hardwood SSL] were separately fermented by the industrially employed SSL-adapted strain Tembec T1 and a natural galactose-assimilating isolate (Y-1528) of Saccharomyces cerevisiae to compare fermentative efficacy. Both strains were confirmed as S. cerevisiae via molecular genotyping. The performance of strain Y-1528 exceeded that of Tembec T1 on all three substrate mixtures, with complete hexose sugar consumption ranging from 10 to 18 h for Y-1528, vs 24 to 28 h for T1. Furthermore, Y-1528 consumed galactose prior to glucose and mannose, in contrast to Tembec T1, which exhibited catabolite repression of galactose metabolism. Ethanol yields were comparable regardless of the substrate utilized. Strains T1 and Y-1528 were also combined in mixed culture to determine the effects of integrating their distinct metabolic capabilities during defined hexose sugar and SSL fermentations. Sugar consumption in the defined mixture was accelerated, with complete exhaustion of hexose sugars occurring in just over 6 h. Galactose was consumed first, followed by glucose and mannose. Ethanol yields were slightly reduced relative to pure cultures of Y-1528, but normal growth kinetics was not impeded. Sugar consumption in the SSLs was also accelerated, with complete utilization of softwood- and hardwood-derived hexose sugars occurring in 6 and 8 h, respectively. Catabolite repression was absent in both SSL fermentations.

Metabolic analysis of the synthesis of high levels of intracellular human SOD in Saccharomyces cerevisiae rhSOD 2060 411 SGA122

The synthesis of human superoxide dismutase (SOD) in batch cultures of a Saccharomyces cerevisiae strain using a glucose-limited minimal medium was studied through metabolic flux analysis. A stoichiometric model was built, which included 78 reactions, according to metabolic pathways operative in these strains during respirofermentative and oxidative metabolism. It allowed calculation of the distribution of metabolic fluxes during diauxic growth on glucose and ethanol. Fermentation profiles and metabolic fluxes were analyzed at different phases of diauxic growth for the recombinant strain (P+) and for its wild type (P-). The synthesis of SOD by the strain P+ resulted in a decrease in specific growth rate of 34 and 54% (growth on glucose and ethanol respectively) in comparison to the wild type. Both strains exhibited similar flux of glucose consumption and ethanol synthesis but important differences in carbon distribution with biomass/substrate yields and ATP production 50% higher in P-. A higher contribution of fermentative metabolism, with 64% of the energy produced at the phosphorylation level, was observed during SOD production. The flux of precursors to amino acids and nucleotides was higher in the recombinant strain, in agreement with the higher total RNA and protein levels. Lower specific growth rates in strain P+ appear to be related to the decrease in the rate of synthesis of nonrecombinant protein, as well as a decrease in the activities of the pentose phosphate (PP) pathway and TCA cycle. A very different way of entry into the stationary phase was observed for each strain: in the wild-type strain most metabolic fluxes decreased and fluxes related to energy reserve synthesis increased, while in the P+ strain the flux of 22 reactions (including PP pathway and amino acids biosynthesis) related to SOD production increased their fluxes. Changes in SOD production rates at different physiological states appear to be related to the differences in building blocks availability between respirofermentative and oxidative metabolism. Using the present expression system, ideal conditions for SOD synthesis are represented by either active growth during respirofermentative metabolism or transition from a growing to a nongrowing state. An increase in SOD flux could be achieved using an expression system nonassociated to growth and potentially eliminating part of the metabolic burden.

Galactose-1-phosphate is a regulator of inositol monophosphatase: a fact or a fiction?

Classic galactosemia is due to the deficiency of galactose-1-phosphate uridyl transferase and is transmitted as an autosomal recessive disorder. Patients suffering from classic galactosemia display acute symptoms such as poor growth, feeding difficulties, jaundice, hepatomegaly etc., which disappear when the individual is on galactose free diet. However, these patients continue to suffer from defects such as neurological disturbances and ovarian dysfunction, due to the accumulation of galactose-1-phosphate, which is a normal intermediate of galactose metabolism. The biochemical mechanism of galactose-1-phosphate mediated toxicity is still an enigma. Recent experiments strongly suggest that galactose-1-phosphate is also a substrate for inositol monophosphatase (IMPase). Phosphatidylinositol bisphosphate [PI(P)2] dependent signaling serves as a second messenger for several neurotransmitters in the brain. Therefore, the brain is critically dependent on IMPase for the supply of free inositol in order to sustain [PI(P)2] signaling. Circumstantial evidence strongly supports the possibility that being a substrate, galactose-1-phosphate could modulate IMPase function in vivo. The implication of this idea is discussed in relation to classic galactosemia as well as bipolar disorder, which has been thought to be due to the hyper-activation of [PI(P)2] mediated second messenger pathways(s).

Molecular characterization of MRG19 of Saccharomyces cerevisiae. Implication in the regulation of galactose and nonfermentable carbon source utilization

We have reported previously that multiple copies of MRG19 suppress GAL genes in a wild-type but not in a gal80 strain of Saccharomyces cerevisiae. In this report we show that disruption of MRG19 leads to a decrease in GAL induction when S. cerevisiae is induced with 0.02% but not with 2.0% galactose. Disruption of MRG19 in a gal3 background (this strain shows long-term adaptation phenotype) further delays the GAL induction, supporting the notion that its function is important only under low inducing signals. As a corollary, disruption of MRG19 in a gal80 strain did not decrease the constitutive expression of GAL genes. These results suggest that MRG19 has a role in GAL regulation only when the induction signal is weak. Unlike the effect on GAL gene expression, disruption of MRG19 leads to de-repression of CYC1-driven beta-galactosidase activity. MRG19 disruptant also showed a twofold increase in the rate of oxygen uptake as compared with the wild-type strain. ADH2, CTA1, DLD1, and CYC7 promoters that are active during nonfermentative growth did not show any de-repression of beta-galactosidase activity in the MRG19 disruptant. Western blot analysis indicated that MRG19 is a glucose repressible gene and is expressed in galactose and glycerol plus lactate. Experiments using green fluorescent protein fusion constructs indicate that Mrg19p is localized in the nucleus consistent with the presence of a consensus nuclear localization signal sequence. Based on the above results, we propose that Mrg19p is a regulator of galactose and nonfermentable carbon utilization.

Monitoring on-line desalted lignocellulosic hydrolysates by microdialysis sampling micro-high performance anion exchange chromatography with integrated pulsed electrochemical detection/mass spectrometry

An on-line system based on microdialysis sampling (MD), micro-high performance anion exchange chromatography (micro-HPAEC), integrated pulsed electrochemical detection (IPED), and electrospray ionization mass spectrometry (MS) for the monitoring of on-line desalted enzymatic hydrolysates is presented. Continuous monitoring of the enzymatic degradation of dissolving pulp from Eucalyptus grandis as well as degradation of sugar cane bagasse in a 5-mL reaction vessel was achieved up to 24 h without any additional sample handling steps. Combining MD with micro-HPAEC-IPED/MS and on-line desalting of hydrolysates enabled injection (5 microL) of at least 23 samples in a study of the sequential action of hydrolytic enzymes in an unmodified environment where the enzymes and substrate were not depleted due to the perm-selectivity of the MD membrane (30 kDa cut-off). Xylanase, phenolic acid esterase and a combination of endoglucanase (EG II) with cellobiohydrolase (CBH I) resulted in the production of DP 1 after the addition of esterase, DP 2 and DP 3 after the addition of EG II and CBH I, from the dissolving pulp substrate. Similar sequential enzyme addition to sugar cane bagasse resulted in DP 1 production after the addition of esterase and DP 1, DP 2 and DP 3 production after the addition of the EG II and CBH I mixture. Combining MS on-line with micro-HPAEC-IPED proved to be a versatile and necessary tool for such a study compared to conventional methods. The mass selectivity of MS revealed complementary information, including the co-elution of saccharides as well as the presence of more than one type of DP 2 in the case of dissolving pulp and several types of DP 2 and DP 3 for sugar cane bagasse. This study demonstrates the limitation of the use of retention time alone for confirmation of the identity of saccharides especially when dealing with complex enzymatic hydrolysates. In situ sampling and sample clean-up combined with on-line desalting of the chromatographic effluent, provides a generic approach to achieve real time monitoring of enzymatic hydrolysates when they are detected by a combination of IPED and MS.