Kinetic study and modelling of the xylitol production using Candida parapsilosis in oxygen-limited culture conditions

Kinetic studies are presented for xylitol production and growth of the yeast Candida parapsilosis ATCC 28474. The oxygen supply influence on xylitol production from xylose was investigated. No metabolic activity was detected in anaerobic conditions. In contrast, it was found that under low aeration rates (0.1-0.2 vvm), xylitol is produced. Xylitol production decreases when air flow to reactor is augmented. An unstructured model is proposed for the kinetic behaviour analysis of yeast growing in batch culture. A simplex method was used for the estimation of model parameters. The parameter confidence intervals were also calculated.     

A small metabolic flux model to identify transient metabolic regulations in Saccharomyces cerevisiae

The understanding of dynamic metabolic regulations is important for physiological studies and strain characterization tasks. The present study combined transient experiments with online metabolic flux analysis (MFA) in order to quantify metabolic regulations, namely carbon catabolite repression of respiration and transient acetic-acid production, in Saccharomyces cerevisiae during aerobic growth on glucose. The aim was to investigate which additional information can be gained from using a small metabolic flux model to study transient growth provoked by shift-up and shift-down experiments, compared to online monitoring alone. The MFA model allowed us to propose new correlations between pathways of the central metabolism. A linear correlation between glycolytic flux and respiratory capacity holds for shift-down and shift-up experiments. This confirmed that respiratory functions were subjected to carbon catabolite repression and suggested that respiratory capacity is controlled by the glycolytic flux rather than the glucose influx. Furthermore, the model showed that control of repression of respiration by the glycolytic flux was a dynamic phenomenon. Co-factor balancing within the MFA model showed that transient acetic-acid production indicated a transient limitation in another part of the central metabolism but not in oxidative phosphorylation. However, at super-critical growth rates and when coupling of anabolism and catabolism is resumed, the limitation shifts to oxidative phosphorylation, with the consequence that ethanol is formed. The online application of small metabolic flux models to transient experiments enhanced the physiological insight into transient growth and opens up the use of transient experiments as an efficient tool to understand dynamic metabolic regulations.     

Utilization of Saccharomyces cerevisiae recombinant strain incapable of both ethanol and glycerol biosynthesis for anaerobic bioproduction

The yeast Saccharomyces cerevisiae produces ethanol and glycerol as major unwanted byproducts, unless ethanol and glycerol are the target compounds. Minimizing the levels of these byproducts is important for bioproduction processes using yeast cells. In this study, we constructed a yeast strain in which both ethanol and glycerol production pathways were disrupted and examined its culture characteristics. In wild-type yeast strain, metabolic pathways that produce ethanol and glycerol play an important role in reoxidizing nicotinamide adenine dinucleotide (NADH) generated during glycolysis, particularly under anaerobic conditions. Strains in which both pathways were disrupted therefore failed to grow and consume glucose under anaerobic conditions. Introduction of desired metabolic reaction(s) coupled with NADH oxidation enabled the engineered strain to consume substrate and produce target compound(s). Here we introduced NADH-oxidization-coupled L-lactate production mechanisms into a yeast strain incapable of ethanol and glycerol biosynthesis, based on in silico simulation using a genome-scale metabolic model of S. cerevisiae. From the results of in silico simulation based on flux balance analysis, a feasible anaerobic non-growing metabolic state, in which L-lactate yield approached the theoretical maximum, was identified and this phenomenon was verified experimentally. The yeast strain incapable of both ethanol and glycerol biosynthesis is a potentially valuable host for bioproduction coupled with NADH oxidation under anaerobic conditions.     

Comprehensive quantitative analysis of central carbon and amino‐acid metabolism in Saccharomyces cerevisiae under multiple conditions by targeted proteomics

Decades of biochemical research have identified most of the enzymes that catalyze metabolic reactions in the yeast Saccharomyces cerevisiae. The adaptation of metabolism to changing nutritional conditions, in contrast, is much less well understood. As an important stepping stone toward such understanding, we exploit the power of proteomics assays based on selected reaction monitoring (SRM) mass spectrometry to quantify abundance changes of the 228 proteins that constitute the central carbon and amino‐acid metabolic network in the yeast Saccharomyces cerevisiae, at five different metabolic steady states. Overall, 90% of the targeted proteins, including families of isoenzymes, were consistently detected and quantified in each sample, generating a proteomic data set that represents a nutritionally perturbed biological system at high reproducibility. The data set is near comprehensive because we detect 95–99% of all proteins that are required under a given condition. Interpreted through flux balance modeling, the data indicate that S. cerevisiae retains proteins not necessarily used in a particular environment. Further, the data suggest differential functionality for several metabolic isoenzymes.     

Determination of metabolic flux changes during fed-batch cultivation from measurements of intracellular amino acids by LC-MS/MS

Metabolic flux analysis using (13)C-labeled substrates is a well-developed method for investigating cellular behavior in steady-state culture condition. To extend its application, in particular to typical industrial conditions, such as batch and fed-batch cultivations, a novel method of (13)C metabolic flux analysis is proposed. An isotopomer balancing model was developed to elucidate flux distributions in the central metabolism and all amino acids synthetic pathways. A lysine-producing strain of Escherichia coli was cultivated by fed-batch mode in a growth medium containing yeast extract. Mass distribution data was derived from both intracellular free amino acids and proteinogenic amino acids measured by LC-MS/MS, and a correction parameter for the protein turnover effect on the mass distributions of intracellular amino acids was introduced. Metabolic flux distributions were determined in both exponential and stationary phases. Using this new approach, a culture phase-dependent metabolic shift was detected in the fed-batch culture. The approach presented here has great potential for investigating cellular behavior in industrial processes, independent of cultivation modes, metabolic phase and growth medium.     

Influences of yeast extract on specific cellular yield of Ovine growth hormone during fed-batch fermentation of E. coli

In most cases of E. coli high cell density fermentation process, maximizing cell concentration helps in increasing the volumetric productivity of recombinant proteins usually at the cost of lower specific cellular protein yield. In this report, we describe a process for maintaining the specific cellular yield of Ovine growth hormone (oGH) from E. coli by optimal feeding of yeast extract during high cell density fermentation process. Recombinant oGH was produced as inclusion bodies in Escherichia coli. Specific cellular yield of recombinant oGH was maintained by feeding yeast extract along with glucose during fed-batch fermentation. Glucose to yeast extract ratio of 0.75 was found to be optimum for maintaining the specific cellular oGH yield of 66 mg/g of E. coli cells. Continuous feeding of yeast extract along with glucose helped in reducing acetic acid secretion and promoted higher cell growth during fed-batch fermentation. High cell growth of E. coli and high specific yield of recombinant oGH thus helped in achieving high volumetric productivity of the expressed protein. A maximum of 2 g/l of ovine growth hormone was expressed as inclusion bodies in 12 h of fed-batch fermentation.     

Pathway analysis of Pichia pastoris to elucidate methanol metabolism and its regulation for production of recombinant proteins

This research rationally analyzes metabolic pathways of Pichia pastoris to study the metabolic flux responses of this yeast under methanol metabolism. A metabolic model of P. pastoris was constructed and analyzed by elementary mode analysis (EMA). EMA was used to comprehensively identify the cell's metabolic flux profiles and its underlying regulation mechanisms for the production of recombinant proteins from methanol. Change in phenotypes and flux profiles during methanol adaptation with varying feed mixture of glycerol and methanol was examined. EMA identified increasing and decreasing fluxes during the glycerol–methanol metabolic shift, which well agreed with experimental observations supporting the validity of the metabolic network model. Analysis of all the identified pathways also led to the determination of the metabolic capacities as well as the optimum metabolic pathways for recombinant protein synthesis during methanol induction. The network sensitivity analysis revealed that the production of proteins can be improved by manipulating the flux ratios at the pyruvate branch point. In addition, EMA suggested that protein synthesis is optimum under hypoxic culture conditions. The metabolic modeling and analysis presented in this study could potentially form a valuable knowledge base for future research on rational design and optimization of P. pastoris by determining target genes, pathways, and culture conditions for enhanced recombinant protein synthesis. The metabolic pathway analysis is also of considerable value for production of therapeutic proteins by P. pastoris in biopharmaceutical applications. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:28–37, 2014     

Stream insects as passive suspension feeders: effects of velocity and food concentration on feeding performance

Benthic suspension feeders are important components of aquatic ecosystems, often dominating the use of space and influencing patterns of material cycling between the water column and benthos. Biomechanical theory predicts that feeding by these consumers is governed by the flux (i.e., product of food concentration and velocity) of particulate material to their feeding appendages. We performed a laboratory flume experiment to test how feeding by larval black flies (Simulium vittatum Zett.) responds to independent manipulations of flow and food concentration. We quantified larval body posture, flick rate of the labral fans, and ingestion rate as a function of two concentrations of a baker's yeast/chalk suspension (0.96 and 4.44 mg l^-1) and five water velocities (20, 30, 45, 60, and 90 cm s^-1). Using analysis of covariance, we found that both flick rate and ingestion rate increased in a decelerating manner with increasing velocity, while fan height decreased linearly with increasing velocity. In contrast, food concentration had no effect on any aspect of feeding behavior. Thus, although both velocity and food concentration contribute to particle flux, our results indicate that the two were not substitutable under the range of conditions tested here.     

Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks

Constraint-based flux balance analysis (FBA) has proven successful in predicting the flux distribution of metabolic networks in diverse environmental conditions. FBA finds one of the alternate optimal solutions that maximizes the biomass production rate. Almaas et al. have shown that the flux distribution follows a power law, and it is possible to associate with most metabolites two reactions which maximally produce and consume a given metabolite, respectively. This observation led to the concept of high-flux backbone (HFB) in metabolic networks. In previous work, the HFB has been computed using a particular optima obtained using FBA. In this paper, we investigate the conservation of HFB of a particular solution for a given medium across different alternate optima and near-optima in metabolic networks of E. coli and S. cerevisiae. Using flux variability analysis (FVA), we propose a method to determine reactions that are guaranteed to be in HFB regardless of alternate solutions. We find that the HFB of a particular optima is largely conserved across alternate optima in E. coli, while it is only moderately conserved in S. cerevisiae. However, the HFB of a particular near-optima shows a large variation across alternate near-optima in both organisms. We show that the conserved set of reactions in HFB across alternate near-optima has a large overlap with essential reactions and reactions which are both uniquely consuming (UC) and uniquely producing (UP). Our findings suggest that the structure of the metabolic network admits a high degree of redundancy and plasticity in near-optimal flow patterns enhancing system robustness for a given environmental condition.     

Is maximization of molar yield in metabolic networks favoured by evolution?

Stoichiometric analysis of metabolic networks allows the calculation of possible metabolic flux distributions in the absence of kinetic data. In order to predict which of the possible fluxes are present under certain conditions, additional constraints and optimization principles can be applied. One approach of calculating unknown fluxes (frequently called flux balance analysis) is based on the optimality principle of maximizing the molar yield of biotransformations. Here, the relevance and applicability of that approach are examined, and it is compared with the principle of maximizing pathway flux. We discuss diverse experimental evidence showing that, often, those biochemical pathways are operative that allow fast but low-yield synthesis of important products, such as fermentation in Saccharomyces cerevisiae and several other yeast species. Together with arguments based on evolutionary game theory, this leads us to the conclusion that maximization of molar yield is by no means a universal principle.     

13C Metabolic Flux Analysis of acetate conversion to lipids by Yarrowia lipolytica

Volatile fatty acids (VFAs) are an inexpensive and renewable carbon source that can be generated from gas fermentation and anaerobic digestion of fermentable wastes. The oleaginous yeast Yarrowia lipolytica is a promising biocatalyst that can utilize VFAs and convert them into triacylglycerides (TAGs). However, currently there is limited knowledge on the metabolism of Y. lipolytica when cultured on VFAs. To develop a better understanding, we used acetate as the sole carbon source to culture two strains, a control strain and a previously engineered strain for lipid overaccumulation. For both strains, metabolism during the growth phase and lipid production phase were investigated by metabolic flux analysis using two parallel sodium acetate tracers. The resolved flux distributions demonstrate that the glyoxylate shunt pathway is constantly active and the flux through gluconeogenesis varies depending on strain and phase. In particular, by regulating the activities of malate transport and pyruvate kinase, the cells divert only a portion of the glyoxylate shunt flux required to satisfy the needs for anaplerotic reactions and NADPH production through gluconeogenesis and the oxidative pentose phosphate pathway (PPP). Excess flux flows back to the tricarboxylic acid (TCA) cycle for energy production. As with the case of glucose as the substrate, the primary source for lipogenic NADPH is derived from the oxidative PPP.     

Origin of cytoplasm substituted rice cultivars found in Japan

Genetic variation of Japanese rice cultivars were examined. Five of 450 lowland cultivars and another five of 200 upland cultivars were determined as the indica type by using isozyme genotypes and the remainder were of the japonica type. The major characteristics of these indica cultivars, revealed a slender shape of grains, a short apiculus hair length, a positive allele for Ph reaction, and allele-3 for the Pgd1 locus. Three of these indica cultivars showed a non-deletion ORF100, which is essential to the japonica-type plastid. The plastid subtype identity (PS-ID) sequences of these plastids is 6C7A, which is also a japonica-specific repeat unit. Thus, these cultivars were concluded to be naturally generated cytoplasm substituted lines. These plastids were introduced into a indica genetic background from japonica cultivars grown elsewhere. The rest of the indica cultivars revealed a deletion-type ORF100 and plastid subtype 8C8A, both of which are indica-specific. These cultivars carried indica-type allelic constitutions for diagnostic isozyme loci. However, other characters were identical to the cytoplasm-substituted cultivars in Japan. In East and Southeast Asia, cultivars carrying a indica-type nuclear genotype with a japonica-type plastid are restricted to Aus cultivars in the Bengal region. Genetic and historical records suggest that Japanese indica cultivars and the Aus cultivars are closely related. The Aus cultivars acquire necessary genetic constitutions from both indica and japonica cultivars through naturally occurring out-crossing to adapt to a particular cultivation condition in the region. The wide adaptability enabled them to be introduced into a northern region like Japan.     

Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems

The elucidation of organism-scale metabolic networks necessitates the development of integrative methods to analyze and interpret the systemic properties of cellular metabolism. A shift in emphasis from single metabolic reactions to systemically defined pathways is one consequence of such an integrative analysis of metabolic systems. The constraints of systemic stoichiometry, and limited thermodynamics have led to the definition of the flux space within the context of convex analysis. The flux space of the metabolic system, containing all allowable flux distributions, is constrained to a convex polyhedral cone in a high-dimensional space. From metabolic pathway analysis, the edges of the high-dimensional flux cone are vectors that correspond to systemically defined "extreme pathways" spanning the capabilities of the system. The addition of maximum flux capacities of individual metabolic reactions serves to further constrain the flux space and has led to the development of flux balance analysis using linear optimization to calculate optimal flux distributions. Here we provide the precise theoretical connections between pathway analysis and flux balance analysis allowing for their combined application to study integrated metabolic function. Shifts in metabolic behavior are calculated using linear optimization and are then interpreted using the extreme pathways to demonstrate the concept of pathway utilization. Changes to the reaction network, such as the removal of a reaction, can lead to the generation of suboptimal phenotypes that can be directly attributed to the loss of pathway function and capabilities. Optimal growth phenotypes are calculated as a function of environmental variables, such as the availability of substrate and oxygen, leading to the definition of phenotypic phase planes. It is illustrated how optimality properties of the computed flux distributions can be interpreted in terms of the extreme pathways. Together these developments are applied to an example network and to core metabolism of Escherichia coli demonstrating the connections between the extreme pathways, optimal flux distributions, and phenotypic phase planes. The consequences of changing environmental and internal conditions of the network are examined for growth on glucose and succinate in the face of a variety of gene deletions. The convergence of the calculation of optimal phenotypes through linear programming and the definition of extreme pathways establishes a different perspective for the understanding of how a defined metabolic network is best used under different environmental and internal conditions or, in other words, a pathway basis for the interpretation of the metabolic reaction norm.     

Genome-Scale NAD(H/+) Availability Patterns as a Differentiating Feature between Saccharomyces cerevisiae and Scheffersomyces stipitis in Relation to Fermentative Metabolism

Scheffersomyces stipitis is a yeast able to ferment pentoses to ethanol, unlike Saccharomyces cerevisiae, it does not present the so-called overflow phenomenon. Metabolic features characterizing the presence or not of this phenomenon have not been fully elucidated. This work proposes that genome-scale metabolic response to variations in NAD(H/⁺) availability characterizes fermentative behavior in both yeasts. Thus, differentiating features in S. stipitis and S. cerevisiae were determined analyzing growth sensitivity response to changes in available reducing capacity in relation to ethanol production capacity and overall metabolic flux span. Using genome-scale constraint-based metabolic models, phenotypic phase planes and shadow price analyses, an excess of available reducing capacity for growth was found in S. cerevisiae at every metabolic phenotype where growth is limited by oxygen uptake, while in S. stipitis this was observed only for a subset of those phenotypes. Moreover, by using flux variability analysis, an increased metabolic flux span was found in S. cerevisiae at growth limited by oxygen uptake, while in S. stipitis flux span was invariant. Therefore, each yeast can be characterized by a significantly different metabolic response and flux span when growth is limited by oxygen uptake, both features suggesting a higher metabolic flexibility in S. cerevisiae. By applying an optimization-based approach on the genome-scale models, three single reaction deletions were found to generate in S. stipitis the reducing capacity availability pattern found in S. cerevisiae, two of them correspond to reactions involved in the overflow phenomenon. These results show a close relationship between the growth sensitivity response given by the metabolic network and fermentative behavior.     

The thermodynamic meaning of metabolic exchange fluxes

Metabolic flux analysis (MFA) deals with the experimental determination of steady-state fluxes in metabolic networks. An important feature of the ¹³C MFA method is its capability to generate information on both directions of bidirectional reaction steps given by exchange fluxes. The biological interpretation of these exchange fluxes and their relation to thermodynamic properties of the respective reaction steps has never been systematically investigated. As a central result, it is shown here that for a general class of enzyme reaction mechanisms the quotients of net and exchange fluxes measured by ¹³C MFA are coupled to Gibbs energies of the reaction steps. To establish this relation the concept of apparent flux ratios of enzymatic isotope-labeling networks is introduced and some computing rules for these flux ratios are given. Application of these rules reveals a conceptional pitfall of ¹³C MFA, which is the inherent dependency of measured exchange fluxes on the chosen tracer atom. However, it is shown that this effect can be neglected for typical biochemical reaction steps under physiological conditions. In this situation, the central result can be formulated as a two-sided inequality relating fluxes, pool sizes, and standard Gibbs energies. This relation has far-reaching consequences for metabolic flux analysis, quantitative metabolomics, and network thermodynamics.     

Metabolic engineering under uncertainty--II: analysis of yeast metabolism

Yeast metabolism has been used extensively in scientific investigations and industrial applications. Understanding the properties of the yeast metabolic network is crucial, yet unaccomplished due to its high complexity, the different culture conditions, and the uncertainty associated with kinetic parameters. We recently developed a computational and mathematical framework using Monte Carlo method in which parameter uncertainty can be addressed through large-scale sampling procedure. This framework was applied on the compartmentalized central carbon pathways of Saccharomyces cerevisiae metabolism considering the growth environment of batch and chemostat reactor and integrating information from metabolic flux analysis. Statistical analysis of the results indicates that yeast cells growing in batch culture condition exhibit dramatically different control schemes from those growing in a chemostat. The difference is mainly due to the feedback introduced by the constraints of the chemostat. The control of the enzymes on the rates of the substrate uptake, product excretion, and cell growth and its practical implication are discussed. Clustering of the reaction steps according to the similarity of their responses to enzyme activity perturbations reveals functional coupling of metabolic reactions.     

System-level insights into yeast metabolism by thermodynamic analysis of elementary flux modes

One of the most obvious phenotypes of a cell is its metabolic activity, which is defined by the fluxes in the metabolic network. Although experimental methods to determine intracellular fluxes are well established, only a limited number of fluxes can be resolved. Especially in eukaryotes such as yeast, compartmentalization and the existence of many parallel routes render exact flux analysis impossible using current methods. To gain more insight into the metabolic operation of S. cerevisiae we developed a new computational approach where we characterize the flux solution space by determining elementary flux modes (EFMs) that are subsequently classified as thermodynamically feasible or infeasible on the basis of experimental metabolome data. This allows us to provably rule out the contribution of certain EFMs to the in vivo flux distribution. From the 71 million EFMs in a medium size metabolic network of S. cerevisiae, we classified 54% as thermodynamically feasible. By comparing the thermodynamically feasible and infeasible EFMs, we could identify reaction combinations that span the cytosol and mitochondrion and, as a system, cannot operate under the investigated glucose batch conditions. Besides conclusions on single reactions, we found that thermodynamic constraints prevent the import of redox cofactor equivalents into the mitochondrion due to limits on compartmental cofactor concentrations. Our novel approach of incorporating quantitative metabolite concentrations into the analysis of the space of all stoichiometrically feasible flux distributions allows generating new insights into the system-level operation of the intracellular fluxes without making assumptions on metabolic objectives of the cell.