Signal transduction dynamics of the protein kinase-A/phosphofructokinase-2 system in Saccharomyces cerevisiae

Two wrongs do not make a right: the assumption that an inhibitor acts as an inverse activator

Models of biochemical networks are often large intractable sets of differential equations. To make sense of the complexity, relationships between genes/proteins are presented as connected graphs, the edges of which are drawn to indicate activation or inhibition relationships. These diagrams are useful for drawing qualitative conclusions in many cases by the identifying recurring of topological motifs, for example positive and negative feedback loops. These topological features are usually classified under the presumption that activation and inhibition are inverse relationships. For example, inhibition of an inhibitor is often classified the same as activation of an activator within a motif classification, effectively treating them as equivalent. Whilst in many contexts this may not lead to catastrophic errors, drawing conclusions about the behavior of motifs, pathways or networks from these broad classes of topological feature without adequate mathematical descriptions can lead to obverse outcomes. We investigate the extent to which a biochemical pathway/network will behave quantitatively dissimilar to pathway/ networks with similar typologies formed by swapping inhibitors as the inverse of activators. The purpose of the study is to determine under what circumstances rudimentary qualitative assessment of network structure can provide reliable conclusions as to the quantitative behaviour of the network. Whilst there are others, We focus on two main mathematical qualities which may cause a divergence in the behaviour of two pathways/networks which would otherwise be classified as similar; (i) a modelling feature we label 'bias' and (ii) the precise positioning of activators and inhibitors within simple pathways/motifs.

Metabolomic and (13)C-metabolic flux analysis of a xylose-consuming Saccharomyces cerevisiae strain expressing xylose isomerase

Over the past two decades, significant progress has been made in the engineering of xylose-consuming Saccharomyces cerevisiae strains for production of lignocellulosic biofuels. However, the ethanol productivities achieved on xylose are still significantly lower than those observed on glucose for reasons that are not well understood. We have undertaken an analysis of central carbon metabolite pool sizes and metabolic fluxes on glucose and on xylose under aerobic and anaerobic conditions in a strain capable of rapid xylose assimilation via xylose isomerase in order to investigate factors that may limit the rate of xylose fermentation. We find that during xylose utilization the flux through the non-oxidative Pentose Phosphate Pathway (PPP) is high but the flux through the oxidative PPP is low, highlighting an advantage of the strain employed in this study. Furthermore, xylose fails to elicit the full carbon catabolite repression response that is characteristic of glucose fermentation in S. cerevisiae. We present indirect evidence that the incomplete activation of the fermentation program on xylose results in a bottleneck in lower glycolysis, leading to inefficient re-oxidation of NADH produced in glycolysis.

Life in the midst of scarcity: adaptations to nutrient availability in Saccharomyces cerevisiae

Cells of all living organisms contain complex signal transduction networks to ensure that a wide range of physiological properties are properly adapted to the environmental conditions. The fundamental concepts and individual building blocks of these signalling networks are generally well-conserved from yeast to man; yet, the central role that growth factors and hormones play in the regulation of signalling cascades in higher eukaryotes is executed by nutrients in yeast. Several nutrient-controlled pathways, which regulate cell growth and proliferation, metabolism and stress resistance, have been defined in yeast. These pathways are integrated into a signalling network, which ensures that yeast cells enter a quiescent, resting phase (G0) to survive periods of nutrient scarceness and that they rapidly resume growth and cell proliferation when nutrient conditions become favourable again. A series of well-conserved nutrient-sensory protein kinases perform key roles in this signalling network: i.e. Snf1, PKA, Tor1 and Tor2, Sch9 and Pho85-Pho80. In this review, we provide a comprehensive overview on the current understanding of the signalling processes mediated via these kinases with a particular focus on how these individual pathways converge to signalling networks that ultimately ensure the dynamic translation of extracellular nutrient signals into appropriate physiological responses.

Deterministic mathematical models of the cAMP pathway in Saccharomyces cerevisiae

BACKGROUND

Cyclic adenosine monophosphate (cAMP) has a key signaling role in all eukaryotic organisms. In Saccharomyces cerevisiae, it is the second messenger in the Ras/PKA pathway which regulates nutrient sensing, stress responses, growth, cell cycle progression, morphogenesis, and cell wall biosynthesis. A stochastic model of the pathway has been reported.

RESULTS

We have created deterministic mathematical models of the PKA module of the pathway, as well as the complete cAMP pathway. First, a simplified conceptual model was created which reproduced the dynamics of changes in cAMP levels in response to glucose addition in wild-type as well as cAMP phosphodiesterase deletion mutants. This model was used to investigate the role of the regulatory Krh proteins that had not been included previously. The Krh-containing conceptual model reproduced very well the experimental evidence supporting the role of Krh as a direct inhibitor of PKA. These results were used to develop the Complete cAMP Model. Upon simulation it illustrated several important features of the yeast cAMP pathway: Pde1p is more important than is Pde2p for controlling the cAMP levels following glucose pulses; the proportion of active PKA is not directly proportional to the cAMP level, allowing PKA to exert negative feedback; negative feedback mechanisms include activating Pde1p and deactivating Ras2 via phosphorylation of Cdc25. The Complete cAMP model is easier to simulate, and although significantly simpler than the existing stochastic one, it recreates cAMP levels and patterns of changes in cAMP levels observed experimentally in vivo in response to glucose addition in wild-type as well as representative mutant strains such as pde1Delta, pde2Delta, cyr1Delta, and others. The complete model is made available in SBML format.

CONCLUSION

We suggest that the lower number of reactions and parameters makes these models suitable for integrating them with models of metabolism or of the cell cycle in S. cerevisiae. Similar models could be also useful for studies in the human pathogen Candida albicans as well as other less well-characterized fungal species.

Modelling dynamic processes in yeast

Yeast molecular and cell biology has accumulated large amounts of qualitative and quantitative data of diverse cellular processes. The results are often summarized as verbal or graphical descriptions. Moreover, a series of mathematical models has been developed that should help to interpret such data, to integrate them into a coherent picture and to allow for an understanding of the underlying processes. Dynamic modelling of regulatory processes in yeast focuses on central carbon metabolism, on a number of selected signalling pathways and on cell cycle regulation. These models can explain questions of general relevance, such as whether the dynamics of a network can be understood from the combination of in vitro kinetics of its individual reactions. They help to elucidate complicated dynamic features, such as glycolytic oscillations, effects of feedback regulation or the optimal regulation of gene expression. The availability of comprehensive qualitative information, such as protein interactions or pathway composition, and sets of quantitative data make yeast a perfect model organism. Therefore, yeast-related data are often used to develop and examine computational approaches and modelling methods.

Mathematical modeling of intracellular signaling pathways

Dynamic modeling and simulation of signal transduction pathways is an important topic in systems biology and is obtaining growing attention from researchers with experimental or theoretical background. Here we review attempts to analyze and model specific signaling systems. We review the structure of recurrent building blocks of signaling pathways and their integration into more comprehensive models, which enables the understanding of complex cellular processes. The variety of mechanisms found and modeling techniques used are illustrated with models of different signaling pathways. Focusing on the close interplay between experimental investigation of pathways and the mathematical representations of cellular dynamics, we discuss challenges and perspectives that emerge in studies of signaling systems.

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.

Analysis of in vivo kinetics of glycolysis in aerobic Saccharomyces cerevisiae by application of glucose and ethanol pulses

This article presents the dynamic responses of several intra- and extracellular components of an aerobic, glucose-limited chemostat culture of Saccharomyces cerevisiae to glucose and ethanol pulses within a time window of 75 sec. Even though the ethanol pulse cannot perturb the glycolytic pathway directly, a distinct response of the metabolites at the lower part of glycolysis was found. We suggest that this response is an indirect effect, caused by perturbation of the NAD/NADH ratio, which is a direct consequence of the conversion of ethanol into acetaldehyde. This effect of the NAD/NADH ratio on glycolysis might serve as an additional explanation for the observed decrease of 3PG, 2PG, and PEP during a glucose pulse. The responses measured during the ethanol pulse were used to evaluate the allosteric regulation of glycolysis. Our results confirm that FBP stimulates pyruvate kinase and suggest that this effect is pronounced. Furthermore, it appears that PEP does not play an important role in the allosteric regulation of phosphofructo kinase.

Cyclic AMP mediates the cell cycle dynamics of energy metabolism in Saccharomyces cerevisiae

We have investigated the role of 3',5'-cyclic-adenosine-monophosphate (cAMP) in mediating the coupling between energy metabolism and cell cycle progression in both synchronous cultures and oscillating continuous cultures of Saccharomyces cerevisiae. For the first time, a peak in intracellular cAMP was shown to precede the observed breakdown of trehalose and glycogen during cell cycle-related oscillations. Measurements in synchronous cultures demonstrated that this peak can be associated with the cell cycle dynamics of cAMP under conditions of glucose-limited growth, which was found to differ significantly from that observed in synchronous glucose-repressed cultures. Our results support the notion that cAMP plays a major role in mediating the integration of energy metabolism and cell cycle progression, both in the single cell and during cell cycle-related oscillations in continuous culture, respectively. Evidence is presented that the dynamic behaviour of intracellular cAMP during the cell cycle is modulated depending on nutrient supply. The implications of these findings regarding the role of cAMP in regulating cell cycle progression and energy metabolism are discussed.