In vivo analysis of metabolic dynamics inSaccharomyces cerevisiae : I. Experimental observations

Theobald, Uwe; Mailinger, Werner; Baltes, Michael; Rizzi, Manfred; Reuß, Matthias

doi:10.1002/(sici)1097-0290(19970720)55:2<305::aid-bit8>3.0.co;2-m

Cited by 327 publications

(262 citation statements)

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“…For the pathway from glucose to glycerol, expression of genes encoding the following enzymes is induced upon hyperosmotic shock: Glk1 and Hxk1 (glucokinase and hexokinase isoform I), as well as Gpd1, Gpp1 and Gpp2. Comprehensive models of yeast carbohydrate metabolism have been reported previously 37,[39][40][41] . For the purpose of this study we combined several metabolic reactions taking into account gene expression changes: glucose uptake (v 1 ), sugar phosphorylation (v 2 ), phosphoglucoisomerase and phosphofructokinase (v 3 ), aldolase (v 4 ), triosephosphate isomerase (v 5 ), the lower part of glycolysis from glyceraldehyde-3-phosphate to pyruvate (v 6 ), the TCA cycle (v 7 ), formation of ethanol from pyruvate (v 8 ), two branches towards biosynthesis of biomass (v 9 , v 10 ) and NADH consumption and ATP formation in the respiratory chain (v 14 ).…”

Section: A R T I C L E Smentioning

confidence: 99%

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Integrative model of the response of yeast to osmotic shock

et al. 2005

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Integration of experimental studies with mathematical modeling allows insight into systems properties, prediction of perturbation effects and generation of hypotheses for further research. We present a comprehensive mathematical description of the cellular response of yeast to hyperosmotic shock. The model integrates a biochemical reaction network comprising receptor stimulation, mitogen-activated protein kinase cascade dynamics, activation of gene expression and adaptation of cellular metabolism with a thermodynamic description of volume regulation and osmotic pressure. Simulations agree well with experimental results obtained under different stress conditions or with specific mutants. The model is predictive since it suggests previously unrecognized features of the system with respect to osmolyte accumulation and feedback control, as confirmed with experiments. The mathematical description presented is a valuable tool for future studies on osmoregulation in yeast and-with appropriate modifications-other organisms. It also serves as a starting point for a comprehensive description of cellular signaling.Osmoregulation encompasses active processes with which cells monitor and adjust osmotic pressure and control shape, turgor and relative water content. Even individual cells in multicellular organisms respond to osmotic changes, and strategies of cellular adaptation are conserved from bacteria to human 1 . The yeast Saccharomyces cerevisiae is a suitable model system to study osmoregulation and a substantial amount of information is available on osmotic shockinduced signal transduction, control of gene expression and accumulation of osmolytes 2 .Osmoregulation is a homeostatic process, though commonly studied as a response to osmotic shock. Central to yeast osmotic adaptation is the high osmolarity glycerol (HOG) signaling system 2,3 (Fig. 1). S. cerevisiae monitors osmotic changes through the plasma membrane-localized sensor histidine kinase Sln1. Under ambient conditions, Sln1 is active and inhibits signaling. Upon loss of turgor pressure, Sln1 is inactivated 4 resulting in activation of a mitogen-activated protein (MAP) kinase cascade and phosphorylation of the MAP kinase Hog1. Active Hog1 accumulates in the nucleus where it affects gene expression. Two HOG target genes encode enzymes in glycerol production. Hence, activation of Hog1 stimulates the production of glycerol, which serves as an osmolyte to increase intracellular osmotic pressure. Glycerol accumulation is also controlled by rapid closing of the aquaglyceroporin Fps1, which is an osmolarity-regulated glycerol channel. Hog1 activation and Hog1-dependent transcriptional stimulation are transient processes, indicating rigorous feedback control. Several protein phosphatases are known as negative regulators of the pathway. Although the overall organization of the systems is well characterized, open questions concern the mechanisms underlying activation and deactivation of the system, feedback control and the causal relationship between different events in...

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Section: A R T I C L E Smentioning

confidence: 99%

“…We considered cellular consumption processes for NAD + (v 15 ) and ATP (v 16 ). The kinetics were chosen to allow for stable steady-state concentrations and fluxes as previously determined 37,41 .…”

Section: A R T I C L E Smentioning

confidence: 99%

Integrative model of the response of yeast to osmotic shock

et al. 2005

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“…The only solution therefore is to perform experiments with whole cells to obtain in vivo kinetic behavior of all enzymes simultaneously. Here rapid pulse experiments as pioneered by the groups of Reuss [20,21] and Heijnen [22] offer advantages, but the challenge is the parameter identifiability problem which calls for model reduction as shown by Nikerel et al [23][24][25].…”

Section: Metabolic Reaction Network Models To Redesign Organisms: Redmentioning

confidence: 99%

Impact of Thermodynamic Principles in Systems Biology

Heijnen

2010

Biosystems Engineering II

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“…In vivo kinetic studies rely partly on rapid dynamic perturbation experiments during which a steady-state chemostat culture is perturbed and the subsequent response in both extracellular and intracellular metabolites is monitored (Theobald et al, 1997;Chassagnole et al, 2002;Visser et al, 2002;Mashego et al, 2004;Wu et al, 2005). Taking into account the high turnover rate of most intracellular metabolites, proper measurement of their concentrations requires rapid broth sampling and instantaneous quenching of enzyme activity.…”

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confidence: 99%