TY - JOUR
AU - Smits, Gertien J.
AB - Abstract Qualitative phenotypic changes are the integrated result of quantitative changes at multiple regulatory levels. To explain the temperature-induced increase of glycolytic flux in fermenting cultures of Saccharomyces cerevisiae, we quantified the contributions of changes in activity at many regulatory levels. We previously showed that a similar temperature increase in glucose-limited cultivations lead to a qualitative change from respiratory to fermentative metabolism, and this change was mainly regulated at the metabolic level. In contrast, in fermenting cells, a combination of different modes of regulation was observed. Regulation by changes in expression and the effect of temperature on enzyme activities contributed much to the increase in flux. Mass spectrometric quantification of glycolytic enzymes revealed that increased enzyme activity did not correlate with increased protein abundance, suggesting a large contribution of post-translational regulation to activity. Interestingly, the differences in the direct effect of temperature on enzyme kinetics can be explained by changes in the expression of the isoenzymes. Therefore, both the interaction of enzyme with its metabolic environment and the temperature dependence of activity are in turn regulated at the hierarchical level. Saccharomyces cerevisiae, temperature control, metabolic flux, adaptive response, gene expression, quantitative physiology Introduction Microorganisms adapt to environmental changes by altering their cellular composition. Such responses aid the cells in surviving and withstanding the stress (Berry & Gasch, 2008; Zakrzewska et al., 2011) and put a significant additional energy burden on the cell (Verduyn, 1991; Zakrzewska et al., 2011). Therefore, it is not surprising that cells also change the flux through energy generating metabolism. In the yeast Saccharomyces cerevisiae, both qualitative and quantitative changes in the flux through central carbon metabolism have been observed in response to a variety of altered environmental conditions, including nutrient starvation and temperature change (van Hoek et al., 1998; Nilsson et al., 2001; Daran-Lapujade et al., 2004, 2007; Rossell et al., 2006; Tai et al., 2007; Postmus et al., 2008). An important question is how the cell orchestrates the energy demands for growth and for adaptive responses to environmental change. A derived question is how the cell regulates flux, and flux distribution, in response to such environmental change. Major changes in the expression of many genes and proteins have been observed. These changes are assumed to regulate the molecular physiological adaptations that are required (Miller et al., 1982; Mager & Ferreira, 1993; Morano et al., 1998; Boy-Marcotte et al., 1999). Importantly, in many cases, the altered expression of genes does not correlate with the changes in protein expression, flux or phenotype (Bro et al., 2003; Daran-Lapujade et al., 2004; Castrillo et al., 2007; Postmus et al., 2008; Zakrzewska et al., 2010). In the complex network that is a living cell, we must stipulate that a phenotypic change, such as a flux change, is the result of the interaction of multiple modes of regulation (ter Kuile & Westerhoff, 2001; Rossell et al., 2006; Postmus et al., 2008). In the case of temperature, one can imagine several possible contributions (Postmus et al., 2008): changes in concentration and/or capacity of (rate-controlling) enzymes (Shulman et al., 1995), changes in the metabolite environment of an enzyme, such as substrate, product and effector concentrations (Hochachka & McClelland, 1997) or a direct effect of the change in temperature on the catalytic properties of the enzymes (Arrhenius, 1884). In a previous study under energy-limited conditions, we quantitatively analysed the six-fold increased flux through yeast glycolysis and shift in metabolism caused by a high temperature challenge (Postmus et al., 2008). We determined the contribution of the above-described cellular processes to the flux increase, using regulation analysis (ter Kuile & Westerhoff, 2001), extended by a term that described the direct effect of temperature. Thus, we could determine the contribution of hierarchical processes, leading to increased enzyme abundance, metabolic processes and the direct effect of temperature on enzyme rates. This revealed that in the glucose-limited cultivation conditions used, the temperature-induced glycolytic flux increase was mainly regulated by changes in the metabolic environment of the enzymes (Postmus et al., 2008). Consequently, the contributions of the transcription cascade and the direct effect of the increased temperature on the enzymes were only minor and hardly contributed to the flux increase. Interestingly, we also determined that respiratory metabolism cannot generate energy above 37 °C (Postmus et al., 2011). To disentangle catabolic and anabolic effects of the temperature perturbation, we decided here to progress with the studies of temperature stress on glycolytic flux using nitrogen-limited chemostats of S. cerevisiae that are fermenting at 30 °C. In baker's yeast, catabolism and anabolism are not tightly coupled, because a glucose pulse in carbon-limited chemostats results in an immediate response in catabolic activity, while biomass formation remains unchanged for at least half an hour (Van Urk et al., 1988). We quantified how hierarchical and metabolic changes, and the direct effect of temperature contributed to the glycolytic flux increase through each enzyme. The analysis revealed that the temperature-induced flux increase is regulated at various levels, differing per enzyme. Noticeably, the behaviour of the various enzymes differed in a cultivation temperature and culture nutrient limitation dependent manner. We used mass spectrometry to quantify the glycolytic proteins and found that the environmental changes resulted in differences in isoenzyme distribution. Such changes likely affect the interaction of the protein, measured as enzyme activity with the metabolite environment, as well as the effect of temperature on enzyme kinetic rate. In conclusion, a linear dissection of the effect of temperature perturbation on the glycolytic flux into effects either at the gene expression, metabolic level or at the level of direct temperature effects on individual enzymes is too simplistic and needs to be refined to include detailed mechanistic information of the enzymes' biophysical properties as well as their control by metabolites, allosteric effectors and other post-translational modes of regulation. Materials and methods Strains and growth conditions Saccharomyces cerevisiae strain CEN.PK113-7D (MATa MAL2-8cSUC2) was cultivated in aerobic, nitrogen-limited 2-L chemostats (Applikon, Schiedam, the Netherlands) with a working volume of 1 L at a dilution rate of 0.1 h−1. Precultures were grown overnight in mineral medium according to Verduyn et al. (1992) supplemented with 20 g L−1 glucose in shake flasks at 30 °C and 200 r.p.m. The same medium was used for chemostat cultivation, only now containing 60 g L−1 glucose and 1.0 g L−1 ammonium sulphate as only nitrogen source for N-limited cultivation, or 7.5 g L−1 glucose for C-limited cultivation (Postmus et al., 2008). The stirrer speed was set to 800 r.p.m., while the pH was set to pH 5.0 and kept constant by automatic titration with 1 M KOH. Stirring rate, pH and temperature were kept constant using an Applikon ADI 1010 Biocontroller (Applikon). The chemostat was aerated by flushing air through the culture at 30 L h−1. Steady states were verified by off gas analysis for oxygen and carbon dioxide and by dry weight (DW) measurements. Off gas analysis The oxygen and carbon dioxide levels were monitored online in the exhaust gas of the fermentors using an oxygen analyser (Servomex Ltd. Paramagnetic O2 transducer) and a carbon dioxide analyser (infrared Servomex Xentra 4100 Gas purity Analyser). Biomass dry weight measurements The DW concentration was determined in triplicate by filtering 10 mL of broth on prewashed and preweighed cellulose acetate membrane filters (pore size 0.45 μm; Schleicher & Schuell MicroSciences, Dassel, Germany). Each filter was washed with one volume of demineralized water and dried in a microwave 450W (Whirlpool Promicro 825, Sweden) for 15 min. Filters were cooled in a desiccator and weighed on an electronic analytical balance (Mettler-Toledo AB104, Columbus, OH). Analysis of metabolites To determine glucose, ethanol, glycerol, succinate and acetate content, 1.0 mL of broth was quickly quenched in 100 μL 35% perchloric acid. Samples were subsequently neutralized with 55 μL 7 M KOH. Culture samples and media samples were analysed by HPLC on a Phenomenex Rezex ROA – Organic Acid H+ column using 7.2 mM H2SO4 as mobile phase. To analyse residual glucose, 5.0 mL of broth was quickly (within seconds) filtered through 0.2-μm-pore size filter (Acrodisc Syringe Filter, Pall Life Science, Ann Arbor, MI). Enzyme activity measurements Enzyme activity assays were carried out according to the protocol described previously (Postmus et al., 2008) and references therein. Briefly, activities were determined using saturating substrate concentrations, in conditions simulating the cytosol (van Eunen et al., 2010b), which was kept as constant as possible for the various enzymes. Regulation analysis To quantitatively dissect the regulation of in vivo enzyme fluxes by changes in enzyme capacity, direct effect of temperature and by metabolic regulation, we used regulation analysis introduced by ter Kuile & Westerhoff (2001) adapted to include the direct effect of temperature on the enzyme's catalytic rate (Postmus et al., 2008). As enzymes are catalysts, enzyme rate equations generally have the shape:   in which v is the enzyme rate, e is the concentration of enzyme, T is the direct effect of temperature on the enzyme rate and X is the vector of substrate, product and other effector concentrations. Important in this equation is that f(e), which equals the Vmax of the enzyme, is independent of X, while g(X) is independent of e. The dissection and quantification of f,q and g are achieved by translating the above equation into logarithmic space, considering a change between two steady states, and dividing both sides of the equation by the relative change in steady-state flux J. Because at steady state, the flux J equals the enzyme rate v, this results in:   Here, ρh is the hierarchical regulation coefficient, which expresses how much of the flux regulation is because of the changes in enzyme concentration (i.e. through gene expression), ρT is the contribution of direct regulation of rate by temperature and ρm is the metabolic regulation coefficient, which quantifies the contribution of changes in the interaction of the enzyme with the rest of metabolism in relation to the change in flux. Quantitative analysis of the glycolytic proteome Protein quantification was performed using a method similar to the one described by Sosinska et al. (2010). In short, identification of the glycolytic enzymes in the complex proteome digest is based on the accurate mass and LC retention time match of their tryptic peptides with the corresponding LCMSMS identified tryptic peptides as recorded for each standard glycolytic enzyme (Sigma-Aldrich Corp, St Louis), and protein quantification is relative to a metabolically15N- labelled reference cell culture. It is expressed as the14N/15N isotopic ratio, averaged over the tryptic peptides for each protein, determined in the tryptic digest of a 1 : 1 mixture of the query14N culture with the reference15N culture. Yeast cultures from chemostats were harvested on ice, washed once using sterile ice-cold water and stored at −20 °C before further analysis. The dry weight of each culture was determined. Aliquots of each culture were mixed with equal aliquots of a reference culture, based on dry weight. The reference culture was a yeast chemostat culture grown under the same conditions as the 30 °C, C-limited culture, but using (15NH4)2SO4 (Isotope enrichment > 99%, Spectra Stable Isotopes, Columbia) as the sole nitrogen source. After pelleting, the mixed cells were resuspended in 50 mM Tris–HCl, pH 7.0, transferred to a 2-mL screw-cap reaction vial and combined with glass beads (diameter 50 μm) and protease inhibitor cocktail (Sigma, Germany). The cells were broken using a Fastprep (MP Biomedicals, Irvine) as checked visually with the microscope. The glass beads were washed three times with 50 mM Tris–HCl, pH 7.0. Walls and membranes were pelleted (5 min. 3000 g at 4 °C), and the supernatant was transferred to a new vial and centrifuged at 140 000 g for 15 min at 4 °C. The collected supernatant was snap-frozen in liquid nitrogen and lyophilized overnight. The lyophilized proteins were dissolved in 8 M urea, 0.1% SDS, 10 mM DTT and incubated at 56 °C for 1 h. After cooling down to room temperature, iodoacetic acid was added to a final concentration of 50 mM. The denaturing, reducing and alkylating reagents were removed by dialysis against 50 mM (NH4)HCO3 at 4 °C. Protein concentrations were determined spectrophotometrically at 562 nm using a bicinchoninic acid assay (Pierce, Rockford) with bovine serum albumin as standard, according to manufacturer's protocol. Trypsin gold (Promega, Madison, WI) was added at a final ratio of 1 : 50 g gDW−1. Samples were incubated for 16 h at 37 °C. Peptides were desalted and concentrated using 20 μL Toptip HILIC (Glycen, Columbia), and eluted with 0.1% trifluoroacetic acid (TFA) solution, yielding a final concentration of 5 μg μL−1. MS analysis and data processing Accurate mass data were acquired using an ApexQ Fourier transform ion cyclotron resonance mass spectrometer (Bruker Daltonic, Bremen, Germany) equipped with a 7T magnet and a CombiSource™ coupled to an Ultimate 3000 (Dionex, Sunnyvale, CA) HPLC system with a PepMap100 C18 (5 μm, 100 Å, 300 μm i.d. × 5 mm) precolumn and a PepMap100 C18 (5 μm, 100 Å, 300 μm i.d. × 250 mm) analytical column (Dionex). Samples containing up to 3 μg of tryptic peptides were injected as a 3 μL 0.1% TFA aqueous solution and loaded onto the precolumn. After injection, a linear gradient (from 0.1% formic acid/100% H2O to 0.1% formic acid/40% CH3CN/60% H2O) was applied over a period of 240 min at a flow rate of 2 μL min−1. During elution, a chromatogram of up to 4500 high-resolution ESI-FT-MS spectra was recorded using an MS duty cycle of about 3 s. The data were processed using the Data Analysis 3.4 software program (Bruker Daltonic). A total of 4500 mass spectra were extracted batch-wise from the chromatogram, and the monoisotopic masses of the peptides were determined using Bruker's peak recognition technology SNAP II™. Mass calibration was achieved by selective extraction and subsequent summation of about 6 mass spectra from the chromatogram corresponding to MSMS/MASCOT identified tryptic peptides originating from glycolytic proteins. With the calculated masses of these calibrant peptides, the summed spectrum was mass calibrated and the resulting calibration parameters were applied to all spectra in the chromatogram. This resulted in a mass calibration of better than 1.5 ppm over the entire chromatogram for all analyses. For each FTMS analysis, the resulting array of up to 4500 monoisotopic mass lists was exported as a MASCOT generic file. Ion abundances in the exported array of monoisotopic mass lists were the spectral intensities of the most abundant isotope summed over all charge states for each peptide. Results Increased temperature results in an increased glycolytic flux In this study, the effect of temperature on yeast glycolytic flux was investigated in a nonenergy-limiting environment using nitrogen-limited chemostats at various temperatures. To analyse the quantitative effect of increased temperature on the fluxes through the individual reactions in glycolysis, we compared cultures from 30 and 38 °C, temperatures at which the maximal specific growth rate in abundance of all nutrients was identical (Postmus et al., 2008). Table 1 shows the physiological characteristics and fluxes of N-limited steady-state cultivations at 30 and 38 °C. The concentrations of succinate, acetate and pyruvate were below detection limit. The fluxes of CO2, ethanol, glucose and glycerol were used to calculate the fluxes through the individual glycolytic enzymes (Fig. 1). The increase in temperature resulted in a 1.4- to 1.8-fold increased flux through all glycolytic enzymes. In a similar study in C-limited chemostats, the same increase resulted in a qualitative change in metabolism, from respiratory to fermentative, was observed. This did not happen in this case, where at both temperatures, metabolism was a mix of respiration and fermentation, which can be deduced from CO2 and ethanol fluxes (qCO2, fermentation = qEtOH; qCO2,respiration = qCO2,total − qCO2,fermentation) to be about one to four. 1 Physiological characteristics of nitrogen-limited chemostat cultures grown at 30 and 38 °C   DW  qGlucose  qO2  qCO2  qEthanol  qGlycerol  Yield  g L−1  mmol gDW−1 h−1  g g−1  30 °C  4.6 ± 0.4  5.4 ± 0.8  3.8 ± 0.5  9.9 ± 2.6  7.3 ± 0.6  0.0 ± 0.0  0.11 ± 0.01  38 °C  3.6 ± 0.5  9.6 ± 2.1  4.3 ± 0.9  15 ± 3.0  12 ± 0  1.3 ± 0.1  0.06 ± 0.01  FC 38/30 °C  0.8  1.8  1.1  1.5  1.7    0.6    DW  qGlucose  qO2  qCO2  qEthanol  qGlycerol  Yield  g L−1  mmol gDW−1 h−1  g g−1  30 °C  4.6 ± 0.4  5.4 ± 0.8  3.8 ± 0.5  9.9 ± 2.6  7.3 ± 0.6  0.0 ± 0.0  0.11 ± 0.01  38 °C  3.6 ± 0.5  9.6 ± 2.1  4.3 ± 0.9  15 ± 3.0  12 ± 0  1.3 ± 0.1  0.06 ± 0.01  FC 38/30 °C  0.8  1.8  1.1  1.5  1.7    0.6  Values represent the mean ± SD of data from at least three independent chemostats. The carbon balances were within 100 ± 10%. View Large 1 Physiological characteristics of nitrogen-limited chemostat cultures grown at 30 and 38 °C   DW  qGlucose  qO2  qCO2  qEthanol  qGlycerol  Yield  g L−1  mmol gDW−1 h−1  g g−1  30 °C  4.6 ± 0.4  5.4 ± 0.8  3.8 ± 0.5  9.9 ± 2.6  7.3 ± 0.6  0.0 ± 0.0  0.11 ± 0.01  38 °C  3.6 ± 0.5  9.6 ± 2.1  4.3 ± 0.9  15 ± 3.0  12 ± 0  1.3 ± 0.1  0.06 ± 0.01  FC 38/30 °C  0.8  1.8  1.1  1.5  1.7    0.6    DW  qGlucose  qO2  qCO2  qEthanol  qGlycerol  Yield  g L−1  mmol gDW−1 h−1  g g−1  30 °C  4.6 ± 0.4  5.4 ± 0.8  3.8 ± 0.5  9.9 ± 2.6  7.3 ± 0.6  0.0 ± 0.0  0.11 ± 0.01  38 °C  3.6 ± 0.5  9.6 ± 2.1  4.3 ± 0.9  15 ± 3.0  12 ± 0  1.3 ± 0.1  0.06 ± 0.01  FC 38/30 °C  0.8  1.8  1.1  1.5  1.7    0.6  Values represent the mean ± SD of data from at least three independent chemostats. The carbon balances were within 100 ± 10%. View Large 1 View largeDownload slide Stoichiometry of the glycolytic pathway. In this simplified scheme, enzymes with fluxes indistinguishable in our approach are boxed together. The numbers next to the boxed enzymes are the calculated fluxes through the enzymes of 30 °C (normal) cultivations and 38 °C (underlined) cultivations, in mmol gDW−1 h−1. 1 View largeDownload slide Stoichiometry of the glycolytic pathway. In this simplified scheme, enzymes with fluxes indistinguishable in our approach are boxed together. The numbers next to the boxed enzymes are the calculated fluxes through the enzymes of 30 °C (normal) cultivations and 38 °C (underlined) cultivations, in mmol gDW−1 h−1. Temperature-induced changes of glycolytic enzyme activity Next, we asked the question how these increases were accomplished. Three possible modes of regulation were considered. First, temperature could have a direct effect on the catalytic activity of enzymes (Arrhenius, 1884). Second, changes in the abundance and thereby capacity of the enzymes could cause flux changes (Shulman et al., 1995). Finally, changes in the environment of the enzymes, such as the concentration of substrates and effectors could cause flux changes (Hochachka & McClelland, 1997). In a cell, any possible combination of these modes can occur (Rossell et al., 2006). To quantify by which process the increase in flux through each glycolytic enzyme is regulated, we applied temperature effect-included regulation analysis, in which the direct effect of temperature on the enzyme activity is accounted for (Postmus et al., 2008). To assess the effect of temperature on the catalytic properties of the glycolytic enzymes, the in vitro Vmax of the enzymes in extracts from chemostats cultivated at 30 and 38 °C was measured both at 30 °C and at 38 °C in conditions resembling those in the cytosol (van Eunen et al., 2010b). In this way, the direct effect of temperature on the Vmax is isolated from that of the adaptive response of the cell to the changed cultivation temperature. The effect of assay temperature on enzyme catalytic rates in cell extracts isolated from cultivations at either 30 or 38 °C ranged from a 1.9-fold increase for ADH activity to 0.6-fold reduction for FBA (Table 2). The rates of HXK, PFK, PGK and PDC were not significantly affected by the temperature increase directly. For all other enzymes, the temperature increase significantly affected catalytic rate, the direct effect of assay temperature was the same in cell extracts from 38 °C cell extracts from 30 °C cultivations (see Table 2). Notable exception was TDH, for which we observed a higher direct temperature effect on catalytic rate in cell-free extracts isolated from 38 °C cultures than on the activity in extracts from cultures grown at 30 °C. 2 In vitro enzyme activity determination of Saccharomyces cerevisiae cell-free extracts, grown in nitrogen-limited aerobic chemostats at 30 and 38 °C. Values represent the mean ± SD of four independent chemostats. The assay temperature effect is expressed as the ratio of enzyme activities measured at 38 °C over those measured at 30 °C for one culture temperature. The P-value indicates the likelihood that the assay temperature effect on extracts from chemostats cultivated at 30 °C is different from the assay temperature effect on extracts from chemostats cultivated at 38 °C. Significantly, different assay temperature effects are indicated in bold italic type. The culture temperature effect is expressed as the ratio of enzyme activities measured at a single assay temperature for cultures grown at 38 °C over those of cultures grown at 30 °C Culture T  30 °C  30 °C  38 °C  38 °C  Assay temperature effect    Culture temperature effect  Assay T  30 °C  38 °C  30 °C  38 °C      A  B  C  D  B vs. A  D vs. C  B/A vs. D/C  C vs. A  D vs. B  Enzyme  mmol min−1 g protein−1  FC  FC  P-value  FC  FC  HXK  1.2 ± 0.2  1.1 ± 0.3  1.3 ± 0.1  1.2 ± 0.2  0.9  0.9  8.0E−01  1.1  1.1  PGI  3.4 ± 0.7  5.5 ± 0.6  5.0 ± 0.3  6.0 ± 0.4  1.6   1.2   1.0E−01  1.4   1.1  PFK  0.4 ± 0.2  0.4 ± 0.1  0.2 ± 0.1  0.3 ± 0.0  1.0  1.1  7.5E−01  0.6  0.6  FBA  0.9 ± 0.2  0.6 ± 0.1  1.1 ± 0.3  0.6 ± 0.1  0.6   0.6   6.5E−01  1.2  1.1  TPI  2.1 ± 0.2  3.4 ± 0.8  1.5 ± 0.3  2.4 ± 0.5  1.6   1.6   9.8E−01  0.7   0.7   TDH  4.5 ± 0.2  5.7 ± 0.2  3.2 ± 0.3  5.2 ± 0.4  1.3   1.7   9.3E−03  0.7   0.9   PGK  7.2 ± 1.0  7.7 ± 0.7  8.3 ± 2.6  10 ± 2.9  1.1  1.2  6.2E−01  1.2  1.3  ENO  0.7 ± 0.1  1.1 ± 0.2  1.2 ± 0.1  1.8 ± 0.1  1.5   1.5   8.5E−01  1.6   1.6   PYK  5.7 ± 0.5  9.4 ± 1.3  8.2 ± 0.4  12 ± 2.4  1.6   1.5   4.6E−01  1.4   1.3   ADH  3.6 ± 0.9  6.9 ± 0.7  5.0 ± 0.2  9.0 ± 0.9  1.9   1.8   7.5E−01  1.4   1.3   PDC  2.4 ± 0.6  2.3 ± 0.2  1.2 ± 0.2  1.3 ± 0.3  1.0  1.1  4.6E−01  0.5   0.6   Culture T  30 °C  30 °C  38 °C  38 °C  Assay temperature effect    Culture temperature effect  Assay T  30 °C  38 °C  30 °C  38 °C      A  B  C  D  B vs. A  D vs. C  B/A vs. D/C  C vs. A  D vs. B  Enzyme  mmol min−1 g protein−1  FC  FC  P-value  FC  FC  HXK  1.2 ± 0.2  1.1 ± 0.3  1.3 ± 0.1  1.2 ± 0.2  0.9  0.9  8.0E−01  1.1  1.1  PGI  3.4 ± 0.7  5.5 ± 0.6  5.0 ± 0.3  6.0 ± 0.4  1.6   1.2   1.0E−01  1.4   1.1  PFK  0.4 ± 0.2  0.4 ± 0.1  0.2 ± 0.1  0.3 ± 0.0  1.0  1.1  7.5E−01  0.6  0.6  FBA  0.9 ± 0.2  0.6 ± 0.1  1.1 ± 0.3  0.6 ± 0.1  0.6   0.6   6.5E−01  1.2  1.1  TPI  2.1 ± 0.2  3.4 ± 0.8  1.5 ± 0.3  2.4 ± 0.5  1.6   1.6   9.8E−01  0.7   0.7   TDH  4.5 ± 0.2  5.7 ± 0.2  3.2 ± 0.3  5.2 ± 0.4  1.3   1.7   9.3E−03  0.7   0.9   PGK  7.2 ± 1.0  7.7 ± 0.7  8.3 ± 2.6  10 ± 2.9  1.1  1.2  6.2E−01  1.2  1.3  ENO  0.7 ± 0.1  1.1 ± 0.2  1.2 ± 0.1  1.8 ± 0.1  1.5   1.5   8.5E−01  1.6   1.6   PYK  5.7 ± 0.5  9.4 ± 1.3  8.2 ± 0.4  12 ± 2.4  1.6   1.5   4.6E−01  1.4   1.3   ADH  3.6 ± 0.9  6.9 ± 0.7  5.0 ± 0.2  9.0 ± 0.9  1.9   1.8   7.5E−01  1.4   1.3   PDC  2.4 ± 0.6  2.3 ± 0.2  1.2 ± 0.2  1.3 ± 0.3  1.0  1.1  4.6E−01  0.5   0.6   P-value < 0.05 for the difference between the samples compared as determined from a two-tailed t-test assuming equal variance. View Large 2 In vitro enzyme activity determination of Saccharomyces cerevisiae cell-free extracts, grown in nitrogen-limited aerobic chemostats at 30 and 38 °C. Values represent the mean ± SD of four independent chemostats. The assay temperature effect is expressed as the ratio of enzyme activities measured at 38 °C over those measured at 30 °C for one culture temperature. The P-value indicates the likelihood that the assay temperature effect on extracts from chemostats cultivated at 30 °C is different from the assay temperature effect on extracts from chemostats cultivated at 38 °C. Significantly, different assay temperature effects are indicated in bold italic type. The culture temperature effect is expressed as the ratio of enzyme activities measured at a single assay temperature for cultures grown at 38 °C over those of cultures grown at 30 °C Culture T  30 °C  30 °C  38 °C  38 °C  Assay temperature effect    Culture temperature effect  Assay T  30 °C  38 °C  30 °C  38 °C      A  B  C  D  B vs. A  D vs. C  B/A vs. D/C  C vs. A  D vs. B  Enzyme  mmol min−1 g protein−1  FC  FC  P-value  FC  FC  HXK  1.2 ± 0.2  1.1 ± 0.3  1.3 ± 0.1  1.2 ± 0.2  0.9  0.9  8.0E−01  1.1  1.1  PGI  3.4 ± 0.7  5.5 ± 0.6  5.0 ± 0.3  6.0 ± 0.4  1.6   1.2   1.0E−01  1.4   1.1  PFK  0.4 ± 0.2  0.4 ± 0.1  0.2 ± 0.1  0.3 ± 0.0  1.0  1.1  7.5E−01  0.6  0.6  FBA  0.9 ± 0.2  0.6 ± 0.1  1.1 ± 0.3  0.6 ± 0.1  0.6   0.6   6.5E−01  1.2  1.1  TPI  2.1 ± 0.2  3.4 ± 0.8  1.5 ± 0.3  2.4 ± 0.5  1.6   1.6   9.8E−01  0.7   0.7   TDH  4.5 ± 0.2  5.7 ± 0.2  3.2 ± 0.3  5.2 ± 0.4  1.3   1.7   9.3E−03  0.7   0.9   PGK  7.2 ± 1.0  7.7 ± 0.7  8.3 ± 2.6  10 ± 2.9  1.1  1.2  6.2E−01  1.2  1.3  ENO  0.7 ± 0.1  1.1 ± 0.2  1.2 ± 0.1  1.8 ± 0.1  1.5   1.5   8.5E−01  1.6   1.6   PYK  5.7 ± 0.5  9.4 ± 1.3  8.2 ± 0.4  12 ± 2.4  1.6   1.5   4.6E−01  1.4   1.3   ADH  3.6 ± 0.9  6.9 ± 0.7  5.0 ± 0.2  9.0 ± 0.9  1.9   1.8   7.5E−01  1.4   1.3   PDC  2.4 ± 0.6  2.3 ± 0.2  1.2 ± 0.2  1.3 ± 0.3  1.0  1.1  4.6E−01  0.5   0.6   Culture T  30 °C  30 °C  38 °C  38 °C  Assay temperature effect    Culture temperature effect  Assay T  30 °C  38 °C  30 °C  38 °C      A  B  C  D  B vs. A  D vs. C  B/A vs. D/C  C vs. A  D vs. B  Enzyme  mmol min−1 g protein−1  FC  FC  P-value  FC  FC  HXK  1.2 ± 0.2  1.1 ± 0.3  1.3 ± 0.1  1.2 ± 0.2  0.9  0.9  8.0E−01  1.1  1.1  PGI  3.4 ± 0.7  5.5 ± 0.6  5.0 ± 0.3  6.0 ± 0.4  1.6   1.2   1.0E−01  1.4   1.1  PFK  0.4 ± 0.2  0.4 ± 0.1  0.2 ± 0.1  0.3 ± 0.0  1.0  1.1  7.5E−01  0.6  0.6  FBA  0.9 ± 0.2  0.6 ± 0.1  1.1 ± 0.3  0.6 ± 0.1  0.6   0.6   6.5E−01  1.2  1.1  TPI  2.1 ± 0.2  3.4 ± 0.8  1.5 ± 0.3  2.4 ± 0.5  1.6   1.6   9.8E−01  0.7   0.7   TDH  4.5 ± 0.2  5.7 ± 0.2  3.2 ± 0.3  5.2 ± 0.4  1.3   1.7   9.3E−03  0.7   0.9   PGK  7.2 ± 1.0  7.7 ± 0.7  8.3 ± 2.6  10 ± 2.9  1.1  1.2  6.2E−01  1.2  1.3  ENO  0.7 ± 0.1  1.1 ± 0.2  1.2 ± 0.1  1.8 ± 0.1  1.5   1.5   8.5E−01  1.6   1.6   PYK  5.7 ± 0.5  9.4 ± 1.3  8.2 ± 0.4  12 ± 2.4  1.6   1.5   4.6E−01  1.4   1.3   ADH  3.6 ± 0.9  6.9 ± 0.7  5.0 ± 0.2  9.0 ± 0.9  1.9   1.8   7.5E−01  1.4   1.3   PDC  2.4 ± 0.6  2.3 ± 0.2  1.2 ± 0.2  1.3 ± 0.3  1.0  1.1  4.6E−01  0.5   0.6   P-value < 0.05 for the difference between the samples compared as determined from a two-tailed t-test assuming equal variance. View Large Modes of regulation of temperature-induced flux increase Enzyme reaction rates are governed by the concentrations and catalytic activities of the enzymes, controlled by the expression cascade, their interactions with substrates, products and effectors and, in this case, the physical effect of temperature on enzymes. To quantitatively analyse how the flux increase through all glycolytic enzymes is brought about by these various contributions, we used regulation analysis (ter Kuile & Westerhoff, 2001; Rossell et al., 2005). Previously, we adapted this formalism to include the direct effect of temperature on enzyme kinetics as a separate term (for details, see Postmus et al., 2008) and Materials and Methods. Briefly, when comparing two steady states, the flux increase through an enzyme can be considered the multiplicative effect of an increase in enzyme abundance, analysed by Vmax, the effect of temperature on the enzyme catalytic rate and a residual term representing enzyme rate dependence on substrate concentration, as well as the concentrations of effectors. The former two contributions can be determined experimentally, and the latter follows from the formalism that states that the sum of the contributions must equal 1. The result of the dissection is shown in Table 0003. 3 Regulation analysis of local flux changes by temperature increase. The contribution to the flux increase of the gene expression cascade (hierarchical regulation), the direct effect of temperature on enzyme activities (temperature regulation) and the effect of changes in metabolic environment (metabolic regulation) were calculated for all glycolytic enzymes. The main contributions are indicated in bold italic type for all enzymes   ρT  ρh  ρm  HXK  −0.2 ± 0.0  0.1 ± 0.1  1.0  PGI  0.6 ± 0.1  0.7 ± 0.3  −0.3  PFK  0.1 ± 0.0  −1.1 ± 0.6  2.0  FBA  −0.9 ± 0.2  0.4 ± 0.3  1.6  TPI  1.3 ± 0.5  −0.9 ± 0.4  0.6  TDH    0.3 ± 0.1  0.7  PGK  0.3 ± 0.0  0.3 ± 0.2  0.4  ENO  0.9 ± 0.1  1.0 ± 0.2  −1.0  PYK  1.0 ± 0.1  0.8 ± 0.1  −0.8  PDC  0.1 ± 0.0  −1.3 ± 0.3  2.2  ADH  1.2 ± 0.1  0.6 ± 0.1  −0.8    ρT  ρh  ρm  HXK  −0.2 ± 0.0  0.1 ± 0.1  1.0  PGI  0.6 ± 0.1  0.7 ± 0.3  −0.3  PFK  0.1 ± 0.0  −1.1 ± 0.6  2.0  FBA  −0.9 ± 0.2  0.4 ± 0.3  1.6  TPI  1.3 ± 0.5  −0.9 ± 0.4  0.6  TDH    0.3 ± 0.1  0.7  PGK  0.3 ± 0.0  0.3 ± 0.2  0.4  ENO  0.9 ± 0.1  1.0 ± 0.2  −1.0  PYK  1.0 ± 0.1  0.8 ± 0.1  −0.8  PDC  0.1 ± 0.0  −1.3 ± 0.3  2.2  ADH  1.2 ± 0.1  0.6 ± 0.1  −0.8  View Large 3 Regulation analysis of local flux changes by temperature increase. The contribution to the flux increase of the gene expression cascade (hierarchical regulation), the direct effect of temperature on enzyme activities (temperature regulation) and the effect of changes in metabolic environment (metabolic regulation) were calculated for all glycolytic enzymes. The main contributions are indicated in bold italic type for all enzymes   ρT  ρh  ρm  HXK  −0.2 ± 0.0  0.1 ± 0.1  1.0  PGI  0.6 ± 0.1  0.7 ± 0.3  −0.3  PFK  0.1 ± 0.0  −1.1 ± 0.6  2.0  FBA  −0.9 ± 0.2  0.4 ± 0.3  1.6  TPI  1.3 ± 0.5  −0.9 ± 0.4  0.6  TDH    0.3 ± 0.1  0.7  PGK  0.3 ± 0.0  0.3 ± 0.2  0.4  ENO  0.9 ± 0.1  1.0 ± 0.2  −1.0  PYK  1.0 ± 0.1  0.8 ± 0.1  −0.8  PDC  0.1 ± 0.0  −1.3 ± 0.3  2.2  ADH  1.2 ± 0.1  0.6 ± 0.1  −0.8    ρT  ρh  ρm  HXK  −0.2 ± 0.0  0.1 ± 0.1  1.0  PGI  0.6 ± 0.1  0.7 ± 0.3  −0.3  PFK  0.1 ± 0.0  −1.1 ± 0.6  2.0  FBA  −0.9 ± 0.2  0.4 ± 0.3  1.6  TPI  1.3 ± 0.5  −0.9 ± 0.4  0.6  TDH    0.3 ± 0.1  0.7  PGK  0.3 ± 0.0  0.3 ± 0.2  0.4  ENO  0.9 ± 0.1  1.0 ± 0.2  −1.0  PYK  1.0 ± 0.1  0.8 ± 0.1  −0.8  PDC  0.1 ± 0.0  −1.3 ± 0.3  2.2  ADH  1.2 ± 0.1  0.6 ± 0.1  −0.8  View Large For PGK and TDH, all parameters contributed in a cooperative way and in the same direction, together leading to the net flux increase through the enzymes. No separate temperature component could be dissected for TDH, because the temperature dependence was significantly different at the two cultivation temperatures (Table 2). For this enzyme, we determined one combined regulation coefficient. Samples from two cultivation temperatures were assayed at the temperature identical to cultivation temperature, so that the regulation coefficient determined is the sum total of ρT and ρH. For HXK, the flux increase was not reflected in either Vmax or in the direct temperature-induced increase in enzymatic rate and was thus regulated mainly at metabolic level (Table 0003). PFK and PDC are the examples of enzymes whose activities decreased with increasing flux at higher environmental temperatures. This was reflected in a negative hierarchical coefficient, while there was hardly a direct temperature effect. However, metabolic regulation of these enzymes was high and assured a sustained flux increase upon increase in the environmental temperature. The opposite was true for PGI, ENO, PYK and ADH, where both the hierarchical and temperature coefficient contributed positively to the flux increase. These enzymes are, however, characterized by a negative metabolic flux regulation coefficient, which corroborates the complexity of the regulation of cellular homoeostasis. For FBA, strikingly, the direct effect of temperature was a decrease in activity, which was partly compensated for by an increased capacity (positive ρh). Positive metabolic regulation of FBA also contributed to the observed flux increase. Lastly, the capacity of TPI was strongly downregulated by a shift from 30 to 38 °C in culture temperature (ρh < 0). This compensated for the strong temperature-induced increase of enzyme reaction rate. Summarizing, almost all of the possible ways to increase flux through an enzyme in response to a temperature-induced flux increase were observed in the glycolytic pathway. Yeast glycolytic isoenzymes respond differently to temperature changes Regulation analysis revealed that the increase in flux in nitrogen-limited cultivations is brought about by various modes of regulation (Table 0003). For most enzymes, the hierarchical coefficient was shown to contribute to the flux increase. This contribution could be brought about by an increase in transcription, in translation, by decreased degradation of mRNA or protein, or by post-translational regulation of activity (Daran-Lapujade et al., 2007). We determined the relative protein abundance of the enzymes responsible for almost all glycolytic and fermentative reactions in cells cultured under both nitrogen-limited and carbon-limited conditions at 30 and 38 °C. We used14N/15N isotope ratio quantification of target peptide pair abundances. We identified enzyme peptides based on accurate mass and HPLC retention behaviour (see ) and based the quantification of 89% of the proteins based on two or more, and 44% of the proteins on five or more peptides (generic to all isoenzymes in case of enzymes for which more than one isoenzyme contributes to the activity) detected in each cultivation condition in two independent chemostat cultivations. The effect of culture temperature on the in vitro enzyme activity (Table 2) likely depends on the concentration of the corresponding enzymes. Figure 2 shows quantitative protein data of glycolytic proteins cultivated in N-limited and C-limited chemostat cultivations at 30 and 38 °C. We identified 74% of the proteins based on two or more and 16% of the proteins on five or more, unique, isoenzyme-specific peptides that could be detected in each cultivation condition in two independent chemostat cultivations. In N-limited cultivations, only the fold change of in vitro activity of HXK matched the protein content. TPI, TDH and PDC showed a lower activity in 38 °C cultivations, but their protein content was increased at 38 °C (Fig. 2a). For the other proteins, the measured change in enzyme activity was smaller than the changes in protein content. In C-limited chemostat cultivations, the change in enzyme activity and protein level only matched for FBA, PGK and ADH (Fig. 2b). Direct comparison of the change in enzyme activity with protein concentration (Fig. 2c) revealed that the two did not significantly correlate. This might indicate that protein stability is protein- and even isoenzyme-dependent. We have, however, no indication that protein stability was different in samples from different conditions (our unpublished data, see Postmus et al., 2008). We conclude therefore that post-translational alterations, be they small molecule modifications or interactions with other proteins, must be an important aspect of the regulation of enzyme activity. 2 View largeDownload slide Quantitative analysis of glycolytic protein abundance from (a) nitrogen-limited 30 °C (white bars) and nitrogen-limited 38 °C (grey bars) cultivations and in (b) carbon-limited 30 °C (white bars) and carbon-limited 38 °C (grey bars) cultivations. (c) Direct comparison of the temperature-induced change (Fold Change FC = ratio 38 °C/30 °C) in enzyme activity and protein levels for N-limited (open symbols) and C-limited (closed symbols) chemostats. Crosshatches indicate changes in protein level that are significant (P-value < 0.05). For enzymes with multiple isoenzymes, peptides generic to all these isoforms were used for quantification, thus giving a ‘total protein’ quantification. No peptides were identified for PFK and PYK, and for GPM, no generic peptides could be identified. 2 View largeDownload slide Quantitative analysis of glycolytic protein abundance from (a) nitrogen-limited 30 °C (white bars) and nitrogen-limited 38 °C (grey bars) cultivations and in (b) carbon-limited 30 °C (white bars) and carbon-limited 38 °C (grey bars) cultivations. (c) Direct comparison of the temperature-induced change (Fold Change FC = ratio 38 °C/30 °C) in enzyme activity and protein levels for N-limited (open symbols) and C-limited (closed symbols) chemostats. Crosshatches indicate changes in protein level that are significant (P-value < 0.05). For enzymes with multiple isoenzymes, peptides generic to all these isoforms were used for quantification, thus giving a ‘total protein’ quantification. No peptides were identified for PFK and PYK, and for GPM, no generic peptides could be identified. In addition to a quantitative change in activity, we also observed a striking discrepancy between the direct effect of temperature on the activity of the enzymes in extracts from N-limited chemostats, compared to our previous data on enzymes from C-limited chemostats: Whereas the direct effect of temperature on enzyme activity was only small for most enzymes from carbon-limited chemostats, in N-limited conditions, the enzymes of particularly lower glycolysis were strongly regulated by temperature alone (Table 2). We postulated that in cultures grown in different conditions, changes in the relative contribution of the different isoenzymes could explain differences in temperature dependence of the enzyme activities. Also, different isoenzyme can have different affinities for substrate, product or effector. In both cases, a change in isoenzyme expression will be reflected in the ρT or ρm, but the regulation in fact takes place at the hierarchical levels of transcript and protein abundance. We therefore analysed the isoenzyme contributions to the various enzymes, again using isotope labelling for protein quantification. Figure 3 shows the relative levels of the isoenzymes for a number of glycolytic proteins. In N-limited cultivations, the only enzyme for which the direct effect of temperature depended on the cultivation temperature was TDH, suggesting a difference in isoenzyme composition of TDH. The activity of this same enzyme was differently affected by temperature if isolated from C-limited chemostats cultivated at different temperatures (Postmus et al., 2008). We were able to identify Tdh1p and Tdh3p. While in N-limited chemostats, the relative contribution of Tdh3p decreased from 30 to 38 °C, in C-limited chemostats, the contribution of this isoenzyme to the total pool of TDH increased with the cultivation temperature upshift. This matches with an increased direct effect of temperature on TDH activity in extracts from N-limited cultivations at 38 °C compared with 30 °C, and a decreased direct effect of temperature on TDH activity in samples from C-limited cultures at 38 °C vs. those at 30 °C. Therefore, we can conclude that the activity of Tdh1p is affected much more by temperature than that of Tdh3p. For PGI, yeast has only one isoform. Therefore, the changed temperature dependence must be caused by other, post-translational mechanisms. 3 View largeDownload slide Quantitative analysis of isoenzyme composition of glycolytic proteins. Asterisks indicate proteins identified based on unique peptides, but sharing elemental peptide composition. The crosshatches indicate significant changes in protein level compared from 30 to 38 °C within one limitation (P-value < 0.05). 3 View largeDownload slide Quantitative analysis of isoenzyme composition of glycolytic proteins. Asterisks indicate proteins identified based on unique peptides, but sharing elemental peptide composition. The crosshatches indicate significant changes in protein level compared from 30 to 38 °C within one limitation (P-value < 0.05). Discussion We asked how yeast regulates its systems properties, such as metabolic flux, when challenged with an increase in temperature. Temperature has a direct effect on chemical reactions, but temperature changes also initiate adaptive responses in living cells. Previous studies, using regulation analysis, showed how glycolytic fluxes are regulated in response to nutrient starvation (Rossell et al., 2005), to gene deletion (Rossell et al., 2008) and in response to increased temperatures under glucose-limited conditions (Postmus et al., 2008). To study the adaptation of metabolism to temperature in the absence of a qualitative metabolic change, under nonenergy-limited conditions, we used nitrogen-limited chemostats. The flux in nitrogen-limited cultivations approximately doubled when the temperature increased from 30 to 38 °C, while under carbon-limited cultivation conditions, the same temperature shift results in a 6-fold flux increase (Postmus et al., 2008). This might indicate that the ATP requirement at high temperatures in nitrogen-limited cells is smaller compared to the carbon-limited cultivations. However, the glucose flux in nitrogen-limited cultures at 30 °C is already much higher than that in C-limited cultures at the same temperature and in fact almost equals that of C-limited cultures at 38 °C, where both types of culture have the same ATP generating mode of metabolism, and it is therefore unlikely that the ATP demand is strongly determined by the cultivation limitation. We showed that the 2-fold flux increase caused by a temperature increase from 30 to 38 °C in these N-limited chemostats was regulated by a diverse set of mechanism for the various enzymes, combining effects of altered expression, the direct effect of temperature on enzyme catalytic rate and changes in the metabolic environment of the enzymes. In contrast, in carbon-limited conditions, changes in metabolic environment were mainly responsible for a 6-fold flux increase and even caused a shift from fully respiratory metabolism to a respiro-fermentative metabolism (Postmus et al., 2008) and inactivation of mitochondrial respiratory chain activity (Postmus et al., 2011). Indeed, it was previously shown that flux regulation differs between cells grown under respiratory conditions and respiro-fermentative conditions (van Eunen et al., 2010a). In the latter, hierarchical regulation was dominant, while in respiratory conditions, the regulation was predominantly metabolic. This indicates that the mechanism of flux adaptation upon identical environmental changes differs dependent on the cell's growth history and therefore the actual state of the network (van Eunen et al., 2010a). On the other hand, glycolytic flux in the N-limited chemostats at 30 °C was already as high as that in the 38 °C C-limited conditions. Therefore, the ‘different’ mode of regulation observed in this study might in fact be additive to the metabolic regulation observed in C-limited chemostats, suggesting that the metabolic regulation can only take the flux up to a certain level, above which other modes of regulation are required. In both cases, the changed mode of regulation may be caused by the fact that under different external conditions, with a different net flux through metabolism and different steady-state concentrations of the metabolites, new reactions may become rate-controlling or constraining (Bordel & Nielsen, 2010). This introduces new possibilities for regulation in a condition or growth history dependent manner. It is known that changes in transcript do not correlate well with subsequent changes in proteome (Griffin et al., 2002; Greenbaum et al., 2003). We used15N metabolic labelling to analyse protein abundance of glycolytic enzymes, allowing us to study relative levels of the various isoenzymes catalysing the glycolytic reactions. The absence of correlation between the levels of glycolytic proteins and enzyme activity corroborates previous studies that show that flux is mainly regulated at the post-translational or metabolic level (Daran-Lapujade et al., 2007; Postmus et al., 2008) and extends the conclusion to state that enzyme activity is regulated to a large extent at a post-translational level. The direct effect of temperature on enzyme kinetics and flux regulation appears to be complex. In our previous studies, we determined that in C-limited chemostats in the temperature range between 30 and 38 °C, most enzymes were only very mildly affected by temperature, suggesting a biological ‘buffering’ of enzyme catalytic rate to changes in temperature (Postmus et al., 2008). In contrast, at low growth temperatures, the direct effect of temperature was a reduction in enzyme kinetic rates by half upon a reduction in temperature by 10 °C. This is close to the chemically expected reaction rate change upon a temperature increase of 10 °C, or Q10, by a factor two (Tai et al., 2007). In this study, we show that in N-limited chemostats, the Q10 was also close to the expected value for more enzymes, suggesting that under these nonenergy-limiting conditions, enzyme rate increases are not buffered similar to the C-limited conditions. To explain this difference in enzyme behaviour, we postulated that different isoenzymes would possess different kinetic properties with respect to temperature, and that a change in isoenzyme expression in cultures grown under carbon-limited conditions vs. those grown under nitrogen-limited would explain the differences observed (Nilsson et al., 2001). Indeed, studying the quantitative presence of multiple isoenzymes revealed the complexity of the interactions of the gene expression cascade, metabolism, and, in this case, temperature. For all enzymes analysed, the increase in cultivation temperature affected the relative abundance of the various isoenzymes, both in N- and in C-limited conditions. Therefore, not only the total amount of enzyme was affected, but also the enzyme's interaction with the physical and metabolic environment. In the case of TDH, the increased abundance of Tdh3p in C-, and of Tdh1p in N-limited cultures at 38 °C, explained why the assay temperature affected the enzymatic rate differently. Apparently, Tdh1p activity is more strongly directly increased by increased temperature than that of Tdh3p. Changes in isoenzyme abundance in response to changes in the environment influences the interpretation of regulation analysis: These changes are hierarchical in nature, but a possible change in affinity for substrate or regulator will alter the interaction of the enzyme with the environment, which is part of the metabolic or temperature regulation coefficient (Rossell et al., 2006). While mathematically it is not too difficult to dissect these contributions (Rossell et al., 2005), experimentally this is rather more complicated. In our in vitro enzyme activity assays, we measured the capacity at a single effector and substrate concentration and therefore ignored changes in affinity for substrate, product and effector that can be displayed by different isoenzymes were such isoforms are known. We show that a changed isoenzyme expression affects not only the interaction with the metabolic environment, but also the temperature dependence of the catalytic rate. In conclusion, our data reveal that the experimental dissection into simple terms for hierarchical regulation, temperature regulation and a deduced term for metabolic regulation requires further experimental sophistication to obtain all relevant enzyme (kinetic) parameters. Hierarchical regulation not only quantitatively affects maximal enzyme kinetic rates, but also the interactions with the metabolic and physical environment. The analysis of quantitative changes of transcript, or even protein levels, does not give us the information required to understand phenotype, even when this phenotype is as simple as the flux through glycolysis. We have shown how the cell regulates its responses to environmental temperature change to a very large extent using the evolved, complex properties of enzymes and their interaction with the other components of the cell. Acknowledgements We would like to thank Martijn Nagtegaal and Henk Dekker for technical assistance. 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Peptide sequences identified using the CoolRToolbox software. Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article. © 2012 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved
TI - Isoenzyme expression changes in response to high temperature determine the metabolic regulation of increased glycolytic flux in yeast
JO - FEMS Yeast Research
DO - 10.1111/j.1567-1364.2012.00807.x
DA - 2012-08-01
UR - https://www.deepdyve.com/lp/oxford-university-press/isoenzyme-expression-changes-in-response-to-high-temperature-determine-0L2emWnoWh
SP - 571
EP - 581
VL - 12
IS - 5
DP - DeepDyve
ER -