Quantitative analysis of the high temperature-induced glycolytic flux increase in Saccharomyces cerevisiae reveals dominant metabolic regulation

Metabolic Plasticity Shapes Microbial Communities across a Temperature Gradient

AbstractA central challenge in community ecology is understanding and predicting the effects of abiotic factors on community assembly. In particular, microbial communities play a central role in the ecosystem, but we do not understand how changing factors like temperature are going to affect community composition or function. In this article, we studied the self-assembly of multiple communities in synthetic environments to understand changes in microbial community composition based on metabolic responses of different functional groups along a temperature gradient. In many microbial communities, different microbial functional groups coexist through the partitioning of carbon sources in an emergent trophic structure (cross-feeding). In this system, respirofermentative bacteria display a preference for the sugars supplied as the only carbon source but secrete secondary carbon sources (organic acids) that are more efficiently consumed by obligate respirators. As a consequence of this trophic structure, the metabolic plasticity of the respirofermenters has downstream consequences for the relative abundance of respirators across temperatures. We found that the effects of different temperatures on microbial composition can largely be described by an increase in fermentation by-products with increasing temperatures from the respirofermentative bacteria. This research highlights the importance of metabolic plasticity and metabolic trade-offs in predicting species interactions and community dynamics across abiotic gradients.

Simultaneous Nanorheometry and Nanothermometry Using Intracellular Diamond Quantum Sensors

The viscoelasticity of the cytoplasm plays a critical role in cell morphology, cell division, and intracellular transport. Viscoelasticity is also interconnected with other biophysical properties, such as temperature, which is known to influence cellular bioenergetics. Probing the connections between intracellular temperature and cytoplasmic viscoelasticity provides an exciting opportunity for the study of biological phenomena, such as metabolism and disease progression. The small length scales and transient nature of changes in these parameters combined with their complex interdependencies pose a challenge for biosensing tools, which are often limited to a single readout modality. Here, we present a dual-mode quantum sensor capable of performing simultaneous nanoscale thermometry and rheometry in dynamic cellular environments. We use nitrogen-vacancy centers in diamond nanocrystals as biocompatible sensors for in vitro measurements. We combine subdiffraction resolution single-particle tracking in a fluidic environment with optically detected magnetic resonance spectroscopy to perform simultaneous sensing of viscoelasticity and temperature. We use our sensor to demonstrate probing of the temperature-dependent viscoelasticity in complex media at the nanoscale. We then investigate the interplay between intracellular forces and the cytoplasmic rheology in live cells. Finally, we identify different rheological regimes and reveal evidence of active trafficking and details of the nanoscale viscoelasticity of the cytoplasm.

Shikonin-Loaded Hollow Fe-MOF Nanoparticles for Enhanced Microwave Thermal Therapy

Microwave (MW) thermal therapy has been widely used for the treatment of cancer in clinics, but it still shows limited efficacy and a high recurrence rate owing to non-selective heat delivery and thermo-resistance. Regulating glycolysis shows great promise to improve MW thermal therapy since glycolysis plays an important role in thermo-resistance, progression, metabolism, and recurrence. Herein, we developed a delivery nanosystem of shikonin (SK)-loaded and hyaluronic acid (HA)-modified hollow Fe-MOF (HFM), HFM@SK@HA, as an efficient glycolysis-meditated agent to improve the efficacy of MW thermal therapy. The HFM@SK@HA nanosystem shows a high SK loading capacity of 31.7 wt %. The loaded SK can be effectively released from the HFM@SK@HA under the stimulation of an acidic tumor microenvironment and MW irradiation, overcoming the intrinsically low solubility and severe toxicity of SK. We also find that the HFM@SK@HA can not only greatly improve the heating effect of MW in the tumor site but also mediate MW-enhancing dynamic therapy efficiency by catalyzing the endogenous H2O2 to generate reactive oxygen species (ROS). As such, the MW irradiation treatment in the presence of HFM@SK@HA in vitro enables a highly improved anti-tumor efficacy due to the combined effect of released SK and generated ROS on inhibiting glycolysis in cancer cells. Our in vivo experiments show that the tumor inhibition rate is up to 94.75% ± 3.63% with no obvious recurrence during the 2 weeks after treatment. This work provides a new strategy for improving the efficacy of MW thermal therapy.

Parameter inference for enzyme and temperature constrained genome-scale models

The metabolism of all living organisms is dependent on temperature, and therefore, having a good method to predict temperature effects at a system level is of importance. A recently developed Bayesian computational framework for enzyme and temperature constrained genome-scale models (etcGEM) predicts the temperature dependence of an organism's metabolic network from thermodynamic properties of the metabolic enzymes, markedly expanding the scope and applicability of constraint-based metabolic modelling. Here, we show that the Bayesian calculation method for inferring parameters for an etcGEM is unstable and unable to estimate the posterior distribution. The Bayesian calculation method assumes that the posterior distribution is unimodal, and thus fails due to the multimodality of the problem. To remedy this problem, we developed an evolutionary algorithm which is able to obtain a diversity of solutions in this multimodal parameter space. We quantified the phenotypic consequences on six metabolic network signature reactions of the different parameter solutions resulting from use of the evolutionary algorithm. While two of these reactions showed little phenotypic variation between the solutions, the remainder displayed huge variation in flux-carrying capacity. This result indicates that the model is under-determined given current experimental data and that more data is required to narrow down the model predictions. Finally, we made improvements to the software to reduce the running time of the parameter set evaluations by a factor of 8.5, allowing for obtaining results faster and with less computational resources.

Cellulosic biofuel production using emulsified simultaneous saccharification and fermentation (eSSF) with conventional and thermotolerant yeasts

BACKGROUND

Future expansion of corn-derived ethanol raises concerns of sustainability and competition with the food industry. Therefore, cellulosic biofuels derived from agricultural waste and dedicated energy crops are necessary. To date, slow and incomplete saccharification as well as high enzyme costs have hindered the economic viability of cellulosic biofuels, and while approaches like simultaneous saccharification and fermentation (SSF) and the use of thermotolerant microorganisms can enhance production, further improvements are needed. Cellulosic emulsions have been shown to enhance saccharification by increasing enzyme contact with cellulose fibers. In this study, we use these emulsions to develop an emulsified SSF (eSSF) process for rapid and efficient cellulosic biofuel production and make a direct three-way comparison of ethanol production between S. cerevisiae, O. polymorpha, and K. marxianus in glucose and cellulosic media at different temperatures.

RESULTS

In this work, we show that cellulosic emulsions hydrolyze rapidly at temperatures tolerable to yeast, reaching up to 40-fold higher conversion in the first hour compared to microcrystalline cellulose (MCC). To evaluate suitable conditions for the eSSF process, we explored the upper temperature limits for the thermotolerant yeasts Kluyveromyces marxianus and Ogataea polymorpha, as well as Saccharomyces cerevisiae, and observed robust fermentation at up to 46, 50, and 42 °C for each yeast, respectively. We show that the eSSF process reaches high ethanol titers in short processing times, and produces close to theoretical yields at temperatures as low as 30 °C. Finally, we demonstrate the transferability of the eSSF technology to other products by producing the advanced biofuel isobutanol in a light-controlled eSSF using optogenetic regulators, resulting in up to fourfold higher titers relative to MCC SSF.

CONCLUSIONS

The eSSF process addresses the main challenges of cellulosic biofuel production by increasing saccharification rate at temperatures tolerable to yeast. The rapid hydrolysis of these emulsions at low temperatures permits fermentation using non-thermotolerant yeasts, short processing times, low enzyme loads, and makes it possible to extend the process to chemicals other than ethanol, such as isobutanol. This transferability establishes the eSSF process as a platform for the sustainable production of biofuels and chemicals as a whole.

Model Parameterization with Quantitative Proteomics: Case Study with Trehalose Metabolism in Saccharomyces cerevisiae

When Saccharomyces cerevisiae undergoes heat stress it stimulates several changes that are necessary for its survival, notably in carbon metabolism. Notable changes include increase in trehalose production and glycolytic flux. The increase in glycolytic flux has been postulated to be due to the regulatory effects in upper glycolysis, but this has not been confirmed. Additionally, trehalose is a useful industrial compound for its protective properties. A model of trehalose metabolism in S. cerevisiae was constructed using Convenient Modeller, a software that uses a combination of convenience kinetics and a genetic algorithm. The model was parameterized with quantitative omics under standard conditions and validated using data collected under heat stress conditions. The completed model was used to show that feedforward activation of pyruvate kinase by fructose 1,6-bisphosphate during heat stress contributes to the increase in metabolic flux. We were also able to demonstrate in silico that overexpression of enzymes involved in production and degradation of trehalose can lead to higher trehalose yield in the cell. By integrating quantitative proteomics with metabolic modelling, we were able to confirm that the flux increase in trehalose metabolic pathways during heat stress is due to regulatory effects and not purely changes in enzyme expression. The overexpression of enzymes involved in trehalose metabolism is a potential approach to be exploited for trehalose production without need for increasing temperature.

Temperature effect on water dynamics in tetramer phosphofructokinase matrix and the super-arrhenius respiration rate

Advances in understanding the temperature effect on water dynamics in cellular respiration are important for the modeling of integrated energy processes and metabolic rates. For more than half a century, experimental studies have contributed to the understanding of the catalytic role of water in respiration combustion, yet the detailed water dynamics remains elusive. We combine a super-Arrhenius model that links the temperature-dependent exponential growth rate of a population of plant cells to respiration, and an experiment on isotope labeled ¹⁸O₂ uptake to H₂¹⁸O transport role and to a rate-limiting step of cellular respiration. We use Phosphofructokinase (PFK-1) as a prototype because this enzyme is known to be a pacemaker (a rate-limiting enzyme) in the glycolysis process of respiration. The characterization shows that PFK-1 water matrix dynamics are crucial for examining how respiration (PFK-1 tetramer complex breathing) rates respond to temperature change through a water and nano-channel network created by the enzyme folding surfaces, at both short and long (evolutionary) timescales. We not only reveal the nano-channel water network of PFK-1 tetramer hydration topography but also clarify how temperature drives the underlying respiration rates by mapping the channels of water diffusion with distinct dynamics in space and time. The results show that the PFK-1 assembly tetramer possesses a sustainable capacity in the regulation of the water network toward metabolic rates. The implications and limitations of the reciprocal-activation-reciprocal-temperature relationship for interpreting PFK-1 tetramer mechanisms are briefly discussed.

Bayesian genome scale modelling identifies thermal determinants of yeast metabolism

The molecular basis of how temperature affects cell metabolism has been a long-standing question in biology, where the main obstacles are the lack of high-quality data and methods to associate temperature effects on the function of individual proteins as well as to combine them at a systems level. Here we develop and apply a Bayesian modeling approach to resolve the temperature effects in genome scale metabolic models (GEM). The approach minimizes uncertainties in enzymatic thermal parameters and greatly improves the predictive strength of the GEMs. The resulting temperature constrained yeast GEM uncovers enzymes that limit growth at superoptimal temperatures, and squalene epoxidase (ERG1) is predicted to be the most rate limiting. By replacing this single key enzyme with an ortholog from a thermotolerant yeast strain, we obtain a thermotolerant strain that outgrows the wild type, demonstrating the critical role of sterol metabolism in yeast thermosensitivity. Therefore, apart from identifying thermal determinants of cell metabolism and enabling the design of thermotolerant strains, our Bayesian GEM approach facilitates modelling of complex biological systems in the absence of high-quality data and therefore shows promise for becoming a standard tool for genome scale modeling.

While temperature impacts the function of all cellular components, it’s hard to rule out how the temperature dependence of cell phenotypes emerged from the dependence of individual components. Here, the authors develop a Bayesian genome scale modelling approach to identify thermal determinants of yeast metabolism.

Differential proteomic analysis by SWATH-MS unravels the most dominant mechanisms underlying yeast adaptation to non-optimal temperatures under anaerobic conditions

Elucidation of temperature tolerance mechanisms in yeast is essential for enhancing cellular robustness of strains, providing more economically and sustainable processes. We investigated the differential responses of three distinct Saccharomyces cerevisiae strains, an industrial wine strain, ADY5, a laboratory strain, CEN.PK113-7D and an industrial bioethanol strain, Ethanol Red, grown at sub- and supra-optimal temperatures under chemostat conditions. We employed anaerobic conditions, mimicking the industrial processes. The proteomic profile of these strains in all conditions was performed by sequential window acquisition of all theoretical spectra-mass spectrometry (SWATH-MS), allowing the quantification of 997 proteins, data available via ProteomeXchange (PXD016567). Our analysis demonstrated that temperature responses differ between the strains; however, we also found some common responsive proteins, revealing that the response to temperature involves general stress and specific mechanisms. Overall, sub-optimal temperature conditions involved a higher remodeling of the proteome. The proteomic data evidenced that the cold response involves strong repression of translation-related proteins as well as induction of amino acid metabolism, together with components related to protein folding and degradation while, the high temperature response mainly recruits amino acid metabolism. Our study provides a global and thorough insight into how growth temperature affects the yeast proteome, which can be a step forward in the comprehension and improvement of yeast thermotolerance.

Selection and subsequent physiological characterization of industrial Saccharomyces cerevisiae strains during continuous growth at sub- and- supra optimal temperatures

A phenotypic screening of 12 industrial yeast strains and the well-studied laboratory strain CEN.PK113-7D at cultivation temperatures between 12 °C and 40 °C revealed significant differences in maximum growth rates and temperature tolerance. From those 12, two strains, one performing best at 12 °C and the other at 40 °C, plus the laboratory strain, were selected for further physiological characterization in well-controlled bioreactors. The strains were grown in anaerobic chemostats, at a fixed specific growth rate of 0.03 h-1 and sequential batch cultures at 12 °C, 30 °C, and 39 °C. We observed significant differences in biomass and ethanol yields on glucose, biomass protein and storage carbohydrate contents, and biomass yields on ATP between strains and cultivation temperatures. Increased temperature tolerance coincided with higher energetic efficiency of cell growth, indicating that temperature intolerance is a result of energy wasting processes, such as increased turnover of cellular components (e.g. proteins) due to temperature induced damage.

Computational modeling of the effect of temperature variations on human pancreatic β-cell activity

The effect of temperature variations on the pancreatic β-cell activity and the role of different model compartments in temperature sensing have been investigated using a computational modeling approach. The results of our study show that temperature variations by several degrees can change the dynamical states of the β-cell system. In addition, temperature variations can alter the characteristic features of the membrane voltage, which correlates with insulin secretion. Simulation results show that the ion channels such as the L-type calcium, the hERG potassium, sodium channels and the glycolysis pathway are the possible sites for sensing temperature variation. Results indicate that for a small temperature change, even though the frequency and amplitude of electrical activity are altered, the area under the membrane potential curve remains almost unchanged, which implies the existence of a thermoregulatory mechanism for preserving the amount of insulin secretion. Furthermore, the computational analysis shows that the β-cell electrical activity exhibits a bursting pattern in physiological temperature (37 °C) while in vitro studies reported almost the spiking activity at lower temperatures. Since hormone-secreting systems work more efficient in bursting mode, we propose that the pancreatic β-cell works better in the physiological temperature compared with the reference temperature (33 °C).

Saccharomyces cerevisiae and S. kudriavzevii Synthetic Wine Fermentation Performance Dissected by Predictive Modeling

Wineries face unprecedented challenges due to new market demands and climate change effects on wine quality. New yeast starters including non-conventional Saccharomyces species, such as S. kudriavzevii, may contribute to deal with some of these challenges. The design of new fermentations using non-conventional yeasts requires an improved understanding of the physiology and metabolism of these cells. Dynamic modeling brings the potential of exploring the most relevant mechanisms and designing optimal processes more systematically. In this work we explore mechanisms by means of a model selection, reduction and cross-validation pipeline which enables to dissect the most relevant fermentation features for the species under consideration, Saccharomyces cerevisiae T73 and Saccharomyces kudriavzevii CR85. The pipeline involved the comparison of a collection of models which incorporate several alternative mechanisms with emphasis on the inhibitory effects due to temperature and ethanol. We focused on defining a minimal model with the minimum number of parameters, to maximize the identifiability and the quality of cross-validation. The selected model was then used to highlight differences in behavior between species. The analysis of model parameters would indicate that the specific growth rate and the transport of hexoses at initial times are higher for S. cervisiae T73 while S. kudriavzevii CR85 diverts more flux for glycerol production and cellular maintenance. As a result, the fermentations with S. kudriavzevii CR85 are typically slower; produce less ethanol but higher glycerol. Finally, we also explored optimal initial inoculation and process temperature to find the best compromise between final product characteristics and fermentation duration. Results reveal that the production of glycerol is distinctive in S. kudriavzevii CR85, it was not possible to achieve the same production of glycerol with S. cervisiae T73 in any of the conditions tested. This result brings the idea that the optimal design of mixed cultures may have an enormous potential for the improvement of final wine quality.

Temperature induces significant changes in both glycolytic reserve and mitochondrial spare respiratory capacity in colorectal cancer cell lines

Thermotherapy, as a method of treating cancer, has recently attracted considerable attention from basic and clinical investigators. A number of studies and clinical trials have shown that thermotherapy can be successfully used as a therapeutic approach for various cancers. However, the effects of temperature on cancer bioenergetics have not been studied in detail with a real time, microplate based, label-free detection approach. This study investigates how changes in temperature affect the bioenergetics characteristics (mitochondrial function and glycolysis) of three colorectal cancer (CRC) cell lines utilizing the Seahorse XF96 technology. Experiments were performed at 32°C, 37°C and 42°C using assay medium conditions and equipment settings adjusted to produce equal oxygen and pH levels ubiquitously at the beginning of all experiments. The results suggest that temperature significantly changes multiple components of glycolytic and mitochondrial function of all cell lines tested. Under hypothermia conditions (32°C), the extracellular acidification rates (ECAR) of CRC cells were significantly lower compared to the same basal ECAR levels measured at 37°C. Mitochondrial stress test for SW480 cells at 37°C vs 42°C demonstrated increased proton leak while all other OCR components remained unchanged (similar results were detected also for the patient-derived xenograft cells Pt.93). Interestingly, the FCCP dose response at 37°C vs 42°C show significant shifts in profiles, suggesting that single dose FCCP experiments might not be sufficient to characterize the mitochondrial metabolic potential when comparing groups, conditions or treatments. These findings provide valuable insights for the metabolic and bioenergetic changes of CRC cells under hypo- and hyperthermia conditions that could potentially lead to development of better targeted and personalized strategies for patients undergoing combined thermotherapy with chemotherapy.

Adaptation to different types of stress converge on mitochondrial metabolism

Yeast cell factories encounter physical and chemical stresses when used for industrial production of fuels and chemicals. These stresses reduce productivity and increase bioprocess costs. Understanding the mechanisms of the stress response is essential for improving cellular robustness in platform strains. We investigated the three most commonly encountered industrial stresses for yeast (ethanol, salt, and temperature) to identify the mechanisms of general and stress-specific responses under chemostat conditions in which specific growth rate-dependent changes are eliminated. By applying systems-level analysis, we found that most stress responses converge on mitochondrial processes. Our analysis revealed that stress-specific factors differ between applied stresses; however, they are underpinned by an increased ATP demand. We found that when ATP demand increases to high levels, respiration cannot provide sufficient ATP, leading to onset of respirofermentative metabolism. Although stress-specific factors increase ATP demand for cellular growth under stressful conditions, increased ATP demand for cellular maintenance underpins a general stress response and is responsible for the onset of overflow metabolism.

Thermotolerant yeasts selected by adaptive evolution express heat stress response at 30 °C

Exposure to long-term environmental changes across >100s of generations results in adapted phenotypes, but little is known about how metabolic and transcriptional responses are optimized in these processes. Here, we show that thermotolerant yeast strains selected by adaptive laboratory evolution to grow at increased temperature, activated a constitutive heat stress response when grown at the optimal ancestral temperature, and that this is associated with a reduced growth rate. This preventive response was perfected by additional transcriptional changes activated when the cultivation temperature is increased. Remarkably, the sum of global transcriptional changes activated in the thermotolerant strains when transferred from the optimal to the high temperature, corresponded, in magnitude and direction, to the global changes observed in the ancestral strain exposed to the same transition. This demonstrates robustness of the yeast transcriptional program when exposed to heat, and that the thermotolerant strains streamlined their path to rapidly and optimally reach post-stress transcriptional and metabolic levels. Thus, long-term adaptation to heat improved yeasts ability to rapidly adapt to increased temperatures, but this also causes a trade-off in the growth rate at the optimal ancestral temperature.

The Biokinetic Spectrum for Temperature

We identify and describe the distribution of temperature-dependent specific growth rates for life on Earth, which we term the biokinetic spectrum for temperature. The spectrum has the potential to provide for more robust modeling in thermal ecology since any conclusions derived from it will be based on observed data rather than using theoretical assumptions. It may also provide constraints for systems biology model predictions and provide insights in physiology. The spectrum has a Δ-shape with a sharp peak at around 42°C. At higher temperatures up to 60°C there was a gap of attenuated growth rates. We found another peak at 67°C and a steady decline in maximum rates thereafter. By using Bayesian quantile regression to summarise and explore the data we were able to conclude that the gap represented an actual biological transition between mesophiles and thermophiles that we term the Mesophile-Thermophile Gap (MTG). We have not identified any organism that grows above the maximum rate of the spectrum. We used a thermodynamic model to recover the Δ-shape, suggesting that the growth rate limits arise from a trade-off between activity and stability of proteins. The spectrum provides underpinning principles that will find utility in models concerned with the thermal responses of biological processes.

Modifying Yeast Tolerance to Inhibitory Conditions of Ethanol Production Processes

Saccharomyces cerevisiae strains having a broad range of substrate utilization, rapid substrate consumption, and conversion to ethanol, as well as good tolerance to inhibitory conditions are ideal for cost-competitive ethanol production from lignocellulose. A major drawback to directly design S. cerevisiae tolerance to inhibitory conditions of lignocellulosic ethanol production processes is the lack of knowledge about basic aspects of its cellular signaling network in response to stress. Here, we highlight the inhibitory conditions found in ethanol production processes, the targeted cellular functions, the key contributions of integrated -omics analysis to reveal cellular stress responses according to these inhibitors, and current status on design-based engineering of tolerant and efficient S. cerevisiae strains for ethanol production from lignocellulose.

Adaptation of Lactococcus lactis to high growth temperature leads to a dramatic increase in acidification rate

Lactococcus lactis is essential for most cheese making, and this mesophilic bacterium has its growth optimum around 30 °C. We have, through adaptive evolution, isolated a mutant TM29 that grows well up to 39 °C, and continuous growth at 40 °C is possible if pre-incubated at a slightly lower temperature. At the maximal permissive temperature for the wild-type, 38 °C, TM29 grows 33% faster and has a 12% higher specific lactate production rate than its parent MG1363, which results in fast lactate accumulation. Genome sequencing was used to reveal the mutations accumulated, most of which were shown to affect thermal tolerance. Of the mutations with more pronounced effects, two affected expression of single proteins (chaperone; riboflavin transporter), two had pleiotropic effects (RNA polymerase) which changed the gene expression profile, and one resulted in a change in the coding sequence of CDP-diglyceride synthase. A large deletion containing 10 genes was also found to affect thermal tolerance significantly. With this study we demonstrate a simple approach to obtain non-GMO derivatives of the important L. lactis that possess properties desirable by the industry, e.g. thermal robustness and increased rate of acidification. The mutations we have identified provide a genetic basis for further investigation of thermal tolerance.

Metabolic efficiency in yeast Saccharomyces cerevisiae in relation to temperature dependent growth and biomass yield

Canonized view on temperature effects on growth rate of microorganisms is based on assumption of protein denaturation, which is not confirmed experimentally so far. We develop an alternative concept, which is based on view that limits of thermal tolerance are based on imbalance of cellular energy allocation. Therefore, we investigated growth suppression of yeast Saccharomyces cerevisiae in the supraoptimal temperature range (30-40°C), i.e. above optimal temperature (Topt). The maximal specific growth rate (μmax) of biomass, its concentration and yield on glucose (Yx/glc) were measured across the whole thermal window (5-40°C) of the yeast in batch anaerobic growth on glucose. Specific rate of glucose consumption, specific rate of glucose consumption for maintenance (mglc), true biomass yield on glucose (Yx/glc(true)), fractional conservation of substrate carbon in product and ATP yield on glucose (Yatp/glc) were estimated from the experimental data. There was a negative linear relationship between ATP, ADP and AMP concentrations and specific growth rate at any growth conditions, whilst the energy charge was always high (~0.83). There were two temperature regions where mglc differed 12-fold, which points to the existence of a 'low' (within 5-31°C) and a 'high' (within 33-40°C) metabolic mode regarding maintenance requirements. The rise from the low to high mode occurred at 31-32°C in step-wise manner and it was accompanied with onset of suppression of μmax. High mglc at supraoptimal temperatures indicates a significant reduction of scope for growth, due to high maintenance cost. Analysis of temperature dependencies of product formation efficiency and Yatp/glc revealed that the efficiency of energy metabolism approaches its lower limit at 26-31°C. This limit is reflected in the predetermined combination of Yx/glc(true), elemental biomass composition and degree of reduction of the growth substrate. Approaching the limit implies a reduction of the safety margin of metabolic efficiency. We hypothesize that a temperature increase above Topt (e.g. >31°C) triggers both an increment in mglc and suppression of μmax, which together contribute to an upshift of Yatp/glc from the lower limit and thus compensate for the loss of the safety margin. This trade-off allows adding 10 more degrees to Topt and extends the thermal window up to 40°C, sustaining survival and reproduction in supraoptimal temperatures. Deeper understanding of the limits of thermal tolerance can be practically exploited in biotechnological applications.

Proteomics approach reveals mechanism underlying susceptibility of loquat fruit to sunburn during color changing period

The objective of this work was to investigate why loquat fruit peels are more sensitive to high temperature and strong sunlight, making them highly susceptible to sunburn, during the color changing period (CCP). Two dimensional gel electrophoresis (2-DE) of the fruit peel proteins was performed over three developmental periods, namely green fruit period (GFP), color changing period and yellow ripening period (YRP). Fifty-five protein spots with at least 2-fold differences in abundance were successfully identified by MALDI-TOF-TOF/MS. The identified proteins were divided into categories related to heat-shock response, stress response and defense, energy metabolism, photosynthesis and protein biosynthesis. The results showed that expression of proteins related to anaerobic respiration and photorespiration were increased while the proteins related to ROS scavenging, polyamine biosynthesis, defense pathogens and photosynthesis were decreased during CCP under heat stress. Our findings provide new insights into the molecular mechanism of loquat fruit susceptible to sunburn during CCP.

The effects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment

Because of its profound effects on the rates of biological processes such as aerobic metabolism, environmental temperature plays an important role in shaping the distribution and abundance of species. As temperature increases, the rate of metabolism increases and then rapidly declines at higher temperatures – a response that can be described using a thermal performance curve (TPC). Although the shape of the TPC for aerobic metabolism is often attributed to the competing effects of thermodynamics, which can be described using the Arrhenius equation, and the effects of temperature on protein stability, this account represents an over-simplification of the factors acting even at the level of single proteins. In addition, it cannot adequately account for the effects of temperature on complex multistep processes, such as aerobic metabolism, that rely on mechanisms acting across multiple levels of biological organization. The purpose of this review is to explore our current understanding of the factors that shape the TPC for aerobic metabolism in response to acute changes in temperature, and to highlight areas where this understanding is weak or insufficient. Developing a more strongly grounded mechanistic model to account for the shape of the TPC for aerobic metabolism is crucial because these TPCs are the foundation of several recent attempts to predict the responses of species to climate change, including the metabolic theory of ecology and the hypothesis of oxygen and capacity-limited thermal tolerance.

Environmental systems biology of cold-tolerant phenotype in Saccharomyces species adapted to grow at different temperatures

Temperature is one of the leading factors that drive adaptation of organisms and ecosystems. Remarkably, many closely related species share the same habitat because of their different temporal or micro-spatial thermal adaptation. In this study, we seek to find the underlying molecular mechanisms of the cold-tolerant phenotype of closely related yeast species adapted to grow at different temperatures, namely S. kudriavzevii CA111 (cryo-tolerant) and S. cerevisiae 96.2 (thermo-tolerant). Using two different systems approaches, i. thermodynamic-based analysis of a genome-scale metabolic model of S. cerevisiae and ii. large-scale competition experiment of the yeast heterozygote mutant collection, genes and pathways important for the growth at low temperature were identified. In particular, defects in lipid metabolism, oxidoreductase and vitamin pathways affected yeast fitness at cold. Combining the data from both studies, a list of candidate genes was generated and mutants for two predicted cold-favouring genes, GUT2 and ADH3, were created in two natural isolates. Compared with the parental strains, these mutants showed lower fitness at cold temperatures, with S. kudriavzevii displaying the strongest defect. Strikingly, in S. kudriavzevii, these mutations also significantly improve the growth at warm temperatures. In addition, overexpression of ADH3 in S. cerevisiae increased its fitness at cold. These results suggest that temperature-induced redox imbalances could be compensated by increased glycerol accumulation or production of cytosolic acetaldehyde through the deletion of GUT2 or ADH3, respectively.

Metabolic network discovery by top-down and bottom-up approaches and paths for reconciliation

The primary focus in the network-centric analysis of cellular metabolism by systems biology approaches is to identify the active metabolic network for the condition of interest. Two major approaches are available for the discovery of the condition-specific metabolic networks. One approach starts from genome-scale metabolic networks, which cover all possible reactions known to occur in the related organism in a condition-independent manner, and applies methods such as the optimization-based Flux-Balance Analysis to elucidate the active network. The other approach starts from the condition-specific metabolome data, and processes the data with statistical or optimization-based methods to extract information content of the data such that the active network is inferred. These approaches, termed bottom-up and top-down, respectively, are currently employed independently. However, considering that both approaches have the same goal, they can both benefit from each other paving the way for the novel integrative analysis methods of metabolome data- and flux-analysis approaches in the post-genomic era. This study reviews the strengths of constraint-based analysis and network inference methods reported in the metabolic systems biology field; then elaborates on the potential paths to reconcile the two approaches to shed better light on how the metabolism functions.

Physiological and transcriptional responses of anaerobic chemostat cultures of Saccharomyces cerevisiae subjected to diurnal temperature cycles

Diurnal temperature cycling is an intrinsic characteristic of many exposed microbial ecosystems. However, its influence on yeast physiology and the yeast transcriptome has not been studied in detail. In this study, 24-h sinusoidal temperature cycles, oscillating between 12°C and 30°C, were imposed on anaerobic, glucose-limited chemostat cultures of Saccharomyces cerevisiae. After three diurnal temperature cycles (DTC), concentrations of glucose and extracellular metabolites as well as CO2 production rates showed regular, reproducible circadian rhythms. DTC also led to waves of transcriptional activation and repression, which involved one-sixth of the yeast genome. A substantial fraction of these DTC-responsive genes appeared to respond primarily to changes in the glucose concentration. Elimination of known glucose-responsive genes revealed an overrepresentation of previously identified temperature-responsive genes as well as genes involved in the cell cycle and de novo purine biosynthesis. In-depth analysis demonstrated that DTC led to a partial synchronization of the cell cycle of the yeast populations in chemostat cultures, which was lost upon release from DTC. Comparison of DTC results with data from steady-state cultures showed that the 24-h DTC was sufficiently slow to allow S. cerevisiae chemostat cultures to acclimate their transcriptome and physiology at the DTC temperature maximum and to approach acclimation at the DTC temperature minimum. Furthermore, this comparison and literature data on growth rate-dependent cell cycle phase distribution indicated that cell cycle synchronization was most likely an effect of imposed fluctuations of the relative growth rate (μ/μmax) rather than a direct effect of temperature.

Control of glycolytic flux in directed biosynthesis of uridine-phosphoryl compounds through the manipulation of ATP availability

Adenosine triphosphate (ATP), the most important energy source for metabolic reactions and pathways, plays a vital role in control of metabolic flux. Considering the importance of ATP in regulation of the glycolytic pathway, the use of ATP-oriented manipulation is a rational and efficient route to regulate metabolic flux. In this paper, a series of efficient ATP-oriented regulation methods, such as changing ambient temperature and altering reduced nicotinamide adenine dinucleotide (NADH), was developed. To satisfy the different demand for ATP at different phases in directed biosynthesis of uridine-phosphoryl compounds, a multiphase ATP supply regulation strategy was also used to enhance to yield of target metabolites.

A kinetic model of catabolic adaptation and protein reprofiling in Saccharomyces cerevisiae during temperature shifts

In this article, we aim to find an explanation for the surprisingly thin line, with regard to temperature, between cell growth, growth arrest and ultimately loss of cell viability. To this end, we used an integrative approach including both experimental and modelling work. We measured the short- and long-term effects of increases in growth temperature from 28 °C to 37, 39, 41, 42 or 43 °C on the central metabolism of Saccharomyces cerevisiae. Based on the experimental data, we developed a kinetic mathematical model that describes the metabolic and energetic changes in growing bakers' yeast when exposed to a specific temperature upshift. The model includes the temperature dependence of core energy-conserving pathways, trehalose synthesis, protein synthesis and proteolysis. Because our model focuses on protein synthesis and degradation, the net result of which is important in determining the cell's capacity to grow, the model includes growth, i.e. glucose is consumed and biomass and adenosine nucleotide cofactors are produced. The model reproduces both the observed initial metabolic response and the subsequent relaxation into a new steady-state, compatible with the new ambient temperature. In addition, it shows that the energy consumption for proteome reprofiling may be a major determinant of heat-induced growth arrest and subsequent recovery or cell death.

Uncovering by atomic force microscopy of an original circular structure at the yeast cell surface in response to heat shock

BACKGROUND

Atomic Force Microscopy (AFM) is a polyvalent tool that allows biological and mechanical studies of full living microorganisms, and therefore the comprehension of molecular mechanisms at the nanoscale level. By combining AFM with genetical and biochemical methods, we explored the biophysical response of the yeast Saccharomyces cerevisiae to a temperature stress from 30°C to 42°C during 1 h.

RESULTS

We report for the first time the formation of an unprecedented circular structure at the cell surface that takes its origin at a single punctuate source and propagates in a concentric manner to reach a diameter of 2-3 μm at least, thus significantly greater than a bud scar. Concomitantly, the cell wall stiffness determined by the Young's Modulus of heat stressed cells increased two fold with a concurrent increase of chitin. This heat-induced circular structure was not found either in wsc1Δ or bck1Δ mutants that are defective in the CWI signaling pathway, nor in chs1Δ, chs3Δ and bni1Δ mutant cells, reported to be deficient in the proper budding process. It was also abolished in the presence of latrunculin A, a toxin known to destabilize actin cytoskeleton.

CONCLUSIONS

Our results suggest that this singular morphological event occurring at the cell surface is due to a dysfunction in the budding machinery caused by the heat shock and that this phenomenon is under the control of the CWI pathway.

Transcriptional regulation is insufficient to explain substrate-induced flux changes in Bacillus subtilis

Regulation of enzyme expression is one key mechanism by which cells control their metabolic programs. In this work, a quantitative analysis of metabolism in a model bacterium under different conditions shows that expression alone cannot explain the majority of the observed metabolic changes.

Most enzymes are indeed highly expressed in conditions where they are more active.

Quantitatively, however, the observed changes in expression between conditions do not match the changes in activity for most enzymes.

A good quantitative match is only observed for enzymes involved in the TCA cycle.

Metabolomics reveals that increased substrate availability explains only a few instances of changes in activity.

One of the key ways in which microbes are thought to regulate their metabolism is by modulating the availability of enzymes through transcriptional regulation. However, the limited success of efforts to manipulate metabolic fluxes by rewiring the transcriptional network has cast doubt on the idea that transcript abundance controls metabolic fluxes. In this study, we investigate control of metabolic flux in the model bacterium Bacillus subtilis by quantifying fluxes, transcripts, and metabolites in eight metabolic states enforced by different environmental conditions. We find that most enzymes whose flux switches between on and off states, such as those involved in substrate uptake, exhibit large corresponding transcriptional changes. However, for the majority of enzymes in central metabolism, enzyme concentrations were insufficient to explain the observed fluxes—only for a number of reactions in the tricarboxylic acid cycle were enzyme changes approximately proportional to flux changes. Surprisingly, substrate changes revealed by metabolomics were also insufficient to explain observed fluxes, leaving a large role for allosteric regulation and enzyme modification in the control of metabolic fluxes.

Transcriptome-based characterization of interactions between Saccharomyces cerevisiae and Lactobacillus delbrueckii subsp. bulgaricus in lactose-grown chemostat cocultures

Mixed populations of Saccharomyces cerevisiae yeasts and lactic acid bacteria occur in many dairy, food, and beverage fermentations, but knowledge about their interactions is incomplete. In the present study, interactions between Saccharomyces cerevisiae and Lactobacillus delbrueckii subsp. bulgaricus, two microorganisms that co-occur in kefir fermentations, were studied during anaerobic growth on lactose. By combining physiological and transcriptome analysis of the two strains in the cocultures, five mechanisms of interaction were identified. (i) Lb. delbrueckii subsp. bulgaricus hydrolyzes lactose, which cannot be metabolized by S. cerevisiae, to galactose and glucose. Subsequently, galactose, which cannot be metabolized by Lb. delbrueckii subsp. bulgaricus, is excreted and provides a carbon source for yeast. (ii) In pure cultures, Lb. delbrueckii subsp. bulgaricus grows only in the presence of increased CO2 concentrations. In anaerobic mixed cultures, the yeast provides this CO2 via alcoholic fermentation. (iii) Analysis of amino acid consumption from the defined medium indicated that S. cerevisiae supplied alanine to the bacterium. (iv) A mild but significant low-iron response in the yeast transcriptome, identified by DNA microarray analysis, was consistent with the chelation of iron by the lactate produced by Lb. delbrueckii subsp. bulgaricus. (v) Transcriptome analysis of Lb. delbrueckii subsp. bulgaricus in mixed cultures showed an overrepresentation of transcripts involved in lipid metabolism, suggesting either a competition of the two microorganisms for fatty acids or a response to the ethanol produced by S. cerevisiae. This study demonstrates that chemostat-based transcriptome analysis is a powerful tool to investigate microbial interactions in mixed populations.

Similar temperature dependencies of glycolytic enzymes: an evolutionary adaptation to temperature dynamics?

BACKGROUND

Temperature strongly affects microbial growth, and many microorganisms have to deal with temperature fluctuations in their natural environment. To understand regulation strategies that underlie microbial temperature responses and adaptation, we studied glycolytic pathway kinetics in Saccharomyces cerevisiae during temperature changes.

RESULTS

Saccharomyces cerevisiae was grown under different temperature regimes and glucose availability conditions. These included glucose-excess batch cultures at different temperatures and glucose-limited chemostat cultures, subjected to fast linear temperature shifts and circadian sinoidal temperature cycles. An observed temperature-independent relation between intracellular levels of glycolytic metabolites and residual glucose concentration for all experimental conditions revealed that it is the substrate availability rather than temperature that determines intracellular metabolite profiles. This observation corresponded with predictions generated in silico with a kinetic model of yeast glycolysis, when the catalytic capacities of all glycolytic enzymes were set to share the same normalized temperature dependency.

CONCLUSIONS

From an evolutionary perspective, such similar temperature dependencies allow cells to adapt more rapidly to temperature changes, because they result in minimal perturbations of intracellular metabolite levels, thus circumventing the need for extensive modification of enzyme levels.

Metabolism in the age of ‘omes’

Much research in comparative physiology is now performed using ‘omics’ tools and many results are interpreted in terms of the effects of changes in gene expression on energy metabolism. However, ‘metabolism’ is a complex phenomenon that spans multiple levels of biological organization. In addition rates and directions of flux change dynamically under various physiological circumstances. Within cells, message level cannot be equated with protein level because multiple mechanisms are at play in the ‘regulatory hierarchy’ from gene to mRNA to enzyme protein. This results in many documented instances wherein change in mRNA levels and change in enzyme levels are unrelated. It is also known from metabolic control analysis that the influence of single steps in pathways on flux is often small. Flux is a system property and its control tends to be distributed among multiple steps. Consequently, change in enzyme levels cannot be equated with change in flux. Approaches developed by Hans Westerhoff and colleagues, called ‘hierarchical regulation analysis’, allow quantitative determination of the extent to which ‘hierarchical regulation’, involving change in enzyme level, and ‘metabolic regulation’, involving the modulation of the activity of preexisting enzyme, regulate flux. We outline these approaches and provide examples to show their applicability to problems of interest to comparative physiologists.

Isoenzyme expression changes in response to high temperature determine the metabolic regulation of increased glycolytic flux in yeast

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.

Use of sequential-batch fermentations to characterize the impact of mild hypothermic temperatures on the anaerobic stoichiometry and kinetics of Saccharomyces cerevisiae

This work presents a characterization of the stoichiometry and kinetics of anaerobic batch growth of Saccharomyces cerevisiae at cultivation temperatures between 12 and 30°C. To minimize the influence of the inoculum condition and ensure full adaptation to the cultivation temperature, the experiments were carried out in sequencing batch reactors. It was observed that the growth rate obtained in the first batch performed after each temperature shift was 10-30% different compared with the subsequent batches at the same temperature, which were much more reproducible. This indicates that the sequencing batch approach provides accurate and reproducible growth rate data. Data reconciliation was applied to the measured time patterns of substrate, biomass, carbon dioxide and byproducts with the constraint that the elemental conservation relations were satisfied, allowing to obtain consistent best estimates of all uptake and secretion rates. Subsequently, it was attempted to obtain an appropriate model description of the temperature dependency of these rates. It was found that the Ratkowsky model provided a better description of the temperature dependency of growth, uptake and secretion rates than the Arrhenius law. Most interesting was to find that most of the biomass-specific rates have the same temperature dependency, leading to a near temperature independent batch stoichiometry.

Genome-wide analysis of yeast stress survival and tolerance acquisition to analyze the central trade-off between growth rate and cellular robustness

A genome-wide analysis of the acquisition of stress cross-tolerance shows that reduction of growth rate is an important determinant of severe stress survival. Cellular functions important for the coupling of growth rate to stress resistance are identified, as are those required for cross-tolerance acquisition independent of growth rate reduction.

All organisms have evolved to cope with changes in environmental conditions, ensuring the optimal combination of proliferation and survival. In yeast, exposure to a mild stress leads to an increased tolerance for other stresses. This suggests that yeast uses information from the environment to prepare for future threats. We used the yeast knockout collection to systematically investigate the genes and functions involved in severe stress survival and in the acquisition of stress (cross-) tolerance. Besides genes and functions relevant for survival of heat, acid, and oxidative stress, we found an inverse correlation between mutant growth rate and stress survival. Using chemostat cultures, we confirmed that growth rate governs stress tolerance, with higher growth efficiency at low growth rates liberating the energy for these investments. Cellular functions required for stress tolerance acquisition, independent of the reduction in growth rate, were involved in vesicular transport, the Rpd3 histone deacetylase complex, and the mitotic cell cycle. Stress resistance and acquired stress tolerance in Saccharomyces cerevisiae are governed by a combination of stress-specific and general processes. The reduction of growth rate, irrespective of the cause of this reduction, leads to redistribution of resources toward stress tolerance functions, thus preparing the cells for impending change.

Dynamic regulation of mitochondrial respiratory chain efficiency in Saccharomyces cerevisiae

To adapt to changes in the environment, cells have to dynamically alter their phenotype in response to, for instance, temperature and oxygen availability. Interestingly, mitochondrial function in Saccharomyces cerevisiae is inherently temperature sensitive; above 37 °C, yeast cells cannot grow on respiratory carbon sources. To investigate this phenomenon, we studied the effect of cultivation temperature on the efficiency (production of ATP per atom of oxygen consumed, or P/O) of the yeast respiratory chain in glucose-limited chemostats. We determined that even though the specific oxygen consumption rate did not change with temperature, oxygen consumption no longer contributed to mitochondrial ATP generation at temperatures higher than 37 °C. Remarkably, between 30 and 37 °C, we observed a linear increase in respiratory efficiency with growth temperature, up to a P/O of 1.4, close to the theoretical maximum that can be reached in vivo. The temperature-dependent increase in efficiency required the presence of the mitochondrial glycerol-3-phosphate dehydrogenase GUT2. Respiratory chain efficiency was also altered in response to changes in oxygen availibility. Our data show that, even in the absence of alternative oxidases or uncoupling proteins, yeast has retained the ability to dynamically regulate the efficiency of coupling of oxygen consumption to proton translocation in the respiratory chain in response to changes in the environment.

Integrated multilaboratory systems biology reveals differences in protein metabolism between two reference yeast strains

The field of systems biology is often held back by difficulties in obtaining comprehensive, high-quality, quantitative data sets. In this paper, we undertook an interlaboratory effort to generate such a data set for a very large number of cellular components in the yeast Saccharomyces cerevisiae, a widely used model organism that is also used in the production of fuels, chemicals, food ingredients and pharmaceuticals. With the current focus on biofuels and sustainability, there is much interest in harnessing this species as a general cell factory. In this study, we characterized two yeast strains, under two standard growth conditions. We ensured the high quality of the experimental data by evaluating a wide range of sampling and analytical techniques. Here we show significant differences in the maximum specific growth rate and biomass yield between the two strains. On the basis of the integrated analysis of the high-throughput data, we hypothesize that differences in phenotype are due to differences in protein metabolism.

Expanding a dynamic flux balance model of yeast fermentation to genome-scale

Background

Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints.

Results

Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol.

Conclusion

A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations.

Analysis of operating principles with S-system models

Operating principles address general questions regarding the response dynamics of biological systems as we observe or hypothesize them, in comparison to a priori equally valid alternatives. In analogy to design principles, the question arises: Why are some operating strategies encountered more frequently than others and in what sense might they be superior? It is at this point impossible to study operation principles in complete generality, but the work here discusses the important situation where a biological system must shift operation from its normal steady state to a new steady state. This situation is quite common and includes many stress responses. We present two distinct methods for determining different solutions to this task of achieving a new target steady state. Both methods utilize the property of S-system models within Biochemical Systems Theory (BST) that steady states can be explicitly represented as systems of linear algebraic equations. The first method uses matrix inversion, a pseudo-inverse, or regression to characterize the entire admissible solution space. Operations on the basis of the solution space permit modest alterations of the transients toward the target steady state. The second method uses standard or mixed integer linear programming to determine admissible solutions that satisfy criteria of functional effectiveness, which are specified beforehand. As an illustration, we use both methods to characterize alternative response patterns of yeast subjected to heat stress, and compare them with observations from the literature.

Quantitative analysis of flux regulation through hierarchical regulation analysis

Regulation analysis is a methodology that quantifies to what extent a change in the flux through a metabolic pathway is regulated by either gene expression or metabolism. Two extensions to regulation analysis were developed over the past years: (i) the regulation of V(max) can be dissected into the various levels of the gene-expression cascade, such as transcription, translation, protein degradation, etc. and (ii) a time-dependent version allows following flux regulation when cells adapt to changes in their environment. The methodology of the original form of regulation analysis as well as of the two extensions will be described in detail. In addition, we will show what is needed to apply regulation analysis in practice. Studies in which the different versions of regulation analysis were applied revealed that flux regulation was distributed over various processes and depended on time, enzyme, and condition of interest. In the case of the regulation of glycolysis in baker's yeast, it appeared, however, that cells that remain under respirofermentative conditions during a physiological challenge tend to invoke more gene-expression regulation, while a shift between respirofermentative and respiratory conditions invokes an important contribution of metabolic regulation. The complexity of the regulation observed in these studies raises the question what is the advantage of this highly distributed and condition-dependent flux regulation.

Complex coordination of multi-scale cellular responses to environmental stress

Cells and organisms are regularly exposed to a variety of stresses, and effective responses are a matter of survival. The article describes a multi-scale experimental and dynamical modeling analysis that clearly indicates concerted stress control in different temporal and organizational domains, and a strong synergy between the dynamics of genes, proteins and metabolites. Specifically, we show with in vivo NMR measurements of metabolic profiles that baker's yeast responds to a paradigmatic stress, heat, at three organizational levels and in two time regimes. At the metabolic level, an almost immediate response is mounted. However, this response is a "quick fix" in comparison to a much more effective response that had been pre-organized in earlier periods of heat stress and is an order of magnitude stronger. Equipped with the metabolic profile data, our modeling efforts resulted in a crisp, quantitative separation of response actions at the levels of metabolic control and gene regulation. They also led to predictions of necessary changes in protein levels and clearly demonstrated that formerly observed temperature profiles of key enzyme activities are not sufficient to explain the accumulation of trehalose as an immediate response to sudden heat stress.

Comparative analysis of transcriptome and fitness profiles reveals general and condition-specific cellular functions involved in adaptation to environmental change in Saccharomyces cerevisiae

The transcriptional responses of yeast cells to a wide variety of stress conditions have been studied extensively. In addition, deletion mutant collections have been widely used to measure the combined effect of gene loss and stress on growth (fitness). Here we present a comparative analysis of 1,095 publicly available transcription and genome-wide fitness profiles in yeast, from different laboratories and experimental platforms. We analyzed these data, using T-profiler, to describe the correlation in behavior of a priori defined functional groups. Two-mode clustering analysis of the fitness T-profiles revealed that functional groups involved in regulating ribosome biogenesis and translation offer general stress resistance. These groups are closely related to growth rate and nutrient availability. General stress sensitivity was found in deletion mutant groups functioning in intracellular vesicular transport, actin cytoskeleton organization, and cell polarity, indicating that they play an key role in maintaining yeast adaptability. Analysis of the phenotypic and transcriptional variability of our a priori defined functional groups showed that the quantitative effect on fitness of both resistant and sensitive groups is highly condition-dependent. Finally, we discuss the implications of our results for combinatorial drug design.