To divide or not to divide: A key role of Rim15 in calorie-restricted yeast cultures

AbstractThe PAS kinase Rim15 is proposed to integrate signals from different nutrient-sensing pathways and to control transcriptional reprogramming of Saccharomyces cerevisiae upon nutrient depletion. Despite this proposed role, previous transcriptome analyses of rim15 mutants solely focused on growing cultures. In the present work, retentostat cultivation enabled analysis of the role of Rim15 under severely calorie-restricted, virtually non-growing conditions. Under these conditions, deletion of RIM15 affected transcription of over 10-fold more genes than in growing cultures. Transcriptional responses, metabolic rates and cellular morphology indicated a key role of Rim15 in controlled cell-cycle arrest upon nutrient depletion. Moreover, deletion of rim15 reduced heat-shock tolerance in non-growing, but not in growing cultures. The failure of rim15 cells to adapt to calorie restriction by entering a robust post-mitotic state resembles cancer cell physiology and shows that retentostat cultivation of yeast strains can provide relevant models for healthy post-mitotic and transformed human cells

Exploiting combinatorial cultivation conditions to infer transcriptional regulation

BACKGROUND: Regulatory networks often employ the model that attributes changes in gene expression levels, as observed across different cellular conditions, to changes in the activity of transcription factors (TFs). Although the actual conditions that trigger a change in TF activity should form an integral part of the generated regulatory network, they are usually lacking. This is due to the fact that the large heterogeneity in the employed conditions and the continuous changes in environmental parameters in the often used shake-flask cultures, prevent the unambiguous modeling of the cultivation conditions within the computational framework. RESULTS: We designed an experimental setup that allows us to explicitly model the cultivation conditions and use these to infer the activity of TFs. The yeast Saccharomyces cerevisiae was cultivated under four different nutrient limitations in both aerobic and anaerobic chemostat cultures. In the chemostats, environmental and growth parameters are accurately controlled. Consequently, the measured transcriptional response can be directly correlated with changes in the limited nutrient or oxygen concentration. We devised a tailor-made computational approach that exploits the systematic setup of the cultivation conditions in order to identify the individual and combined effects of nutrient limitations and oxygen availability on expression behavior and TF activity. CONCLUSION: Incorporating the actual growth conditions when inferring regulatory relationships provides detailed insight in the functionality of the TFs that are triggered by changes in the employed cultivation conditions. For example, our results confirm the established role of TF Hap4 in both aerobic regulation and glucose derepression. Among the numerous inferred condition-specific regulatory associations between gene sets and TFs, also many novel putative regulatory mechanisms, such as the possible role of Tye7 in sulfur metabolism, were identified

Transcription factor control of growth rate dependent genes in Saccharomyces cerevisiae: A three factor design

<p>Abstract</p> <p>Background</p> <p>Characterization of cellular growth is central to understanding living systems. Here, we applied a three-factor design to study the relationship between specific growth rate and genome-wide gene expression in 36 steady-state chemostat cultures of <it>Saccharomyces cerevisiae</it>. The three factors we considered were specific growth rate, nutrient limitation, and oxygen availability.</p> <p>Results</p> <p>We identified 268 growth rate dependent genes, independent of nutrient limitation and oxygen availability. The transcriptional response was used to identify key areas in metabolism around which mRNA expression changes are significantly associated. Among key metabolic pathways, this analysis revealed <it>de novo </it>synthesis of pyrimidine ribonucleotides and ATP producing and consuming reactions at fast cellular growth. By scoring the significance of overlap between growth rate dependent genes and known transcription factor target sets, transcription factors that coordinate balanced growth were also identified. Our analysis shows that Fhl1, Rap1, and Sfp1, regulating protein biosynthesis, have significantly enriched target sets for genes up-regulated with increasing growth rate. Cell cycle regulators, such as Ace2 and Swi6, and stress response regulators, such as Yap1, were also shown to have significantly enriched target sets.</p> <p>Conclusion</p> <p>Our work, which is the first genome-wide gene expression study to investigate specific growth rate and consider the impact of oxygen availability, provides a more conservative estimate of growth rate dependent genes than previously reported. We also provide a global view of how a small set of transcription factors, 13 in total, contribute to control of cellular growth rate. We anticipate that multi-factorial designs will play an increasing role in elucidating cellular regulation.</p

Combinatorial effects of environmental parameters on transcriptional regulation in Saccharomyces cerevisiae: A quantitative analysis of a compendium of chemostat-based transcriptome data

<p>Abstract</p> <p>Background</p> <p>Microorganisms adapt their transcriptome by integrating multiple chemical and physical signals from their environment. Shake-flask cultivation does not allow precise manipulation of individual culture parameters and therefore precludes a quantitative analysis of the (combinatorial) influence of these parameters on transcriptional regulation. Steady-state chemostat cultures, which do enable accurate control, measurement and manipulation of individual cultivation parameters (e.g. specific growth rate, temperature, identity of the growth-limiting nutrient) appear to provide a promising experimental platform for such a combinatorial analysis.</p> <p>Results</p> <p>A microarray compendium of 170 steady-state chemostat cultures of the yeast <it>Saccharomyces cerevisiae </it>is presented and analyzed. The 170 microarrays encompass 55 unique conditions, which can be characterized by the combined settings of 10 different cultivation parameters. By applying a regression model to assess the impact of (combinations of) cultivation parameters on the transcriptome, most <it>S. cerevisiae </it>genes were shown to be influenced by multiple cultivation parameters, and in many cases by combinatorial effects of cultivation parameters. The inclusion of these combinatorial effects in the regression model led to higher explained variance of the gene expression patterns and resulted in higher function enrichment in subsequent analysis. We further demonstrate the usefulness of the compendium and regression analysis for interpretation of shake-flask-based transcriptome studies and for guiding functional analysis of (uncharacterized) genes and pathways.</p> <p>Conclusion</p> <p>Modeling the combinatorial effects of environmental parameters on the transcriptome is crucial for understanding transcriptional regulation. Chemostat cultivation offers a powerful tool for such an approach.</p

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

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.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

Full humanization of the glycolytic pathway in Saccharomyces cerevisiae

Although transplantation of single genes in yeast plays a key role in elucidating gene functionality in metazoans, technical challenges hamper humanization of full pathways and processes. Empowered by advances in synthetic biology, this study demonstrates the feasibility and implementation of full humanization of glycolysis in yeast. Single gene and full pathway transplantation revealed the remarkable conservation of glycolytic and moonlighting functions and, combined with evolutionary strategies, brought to light context-dependent responses. Human hexokinase 1 and 2, but not 4, required mutations in their catalytic or allosteric sites for functionality in yeast, whereas hexokinase 3 was unable to complement its yeast ortholog. Comparison with human tissues cultures showed preservation of turnover numbers of human glycolytic enzymes in yeast and human cell cultures. This demonstration of transplantation of an entire essential pathway paves the way for establishment of species-, tissue-, and disease-specific metazoan models

Proteome analysis of yeast response to various nutrient limitations

We compared the response of Saccharomyces cerevisiae to carbon (glucose) and nitrogen (ammonia) limitation in chemostat cultivation at the proteome level. Protein levels were differentially quantified using unlabeled and (15)N metabolically labeled yeast cultures. A total of 928 proteins covering a wide range of isoelectric points, molecular weights and subcellular localizations were identified. Stringent statistical analysis identified 51 proteins upregulated in response to glucose limitation and 51 upregulated in response to ammonia limitation. Under glucose limitation, typical glucose-repressed genes encoding proteins involved in alternative carbon source utilization, fatty acids β-oxidation and oxidative phosphorylation displayed an increased protein level. Proteins upregulated in response to nitrogen limitation were mostly involved in scavenging of alternative nitrogen sources and protein degradation. Comparison of transcript and protein levels clearly showed that upregulation in response to glucose limitation was mainly transcriptionally controlled, whereas upregulation in response to nitrogen limitation was essentially controlled at the post-transcriptional level by increased translational efficiency and/or decreased protein degradation. These observations underline the need for multilevel analysis in yeast systems biology

De novo sequencing, assembly and analysis of the genome of the laboratory strain Saccharomyces cerevisiae CEN.PK113-7D, a model for modern industrial biotechnology

Saccharomyces cerevisiae CEN.PK 113-7D is widely used for metabolic engineering and systems biology research in industry and academia. We sequenced, assembled, annotated and analyzed its genome. Single-nucleotide variations (SNV), insertions/deletions (indels) and differences in genome organization compared to the reference strain S. cerevisiae S288C were analyzed. In addition to a few large deletions and duplications, nearly 3000 indels were identified in the CEN.PK113-7D genome relative to S288C. These differences were overrepresented in genes whose functions are related to transcriptional regulation and chromatin remodelling. Some of these variations were caused by unstable tandem repeats, suggesting an innate evolvability of the corresponding genes. Besides a previously characterized mutation in adenylate cyclase, the CEN.PK113-7D genome sequence revealed a significant enrichment of non-synonymous mutations in genes encoding for components of the cAMP signalling pathway. Some phenotypic characteristics of the CEN.PK113-7D strains were explained by the presence of additional specific metabolic genes relative to S288C. In particular, the presence of the BIO1 and BIO6 genes correlated with a biotin prototrophy of CEN.PK113-7D. Furthermore, the copy number, chromosomal location and sequences of the MAL loci were resolved. The assembled sequence reveals that CEN.PK113-7D has a mosaic genome that combines characteristics of laboratory strains and wild-industrial strains

The Crabtree effect shapes the Saccharomyces cerevisiae lag phase during the switch between different carbon sources

When faced with environmental changes, microbes often enter a temporary growth arrest during which they reprogram the expression of specific genes to adapt to the new conditions. A prime example of such a lag phase occurs when microbes need to switch from glucose to other, less-preferred carbon sources. Despite its industrial relevance, the genetic network that determines the duration of the lag phase has not been studied in much detail. Here, we performed a genome-wide Bar-Seq screen to identify genetic determinants of the Saccharomyces cerevisiae glucose-to-galactose lag phase. The results show that genes involved in respiration, and specifically those encoding complexes III and IV of the electron transport chain, are needed for efficient growth resumption after the lag phase. Anaerobic growth experiments confirmed the importance of respiratory energy conversion in determining the lag phase duration. Moreover, overexpression of the central regulator of respiration, HAP4, leads to significantly shorter lag phases. Together, these results suggest that the glucose-induced repression of respiration, known as the Crabtree effect, is a major determinant of microbial fitness in fluctuating carbon environments. IMPORTANCE: The lag phase is arguably one of the prime characteristics of microbial growth. Longer lag phases result in lower competitive fitness in variable environments, and the duration of the lag phase is also important in many industrial processes where long lag phases lead to sluggish, less efficient fermentations. Despite the immense importance of the lag phase, surprisingly little is known about the exact molecular processes that determine its duration. Our study uses the molecular toolbox of S. cerevisiae combined with detailed growth experiments to reveal how the transition from fermentative to respirative metabolism is a key bottleneck for cells to overcome the lag phase. Together, our findings not only yield insight into the key molecular processes and genes that influence lag duration but also open routes to increase the efficiency of industrial fermentations and offer an experimental framework to study other types of lag behavior

Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies.

When conditions change, unicellular organisms rewire their metabolism to sustain cell maintenance and cellular growth. Such rewiring may be understood as resource re-allocation under cellular constraints. Eukaryal cells contain metabolically active organelles such as mitochondria, competing for cytosolic space and resources, and the nature of the relevant cellular constraints remain to be determined for such cells. Here, we present a comprehensive metabolic model of the yeast cell, based on its full metabolic reaction network extended with protein synthesis and degradation reactions. The model predicts metabolic fluxes and corresponding protein expression by constraining compartment-specific protein pools and maximising growth rate. Comparing model predictions with quantitative experimental data suggests that under glucose limitation, a mitochondrial constraint limits growth at the onset of ethanol formation-known as the Crabtree effect. Under sugar excess, however, a constraint on total cytosolic volume dictates overflow metabolism. Our comprehensive model thus identifies condition-dependent and compartment-specific constraints that can explain metabolic strategies and protein expression profiles from growth rate optimisation, providing a framework to understand metabolic adaptation in eukaryal cells