Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator

Enhanced xylose fermentation capacity related to an altered glucose sensing and repression network in a recombinant Saccharomyces cerevisiae

The co-fermentation of glucose and xylose is one of the issues in decreasing the price of biofuel or chemicals produced from lignocellulosic materials. A glucose and xylose co-utilizing Saccharomyces cerevisiae was obtained through rational genetic manipulation. Non-rational evolution in xylose was performed, and the xylose utilization efficiency of the engineered strain was significantly enhanced. The results of transcriptome study suggested that Snf1/Mig1-mediated regulation, a part of glucose sensing and repression network, was altered in the evolved strain and might be related to the enhancement of xylose utilization.

The AMPK family member Snf1 protects Saccharomyces cerevisiae cells upon glutathione oxidation

The AMPK/Snf1 kinase has a central role in carbon metabolism homeostasis in Saccharomyces cerevisiae. In this study, we show that Snf1 activity, which requires phosphorylation of the Thr210 residue, is needed for protection against selenite toxicity. Such protection involves the Elm1 kinase, which acts upstream of Snf1 to activate it. Basal Snf1 activity is sufficient for the defense against selenite, although Snf1 Thr210 phosphorylation levels become increased at advanced treatment times, probably by inhibition of the Snf1 dephosphorylation function of the Reg1 phosphatase. Contrary to glucose deprivation, Snf1 remains cytosolic during selenite treatment, and the protective function of the kinase does not require its known nuclear effectors. Upon selenite treatment, a null snf1 mutant displays higher levels of oxidized versus reduced glutathione compared to wild type cells, and its hypersensitivity to the agent is rescued by overexpression of the glutathione reductase gene GLR1. In the presence of agents such as diethyl maleate or diamide, which cause alterations in glutathione redox homeostasis by increasing the levels of oxidized glutathione, yeast cells also require Snf1 in an Elm1-dependent manner for growth. These observations demonstrate a role of Snf1 to protect yeast cells in situations where glutathione-dependent redox homeostasis is altered to a more oxidant intracellular environment and associates AMPK to responses against oxidative stress.

The evolutionary rewiring of ubiquitination targets has reprogrammed the regulation of carbon assimilation in the pathogenic yeast Candida albicans

Microbes must assimilate carbon to grow and colonize their niches. Transcript profiling has suggested that Candida albicans, a major pathogen of humans, regulates its carbon assimilation in an analogous fashion to the model yeast Saccharomyces cerevisiae, repressing metabolic pathways required for the use of alterative nonpreferred carbon sources when sugars are available. However, we show that there is significant dislocation between the proteome and transcriptome in C. albicans. Glucose triggers the degradation of the ICL1 and PCK1 transcripts in C. albicans, yet isocitrate lyase (Icl1) and phosphoenolpyruvate carboxykinase (Pck1) are stable and are retained. Indeed, numerous enzymes required for the assimilation of carboxylic and fatty acids are not degraded in response to glucose. However, when expressed in C. albicans, S. cerevisiae Icl1 (ScIcl1) is subjected to glucose-accelerated degradation, indicating that like S. cerevisiae, this pathogen has the molecular apparatus required to execute ubiquitin-dependent catabolite inactivation. C. albicans Icl1 (CaIcl1) lacks analogous ubiquitination sites and is stable under these conditions, but the addition of a ubiquitination site programs glucose-accelerated degradation of CaIcl1. Also, catabolite inactivation is slowed in C. albicans ubi4 cells. Ubiquitination sites are present in gluconeogenic and glyoxylate cycle enzymes from S. cerevisiae but absent from their C. albicans homologues. We conclude that evolutionary rewiring of ubiquitination targets has meant that following glucose exposure, C. albicans retains key metabolic functions, allowing it to continue to assimilate alternative carbon sources. This metabolic flexibility may be critical during infection, facilitating the rapid colonization of dynamic host niches containing complex arrays of nutrients.

Pathogenic microbes must assimilate a range of carbon sources to grow and colonize their hosts. Current views about carbon assimilation in the pathogenic yeast Candida albicans are strongly influenced by the Saccharomyces cerevisiae paradigm in which cells faced with choices of nutrients first use energetically favorable sugars, degrading enzymes required for the assimilation of less favorable alternative carbon sources. We show that this is not the case in C. albicans because there has been significant evolutionary rewiring of the molecular signals that promote enzyme degradation in response to glucose. As a result, this major pathogen of humans retains enzymes required for the utilization of physiologically relevant carbon sources such as lactic acid and fatty acids, allowing it to continue to use these host nutrients even when glucose is available. This phenomenon probably enhances efficient colonization of host niches where sugars are only transiently available.

Nutritional control of growth and development in yeast

Availability of key nutrients, such as sugars, amino acids, and nitrogen compounds, dictates the developmental programs and the growth rates of yeast cells. A number of overlapping signaling networks--those centered on Ras/protein kinase A, AMP-activated kinase, and target of rapamycin complex I, for instance--inform cells on nutrient availability and influence the cells' transcriptional, translational, posttranslational, and metabolic profiles as well as their developmental decisions. Here I review our current understanding of the structures of the networks responsible for assessing the quantity and quality of carbon and nitrogen sources. I review how these signaling pathways impinge on transcriptional, metabolic, and developmental programs to optimize survival of cells under different environmental conditions. I highlight the profound knowledge we have gained on the structure of these signaling networks but also emphasize the limits of our current understanding of the dynamics of these signaling networks. Moreover, the conservation of these pathways has allowed us to extrapolate our finding with yeast to address issues of lifespan, cancer metabolism, and growth control in more complex organisms.

Snf1/AMPK regulates Gcn5 occupancy, H3 acetylation and chromatin remodelling at S. cerevisiae ADY2 promoter

The ability of cells to respond to changes in their environment is mediated by transcription factors that remodel chromatin and reprogram expression of specific subsets of genes. In Saccharomyces cerevisiae, changes in carbon source lead to gene induction by Adr1 and Cat8 that are known to require the upstream function of the Snf1 protein kinase, the central regulator of carbon metabolism, to exert their activating effect. How Snf1 facilitates transcription activation by Adr1 and Cat8 is not known. Here we show that under derepressing conditions, deletion of SNF1 abolishes the increase of histone H3 acetylation at the promoter of the glucose-repressed ADY2 gene, and as a consequence profoundly affects the chromatin structural alterations accompanying transcriptional activation. Adr1 and Cat8 are not required to regulate the acetylation switch and show only a partial influence on chromatin remodelling at this promoter, though their double deletion completely abolishes mRNA accumulation. Finally, we show that under derepressing conditions the recruitment of the histone acetyltransferase Gcn5 is abolished by SNF1 deletion, possibly explaining the lack of increased histone H3 acetylation and nucleosome remodelling. The results highlight a mechanism by which signalling to chromatin provides an essential permissive signal that is required for activation by glucose-responsive transcription factors.

Correlation of gene expression and protein production rate - a system wide study

BACKGROUND

Growth rate is a major determinant of intracellular function. However its effects can only be properly dissected with technically demanding chemostat cultivations in which it can be controlled. Recent work on Saccharomyces cerevisiae chemostat cultivations provided the first analysis on genome wide effects of growth rate. In this work we study the filamentous fungus Trichoderma reesei (Hypocrea jecorina) that is an industrial protein production host known for its exceptional protein secretion capability. Interestingly, it exhibits a low growth rate protein production phenotype.

RESULTS

We have used transcriptomics and proteomics to study the effect of growth rate and cell density on protein production in chemostat cultivations of T. reesei. Use of chemostat allowed control of growth rate and exact estimation of the extracellular specific protein production rate (SPPR). We find that major biosynthetic activities are all negatively correlated with SPPR. We also find that expression of many genes of secreted proteins and secondary metabolism, as well as various lineage specific, mostly unknown genes are positively correlated with SPPR. Finally, we enumerate possible regulators and regulatory mechanisms, arising from the data, for this response.

CONCLUSIONS

Based on these results it appears that in low growth rate protein production energy is very efficiently used primarly for protein production. Also, we propose that flux through early glycolysis or the TCA cycle is a more fundamental determining factor than growth rate for low growth rate protein production and we propose a novel eukaryotic response to this i.e. the lineage specific response (LSR).

Mapping the interaction of Snf1 with TORC1 in Saccharomyces cerevisiae

Nutrient sensing and coordination of metabolic pathways are crucial functions for living cells. A combined analysis of the yeast transcriptome, phosphoproteome and metabolome is used to investigate the interactions between the Snf1 and TORC1 pathways under nutrient-limited conditions.

Snf1 regulates a broad range of biological processes, while target of rapamycin complex 1 (TORC1) seems to be repressed under both glucose- and ammonium-limited conditions.

Snf1 has a role in regulating amino acids by upregulating the NADP+-dependent glutamate dehydrogenase (encoded by GDH3) under glucose-limited condition.

In addition to the accepted role of Snf1 in regulating fatty acid (FA) metabolism, TORC1 may also regulate FA metabolism.

Direct interactions between Snf1 and TORC1 pathways are unlikely under nutrient-limited conditions and TORC1 might be repressed in a manner that is independent of Snf1.

Nutrient sensing and coordination of metabolic pathways are crucial functions for all living cells, but details of the coordination under different environmental conditions remain elusive. We therefore undertook a systems biology approach to investigate the interactions between the Snf1 and the target of rapamycin complex 1 (TORC1) in Saccharomyces cerevisiae. We show that Snf1 regulates a much broader range of biological processes compared with TORC1 under both glucose- and ammonium-limited conditions. We also find that Snf1 has a role in upregulating the NADP⁺-dependent glutamate dehydrogenase (encoded by GDH3) under derepressing condition, and therefore may also have a role in ammonium assimilation and amino-acid biosynthesis, which can be considered as a convergence of Snf1 and TORC1 pathways. In addition to the accepted role of Snf1 in regulating fatty acid (FA) metabolism, we show that TORC1 also regulates FA metabolism, likely through modulating the peroxisome and β-oxidation. Finally, we conclude that direct interactions between Snf1 and TORC1 pathways are unlikely under nutrient-limited conditions and propose that TORC1 is repressed in a manner that is independent of Snf1.

The AMPK/SNF1/SnRK1 fuel gauge and energy regulator: structure, function and regulation

All life forms on earth require a continuous input and monitoring of carbon and energy supplies. The AMP-activated kinase (AMPK)/sucrose non-fermenting1 (SNF1)/Snf1-related kinase1 (SnRK1) protein kinases are evolutionarily conserved metabolic sensors found in all eukaryotic organisms from simple unicellular fungi (yeast SNF1) to animals (AMPK) and plants (SnRK1). Activated by starvation and energy-depleting stress conditions, they enable energy homeostasis and survival by up-regulating energy-conserving and energy-producing catabolic processes, and by limiting energy-consuming anabolic metabolism. In addition, they control normal growth and development as well as metabolic homeostasis at the organismal level. As such, the AMPK/SNF1/SnRK1 kinases act in concert with other central signaling components to control carbohydrate uptake and metabolism, fatty acid and lipid biosynthesis and the storage of carbon energy reserves. Moreover, they have a tremendous impact on developmental processes that are triggered by environmental changes such as nutrient depletion or stress. Although intensive research by many groups has partly unveiled the factors that regulate AMPK/SNF1/SnRK1 kinase activity as well as the pathways and substrates they control, several fundamental issues still await to be clarified. In this review, we will highlight these issues and focus on the structure, function and regulation of the AMPK/SNF1/SnRK1 kinases.

Lipid biosynthesis monitored at the single-cell level in Saccharomyces cerevisiae

There is increasing interest in bioengineering of lipids for use in functional foods, pharmaceuticals, and biofuels. Saccharomyces cerevisiae is a widely utilized cell factory for biotechnological production, thus a tempting alternative. Herein, we show how its neutral lipid accumulation varies throughout metabolic phases under nutritional conditions relevant for large-scale fermentation. Population-averaged metabolic data were correlated with lipid storage at the single-cell level monitored at submicron resolution by label-free coherent anti-Stokes Raman scattering (CARS) microscopy. While lipid droplet sizes are fairly constant, the number of droplets is a dynamic parameter determined by glucose and ethanol levels. The lowest number of lipid droplets is observed in the transition phase between glucose and ethanol fermentation. It is followed by a buildup during the ethanol phase. The surplus of accumulated lipids is then mobilized at concurrent glucose and ethanol starvation in the subsequent stationary phase. Thus, the highest amount of lipids is found in the ethanol phase, which is about 0.3 fL/cell. Our results indicate that the budding yeast, S. cerevisiae, can be used for the biosynthesis of lipids and demonstrate the strength of CARS microscopy for monitoring the dynamics of lipid metabolism at the single-cell level of importance for optimized lipid production.

Cell growth and cell cycle in Saccharomyces cerevisiae: basic regulatory design and protein-protein interaction network

In this review we summarize the major connections between cell growth and cell cycle in the model eukaryote Saccharomyces cerevisiae. In S. cerevisiae regulation of cell cycle progression is achieved predominantly during a narrow interval in the late G1 phase known as START (Pringle and Hartwell, 1981). At START a yeast cell integrates environmental and internal signals (such as nutrient availability, presence of pheromone, attainment of a critical size, status of the metabolic machinery) and decides whether to enter a new cell cycle or to undertake an alternative developmental program. Several signaling pathways, that act to connect the nutritional status to cellular actions, are briefly outlined. A Growth & Cycle interaction network has been manually curated. More than one fifth of the edges within the Growth & Cycle network connect Growth and Cycle proteins, indicating a strong interconnection between the processes of cell growth and cell cycle. The backbone of the Growth & Cycle network is composed of middle-degree nodes suggesting that it shares some properties with HOT networks. The development of multi-scale modeling and simulation analysis will help to elucidate relevant central features of growth and cycle as well as to identify their system-level properties. Confident collaborative efforts involving different expertises will allow to construct consensus, integrated models effectively linking the processes of cell growth and cell cycle, ultimately contributing to shed more light also on diseases in which an altered proliferation ability is observed, such as cancer.

Regulation and control of metabolic fluxes in microbes

After about ten years of research renaissance in metabolism, the present challenge is to understand how metabolic fluxes are controlled by a complex interplay of overlapping regulatory mechanisms. Reconstruction of various regulatory network topologies is steaming, illustrating that we underestimated the broad importance of post-translational modifications such as enzyme phosphorylation or acetylation for microbial metabolism. With the growing topological knowledge, the functional relevance of these regulatory events becomes an even more pressing need. A major knowledge gap resides in the regulatory network of protein-metabolite interactions, simply because we lacked pertinent methods for systematic analyses - but a start has now been made. Perhaps most dramatic was the conceptual shift in our perception of metabolism from an engine of cellular operation to a generator of input and feedback signals for regulatory circuits that govern many important decisions on cell proliferation, differentiation, death, and naturally metabolism.

Toward a global analysis of metabolites in regulatory mutants of yeast

The AMP-activated protein kinase in yeast, Snf1, coordinates expression and activity of numerous intracellular signaling and developmental pathways, including those regulating cellular differentiation, response to stress, meiosis, autophagy, and the diauxic transition. Snf1 phosphorylates metabolic enzymes and transcription factors to change cellular physiology and metabolism. Adr1 and Cat8, transcription factors that activate gene expression after the diauxic transition, are regulated by Snf1; Cat8 through direct phosphorylation and Adr1 by dephosphorylation in a Snf1-dependent manner. Adr1 and Cat8 coordinately regulate numerous genes encoding enzymes of gluconeogenesis, the glyoxylate cycle, β-oxidation of fatty acids, and the utilization of alternative fermentable sugars and nonfermentable substrates. To determine the roles of Adr1, Cat8, and Snf1 in metabolism, two-dimensional gas chromatography coupled to time-of-flight mass spectrometry and liquid chromatography coupled to tandem mass spectrometry were used to identify metabolites whose levels change after the diauxic transition in wild-type-, ADR1-, CAT8-, and SNF1-deficient yeast. A discovery-based approach to data analysis utilized chemometric algorithms to identify, quantify, and compare 63 unique metabolites between wild type, adr1∆, cat8∆, adr1∆cat8∆, and snf1∆ strains. The primary metabolites found to differ were those of gluconeogenesis, the glyoxylate and tricarboxylic acid cycles, and amino acid metabolism. In general, good agreement was observed between the levels of metabolites derived from these pathways and the levels of transcripts from the same strains, suggesting that transcriptional control plays a major role in regulating the levels of metabolites after the diauxic transition.

Codon usage variability determines the correlation between proteome and transcriptome fold changes

Background

The availability of high throughput experimental methods has made possible to observe the relationships between proteome and transcirptome. The protein abundances show a positive but weak correlation with the concentrations of their cognate mRNAs. This weak correlation implies that there are other crucial effects involved in the regulation of protein translation, different from the sole availability of mRNA. It is well known that ribosome and tRNA concentrations are sources of variation in protein levels. Thus, by using integrated analysis of omics data, genomic information, transcriptome and proteome, we aim to unravel important variables affecting translation.

Results

We identified how much of the variability in the correlation between protein and mRNA concentrations can be attributed to the gene codon frequencies. We propose the hypothesis that the influence of codon frequency is due to the competition of cognate and near-cognate tRNA binding; which in turn is a function of the tRNA concentrations. Transcriptome and proteome data were combined in two analytical steps; first, we used Self-Organizing Maps (SOM) to identify similarities among genes, based on their codon frequencies, grouping them into different clusters; and second, we calculated the variance in the protein mRNA correlation in the sampled genes from each cluster. This procedure is justified within a mathematical framework.

Conclusions

With the proposed method we observed that in all the six studied cases most of the variability in the relation protein-transcript could be explained by the variation in codon composition.

Use of genome-scale metabolic models in evolutionary systems biology

One of the major aims of the nascent field of evolutionary systems biology is to test evolutionary hypotheses that are not only realistic from a population genetic point of view but also detailed in terms of molecular biology mechanisms. By providing a mapping between genotype and phenotype for hundreds of genes, genome-scale systems biology models of metabolic networks have already provided valuable insights into the evolution of metabolic gene contents and phenotypes of yeast and other microbial species. Here we review the recent use of these computational models to predict the fitness effect of mutations, genetic interactions, evolutionary outcomes, and to decipher the mechanisms of mutational robustness. While these studies have demonstrated that even simplified models of biochemical reaction networks can be highly informative for evolutionary analyses, they have also revealed the weakness of this modeling framework to quantitatively predict mutational effects, a challenge that needs to be addressed for future progress in evolutionary systems biology.

Perturbation of the yeast N-acetyltransferase NatB induces elevation of protein phosphorylation levels

BACKGROUND

The addition of an acetyl group to protein N-termini is a widespread co-translational modification. NatB is one of the main N-acetyltransferases that targets a subset of proteins possessing an N-terminal methionine, but so far only a handful of substrates have been reported. Using a yeast nat3Δ strain, deficient for the catalytic subunit of NatB, we employed a quantitative proteomics strategy to identify NatB substrates and to characterize downstream effects in nat3Δ.

RESULTS

Comparing by proteomics WT and nat3Δ strains, using metabolic 15N isotope labeling, we confidently identified 59 NatB substrates, out of a total of 756 detected acetylated protein N-termini. We acquired in-depth proteome wide measurements of expression levels of about 2580 proteins. Most remarkably, NatB deletion led to a very significant change in protein phosphorylation.

CONCLUSIONS

Protein expression levels change only marginally in between WT and nat3Δ. A comparison of the detected NatB substrates with their orthologous revealed remarkably little conservation throughout the phylogenetic tree. We further present evidence of post-translational N-acetylation on protein variants at non-annotated N-termini. Moreover, analysis of downstream effects in nat3Δ revealed elevated protein phosphorylation levels whereby the kinase Snf1p is likely a key element in this process.

Isolation and characterization of the carbon catabolite-derepressing protein kinase Snf1 from the stress tolerant yeast Torulaspora delbrueckii

We cloned a genomic DNA fragment of the yeast Torulaspora delbrueckii by complementation of a Saccharomyces cerevisiae snf1Δ mutant strain. DNA sequence analysis revealed that the fragment contained a complete open reading frame (ORF), which shares a high similarity with the S. cerevisiae energy sensor protein kinase Snf1. The cloned TdSNF1 gene was able to restore growth of the S. cerevisiae snf1Δ mutant strain on media containing nonfermentable carbon sources. Furthermore, cells of the Tdsnf1Δ mutant were unable to proliferate under nonfermenting conditions. Finally, protein domain analysis showed that TdSnf1p contains a typical catalytic protein kinase domain (positions 41-293), which is also present in other Snf1p homologues. Within this region we identified a protein kinase ATP-binding region (positions 48-71) and a consensus Ser/Thr protein kinase active site (positions 160-172).

Glucose signaling-mediated coordination of cell growth and cell cycle in Saccharomyces cerevisiae

Besides being the favorite carbon and energy source for the budding yeast Sacchromyces cerevisiae, glucose can act as a signaling molecule to regulate multiple aspects of yeast physiology. Yeast cells have evolved several mechanisms for monitoring the level of glucose in their habitat and respond quickly to frequent changes in the sugar availability in the environment: the cAMP/PKA pathways (with its two branches comprising Ras and the Gpr1/Gpa2 module), the Rgt2/Snf3-Rgt1 pathway and the main repression pathway involving the kinase Snf1. The cAMP/PKA pathway plays the prominent role in responding to changes in glucose availability and initiating the signaling processes that promote cell growth and division. Snf1 (the yeast homologous to mammalian AMP-activated protein kinase) is primarily required for the adaptation of yeast cell to glucose limitation and for growth on alternative carbon source, but it is also involved in the cellular response to various environmental stresses. The Rgt2/Snf3-Rgt1 pathway regulates the expression of genes required for glucose uptake. Many interconnections exist between the diverse glucose sensing systems, which enables yeast cells to fine tune cell growth, cell cycle and their coordination in response to nutritional changes.

Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

Background

Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives.

Results

Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient-sensing and metabolic regulatory signal transduction pathways (STP) operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs) and 779 protein-protein interactions. A number of proteins were identified having interactions with more than one of the protein kinases. The fully reconstructed interaction network includes all the information available in separate databases for all the proteins included in the network (nodes) and for all the interactions between them (edges). The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner.

Conclusions

The reported fully annotated interaction model serves as a platform for integrated systems biology studies of nutrient sensing and regulation in S. cerevisiae. Furthermore, we propose this annotated reconstruction as a first step towards generation of an extensive annotated protein-protein interaction network of signal transduction and metabolic regulation in this yeast.

Toward design-based engineering of industrial microbes

Engineering industrial microbes has been hampered by incomplete knowledge of cell biology. Thus an iterative engineering cycle of modeling, implementation, and analysis has been used to increase knowledge of the underlying biology while achieving engineering goals. Recent advances in Systems Biology technologies have drastically improved the amount of information that can be collected in each iteration. As well, Synthetic Biology tools are melding modeling and molecular implementation. These advances promise to move microbial engineering from the iterative approach to a design-oriented paradigm, similar to electrical circuits and architectural design. Genome-scale metabolic models, new tools for controlling expression, and integrated -omics analysis are described as key contributors in moving the field toward Design-based Engineering.

Systems biology of microbial metabolism

One current challenge in metabolic systems biology is to map out the regulation networks that control metabolism. From progress in this area, we conclude that non-transcriptional mechanisms (e.g. metabolite-protein interactions and protein phosphorylation) are highly relevant in actually controlling metabolic function. Furthermore, recent results highlight more functions of enzymes and metabolites than currently appreciated in genome-scale metabolic reconstructions, thereby adding another level of complexity. Combining experimental analyses and modeling efforts we are also beginning to understand how metabolic behavior emerges. Particularly, we recognize that metabolism is not simply a dull workhorse process but rather takes very active control of itself and other cellular processes, rendering true system-level understanding of metabolism possibly more difficult than for other cellular systems.