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

Exploring carbon source related localization and phosphorylation in the Snf1/Mig1 network using population and single cell-based approaches

The AMPK/SNF1 pathway governs energy balance in eukaryotic cells, notably influencing glucose de-repression. In S. cerevisiae, Snf1 is phosphorylated and hence activated upon glucose depletion. This activation is required but is not sufficient for mediating glucose de-repression, indicating further glucose-dependent regulation mechanisms. Employing fluorescence recovery after photobleaching (FRAP) in conjunction with non-linear mixed effects modelling, we explore the spatial dynamics of Snf1 as well as the relationship between Snf1 phosphorylation and its target Mig1 controlled by hexose sugars. Our results suggest that inactivation of Snf1 modulates Mig1 localization and that the kinetic of Snf1 localization to the nucleus is modulated by the presence of non-fermentable carbon sources. Our data offer insight into the true complexity of regulation of this central signaling pathway in orchestrating cellular responses to fluctuating environmental cues. These insights not only expand our understanding of glucose homeostasis but also pave the way for further studies evaluating the importance of Snf1 localization in relation to its phosphorylation state and regulation of downstream targets.

Increased CO2 fixation enables high carbon-yield production of 3-hydroxypropionic acid in yeast

CO2 fixation plays a key role to make biobased production cost competitive. Here, we use 3-hydroxypropionic acid (3-HP) to showcase how CO2 fixation enables approaching theoretical-yield production. Using genome-scale metabolic models to calculate the production envelope, we demonstrate that the provision of bicarbonate, formed from CO2, restricts previous attempts for high yield production of 3-HP. We thus develop multiple strategies for bicarbonate uptake, including the identification of Sul1 as a potential bicarbonate transporter, domain swapping of malonyl-CoA reductase, identification of Esbp6 as a potential 3-HP exporter, and deletion of Uga1 to prevent 3-HP degradation. The combined rational engineering increases 3-HP production from 0.14 g/L to 11.25 g/L in shake flask using 20 g/L glucose, approaching the maximum theoretical yield with concurrent biomass formation. The engineered yeast forms the basis for commercialization of bio-acrylic acid, while our CO2 fixation strategies pave the way for CO2 being used as the sole carbon source.

The yeast AMP-activated protein kinase Snf1 phosphorylates the inositol polyphosphate kinase Kcs1

The yeast Snf1/AMP-activated kinase (AMPK) maintains energy homeostasis, controlling metabolic processes and glucose derepression in response to nutrient levels and environmental cues. Under conditions of nitrogen or glucose limitation, Snf1 regulates pseudohyphal growth, a morphological transition characterized by the formation of extended multicellular filaments. During pseudohyphal growth, Snf1 is required for wild-type levels of inositol polyphosphate (InsP), soluble phosphorylated species of the six-carbon cyclitol inositol that function as conserved metabolic second messengers. InsP levels are established through the activity of a family of inositol kinases, including the yeast inositol polyphosphate kinase Kcs1, which principally generates pyrophosphorylated InsP7. Here, we report that Snf1 regulates Kcs1, affecting Kcs1 phosphorylation and inositol kinase activity. A snf1 kinase-defective mutant exhibits decreased Kcs1 phosphorylation, and Kcs1 is phosphorylated in vivo at Ser residues 537 and 646 during pseudohyphal growth. By in vitro analysis, Snf1 directly phosphorylates Kcs1, predominantly at amino acids 537 and 646. A yeast strain carrying kcs1 encoding Ser-to-Ala point mutations at these residues (kcs1-S537A,S646A) shows elevated levels of pyrophosphorylated InsP7, comparable to InsP7 levels observed upon deletion of SNF1. The kcs1-S537A,S646A mutant exhibits decreased pseudohyphal growth, invasive growth, and cell elongation. Transcriptional profiling indicates extensive perturbation of metabolic pathways in kcs1-S537A,S646A. Growth of kcs1-S537A,S646A is affected on medium containing sucrose and antimycin A, consistent with decreased Snf1p signaling. This work identifies Snf1 phosphorylation of Kcs1, collectively highlighting the interconnectedness of AMPK activity and InsP signaling in coordinating nutrient availability, energy homoeostasis, and cell growth.

Lipid Accumulation by Snf-β Engineered Mucor circinelloides Strains on Glucose and Xylose

Sucrose non-fermenting 1 (SNF1) protein kinase plays the regulatory roles in the utilization of selective carbon sources and lipid metabolism. Previously, the role of β subunit of SNF1 in lipid accumulation was evaluated by overexpression and knockout of Snf-β in oleaginous fungus M. circinelloides. In the present study, the growth and lipid accumulation of Snf-β overexpression and knockout strains were further analyzed and compared with glucose or xylose as a single or mixed carbon sources. The results showed that the lipid contents in Snf-β knockout strain improved by 23.2% (for glucose), 28.4% (for xylose), and 30.5% (for mixed glucose and xylose) compared with that of the control strain, respectively. The deletion of Snf-β subunit also altered the transcriptional level of acetyl-CoA carboxylase (ACC). The highest transcriptional levels of ACC1 in Snf-β knockout strain at 24 h were increased by 2.4-fold (for glucose), 2.8-fold (for xylose), and 3.1-fold (for mixed glucose and xylose) compared with that of the control strain, respectively. Our results indicated that Snf-β subunit enhanced lipid accumulation through the regulation of ACC1 in response to xylose or mixed sugars of glucose and xylose more significantly than that of response to glucose. This is the first study to explore the effect of Snf-β subunit of M. circinelloides in regulating lipid accumulation responding to different carbon nutrient signals of glucose and xylose. This study provides a foundation for the future application of the Snf-β engineered strains in lipid production from lignocellulose.

Advances in S. cerevisiae Engineering for Xylose Fermentation and Biofuel Production: Balancing Growth, Metabolism, and Defense

Genetically engineering microorganisms to produce chemicals has changed the industrialized world. The budding yeast Saccharomyces cerevisiae is frequently used in industry due to its genetic tractability and unique metabolic capabilities. S. cerevisiae has been engineered to produce novel compounds from diverse sugars found in lignocellulosic biomass, including pentose sugars, like xylose, not recognized by the organism. Engineering high flux toward novel compounds has proved to be more challenging than anticipated since simply introducing pathway components is often not enough. Several studies show that the rewiring of upstream signaling is required to direct products toward pathways of interest, but doing so can diminish stress tolerance, which is important in industrial conditions. As an example of these challenges, we reviewed S. cerevisiae engineering efforts, enabling anaerobic xylose fermentation as a model system and showcasing the regulatory interplay's controlling growth, metabolism, and stress defense. Enabling xylose fermentation in S. cerevisiae requires the introduction of several key metabolic enzymes but also regulatory rewiring of three signaling pathways at the intersection of the growth and stress defense responses: the RAS/PKA, Snf1, and high osmolarity glycerol (HOG) pathways. The current studies reviewed here suggest the modulation of global signaling pathways should be adopted into biorefinery microbial engineering pipelines to increase efficient product yields.

Lipid accumulation and SNF1 transcriptional analysis of Mucor circinelloides on xylose under nitrogen limitation

Sucrose non-fermenting 1 (SNF1) plays a crucial role in utilizing non-glucose carbon sources and regulating lipid metabolism. However, the mechanism by which SNF1 regulates lipid accumulation in oleaginous filamentous fungi in response to nutrient signals remains unclear. In the present study, by analysing the growth and lipid accumulation of M. circinelloides on xylose under nitrogen limitation, combined with the transcriptional changes of each subunit of SNF1, the regulation of SNF1 between nutrient signal and lipid accumulation was explored. The results showed that with the increase of carbon/nitrogen (C/N) ratio, the xylose consumption and cell growth of M. circinelloides decreased, and the lipid accumulation increased gradually. The optimal C/N ratio was 160:1, and the maximum lipid yield was 4.1 g/L. Two subunits of SNF1, Snf-α1 and Snf-β, are related to the regulation of lipid metabolism in response to nutrient signals from different external nitrogen sources. This is the first report on the transcriptional analysis of SNF1 subunits on xylose metabolism under nitrogen limitation. This study provides a basis for further understanding of lipid synthesis mechanism on xylose in oleaginous fungi, and it also lays a foundation for the genetic engineering of high-lipid strain.

Flux regulation through glycolysis and respiration is balanced by inositol pyrophosphates in yeast

Although many prokaryotes have glycolysis alternatives, it's considered as the only energy-generating glucose catabolic pathway in eukaryotes. Here, we managed to create a hybrid-glycolysis yeast. Subsequently, we identified an inositol pyrophosphatase encoded by OCA5 that could regulate glycolysis and respiration by adjusting 5-diphosphoinositol 1,2,3,4,6-pentakisphosphate (5-InsP₇) levels. 5-InsP₇ levels could regulate the expression of genes involved in glycolysis and respiration, representing a global mechanism that could sense ATP levels and regulate central carbon metabolism. The hybrid-glycolysis yeast did not produce ethanol during growth under excess glucose and could produce 2.68 g/L free fatty acids, which is the highest reported production in shake flask of Saccharomyces cerevisiae. This study demonstrated the significance of hybrid-glycolysis yeast and determined Oca5 as an inositol pyrophosphatase controlling the balance between glycolysis and respiration, which may shed light on the role of inositol pyrophosphates in regulating eukaryotic metabolism.

Modelling of glucose repression signalling in yeast Saccharomyces cerevisiae

Saccharomyces cerevisiae has a sophisticated signalling system that plays a crucial role in cellular adaptation to changing environments. The SNF1 pathway regulates energy homeostasis upon glucose derepression; hence, it plays an important role in various processes, such as metabolism, cell cycle and autophagy. To unravel its behaviour, SNF1 signalling has been extensively studied. However, the pathway components are strongly interconnected and inconstant; therefore, elucidating its dynamic behaviour based on experimental data only is challenging. To tackle this complexity, systems biology approaches have been successfully employed. This review summarizes the progress, advantages and disadvantages of the available mathematical modelling frameworks covering Boolean, dynamic kinetic, single-cell models, which have been used to study processes and phenomena ranging from crosstalks to sources of cell-to-cell variability in the context of SNF1 signalling. Based on the lessons from existing models, we further discuss how to develop a consensus dynamic mechanistic model of the entire SNF1 pathway that can provide novel insights into the dynamics of nutrient signalling.

Valproate activates the Snf1 kinase in Saccharomyces cerevisiae by decreasing the cytosolic pH

Valproate (VPA) is a widely used mood stabilizer, but its therapeutic mechanism of action is not understood. This knowledge gap hinders the development of more effective drugs with fewer side effects. Using the yeast model to elucidate the effects of VPA on cellular metabolism, we determined that the drug upregulated expression of genes normally repressed during logarithmic growth on glucose medium and increased levels of activated (phosphorylated) Snf1 kinase, the major metabolic regulator of these genes. VPA also decreased the cytosolic pH (pH_c) and reduced glycolytic production of 2/3-phosphoglycerate. ATP levels and mitochondrial membrane potential were increased, and glucose-mediated extracellular acidification decreased in the presence of the drug, as indicated by a smaller glucose-induced shift in pH, suggesting that the major P-type proton pump Pma1 was inhibited. Interestingly, decreasing the pH_c by omeprazole-mediated inhibition of Pma1 led to Snf1 activation. We propose a model whereby VPA lowers the pH_c causing a decrease in glycolytic flux. In response, Pma1 is inhibited and Snf1 is activated, resulting in increased expression of normally repressed metabolic genes. These findings suggest a central role for pH_c in regulating the metabolic program of yeast cells.

Improving the Production of Punicic Acid in Baker's Yeast by Engineering Genes in Acyl Channeling Processes and Adjusting Precursor Supply

Punicic acid (PuA) is a high-value edible conjugated fatty acid with strong bioactivities and has important potential applications in nutraceutical, pharmaceutical, feeding, and oleochemical industries. Since the production of PuA is severely limited by the fact that its natural source (pomegranate seed oil) is not readily available on a large scale, there is considerable interest in understanding the biosynthesis and accumulation of this plant-based unusual fatty acid in transgenic microorganisms to support the rational design of biotechnological approaches for PuA production via fermentation. Here, we tested the effectiveness of genetic engineering and precursor supply in PuA production in the model yeast strain Saccharomyces cerevisiae. The results revealed that the combination of precursor feeding and co-expression of selected genes in acyl channeling processes created an effective "push-pull" approach to increase PuA content, which could prove valuable in future efforts to produce PuA in industrial yeast and other microorganisms via fermentation.

Towards model-driven characterization and manipulation of plant lipid metabolism

Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.

A novel genetic circuitry governing hypoxic metabolic flexibility, commensalism and virulence in the fungal pathogen Candida albicans

Inside the human host, the pathogenic yeast Candida albicans colonizes predominantly oxygen-poor niches such as the gastrointestinal and vaginal tracts, but also oxygen-rich environments such as cutaneous epithelial cells and oral mucosa. This suppleness requires an effective mechanism to reversibly reprogram the primary metabolism in response to oxygen variation. Here, we have uncovered that Snf5, a subunit of SWI/SNF chromatin remodeling complex, is a major transcriptional regulator that links oxygen status to the metabolic capacity of C. albicans. Snf5 and other subunits of SWI/SNF complex were required to activate genes of carbon utilization and other carbohydrates related process specifically under hypoxia. snf5 mutant exhibited an altered metabolome reflecting that SWI/SNF plays an essential role in maintaining metabolic homeostasis and carbon flux in C. albicans under hypoxia. Snf5 was necessary to activate the transcriptional program linked to both commensal and invasive growth. Accordingly, snf5 was unable to maintain its growth in the stomach, the cecum and the colon of mice. snf5 was also avirulent as it was unable to invade Galleria larvae or to cause damage to human enterocytes and murine macrophages. Among candidates of signaling pathways in which Snf5 might operate, phenotypic analysis revealed that mutants of Ras1-cAMP-PKA pathway, as well as mutants of Yak1 and Yck2 kinases exhibited a similar carbon flexibility phenotype as did snf5 under hypoxia. Genetic interaction analysis indicated that the adenylate cyclase Cyr1, a key component of the Ras1-cAMP pathway interacted genetically with Snf5. Our study yielded new insight into the oxygen-sensitive regulatory circuit that control metabolic flexibility, stress, commensalism and virulence in C. albicans.

A critical aspect of eukaryotic cell fitness is the ability to sense and adapt to variations in oxygen level in their local environment. Hypoxia leads to a substantial remodeling of cell metabolism and energy homeostasis, and thus, organisms must develop an effective regulatory mechanism to cope with oxygen depletion. Candida albicans is an opportunistic yeast that is the most prevalent human fungal pathogens. This yeast colonizes diverse niches inside the human host with contrasting carbon sources and oxygen concentrations. While hypoxia is the predominant condition that C. albicans encounters inside most of the niches, the impact of this condition on metabolic flexibility, a major determinant of fungal virulence, was completely unexplored. Here, we uncovered that the chromatin remodelling complex SWI/SNF is a master regulator of the circuit that links oxygen status to a broad spectrum of carbon utilization routes. Snf5 was essential for the maintenance of C. albicans as a commensal and also for the expression of its virulence. The oxygen-sensitive regulators identified in this work provide a framework to comprehensively understand the virulence of human fungal pathogens and represent a therapeutic value to fight fungal infections.

AMPK regulates ESCRT-dependent microautophagy of proteasomes concomitant with proteasome storage granule assembly during glucose starvation

The ubiquitin-proteasome system regulates numerous cellular processes and is central to protein homeostasis. In proliferating yeast and many mammalian cells, proteasomes are highly enriched in the nucleus. In carbon-starved yeast, proteasomes migrate to the cytoplasm and collect in proteasome storage granules (PSGs). PSGs dissolve and proteasomes return to the nucleus within minutes of glucose refeeding. The mechanisms by which cells regulate proteasome homeostasis under these conditions remain largely unknown. Here we show that AMP-activated protein kinase (AMPK) together with endosomal sorting complexes required for transport (ESCRTs) drive a glucose starvation-dependent microautophagy pathway that preferentially sorts aberrant proteasomes into the vacuole, thereby biasing accumulation of functional proteasomes in PSGs. The proteasome core particle (CP) and regulatory particle (RP) are regulated differently. Without AMPK, the insoluble protein deposit (IPOD) serves as an alternative site that specifically sequesters CP aggregates. Our findings reveal a novel AMPK-controlled ESCRT-mediated microautophagy mechanism in the regulation of proteasome trafficking and homeostasis under carbon starvation.

Big data in yeast systems biology

Systems biology uses computational and mathematical modeling to study complex interactions in a biological system. The yeast Saccharomyces cerevisiae, which has served as both an important model organism and cell factory, has pioneered both the early development of such models and modeling concepts, and the more recent integration of multi-omics big data in these models to elucidate fundamental principles of biology. Here, we review the advancement of big data technologies to gain biological insight in three aspects of yeast systems biology: gene expression dynamics, cellular metabolism and the regulation network between gene expression and metabolism. The role of big data and complementary modeling approaches, including the expansion of genome-scale metabolic models and machine learning methodologies, are discussed as key drivers in the rapid advancement of yeast systems biology.

Yeast Systems Biology: Model Organism and Cell Factory

For thousands of years, the yeast Saccharomyces cerevisiae (S. cerevisiae) has served as a cell factory for the production of bread, beer, and wine. In more recent years, this yeast has also served as a cell factory for producing many different fuels, chemicals, food ingredients, and pharmaceuticals. S. cerevisiae, however, has also served as a very important model organism for studying eukaryal biology, and even today many new discoveries, important for the treatment of human diseases, are made using this yeast as a model organism. Here a brief review of the use of S. cerevisiae as a model organism for studying eukaryal biology, its use as a cell factory, and how advances in systems biology underpin developments in both these areas, is provided.

Methionine supplementation stimulates mitochondrial respiration

Mitochondria play essential metabolic functions in eukaryotes. Although their major role is the generation of energy in the form of ATP, they are also involved in maintenance of cellular redox state, conversion and biosynthesis of metabolites and signal transduction. Most mitochondrial functions are conserved in eukaryotic systems and mitochondrial dysfunctions trigger several human diseases. By using multi-omics approach, we investigate the effect of methionine supplementation on yeast cellular metabolism, considering its role in the regulation of key cellular processes. Methionine supplementation induces an up-regulation of proteins related to mitochondrial functions such as TCA cycle, electron transport chain and respiration, combined with an enhancement of mitochondrial pyruvate uptake and TCA cycle activity. This metabolic signature is more noticeable in cells lacking Snf1/AMPK, the conserved signalling regulator of energy homeostasis. Remarkably, snf1Δ cells strongly depend on mitochondrial respiration and suppression of pyruvate transport is detrimental for this mutant in methionine condition, indicating that respiration mostly relies on pyruvate flux into mitochondrial pathways. These data provide new insights into the regulation of mitochondrial metabolism and extends our understanding on the role of methionine in regulating energy signalling pathways.

Overexpression of SNF4 and deletions of REG1- and REG2-enhanced maltose metabolism and leavening ability of baker's yeast in lean dough

Maltose metabolism of baker's yeast (Saccharomyces cerevisiae) in lean dough is suppressed by the glucose effect, which negatively affects dough fermentation. In this study, differences and interactions among SNF4 (encoding for the regulatory subunit of Snf1 kinase) overexpression and REG1 and REG2 (which encodes for the regulatory subunits of the type I protein phosphatase) deletions in maltose metabolism of baker's yeast were investigated using various mutants. Results revealed that SNF4 overexpression and REG1 and REG2 deletions effectively alleviated glucose repression at different levels, thereby enhancing maltose metabolism and leavening ability to varying degrees. SNF4 overexpression combined with REG1/REG2 deletions further enhanced the increases in glucose derepression and maltose metabolism. The overexpressed SNF4 with deleted REG1 and REG2 mutant ΔREG1ΔREG2 + SNF4 displayed the highest maltose metabolism and strongest leavening ability under the test conditions. Such baker's yeast strains had excellent potential applications.

Snf1/AMPK is involved in the mitotic spindle alignment in Saccharomyces cerevisiae

Before anaphase onset, budding yeast cells must align the mitotic spindle parallel to the mother-bud axis to ensure proper chromosome segregation. The protein kinase Snf1/AMPK is a highly conserved energy sensor, essential for adaptation to glucose limitation and in response to cellular stresses. However, recent findings indicate that it plays important functions also in non-limiting glucose conditions. Here we report a novel role of Snf1/AMPK in the progression through mitosis in glucose-repressing condition. We show that active Snf1 is localized to the bud neck from bud emergence to cytokinesis in a septin-dependent manner. In addition, loss of Snf1 induces a delay of the metaphase to anaphase transition that is due to a defect in the correct alignment of the mitotic spindle. In particular, genetic data indicate that Snf1 promotes spindle orientation acting in parallel with Dyn1 and in concert with Kar9. Altogether this study describes a new role for Snf1 in mitosis and connects cellular metabolism to mitosis progression.

Glycolytic Enzymes Coalesce in G Bodies under Hypoxic Stress

Glycolysis is upregulated under conditions such as hypoxia and high energy demand to promote cell proliferation, although the mechanism remains poorly understood. We find that hypoxia in Saccharomyces cerevisiae induces concentration of glycolytic enzymes, including the Pfk2p subunit of the rate-limiting phosphofructokinase, into a single, non-membrane-bound granule termed the "glycolytic body" or "G body." A yeast kinome screen identifies the yeast ortholog of AMP-activated protein kinase, Snf1p, as necessary for G-body formation. Many G-body components identified by proteomics are required for G-body integrity. Cells incapable of forming G bodies in hypoxia display abnormal cell division and produce inviable daughter cells. Conversely, cells with G bodies show increased glucose consumption and decreased levels of glycolytic intermediates. Importantly, G bodies form in human hepatocarcinoma cells in hypoxia. Together, our results suggest that G body formation is a conserved, adaptive response to increase glycolytic output during hypoxia or tumorigenesis.

Systems Biology of Metabolism

Metabolism is highly complex and involves thousands of different connected reactions; it is therefore necessary to use mathematical models for holistic studies. The use of mathematical models in biology is referred to as systems biology. In this review, the principles of systems biology are described, and two different types of mathematical models used for studying metabolism are discussed: kinetic models and genome-scale metabolic models. The use of different omics technologies, including transcriptomics, proteomics, metabolomics, and fluxomics, for studying metabolism is presented. Finally, the application of systems biology for analyzing global regulatory structures, engineering the metabolism of cell factories, and analyzing human diseases is discussed.

Machine Learning of Global Phosphoproteomic Profiles Enables Discrimination of Direct versus Indirect Kinase Substrates

Mass spectrometry allows quantification of tens of thousands of phosphorylation sites from minute amounts of cellular material. Despite this wealth of information, our understanding of phosphorylation-based signaling is limited, in part because it is not possible to deconvolute substrate phosphorylation that is directly mediated by a particular kinase versus phosphorylation that is mediated by downstream kinases. Here, we describe a framework for assignment of direct in vivo kinase substrates using a combination of selective chemical inhibition, quantitative phosphoproteomics, and machine learning techniques. Our workflow allows classification of phosphorylation events following inhibition of an analog-sensitive kinase into kinase-independent effects of the inhibitor, direct effects on cognate substrates, and indirect effects mediated by downstream kinases or phosphatases. We applied this method to identify many direct targets of Cdc28 and Snf1 kinases in the budding yeast Saccharomyces cerevisiae Global phosphoproteome analysis of acute time-series demonstrated that dephosphorylation of direct kinase substrates occurs more rapidly compared with indirect substrates, both after inhibitor treatment and under a physiological nutrient shift in wt cells. Mutagenesis experiments revealed a high proportion of functionally relevant phosphorylation sites on Snf1 targets. For example, Snf1 itself was inhibited through autophosphorylation on Ser³⁹¹ and new phosphosites were discovered that modulate the activity of the Reg1 regulatory subunit of the Glc7 phosphatase and the Gal83 β-subunit of SNF1 complex. This methodology applies to any kinase for which a functional analog sensitive version can be constructed to facilitate the dissection of the global phosphorylation network.

The Transcriptome of Exophiala dermatitidis during Ex-vivo Skin Model Infection

The black yeast Exophiala dermatitidis is a widespread polyextremophile and human pathogen, that is found in extreme natural habitats and man-made environments such as dishwashers. It can cause various diseases ranging from phaeohyphomycosis and systemic infections, with fatality rates reaching 40%. While the number of cases in immunocompromised patients are increasing, knowledge of the infections, virulence factors and host response is still scarce. In this study, for the first time, an artificial infection of an ex-vivo skin model with Exophiala dermatitidis was monitored microscopically and transcriptomically. Results show that Exophiala dermatitidis is able to actively grow and penetrate the skin. The analysis of the genomic and RNA-sequencing data delivers a rich and complex transcriptome where circular RNAs, fusion transcripts, long non-coding RNAs and antisense transcripts are found. Changes in transcription strongly affect pathways related to nutrients acquisition, energy metabolism, cell wall, morphological switch, and known virulence factors. The L-Tyrosine melanin pathway is specifically upregulated during infection. Moreover the production of secondary metabolites, especially alkaloids, is increased. Our study is the first that gives an insight into the complexity of the transcriptome of Exophiala dermatitidis during artificial skin infections and reveals new virulence factors.

Similar environments but diverse fates: Responses of budding yeast to nutrient deprivation

Diploid budding yeast (Saccharomyces cerevisiae) can adopt one of several alternative differentiation fates in response to nutrient limitation, and each of these fates provides distinct biological functions. When different strain backgrounds are taken into account, these various fates occur in response to similar environmental cues, are regulated by the same signal transduction pathways, and share many of the same master regulators. I propose that the relationships between fate choice, environmental cues and signaling pathways are not Boolean, but involve graded levels of signals, pathway activation and master-regulator activity. In the absence of large differences between environmental cues, small differences in the concentration of cues may be reinforced by cell-to-cell signals. These signals are particularly essential for fate determination within communities, such as colonies and biofilms, where fate choice varies dramatically from one region of the community to another. The lack of Boolean relationships between cues, signaling pathways, master regulators and cell fates may allow yeast communities to respond appropriately to the wide range of environments they encounter in nature.

Genome scale models of yeast: towards standardized evaluation and consistent omic integration

Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are currently used for metabolic engineering and elucidating biological interactions. Here we review the history of yeast's GEMs, focusing on recent developments. We study how these models are typically evaluated, using both descriptive and predictive metrics. Additionally, we analyze the different ways in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted.

An overview of bioinformatics methods for modeling biological pathways in yeast

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed.

Branched-Chain Aminotransferases Control TORC1 Signaling in Saccharomyces cerevisiae

The conserved target of rapamycin complex 1 (TORC1) integrates nutrient signals to orchestrate cell growth and proliferation. Leucine availability is conveyed to control TORC1 activity via the leu-tRNA synthetase/EGOC-GTPase module in yeast and mammals, but the mechanisms sensing leucine remain only partially understood. We show here that both leucine and its α-ketoacid metabolite, α-ketoisocaproate, effectively activate the yeast TORC1 kinase via both EGOC GTPase-dependent and -independent mechanisms. Leucine and α-ketoisocaproate are interconverted by ubiquitous branched-chain aminotransferases (BCAT), which in yeast are represented by the mitochondrial and cytosolic enzymes Bat1 and Bat2, respectively. BCAT yeast mutants exhibit severely compromised TORC1 activity, which is partially restored by expression of Bat1 active site mutants, implicating both catalytic and structural roles of BCATs in TORC1 control. We find that Bat1 interacts with branched-chain amino acid metabolic enzymes and, in a leucine-dependent fashion, with the tricarboxylic acid (TCA)-cycle enzyme aconitase. BCAT mutation perturbed TCA-cycle intermediate levels, consistent with a TCA-cycle block, and resulted in low ATP levels, activation of AMPK, and TORC1 inhibition. We propose the biosynthetic capacity of BCAT and its role in forming multicomplex metabolons connecting branched-chain amino acids and TCA-cycle metabolism governs TCA-cycle flux to activate TORC1 signaling. Because mammalian mitochondrial BCAT is known to form a supramolecular branched-chain α-keto acid dehydrogenase enzyme complex that links leucine metabolism to the TCA-cycle, these findings establish a precedent for understanding TORC1 signaling in mammals.

In all organisms from yeasts to mammals the target of rapamycin TORC1 pathway controls growth in response to nutrients such as leucine, but the leucine sensing mechanisms are only partially characterized. We show that both leucine and its α-ketoacid metabolite, α-ketoisocaproate, are similarly capable of activating TORC1 kinase via EGOC GTPase-dependent and -independent mechanisms. Activation of TORC1 by leucine or α-ketoisocaproate is only partially mediated via EGOC-GTPase. Leucine and α-ketoisocaproate are interconverted by ubiquitous branched-chain aminotransferases (BCAT). Disruption of BCAT caused reduced TORC1 activity, which was partially restored by expression of BCAT active site mutants, arguing for both structural and catalytic roles of BCAT in TORC1 control. We find BCAT interacts with several branched-chain amino acid metabolic enzymes, and in a leucine-dependent fashion with the tricarboxylic acid (TCA)-cycle enzyme aconitase. Both aconitase mutation or TCA-cycle inhibition impaired TORC1 activity. Mutation of BCAT resulted in a TCA-cycle intermediate profile consistent with a TCA-cycle block, low ATP levels, activation of AMPK, and TORC1 inhibition. Our results suggest a model whereby BCAT coordinates leucine and TCA cycle metabolism to control TORC1 signaling. Taken together, our findings forge key insights into how the TORC1 signaling cascade senses nutrients to control cell growth.

Snf1/AMPK promotes the formation of Kog1/Raptor-bodies to increase the activation threshold of TORC1 in budding yeast

The target of rapamycin complex I (TORC1) regulates cell growth and metabolism in eukaryotes. Previous studies have shown that nitrogen and amino acid signals activate TORC1 via the small GTPases, Gtr1/2. However, little is known about the way that other nutrient signals are transmitted to TORC1. Here we report that glucose starvation triggers disassembly of TORC1, and movement of the key TORC1 component Kog1/Raptor to a single body near the edge of the vacuole. These events are driven by Snf1/AMPK-dependent phosphorylation of Kog1 at Ser 491/494 and two nearby prion-like motifs. Kog1-bodies then serve to increase the threshold for TORC1 activation in cells that have been starved for a significant period of time. Together, our data show that Kog1-bodies create hysteresis (memory) in the TORC1 pathway and help ensure that cells remain committed to a quiescent state under suboptimal conditions. We suggest that other protein bodies formed in starvation conditions have a similar function.

DOI:http://dx.doi.org/10.7554/eLife.09181.001

In humans, yeast and other eukaryotes, a group of proteins called the Target of Rapamycin Complex I (TORC1) promote cell growth and increase metabolic activity when nutrients are plentiful. Previous studies have shown how molecules that contain the nutrient nitrogen – which is needed to make proteins – activate TORC1. However, it is not clear how other nutrients regulate this complex.

Bakers yeast is a simple, single celled organism that researchers often use as a model to study how cells work. The yeast TORC1 is made up of three core proteins, including Kog1 and Tor1. Kog1 selectively recruits proteins to the complex, where they are modified by Tor1 to regulate their activity. Here, Hughes Hallett et al. used microscopy to study what effect sugar starvation has on the complex.

In the experiments, yeast cells were genetically engineered so that Kog1 and Tor1 appeared fluorescent under the microscope. The experiments reveal that, when sugar is in short supply, Kog1 breaks away from the rest of the TORC1 and moves to another part of the cell where it accumulates to form a cluster called a “body”. This movement is driven by a “kinase” enzyme that adds chemical groups called phosphates to Kog1, and by regions within the Kog1 protein known as prion like domains. When sugar first becomes available again, Kog1 is still in the body so Tor1 cannot immediately trigger cell growth. However, once a steady supply of sugar resumes, Kog1 rejoins the rest of the complex and the cells start to grow.

Together, Hughes Hallett et al.’s findings reveal that the formation of Kog1 bodies during sugar starvation creates a “memory” that prevents TORC1 from reactivating cell growth if sugar is only temporarily available. Humans have over 100 proteins that contain prion like domains. Therefore a future challenge is to find out whether any of these proteins form similar bodies that enable our cells to remember past events.

DOI:http://dx.doi.org/10.7554/eLife.09181.002

The opposing actions of target of rapamycin and AMP-activated protein kinase in cell growth control

Cell growth is a highly regulated, plastic process. Its control involves balancing positive regulation of anabolic processes with negative regulation of catabolic processes. Although target of rapamycin (TOR) is a major promoter of growth in response to nutrients and growth factors, AMP-activated protein kinase (AMPK) suppresses anabolic processes in response to energy stress. Both TOR and AMPK are conserved throughout eukaryotic evolution. Here, we review the fundamentally important roles of these two kinases in the regulation of cell growth with particular emphasis on their mutually antagonistic signaling.

Glucose repression in Saccharomyces cerevisiae

Glucose is the primary source of energy for the budding yeast Saccharomyces cerevisiae. Although yeast cells can utilize a wide range of carbon sources, presence of glucose suppresses molecular activities involved in the use of alternate carbon sources as well as it represses respiration and gluconeogenesis. This dominant effect of glucose on yeast carbon metabolism is coordinated by several signaling and metabolic interactions that mainly regulate transcriptional activity but are also effective at post-transcriptional and post-translational levels. This review describes effects of glucose repression on yeast carbon metabolism with a focus on roles of the Snf3/Rgt2 glucose-sensing pathway and Snf1 signal transduction in establishment and relief of glucose repression.

The role of Snf1 signaling in glucose repression and carbon metabolism in Saccharomyces cerevisae.

Protein kinase Snf1 is involved in the proper regulation of the unfolded protein response in Saccharomyces cerevisiae

Glc7 is the only catalytic subunit of the protein phosphatase type 1 in the yeast S. cerevisiae and, together with its regulatory subunits, is involved in many essential processes. Analysis of the non-essential mutants in the regulatory subunits of Glc7 revealed that the lack of Reg1, and no other subunit, causes hypersensitivity to unfolded protein response (UPR)-inducers, which was concomitant with an augmented UPR element-dependent transcriptional response. The Glc7-Reg1 complex takes part in the regulation of the yeast AMP-activated serine/threonine protein kinase Snf1 in response to glucose. We demonstrate in the present study that the observed phenotypes of reg1 mutant cells are attributable to the inappropriate activation of Snf1. Indeed, growth in the presence of limited concentrations of glucose, where Snf1 is active, or expression of active forms of Snf1 in a wild-type strain increased the sensitivity to the UPR-inducer tunicamycin. Furthermore, reg1 mutant cells showed a sustained HAC1 mRNA splicing and KAR2 mRNA levels during the recovery phase of the UPR, and dysregulation of the Ire1-oligomeric equilibrium. Finally, overexpression of protein phosphatases Ptc2 and Ptc3 alleviated the growth defect of reg1 cells under endoplasmic reticulum (ER) stress conditions. Altogether, our results reveal that Snf1 plays an important role in the attenuation of the UPR, as well as identifying the protein kinase and its effectors as possible pharmacological targets for human diseases that are associated with insufficient UPR activation.

Enhanced amino acid utilization sustains growth of cells lacking Snf1/AMPK

The metabolism of proliferating cells shows common features even in evolutionary distant organisms such as mammals and yeasts, for example the requirement for anabolic processes under tight control of signaling pathways. Analysis of the rewiring of metabolism, which occurs following the dysregulation of signaling pathways, provides new knowledge about the mechanisms underlying cell proliferation. The key energy regulator in yeast Snf1 and its mammalian ortholog AMPK have earlier been shown to have similar functions at glucose limited conditions and here we show that they also have analogies when grown with glucose excess. We show that loss of Snf1 in cells growing in 2% glucose induces an extensive transcriptional reprogramming, enhances glycolytic activity, fatty acid accumulation and reliance on amino acid utilization for growth. Strikingly, we demonstrate that Snf1/AMPK-deficient cells remodel their metabolism fueling mitochondria and show glucose and amino acids addiction, a typical hallmark of cancer cells.

Proteasomes, Sir2, and Hxk2 form an interconnected aging network that impinges on the AMPK/Snf1-regulated transcriptional repressor Mig1

Elevated proteasome activity extends lifespan in model organisms such as yeast, worms and flies. This pro-longevity effect might be mediated by improved protein homeostasis, as this protease is an integral module of the protein homeostasis network. Proteasomes also regulate cellular processes through temporal and spatial degradation of signaling pathway components. Here we demonstrate that the regulatory function of the proteasome plays an essential role in aging cells and that the beneficial impact of elevated proteasome capacity on lifespan partially originates from deregulation of the AMPK signaling pathway. Proteasome-mediated lifespan extension activity was carbon-source dependent and cells with enhancement proteasome function exhibited increased respiratory activity and oxidative stress response. These findings suggested that the pro-aging impact of proteasome upregulation might be related to changes in the metabolic state through a premature induction of respiration. Deletion of yeast AMPK, SNF1, or its activator SNF4 abrogated proteasome-mediated lifespan extension, supporting this hypothesis as the AMPK pathway regulates metabolism. We found that the premature induction of respiration in cells with increased proteasome activity originates from enhanced turnover of Mig1, an AMPK/Snf1 regulated transcriptional repressor that prevents the induction of genes required for respiration. Increasing proteasome activity also resulted in partial relocation of Mig1 from the nucleus to the mitochondria. Collectively, the results argue for a model in which elevated proteasome activity leads to the uncoupling of Snf1-mediated Mig1 regulation, resulting in a premature activation of respiration and thus the induction of a mitohormetic response, beneficial to lifespan. In addition, we observed incorrect Mig1 localization in two other long-lived yeast aging models: cells that overexpress SIR2 or deleted for the Mig1-regulator HXK2. Finally, compromised proteasome function blocks lifespan extension in both strains. Thus, our findings suggest that proteasomes, Sir2, Snf1 and Hxk2 form an interconnected aging network that controls metabolism through coordinated regulation of Mig1.

Advanced cellular age is associated with decreased efficiency of the proteostasis network. The proteasome, a protease in the cytoplasm and nuclei of eukaryotic cells, is an important component of this network. Recent studies demonstrate that increased proteasome capacity has a positive impact on longevity. The underlying mechanisms, however, have not been fully identified. Here we report that proteasomes are involved in regulating the AMP-activated kinase (AMPK) pathway and thus participate in correct metabolic adaptation. We find that Mig1, a transcriptional repressor downstream of yeast AMPK, Snf1, is a proteasome target and a negative regulator of lifespan. Increased proteasome activity results in enhanced turnover and incorrect localization of Mig1. The reduced Mig1 levels result in the induction of respiration and upregulation of the oxidative stress response. Premature Mig1 inactivation is also observed in two additional long-lived strains that overexpress SIR2 or are deleted for HXK2 and lifespan extension in both strains requires correct proteasome function. Our results uncover an interconnected network comprised of the proteasome, Sir2 and AMPK/Hxk2 signaling that impacts longevity through regulation of Mig1 and modulates respiratory metabolism. Mechanistic information on the cross-communication between these pathways is expected to facilitate the identification of novel pro-aging interventions.

Model-guided identification of gene deletion targets for metabolic engineering in Saccharomyces cerevisiae

Identification of metabolic engineering strategies for rerouting intracellular fluxes towards a desired product is often a challenging task owing to the topological and regulatory complexity of metabolic networks. Genome-scale metabolic models help tackling this complexity through systematic consideration of mass balance and reaction directionality constraints over the entire network. Here, we describe how genome-scale metabolic models can be used for identifying gene deletion targets leading to increased production of the desired product. Vanillin production in Saccharomyces cerevisiae is used as a case study throughout this chapter.

Systematic lipidomic analysis of yeast protein kinase and phosphatase mutants reveals novel insights into regulation of lipid homeostasis

The regulatory pathways required to maintain eukaryotic lipid homeostasis are largely unknown. We developed a systematic approach to uncover new players in the regulation of lipid homeostasis. Through an unbiased mass spectrometry-based lipidomic screening, we quantified hundreds of lipid species, including glycerophospholipids, sphingolipids, and sterols, from a collection of 129 mutants in protein kinase and phosphatase genes of Saccharomyces cerevisiae. Our approach successfully identified known kinases involved in lipid homeostasis and uncovered new ones. By clustering analysis, we found connections between nutrient-sensing pathways and regulation of glycerophospholipids. Deletion of members of glucose- and nitrogen-sensing pathways showed reciprocal changes in glycerophospholipid acyl chain lengths. We also found several new candidates for the regulation of sphingolipid homeostasis, including a connection between inositol pyrophosphate metabolism and complex sphingolipid homeostasis through transcriptional regulation of AUR1 and SUR1. This robust, systematic lipidomic approach constitutes a rich, new source of biological information and can be used to identify novel gene associations and function.

The reduced kinome of Ostreococcus tauri: core eukaryotic signalling components in a tractable model species

BACKGROUND

The current knowledge of eukaryote signalling originates from phenotypically diverse organisms. There is a pressing need to identify conserved signalling components among eukaryotes, which will lead to the transfer of knowledge across kingdoms. Two useful properties of a eukaryote model for signalling are (1) reduced signalling complexity, and (2) conservation of signalling components. The alga Ostreococcus tauri is described as the smallest free-living eukaryote. With less than 8,000 genes, it represents a highly constrained genomic palette.

RESULTS

Our survey revealed 133 protein kinases and 34 protein phosphatases (1.7% and 0.4% of the proteome). We conducted phosphoproteomic experiments and constructed domain structures and phylogenies for the catalytic protein-kinases. For each of the major kinases families we review the completeness and divergence of O. tauri representatives in comparison to the well-studied kinomes of the laboratory models Arabidopsis thaliana and Saccharomyces cerevisiae, and of Homo sapiens. Many kinase clades in O. tauri were reduced to a single member, in preference to the loss of family diversity, whereas TKL and ABC1 clades were expanded. We also identified kinases that have been lost in A. thaliana but retained in O. tauri. For three, contrasting eukaryotic pathways - TOR, MAPK, and the circadian clock - we established the subset of conserved components and demonstrate conserved sites of substrate phosphorylation and kinase motifs.

CONCLUSIONS

We conclude that O. tauri satisfies our two central requirements. Several of its kinases are more closely related to H. sapiens orthologs than S. cerevisiae is to H. sapiens. The greatly reduced kinome of O. tauri is therefore a suitable model for signalling in free-living eukaryotes.

MIRA: mutual information-based reporter algorithm for metabolic networks

MOTIVATION

Discovering the transcriptional regulatory architecture of the metabolism has been an important topic to understand the implications of transcriptional fluctuations on metabolism. The reporter algorithm (RA) was proposed to determine the hot spots in metabolic networks, around which transcriptional regulation is focused owing to a disease or a genetic perturbation. Using a z-score-based scoring scheme, RA calculates the average statistical change in the expression levels of genes that are neighbors to a target metabolite in the metabolic network. The RA approach has been used in numerous studies to analyze cellular responses to the downstream genetic changes. In this article, we propose a mutual information-based multivariate reporter algorithm (MIRA) with the goal of eliminating the following problems in detecting reporter metabolites: (i) conventional statistical methods suffer from small sample sizes, (ii) as z-score ranges from minus to plus infinity, calculating average scores can lead to canceling out opposite effects and (iii) analyzing genes one by one, then aggregating results can lead to information loss. MIRA is a multivariate and combinatorial algorithm that calculates the aggregate transcriptional response around a metabolite using mutual information. We show that MIRA's results are biologically sound, empirically significant and more reliable than RA.

RESULTS

We apply MIRA to gene expression analysis of six knockout strains of Escherichia coli and show that MIRA captures the underlying metabolic dynamics of the switch from aerobic to anaerobic respiration. We also apply MIRA to an Autism Spectrum Disorder gene expression dataset. Results indicate that MIRA reports metabolites that highly overlap with recently found metabolic biomarkers in the autism literature. Overall, MIRA is a promising algorithm for detecting metabolic drug targets and understanding the relation between gene expression and metabolic activity.

AVAILABILITY AND IMPLEMENTATION

The code is implemented in C# language using .NET framework. Project is available upon request.

The mammalian AMP-activated protein kinase complex mediates glucose regulation of gene expression in the yeast Saccharomyces cerevisiae

The AMP-activated protein kinase (AMPK) controls energy homeostasis in eukaryotic cells. Here we expressed hetero-trimeric mammalian AMPK complexes in a Saccharomyces cerevisiae mutant lacking all five genes encoding yeast AMPK/SNF1 components. Certain mammalian complexes complemented the growth defect of the yeast mutant on non-fermentable carbon sources. Phosphorylation of the AMPK α1-subunit was glucose-regulated, albeit not by the Glc7-Reg1/2 phosphatase, which performs this function on yeast AMPK/SNF1. AMPK could take over SNF1 function in glucose derepression. While indirectly acting anti-diabetic drugs had no effect on AMPK in yeast, compound 991 stimulated α1-subunit phosphorylation. Our results demonstrate a remarkable functional conservation of AMPK and that glucose regulation of AMPK may not be mediated by regulatory features of a specific phosphatase.

Contribution of network connectivity in determining the relationship between gene expression and metabolite concentration changes

One of the primary mechanisms through which a cell exerts control over its metabolic state is by modulating expression levels of its enzyme-coding genes. However, the changes at the level of enzyme expression allow only indirect control over metabolite levels, for two main reasons. First, at the level of individual reactions, metabolite levels are non-linearly dependent on enzyme abundances as per the reaction kinetics mechanisms. Secondly, specific metabolite pools are tightly interlinked with the rest of the metabolic network through their production and consumption reactions. While the role of reaction kinetics in metabolite concentration control is well studied at the level of individual reactions, the contribution of network connectivity has remained relatively unclear. Here we report a modeling framework that integrates both reaction kinetics and network connectivity constraints for describing the interplay between metabolite concentrations and mRNA levels. We used this framework to investigate correlations between the gene expression and the metabolite concentration changes in Saccharomyces cerevisiae during its metabolic cycle, as well as in response to three fundamentally different biological perturbations, namely gene knockout, nutrient shock and nutrient change. While the kinetic constraints applied at the level of individual reactions were found to be poor descriptors of the mRNA-metabolite relationship, their use in the context of the network enabled us to correlate changes in the expression of enzyme-coding genes to the alterations in metabolite levels. Our results highlight the key contribution of metabolic network connectivity in mediating cellular control over metabolite levels, and have implications towards bridging the gap between genotype and metabolic phenotype.

Glucose de-repression by yeast AMP-activated protein kinase SNF1 is controlled via at least two independent steps

The AMP-activated protein kinase, AMPK, controls energy homeostasis in eukaryotic cells but little is known about the mechanisms governing the dynamics of its activation/deactivation. The yeast AMPK, SNF1, is activated in response to glucose depletion and mediates glucose de-repression by inactivating the transcriptional repressor Mig1. Here we show that overexpression of the Snf1-activating kinase Sak1 results, in the presence of glucose, in constitutive Snf1 activation without alleviating glucose repression. Co-overexpression of the regulatory subunit Reg1 of the Glc-Reg1 phosphatase complex partly restores glucose regulation of Snf1. We generated a set of 24 kinetic mathematical models based on dynamic data of Snf1 pathway activation and deactivation. The models that reproduced our experimental observations best featured (a) glucose regulation of both Snf1 phosphorylation and dephosphorylation, (b) determination of the Mig1 phosphorylation status in the absence of glucose by Snf1 activity only and (c) a regulatory step directing active Snf1 to Mig1 under glucose limitation. Hence it appears that glucose de-repression via Snf1-Mig1 is regulated by glucose via at least two independent steps: the control of activation of the Snf1 kinase and directing active Snf1 to inactivating its target Mig1.

Nutrient sensing and signaling in the yeast Saccharomyces cerevisiae

The yeast Saccharomyces cerevisiae has been a favorite organism for pioneering studies on nutrient-sensing and signaling mechanisms. Many specific nutrient responses have been elucidated in great detail. This has led to important new concepts and insight into nutrient-controlled cellular regulation. Major highlights include the central role of the Snf1 protein kinase in the glucose repression pathway, galactose induction, the discovery of a G-protein-coupled receptor system, and role of Ras in glucose-induced cAMP signaling, the role of the protein synthesis initiation machinery in general control of nitrogen metabolism, the cyclin-controlled protein kinase Pho85 in phosphate regulation, nitrogen catabolite repression and the nitrogen-sensing target of rapamycin pathway, and the discovery of transporter-like proteins acting as nutrient sensors. In addition, a number of cellular targets, like carbohydrate stores, stress tolerance, and ribosomal gene expression, are controlled by the presence of multiple nutrients. The protein kinase A signaling pathway plays a major role in this general nutrient response. It has led to the discovery of nutrient transceptors (transporter receptors) as nutrient sensors. Major shortcomings in our knowledge are the relationship between rapid and steady-state nutrient signaling, the role of metabolic intermediates in intracellular nutrient sensing, and the identity of the nutrient sensors controlling cellular growth.

Integration of transcription and flux data reveals molecular paths associated with differences in oxygen-dependent phenotypes of Saccharomyces cerevisiae

BACKGROUND

Saccharomyces cerevisiae is able to adapt to a wide range of external oxygen conditions. Previously, oxygen-dependent phenotypes have been studied individually at the transcriptional, metabolite, and flux level. However, the regulation of cell phenotype occurs across the different levels of cell function. Integrative analysis of data from multiple levels of cell function in the context of a network of several known biochemical interaction types could enable identification of active regulatory paths not limited to a single level of cell function.

RESULTS

The graph theoretical method called Enriched Molecular Path detection (EMPath) was extended to enable integrative utilization of transcription and flux data. The utility of the method was demonstrated by detecting paths associated with phenotype differences of S. cerevisiae under three different conditions of oxygen provision: 20.9%, 2.8% and 0.5%. The detection of molecular paths was performed in an integrated genome-scale metabolic and protein-protein interaction network.

CONCLUSIONS

The molecular paths associated with the phenotype differences of S. cerevisiae under conditions of different oxygen provisions revealed paths of molecular interactions that could potentially mediate information transfer between processes that respond to the particular oxygen availabilities.

Mapping condition-dependent regulation of lipid metabolism in Saccharomyces cerevisiae

Lipids play a central role in cellular function as constituents of membranes, as signaling molecules, and as storage materials. Although much is known about the role of lipids in regulating specific steps of metabolism, comprehensive studies integrating genome-wide expression data, metabolite levels, and lipid levels are currently lacking. Here, we map condition-dependent regulation controlling lipid metabolism in Saccharomyces cerevisiae by measuring 5636 mRNAs, 50 metabolites, 97 lipids, and 57 (13)C-reaction fluxes in yeast using a three-factor full-factorial design. Correlation analysis across eight environmental conditions revealed 2279 gene expression level-metabolite/lipid relationships that characterize the extent of transcriptional regulation in lipid metabolism relative to major metabolic hubs within the cell. To query this network, we developed integrative methods for correlation of multi-omics datasets that elucidate global regulatory signatures. Our data highlight many characterized regulators of lipid metabolism and reveal that sterols are regulated more at the transcriptional level than are amino acids. Beyond providing insights into the systems-level organization of lipid metabolism, we anticipate that our dataset and approach can join an emerging number of studies to be widely used for interrogating cellular systems through the combination of mathematical modeling and experimental biology.

Single cell synchrotron FT-IR microspectroscopy reveals a link between neutral lipid and storage carbohydrate fluxes in S. cerevisiae

In most organisms, storage lipids are packaged into specialized structures called lipid droplets. These contain a core of neutral lipids surrounded by a monolayer of phospholipids, and various proteins which vary depending on the species. Hydrophobic structural proteins stabilize the interface between the lipid core and aqueous cellular environment (perilipin family of proteins, apolipoproteins, oleosins). We developed a genetic approach using heterologous expression in Saccharomyces cerevisiae of the Arabidopsis thaliana lipid droplet oleosin and caleosin proteins AtOle1 and AtClo1. These transformed yeasts overaccumulate lipid droplets, leading to a specific increase in storage lipids. The phenotype of these cells was explored using synchrotron FT-IR microspectroscopy to investigate the dynamics of lipid storage and cellular carbon fluxes reflected as changes in spectral fingerprints. Multivariate statistical analysis of the data showed a clear effect on storage carbohydrates and more specifically, a decrease in glycogen in our modified strains. These observations were confirmed by biochemical quantification of the storage carbohydrates glycogen and trehalose. Our results demonstrate that neutral lipid and storage carbohydrate fluxes are tightly connected and co-regulated.