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

Adaptive responses of yeast strains tolerant to acidic pH, acetate, and supraoptimal temperature

Ethanol fermentations can be prematurely halted as Saccharomyces cerevisiae faces adverse conditions, such as acidic pH, presence of acetic acid, and supraoptimal temperatures. The knowledge on yeast responses to these conditions is essential to endowing a tolerant phenotype to another strain by targeted genetic manipulation. In this study, physiological and whole-genome analyses were conducted to obtain insights on molecular responses which potentially render yeast tolerant towards thermoacidic conditions. To this end, we used thermotolerant TTY23, acid tolerant AT22, and thermo-acid tolerant TAT12 strains previously generated by adaptive laboratory evolution (ALE) experiments. The results showed an increase in thermoacidic profiles in the tolerant strains. The whole-genome sequence revealed the importance of genes related to: H⁺, iron, and glycerol transport (i.e., PMA1, FRE1/2, JEN1, VMA2, VCX1, KHA1, AQY3, and ATO2); transcriptional regulation of stress responses to drugs, reactive oxygen species and heat-shock (i.e., HSF1, SKN7, BAS1, HFI1, and WAR1); and adjustments of fermentative growth and stress responses by glucose signaling pathways (i.e., ACS1, GPA1/2, RAS2, IRA2, and REG1). At 30 °C and pH 5.5, more than a thousand differentially expressed genes (DEGs) were identified in each strain. The integration of results revealed that evolved strains adjust their intracellular pH by H⁺ and acetic acid transport, modify their metabolism and stress responses via glucose signaling pathways, control of cellular ATP pools by regulating translation and de novo synthesis of nucleotides, and direct the synthesis, folding and rescue of proteins throughout the heat-shock stress response. Moreover, the motifs analysis in mutated transcription factors suggested a significant association of SFP1, YRR1, BAS1, HFI1, HSF1, and SKN7 TFs with DEGs found in thermoacidic tolerant yeast strains. KEY POINTS: • All the evolved strains overexpressed the plasma membrane H⁺ -ATPase PMA1 at optimal conditions • Tolerant strain TAT12 mutated genes encoding weak acid and heat response TFs HSF1, SKN7, and WAR1 • TFs HSF1 and SKN7 likely controlled the transcription of metabolic genes associated to heat and acid tolerance.

In vivo protein kinase activity of SnRK1 fluctuates in Arabidopsis rosettes during light-dark cycles

Sucrose-nonfermenting 1 (SNF1)-related kinase 1 (SnRK1) is a central hub in carbon and energy signaling in plants, and is orthologous with SNF1 in yeast and the AMP-activated protein kinase (AMPK) in animals. Previous studies of SnRK1 relied on in vitro activity assays or monitoring of putative marker gene expression. Neither approach gives unambiguous information about in vivo SnRK1 activity. We have monitored in vivo SnRK1 activity using Arabidopsis (Arabidopsis thaliana) reporter lines that express a chimeric polypeptide with an SNF1/SnRK1/AMPK-specific phosphorylation site. We investigated responses during an equinoctial diel cycle and after perturbing this cycle. As expected, in vivo SnRK1 activity rose toward the end of the night and rose even further when the night was extended. Unexpectedly, although sugars rose after dawn, SnRK1 activity did not decline until about 12 h into the light period. The sucrose signal metabolite, trehalose 6-phosphate (Tre6P), has been shown to inhibit SnRK1 in vitro. We introduced the SnRK1 reporter into lines that harbored an inducible trehalose-6-phosphate synthase construct. Elevated Tre6P decreased in vivo SnRK1 activity in the light period, but not at the end of the night. Reporter polypeptide phosphorylation was sometimes negatively correlated with Tre6P, but a stronger and more widespread negative correlation was observed with glucose-6-phosphate. We propose that SnRK1 operates within a network that controls carbon utilization and maintains diel sugar homeostasis, that SnRK1 activity is regulated in a context-dependent manner by Tre6P, probably interacting with further inputs including hexose phosphates and the circadian clock, and that SnRK1 signaling is modulated by factors that act downstream of SnRK1.

Scalable and flexible inference framework for stochastic dynamic single-cell models

Understanding the inherited nature of how biological processes dynamically change over time and exhibit intra- and inter-individual variability, due to the different responses to environmental stimuli and when interacting with other processes, has been a major focus of systems biology. The rise of single-cell fluorescent microscopy has enabled the study of those phenomena. The analysis of single-cell data with mechanistic models offers an invaluable tool to describe dynamic cellular processes and to rationalise cell-to-cell variability within the population. However, extracting mechanistic information from single-cell data has proven difficult. This requires statistical methods to infer unknown model parameters from dynamic, multi-individual data accounting for heterogeneity caused by both intrinsic (e.g. variations in chemical reactions) and extrinsic (e.g. variability in protein concentrations) noise. Although several inference methods exist, the availability of efficient, general and accessible methods that facilitate modelling of single-cell data, remains lacking. Here we present a scalable and flexible framework for Bayesian inference in state-space mixed-effects single-cell models with stochastic dynamic. Our approach infers model parameters when intrinsic noise is modelled by either exact or approximate stochastic simulators, and when extrinsic noise is modelled by either time-varying, or time-constant parameters that vary between cells. We demonstrate the relevance of our approach by studying how cell-to-cell variation in carbon source utilisation affects heterogeneity in the budding yeast Saccharomyces cerevisiae SNF1 nutrient sensing pathway. We identify hexokinase activity as a source of extrinsic noise and deduce that sugar availability dictates cell-to-cell variability.

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.

Protein kinases Elm1 and Sak1 of Saccharomyces cerevisiae exerted different functions under high-glucose and heat shock stresses

Phosphorylation catalyzed by protein kinases is the most common and important regulatory pathway in the adaptive physiological responses to the changes in nutrition and environment of yeast. This study focused on the functions of Elm1, Sak1, and Tos3, which are three upstream protein kinases of Snf1 in Saccharomyces cerevisiae, in response to high-glucose and heat shock stresses. Results suggested that changing the gene dosage of ELM1/SAK1/TOS3 had different effects under high-glucose and heat shock stresses. ELM1 and SAK1 overexpressions could enhance the tolerance of S. cerevisiae to high-glucose and heat shock stresses, respectively. Nevertheless, the overexpression of TOS3 decreased the tolerance to high-glucose stress, and a native level of Tos3 was important for the normal adaptation to heat shock condition. The overexpression of ELM1 increased the accumulation of trehalose and ergosterol and altered the composition of fatty acids with altered gene expressions involved in the metabolism of three metabolites. Enhanced resistance to heat shock stress in SAK1 overexpression might be related to the enhanced accumulation of trehalose and ergosterol and upregulated transcription of genes related to the metabolism of trehalose and ergosterol. Furthermore, Elm1 might regulate the metabolism of trehalose, ergosterol, and fatty acids in a Snf1-independent form under high-glucose stress. A Snf1-independent pathway might be involved in the regulation of trehalose metabolism by Sak1 under heat shock condition. However, Sak1 and Snf1 may have an indirect relationship in the regulation of ergosterol synthesis. KEY POINTS: • Altering the gene dosage of ELM1/SAK1/TOS3 had different effects on stress responses • Elm1 regulated high-glucose response in a Snf1-independent manner • Sak1 and Snf1 had an indirect relationship in the regulation of heat shock response.

Modeling and analysis of the macronutrient signaling network in budding yeast

Adaptive modulation of the global cellular growth state of unicellular organisms is crucial for their survival in fluctuating nutrient environments. Because these organisms must be able to respond reliably to ever varying and unpredictable nutritional conditions, their nutrient signaling networks must have a certain inbuilt robustness. In eukaryotes, such as the budding yeast Saccharomyces cerevisiae, distinct nutrient signals are relayed by specific plasma membrane receptors to signal transduction pathways that are interconnected in complex information-processing networks, which have been well characterized. However, the complexity of the signaling network confounds the interpretation of the overall regulatory "logic" of the control system. Here, we propose a literature-curated molecular mechanism of the integrated nutrient signaling network in budding yeast, focusing on early temporal responses to carbon and nitrogen signaling. We build a computational model of this network to reconcile literature-curated quantitative experimental data with our proposed molecular mechanism. We evaluate the robustness of our estimates of the model's kinetic parameter values. We test the model by comparing predictions made in mutant strains with qualitative experimental observations made in the same strains. Finally, we use the model to predict nutrient-responsive transcription factor activities in a number of mutant strains undergoing complex nutrient shifts.

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.

Role of Elm1, Tos3, and Sak1 Protein Kinases in the Maltose Metabolism of Baker's Yeast

Glucose repression is a key regulatory system controlling the metabolism of non-glucose carbon source in yeast. Glucose represses the utilization of maltose, the most abundant fermentable sugar in lean dough and wort, thereby negatively affecting the fermentation efficiency and product quality of pasta products and beer. In this study, the focus was on the role of three kinases, Elm1, Tos3, and Sak1, in the maltose metabolism of baker’s yeast in lean dough. The results suggested that the three kinases played different roles in the regulation of the maltose metabolism of baker’s yeast with differential regulations on MAL genes. Elm1 was necessary for the maltose metabolism of baker’s yeast in maltose and maltose-glucose, and the overexpression of ELM1 could enhance the maltose metabolism and lean dough fermentation ability by upregulating the transcription of MALx1 (x is the locus) in maltose and maltose-glucose and MALx2 in maltose. The native level of TOS3 and SAK1 was essential for yeast cells to adapt glucose repression, but the overexpression of TOS3 and SAK1 alone repressed the expression of MALx1 in maltose-glucose and MALx2 in maltose. Moreover, the three kinases might regulate the maltose metabolism via the Snf1-parallel pathways with a carbon source-dependent manner. These results, for the first time, suggested that Elm1, rather than Tos3 and Sak1, might be the dominant regulator in the maltose metabolism of baker’s yeast. These findings provided knowledge about the glucose repression of maltose and gave a new perspective for breeding industrial yeasts with rapid maltose metabolism.

The regulation of Saccharomyces cerevisiae Snf1 protein kinase on glucose utilization is in a glucose-dependent manner

Protein phosphorylation catalyzed by protein kinases is the major regulatory mechanism that controls many cellular processes. The regulatory mechanism of one protein kinase in different signals is distinguished, probably inducing multiple phenotypes. The Saccharomyces cerevisiae Snf1 protein kinase, a member of the AMP‑activated protein kinase family, plays important roles in the response to nutrition and environmental stresses. Glucose is an important nutrient for life activities of cells, but glucose repression and osmotic pressure could be produced at certain concentrations. To deeply understand the role of Snf1 in the regulation of nutrient metabolism and stress response of S. cerevisiae cells, the role and the regulatory mechanism of Snf1 in glucose metabolism are discussed in different level of glucose: below 1% (glucose derepression status), in 2% (glucose repression status), and in 30% glucose (1.66 M, an osmotic equivalent to 0.83 M NaCl). In summary, Snf1 regulates glucose metabolism in a glucose-dependent manner, which is associated with the different regulation on activation, localization, and signal pathways of Snf1 by varied glucose. Exploring the regulatory mechanism of Snf1 in glucose metabolism in different concentrations of glucose can provide insights into the study of the global regulatory mechanism of Snf1 in yeast and can help to better understand the complexity of physiological response of cells to stresses.

Transcriptional regulatory proteins in central carbon metabolism of Pichia pastoris and Saccharomyces cerevisiae

System-wide interactions in living cells and discovery of the diverse roles of transcriptional regulatory proteins that are mediator proteins with catalytic domains and regulatory subunits and transcription factors in the cellular pathways have become crucial for understanding the cellular response to environmental conditions. This review provides information for future metabolic engineering strategies through analyses on the highly interconnected regulatory networks in Saccharomyces cerevisiae and Pichia pastoris and identifying their components. We discuss the current knowledge on the carbon catabolite repression (CCR) mechanism, interconnecting regulatory system of the central metabolic pathways that regulate cell metabolism based on nutrient availability in the industrial yeasts. The regulatory proteins and their functions in the CCR signalling pathways in both yeasts are presented and discussed. We highlight the importance of metabolic signalling networks by signifying ways on how effective engineering strategies can be designed for generating novel regulatory circuits, furthermore to activate pathways that reconfigure the network architecture. We summarize the evidence that engineering of multilayer regulation is needed for directed evolution of the cellular network by putting the transcriptional control into a new perspective for the regulation of central carbon metabolism of the industrial yeasts; furthermore, we suggest research directions that may help to enhance production of recombinant products in the widely used, creatively engineered, but relatively less studied P. pastoris through de novo metabolic engineering strategies based on the discovery of components of signalling pathways in CCR metabolism. KEY POINTS: • Transcriptional regulation and control is the key phenomenon in the cellular processes. • Designing de novo metabolic engineering strategies depends on the discovery of signalling pathways in CCR metabolism. • Crosstalk between pathways occurs through essential parts of transcriptional machinery connected to specific catalytic domains. • In S. cerevisiae, a major part of CCR metabolism is controlled through Snf1 kinase, Glc7 phosphatase, and Srb10 kinase. • In P. pastoris, signalling pathways in CCR metabolism have not yet been clearly known yet. • Cellular regulations on the transcription of promoters are controlled with carbon sources.

Enhanced multi-stress tolerance and glucose utilization of Saccharomyces cerevisiae by overexpression of the SNF1 gene and varied beta isoform of Snf1 dominates in stresses

Background

The Saccharomyces cerevisiae Snf1 complex is a member of the AMP-activated protein kinase family and plays an important role in response to environmental stress. The α catalytic subunit Snf1 regulates the activity of the protein kinase, while the β regulatory subunits Sip1/Sip2/Gal83 specify substrate preferences and stress response capacities of Snf1. In this study, we aim to investigate the effects of SNF1 overexpression on the cell tolerance and glucose consumption of S. cerevisiae in high glucose, ethanol, and heat stresses and to explore the valid Snf1 form in the light of β subunits in these stresses.

Results

The results suggest that overexpression of SNF1 is effective to improve cell resistance and glucose consumption of S. cerevisiae in high glucose, ethanol, and heat stresses, which might be related to the changed accumulation of fatty acids and amino acids and altered expression levels of genes involved in glucose transport and glycolysis. However, different form of β regulatory subunits dominated in stresses with regard to cell tolerance and glucose utilization. The Sip1 isoform was more necessary to the growth and glucose consumption in ethanol stress. The glucose uptake largely depended on the Sip2 isoform in high sugar and ethanol stresses. The Gal83 isoform only contributed inferior effect on the growth in ethanol stress. Therefore, redundancy and synergistic effect of β subunits might occur in high glucose, ethanol, and heat stresses, but each subunit showed specificity under various stresses.

Conclusions

This study enriches the understanding of the function of Snf1 protein kinase and provides an insight to breed multi-stress tolerant yeast strains.

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.

Host Adaptive Immune Status Regulates Expression of the Schistosome AMP-Activated Protein Kinase

Schistosomes exhibit profound developmental adaptations in response to the immune status of their mammalian host, including significant attenuation of parasite growth, development and reproduction in response to deficits in host adaptive immunity. These observations led us to hypothesize that schistosomes regulate the utilization of energy resources in response to immunological conditions within the host. To test this hypothesis, we identified and characterized the Schistosoma mansoni AMP-activated protein kinase (AMPK), a heterotrimeric enzyme complex that is central to regulating energy metabolism at the cellular and organismal level in eukaryotes. We show that expression of the catalytic α subunit is developmentally regulated during the parasite life cycle, with peak expression occurring in adult worms. However, the protein is present and phosphorylated in all life cycle stages examined, suggesting a need for active regulation of energy resources throughout the life cycle. In contrast, transcription of the AMPK α gene is down-regulated in cercariae and schistosomula, suggesting that the protein in these life cycle stages is pre-synthesized in the sporocyst and that expression must be re-initiated once inside the mammalian host. We also show that schistosome AMPK α activity in adult worms is sensitive to changes in the parasite's environment, suggesting a mechanism by which schistosome metabolism may be responsive to host immune factors. Finally, we show that AMPK α expression is significantly down-regulated in parasites isolated from immunodeficient mice, suggesting that modulation of parasite energy metabolism may contribute to the attenuation of schistosome growth and reproduction in immunodeficient hosts. These findings provide insights into the molecular interactions between schistosomes and their vertebrate hosts and suggest that parasite energy metabolism may represent a novel target for anti-schistosome interventions.

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.

Carbon Catabolite Repression in Filamentous Fungi

Carbon Catabolite Repression (CCR) has fascinated scientists and researchers around the globe for the past few decades. This important mechanism allows preferential utilization of an energy-efficient and readily available carbon source over relatively less easily accessible carbon sources. This mechanism helps microorganisms to obtain maximum amount of glucose in order to keep pace with their metabolism. Microorganisms assimilate glucose and highly favorable sugars before switching to less-favored sources of carbon such as organic acids and alcohols. In CCR of filamentous fungi, CreA acts as a transcription factor, which is regulated to some extent by ubiquitination. CreD-HulA ubiquitination ligase complex helps in CreA ubiquitination, while CreB-CreC deubiquitination (DUB) complex removes ubiquitin from CreA, which causes its activation. CCR of fungi also involves some very crucial elements such as Hexokinases, cAMP, Protein Kinase (PKA), Ras proteins, G protein-coupled receptor (GPCR), Adenylate cyclase, RcoA and SnfA. Thorough study of molecular mechanism of CCR is important for understanding growth, conidiation, virulence and survival of filamentous fungi. This review is a comprehensive revision of the regulation of CCR in filamentous fungi as well as an updated summary of key regulators, regulation of different CCR-dependent mechanisms and its impact on various physical characteristics of filamentous fungi.

The Transcriptional Response of Candida albicans to Weak Organic Acids, Carbon Source, and MIG1 Inactivation Unveils a Role for HGT16 in Mediating the Fungistatic Effect of Acetic Acid

Candida albicans is a resident fungus of the human intestinal microflora. Commonly isolated at low abundance in healthy people, C. albicans outcompetes local microbiota during candidiasis episodes. Under normal conditions, members of the human gastrointestinal (GI) microbiota were shown to keep C. albicans colonization under control. By releasing weak organic acids (WOAs), bacteria are able to moderate yeast growth. This mechanism displays a synergistic effect in vitro with the absence of glucose in medium of culture, which underlines the complex interactions that C. albicans faces in its natural environment. Inactivation of the transcriptional regulator MIG1 in C. albicans results in a lack of sensitivity to this synergistic outcome. To decipher C. albicans transcriptional responses to glucose, WOAs, and the role of MIG1, we performed RNA sequencing (RNA-seq) on four biological replicates exposed to combinations of these three parameters. We were able to characterize the (i) glucose response, (ii) response to acetic and butyric acid, (iii) MIG1 regulation of C. albicans, and (iv) genes responsible for WOA resistance. We identified a group of six genes linked to WOA sensitivity in a glucose-MIG1-dependent manner and inactivated one of these genes, the putative glucose transporter HGT16, in a SC5314 wild-type background. As expected, the mutant displayed a partial complementation to WOA resistance in the absence of glucose. This result points toward a mechanism of WOA sensitivity in C. albicans involving membrane transporters, which could be exploited to control yeast colonization in human body niches.

Single-cell study links metabolism with nutrient signaling and reveals sources of variability

BACKGROUND

The yeast AMPK/SNF1 pathway is best known for its role in glucose de/repression. When glucose becomes limited, the Snf1 kinase is activated and phosphorylates the transcriptional repressor Mig1, which is then exported from the nucleus. The exact mechanism how the Snf1-Mig1 pathway is regulated is not entirely elucidated.

RESULTS

Glucose uptake through the low affinity transporter Hxt1 results in nuclear accumulation of Mig1 in response to all glucose concentrations upshift, however with increasing glucose concentration the nuclear localization of Mig1 is more intense. Strains expressing Hxt7 display a constant response to all glucose concentration upshifts. We show that differences in amount of hexose transporter molecules in the cell could cause cell-to-cell variability in the Mig1-Snf1 system. We further apply mathematical modelling to our data, both general deterministic and a nonlinear mixed effect model. Our model suggests a presently unrecognized regulatory step of the Snf1-Mig1 pathway at the level of Mig1 dephosphorylation. Model predictions point to parameters involved in the transport of Mig1 in and out of the nucleus as a majorsource of cell to cell variability.

CONCLUSIONS

With this modelling approach we have been able to suggest steps that contribute to the cell-to-cell variability. Our data indicate a close link between the glucose uptake rate, which determines the glycolytic rate, and the activity of the Snf1/Mig1 system. This study hence establishes a close relation between metabolism and signalling.

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.

Real-time monitoring of the sugar sensing in Saccharomyces cerevisiae indicates endogenous mechanisms for xylose signaling

Background

The sugar sensing and carbon catabolite repression in Baker’s yeast Saccharomyces cerevisiae is governed by three major signaling pathways that connect carbon source recognition with transcriptional regulation. Here we present a screening method based on a non-invasive in vivo reporter system for real-time, single-cell screening of the sugar signaling state in S. cerevisiae in response to changing carbon conditions, with a main focus on the response to glucose and xylose.

Results

The artificial reporter system was constructed by coupling a green fluorescent protein gene (yEGFP3) downstream of endogenous yeast promoters from the Snf3p/Rgt2p, SNF1/Mig1p and cAMP/PKA signaling pathways: HXT1p/2p/4p; SUC2p, CAT8p; TPS1p/2p and TEF4p respectively. A panel of eight biosensors strains was generated by single copy chromosomal integration of the different constructs in a W303-derived strain. The signaling biosensors were validated for their functionality with flow cytometry by comparing the fluorescence intensity (FI) response in the presence of high or nearly depleted glucose to the known induction/repression conditions of the eight different promoters. The FI signal correlated with the known patterns of the selected promoters while maintaining a non-invasive property on the cellular phenotype, as was demonstrated in terms of growth, metabolites and enzyme activity.

Conclusions

Once verified, the sensors were used to evaluate the signaling response to varying conditions of extracellular glucose, glycerol and xylose by screening in 96-well microtiter plates. We show that these yeast strains, which do not harbor any recombinant pathways for xylose utilization, are lacking a signaling response for extracellular xylose. However, for the HXT2p/4p sensors, a shift in the flow cytometry population dynamics indicated that internalized xylose does affect the signaling. These results suggest that the previously observed effects of this pentose on the S. cerevisiae physiology and gene regulation can be attributed to xylose and not only to a lack of glucose.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-016-0580-x) contains supplementary material, which is available to authorized users.

The β subunit of yeast AMP-activated protein kinase directs substrate specificity in response to alkaline stress

Saccharomyces cerevisiae express three isoforms of Snf1 kinase that differ by which β subunit is present, Gal83, Sip1 or Sip2. Here we investigate the abundance, activation, localization and signaling specificity of the three Snf1 isoforms. The relative abundance of these isoforms was assessed by quantitative immunoblotting using two different protein extraction methods and by fluorescence microscopy. The Gal83 containing isoform is the most abundant in all assays while the abundance of the Sip1 and Sip2 isoforms is typically underestimated especially in glass-bead extractions. Earlier studies to assess Snf1 isoform function utilized gene deletions as a means to inactivate specific isoforms. Here we use point mutations in Gal83 and Sip2 and a 17 amino acid C-terminal truncation of Sip1 to inactivate specific isoforms without affecting their abundance or association with the other subunits. The effect of low glucose and alkaline stresses was examined for two Snf1 phosphorylation substrates, the Mig1 and Mig2 proteins. Any of the three isoforms was capable of phosphorylating Mig1 in response to glucose stress. In contrast, the Gal83 isoform of Snf1 was both necessary and sufficient for the phosphorylation of the Mig2 protein in response to alkaline stress. Alkaline stress led to the activation of all three isoforms yet only the Gal83 isoform translocates to the nucleus and phosphorylates Mig2. Deletion of the SAK1 gene blocked nuclear translocation of Gal83 and signaling to Mig2. These data strongly support the idea that Snf1 signaling specificity is mediated by localization of the different Snf1 isoforms.

Network reconstruction and validation of the Snf1/AMPK pathway in baker's yeast based on a comprehensive literature review

BACKGROUND/OBJECTIVES

The SNF1/AMPK protein kinase has a central role in energy homeostasis in eukaryotic cells. It is activated by energy depletion and stimulates processes leading to the production of ATP while it downregulates ATP-consuming processes. The yeast SNF1 complex is best known for its role in glucose derepression.

METHODS

We performed a network reconstruction of the Snf1 pathway based on a comprehensive literature review. The network was formalised in the rxncon language, and we used the rxncon toolbox for model validation and gap filling.

RESULTS

We present a machine-readable network definition that summarises the mechanistic knowledge of the Snf1 pathway. Furthermore, we used the known input/output relationships in the network to identify and fill gaps in the information transfer through the pathway, to produce a functional network model. Finally, we convert the functional network model into a rule-based model as a proof-of-principle.

CONCLUSIONS

The workflow presented here enables large scale reconstruction, validation and gap filling of signal transduction networks. It is analogous to but distinct from that established for metabolic networks. We demonstrate the workflow capabilities, and the direct link between the reconstruction and dynamic modelling, with the Snf1 network. This network is a distillation of the knowledge from all previous publications on the Snf1/AMPK pathway. The network is a knowledge resource for modellers and experimentalists alike, and a template for similar efforts in higher eukaryotes. Finally, we envisage the workflow as an instrumental tool for reconstruction of large signalling networks across Eukaryota.

A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast

The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend to be faster, more extended, and displays an increased cell-to-cell variability.

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.

Yeast AMP-activated protein kinase monitors glucose concentration changes and absolute glucose levels

Analysis of the time-dependent behavior of a signaling system can provide insight into its dynamic properties. We employed the nucleocytoplasmic shuttling of the transcriptional repressor Mig1 as readout to characterize Snf1-Mig1 dynamics in single yeast cells. Mig1 binds to promoters of target genes and mediates glucose repression. Mig1 is predominantly located in the nucleus when glucose is abundant. Upon glucose depletion, Mig1 is phosphorylated by the yeast AMP-activated kinase Snf1 and exported into the cytoplasm. We used a three-channel microfluidic device to establish a high degree of control over the glucose concentration exposed to cells. Following regimes of glucose up- and downshifts, we observed a very rapid response reaching a new steady state within less than 1 min, different glucose threshold concentrations depending on glucose up- or downshifts, a graded profile with increased cell-to-cell variation at threshold glucose concentrations, and biphasic behavior with a transient translocation of Mig1 upon the shift from high to intermediate glucose concentrations. Fluorescence loss in photobleaching and fluorescence recovery after photobleaching data demonstrate that Mig1 shuttles constantly between the nucleus and cytoplasm, although with different rates, depending on the presence of glucose. Taken together, our data suggest that the Snf1-Mig1 system has the ability to monitor glucose concentration changes as well as absolute glucose levels. The sensitivity over a wide range of glucose levels and different glucose concentration-dependent response profiles are likely determined by the close integration of signaling with the metabolism and may provide for a highly flexible and fast adaptation to an altered nutritional status.