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

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.

The yeast 14-3-3 proteins Bmh1 and Bmh2 regulate key signaling pathways

Cell signaling regulates several physiological processes by receiving, processing, and transmitting signals between the extracellular and intracellular environments. In signal transduction, phosphorylation is a crucial effector as the most common posttranslational modification. Selectively recognizing specific phosphorylated motifs of target proteins and modulating their functions through binding interactions, the yeast 14-3-3 proteins Bmh1 and Bmh2 are involved in catabolite repression, carbon metabolism, endocytosis, and mitochondrial retrograde signaling, among other key cellular processes. These conserved scaffolding molecules also mediate crosstalk between ubiquitination and phosphorylation, the spatiotemporal control of meiosis, and the activity of ion transporters Trk1 and Nha1. In humans, deregulation of analogous processes triggers the development of serious diseases, such as diabetes, cancer, viral infections, microbial conditions and neuronal and age-related diseases. Accordingly, the aim of this review article is to provide a brief overview of the latest findings on the functions of yeast 14-3-3 proteins, focusing on their role in modulating the aforementioned processes.

Glucose restriction in Saccharomyces cerevisiae modulates the phosphorylation pattern of the 20S proteasome and increases its activity

Caloric restriction is known to extend the lifespan and/or improve diverse physiological parameters in a vast array of organisms. In the yeast Saccharomyces cerevisiae, caloric restriction is performed by reducing the glucose concentration in the culture medium, a condition previously associated with increased chronological lifespan and 20S proteasome activity in cell extracts, which was not due to increased proteasome amounts in restricted cells. Herein, we sought to investigate the mechanisms through which glucose restriction improved proteasome activity and whether these activity changes were associated with modifications in the particle conformation. We show that glucose restriction increases the ability of 20S proteasomes, isolated from Saccharomyces cerevisiae cells, to degrade model substrates and whole proteins. In addition, threonine 55 and/or serine 56 of the α5-subunit, were/was consistently found to be phosphorylated in proteasomes isolated from glucose restricted cells, which may be involved in the increased proteolysis capacity of proteasomes from restricted cells. We were not able to observe changes in the gate opening nor in the spatial conformation in 20S proteasome particles isolated from glucose restricted cells, suggesting that the changes in activity were not accompanied by large conformational alterations in the 20S proteasome but involved allosteric activation of proteasome catalytic site.

The impact of metabolism on the adaptation of organisms to environmental change

Since Jacob and Monod's discovery of the lac operon ∼1960, the explanations offered for most metabolic adaptations have been genetic. The focus has been on the adaptive changes in gene expression that occur, which are often referred to as "metabolic reprogramming." The contributions metabolism makes to adaptation have been largely ignored. Here we point out that metabolic adaptations, including the associated changes in gene expression, are highly dependent on the metabolic state of an organism prior to the environmental change to which it is adapting, and on the plasticity of that state. In support of this hypothesis, we examine the paradigmatic example of a genetically driven adaptation, the adaptation of E. coli to growth on lactose, and the paradigmatic example of a metabolic driven adaptation, the Crabtree effect in yeast. Using a framework based on metabolic control analysis, we have reevaluated what is known about both adaptations, and conclude that knowledge of the metabolic properties of these organisms prior to environmental change is critical for understanding not only how they survive long enough to adapt, but also how the ensuing changes in gene expression occur, and their phenotypes post-adaptation. It would be useful if future explanations for metabolic adaptations acknowledged the contributions made to them by metabolism, and described the complex interplay between metabolic systems and genetic systems that make these adaptations possible.

The Effect of Calorie Restriction on Protein Quality Control in Yeast

Initially, protein aggregates were regarded as a sign of a pathological state of the cell. Later, it was found that these assemblies are formed in response to stress, and that some of them serve as signalling mechanisms. This review has a particular focus on how intracellular protein aggregates are related to altered metabolism caused by different glucose concentrations in the extracellular environment. We summarise the current knowledge of the role of energy homeostasis signalling pathways in the consequent effect on intracellular protein aggregate accumulation and removal. This covers regulation at different levels, including elevated protein degradation and proteasome activity mediated by the Hxk2 protein, the enhanced ubiquitination of aberrant proteins through Torc1/Sch9 and Msn2/Whi2, and the activation of autophagy mediated through ATG genes. Finally, certain proteins form reversible biomolecular aggregates in response to stress and reduced glucose levels, which are used as a signalling mechanism in the cell, controlling major primary energy pathways related to glucose sensing.

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.

Metabolic remodeling maintains a reducing environment for rapid activation of the yeast DNA replication checkpoint

Nucleotide metabolism fuels normal DNA replication and is also primarily targeted by the DNA replication checkpoint when replication stalls. To reveal a comprehensive interconnection between genome maintenance and metabolism, we analyzed the metabolomic changes upon replication stress in the budding yeast S. cerevisiae. We found that upon treatment of cells with hydroxyurea, glucose is rapidly diverted to the oxidative pentose phosphate pathway (PPP). This effect is mediated by the AMP-dependent kinase, SNF1, which phosphorylates the transcription factor Mig1, thereby relieving repression of the gene encoding the rate-limiting enzyme of the PPP. Surprisingly, NADPH produced by the PPP is required for efficient recruitment of replication protein A (RPA) to single-stranded DNA, providing the signal for the activation of the Mec1/ATR-Rad53/CHK1 checkpoint signaling kinase cascade. Thus, SNF1, best known as a central energy controller, determines a fast mode of replication checkpoint activation through a redox mechanism. These findings establish that SNF1 provides a hub with direct links to cellular metabolism, redox, and surveillance of DNA replication in eukaryotes.

Single-Molecule Narrow-Field Microscopy of Protein-DNA Binding Dynamics in Glucose Signal Transduction of Live Yeast Cells

Single-molecule narrow-field microscopy is a versatile tool to investigate a diverse range of protein dynamics in live cells and has been extensively used in bacteria. Here, we describe how these methods can be extended to larger eukaryotic, yeast cells, which contain subcellular compartments. We describe how to obtain single-molecule microscopy data but also how to analyze these data to track and obtain the stoichiometry of molecular complexes diffusing in the cell. We chose glucose-mediated signal transduction of live yeast cells as the system to demonstrate these single-molecule techniques as transcriptional regulation is fundamentally a single-molecule problem-a single repressor protein binding a single binding site in the genome can dramatically alter behavior at the whole cell and population levels.

The α-arrestin family of ubiquitin ligase adaptors links metabolism with selective endocytosis

The regulation of nutrient uptake into cells is important, as it allows to either increase biomass for cell growth or to preserve homoeostasis. A key strategy to adjust cellular nutrient uptake is the reconfiguration of the nutrient transporter repertoire at the plasma membrane by the addition of nutrient transporters through the secretory pathway and by their endocytic removal. In this review, we focus on the mechanisms that regulate selective nutrient transporter endocytosis, which is mediated by the α-arrestin protein family. In the budding yeast Saccharomyces cerevisiae, 14 different α-arrestins (also named arrestin-related trafficking adaptors, ARTs) function as adaptors for the ubiquitin ligase Rsp5. They instruct Rsp5 to ubiquitinate subsets of nutrient transporters to orchestrate their endocytosis. The ART proteins are under multilevel control of the major nutrient sensing systems, including amino acid sensing by the general amino acid control and target of rapamycin pathways, and energy sensing by 5'-adenosine-monophosphate-dependent kinase. The function of the six human α-arrestins is comparably under-characterised. Here, we summarise the current knowledge about the function, regulation and substrates of yeast ARTs and human α-arrestins, and highlight emerging communalities and general principles.

Noise buffering by biomolecular condensates in glucose sensing

Many cellular processes involve buffering mechanisms against noise to enhance state stability. Such processes include the cell cycle and the switch between respiration and fermentation. In recent years, protein aggregation/condensation has emerged as an important regulatory mechanism. In this article, we examine the regulation of Std1, an activator of the Snf1/AMPK kinase, by sequestration into foci of liquid drops, and how foci of metabolic signaling and enzymatic proteins are regulated by chaperones, anti-aggregases and by phosphorylation.

Mig1 localization exhibits biphasic behavior which is controlled by both metabolic and regulatory roles of the sugar kinases

Glucose, fructose and mannose are the preferred carbon/energy sources for the yeast Saccharomyces cerevisiae. Absence of preferred energy sources activates glucose derepression, which is regulated by the kinase Snf1. Snf1 phosphorylates the transcriptional repressor Mig1, which results in its exit from the nucleus and subsequent derepression of genes. In contrast, Snf1 is inactive when preferred carbon sources are available, which leads to dephosphorylation of Mig1 and its translocation to the nucleus where Mig1 acts as a transcription repressor. Here we revisit the role of the three hexose kinases, Hxk1, Hxk2 and Glk1, in glucose de/repression. We demonstrate that all three sugar kinases initially affect Mig1 nuclear localization upon addition of glucose, fructose and mannose. This initial import of Mig1 into the nucleus was temporary; for continuous nucleocytoplasmic shuttling of Mig1, Hxk2 is required in the presence of glucose and mannose and in the presence of fructose Hxk2 or Hxk1 is required. Our data suggest that Mig1 import following exposure to preferred energy sources is controlled via two different pathways, where (1) the initial import is regulated by signals derived from metabolism and (2) continuous shuttling is regulated by the Hxk2 and Hxk1 proteins. Mig1 nucleocytoplasmic shuttling appears to be important for the maintenance of the repressed state in which Hxk1/2 seems to play an essential role.

Fine-Tuning of Energy Levels Regulates SUC2 via a SNF1-Dependent Feedback Loop

Nutrient sensing pathways are playing an important role in cellular response to different energy levels. In budding yeast, Saccharomyces cerevisiae, the sucrose non-fermenting protein kinase complex SNF1 is a master regulator of energy homeostasis. It is affected by multiple inputs, among which energy levels is the most prominent. Cells which are exposed to a switch in carbon source availability display a change in the gene expression machinery. It has been shown that the magnitude of the change varies from cell to cell. In a glucose rich environment Snf1/Mig1 pathway represses the expression of its downstream target, such as SUC2. However, upon glucose depletion SNF1 is activated which leads to an increase in SUC2 expression. Our single cell experiments indicate that upon starvation, gene expression pattern of SUC2 shows rapid increase followed by a decrease to initial state with high cell-to-cell variability. The mechanism behind this behavior is currently unknown. In this work we study the long-term behavior of the Snf1/Mig1 pathway upon glucose starvation with a microfluidics and non-linear mixed effect modeling approach. We show a negative feedback mechanism, involving Snf1 and Reg1, which reduces SUC2 expression after the initial strong activation. Snf1 kinase activity plays a key role in this feedback mechanism. Our systems biology approach proposes a negative feedback mechanism that works through the SNF1 complex and is controlled by energy levels. We further show that Reg1 likely is involved in the negative feedback mechanism.

FLO Genes Family and Transcription Factor MIG1 Regulate Saccharomyces cerevisiae Biofilm Formation During Immobilized Fermentation

Saccharomyces cerevisiae immobilization is commonly used for efficient ethanol fuel production in industry due to the relatively higher ethanol stress resistance of S. cerevisiae in biofilms relative to planktonic cells. The mechanisms of biofilm formation and stress resistance, however, remain ambiguous. By analyzing biofilm and planktonic cell transcriptomes, this study observed that MIG1 (encoding a transcription factor) expression in cells increases during the biofilm formation process. To identify the role of MIG1 in yeast biofilm formation and the ethanol resistance of these cells, MIG1 was deleted and complemented in S. cerevisiae 1308. Results showed the MIG1 deletion mutant strain demonstrated weaker biofilm formation ability both on fibers and plastic than the wild-type and these could be restored by expressing MIG1 in deletion mutant. To verify the ability of MIG1 to regulate the expression of FLO genes, which encode adhesions responsible for yeast biofilm formation, FLO gene transcription levels were measured via qRT-PCR. Relative to wild-type S. cerevisiae, the adhesion genes FLO1, 5, and 9 which also demonstrate increased expression in the transcriptome of yeast cells during biofilm formation, but not FLO11, were down-regulated in the MIG1 mutant strain. Additionally, the MIG1 mutant lost a majority of its flocculation ability, which depended on cell-cell adhesions and its slightly invasive growth ability, dependent on cell-substrate adhesion. Deleting FLO1, 5, and 9 decreased biofilm formation on plastics, suggesting these FLO genes contribute to the biofilm formation process alongside FLO11. Moreover, the ethanol tolerance of yeast decreased in the MIG1 deletion mutant as well as the FLO11 deletion mutant, resulting in reduced biofilm formation during fermentation. It remains possible that in the later period of fermentation, when ethanol has accumulated, an over-expression of the FLO1, 5, and 9 genes regulated by MIG1 would enhanced cell-cell adhesions and thus protect cells in the outer layer of biofilms from ethanol, a function primarily dependent on cell-cell adhesions. This work offers a possible explanation for how biofilm formation is regulated during the immobilized fermentation process, and can enhance environmental tolerance in industrial production.

Transcription factors in eukaryotic cells can functionally regulate gene expression by acting in oligomeric assemblies formed from an intrinsically disordered protein phase transition enabled by molecular crowding

High-speed single-molecule fluorescence microscopy in vivo shows that transcription factors in eukaryotes can act in oligomeric clusters mediated by molecular crowding and intrinsically disordered protein. This finding impacts on the longstanding puzzle of how transcription factors find their gene targets so efficiently in the complex, heterogeneous environment of the cell.

Abbreviations CDF - cumulative distribution function; FRAP - fluorescence recovery after photobleaching; GFP - Green fluorescent protein; STORM - stochastic optical reconstruction microscopy; TF - Transcription factor; YFP - Yellow fluorescent protein

The yeast Mig1 transcriptional repressor is dephosphorylated by glucose-dependent and -independent mechanisms

A yeast Saccharomyces cerevisiae Snf1 kinase, an analog of mammalian AMPK, regulates glucose derepression of genes required for utilization of alternative carbon sources through the transcriptional repressor Mig1. It has been suggested that the Glc7-Reg1 phosphatase dephosphorylates Mig1. Here we report that Mig1 is dephosphorylated by Glc7-Reg1 in an apparently glucose-dependent mechanism but also by a mechanism independent of glucose and Glc7-Reg1. In addition to serine/threonine phosphatases another process including tyrosine phosphorylation seems crucial for Mig1 regulation. Taken together, Mig1 dephosphorylation appears to be controlled in a complex manner, in line with the importance for rapid and sensitive regulation upon altered glucose concentrations in the growth medium.

Applying Microfluidic Systems to Study Effects of Glucose at Single-Cell Level

Microfluidic systems in combination with microscopy (e.g., fluorescence) can be a powerful tool to study, at single-cell level, the behavior and morphology of biological cells after uptake of glucose. Here, we briefly discuss the advantages of using microfluidic systems. We further describe how microfluidic systems are fabricated and how they are utilized. Finally, we discuss how the large amount of data can be analyzed in a "semi-automatic" manner using custom-made software. In summary, we provide a guide to how to use microfluidic systems in single-cell studies.

Transcription factor clusters regulate genes in eukaryotic cells

Transcription is regulated through binding factors to gene promoters to activate or repress expression, however, the mechanisms by which factors find targets remain unclear. Using single-molecule fluorescence microscopy, we determined in vivo stoichiometry and spatiotemporal dynamics of a GFP tagged repressor, Mig1, from a paradigm signaling pathway of Saccharomyces cerevisiae. We find the repressor operates in clusters, which upon extracellular signal detection, translocate from the cytoplasm, bind to nuclear targets and turnover. Simulations of Mig1 configuration within a 3D yeast genome model combined with a promoter-specific, fluorescent translation reporter confirmed clusters are the functional unit of gene regulation. In vitro and structural analysis on reconstituted Mig1 suggests that clusters are stabilized by depletion forces between intrinsically disordered sequences. We observed similar clusters of a co-regulatory activator from a different pathway, supporting a generalized cluster model for transcription factors that reduces promoter search times through intersegment transfer while stabilizing gene expression.

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.

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.

Microfluidics and microbial engineering

The combination of microbial engineering and microfluidics is synergistic in nature. For example, microfluidics is benefiting from the outcome of microbial engineering and many reported point-of-care microfluidic devices employ engineered microbes as functional parts for the microsystems. In addition, microbial engineering is facilitated by various microfluidic techniques, due to their inherent strength in high-throughput screening and miniaturization. In this review article, we firstly examine the applications of engineered microbes for toxicity detection, biosensing, and motion generation in microfluidic platforms. Secondly, we look into how microfluidic technologies facilitate the upstream and downstream processes of microbial engineering, including DNA recombination, transformation, target microbe selection, mutant characterization, and microbial function analysis. Thirdly, we highlight an emerging concept in microbial engineering, namely, microbial consortium engineering, where the behavior of a multicultural microbial community rather than that of a single cell/species is delineated. Integrating the disciplines of microfluidics and microbial engineering opens up many new opportunities, for example in diagnostics, engineering of microbial motors, development of portable devices for genetics, high throughput characterization of genetic mutants, isolation and identification of rare/unculturable microbial species, single-cell analysis with high spatio-temporal resolution, and exploration of natural microbial communities.

Sugar and Glycerol Transport in Saccharomyces cerevisiae

In Saccharomyces cerevisiae the process of transport of sugar substrates into the cell comprises a complex network of transporters and interacting regulatory mechanisms. Members of the large family of hexose (HXT) transporters display uptake efficiencies consistent with their environmental expression and play physiological roles in addition to feeding the glycolytic pathway. Multiple glucose-inducing and glucose-independent mechanisms serve to regulate expression of the sugar transporters in yeast assuring that expression levels and transporter activity are coordinated with cellular metabolism and energy needs. The expression of sugar transport activity is modulated by other nutritional and environmental factors that may override glucose-generated signals. Transporter expression and activity is regulated transcriptionally, post-transcriptionally and post-translationally. Recent studies have expanded upon this suite of regulatory mechanisms to include transcriptional expression fine tuning mediated by antisense RNA and prion-based regulation of transcription. Much remains to be learned about cell biology from the continued analysis of this dynamic process of substrate acquisition.

Single-Molecule Narrow-Field Microscopy of Protein-DNA Binding Dynamics in Glucose Signal Transduction of Live Yeast Cells

Single-molecule narrow-field microscopy is a versatile tool to investigate a diverse range of protein dynamics in live cells and has been extensively used in bacteria. Here, we describe how these methods can be extended to larger eukaryotic, yeast cells, which contain subcellular compartments. We describe how to obtain single-molecule microscopy data but also how to analyze these data to track and obtain the stoichiometry of molecular complexes diffusing in the cell. We chose glucose mediated signal transduction of live yeast cells as the system to demonstrate these single-molecule techniques as transcriptional regulation is fundamentally a single-molecule problem-a single repressor protein binding a single binding site in the genome can dramatically alter behavior at the whole cell and population level.

Sucrose and Saccharomyces cerevisiae: a relationship most sweet

Sucrose is an abundant, readily available and inexpensive substrate for industrial biotechnology processes and its use is demonstrated with much success in the production of fuel ethanol in Brazil. Saccharomyces cerevisiae, which naturally evolved to efficiently consume sugars such as sucrose, is one of the most important cell factories due to its robustness, stress tolerance, genetic accessibility, simple nutrient requirements and long history as an industrial workhorse. This minireview is focused on sucrose metabolism in S. cerevisiae, a rather unexplored subject in the scientific literature. An analysis of sucrose availability in nature and yeast sugar metabolism was performed, in order to understand the molecular background that makes S. cerevisiae consume this sugar efficiently. A historical overview on the use of sucrose and S. cerevisiae by humans is also presented considering sugarcane and sugarbeet as the main sources of this carbohydrate. Physiological aspects of sucrose consumption are compared with those concerning other economically relevant sugars. Also, metabolic engineering efforts to alter sucrose catabolism are presented in a chronological manner. In spite of its extensive use in yeast-based industries, a lot of basic and applied research on sucrose metabolism is imperative, mainly in fields such as genetics, physiology and metabolic engineering.

Millisecond single-molecule localization microscopy combined with convolution analysis and automated image segmentation to determine protein concentrations in complexly structured, functional cells, one cell at a time

We present a single-molecule tool called the CoPro (concentration of proteins) method that uses millisecond imaging with convolution analysis, automated image segmentation and super-resolution localization microscopy to generate robust estimates for protein concentration in different compartments of single living cells, validated using realistic simulations of complex multiple compartment cell types. We demonstrate its utility experimentally on model Escherichia coli bacteria and Saccharomyces cerevisiae budding yeast cells, and use it to address the biological question of how signals are transduced in cells. Cells in all domains of life dynamically sense their environment through signal transduction mechanisms, many involving gene regulation. The glucose sensing mechanism of S. cerevisiae is a model system for studying gene regulatory signal transduction. It uses the multi-copy expression inhibitor of the GAL gene family, Mig1, to repress unwanted genes in the presence of elevated extracellular glucose concentrations. We fluorescently labelled Mig1 molecules with green fluorescent protein (GFP) via chromosomal integration at physiological expression levels in living S. cerevisiae cells, in addition to the RNA polymerase protein Nrd1 with the fluorescent protein reporter mCherry. Using CoPro we make quantitative estimates of Mig1 and Nrd1 protein concentrations in the cytoplasm and nucleus compartments on a cell-by-cell basis under physiological conditions. These estimates indicate a ∼4-fold shift towards higher values in the concentration of diffusive Mig1 in the nucleus if the external glucose concentration is raised, whereas equivalent levels in the cytoplasm shift to smaller values with a relative change an order of magnitude smaller. This compares with Nrd1 which is not involved directly in glucose sensing, and which is almost exclusively localized in the nucleus under high and low external glucose levels. CoPro facilitates time-resolved quantification of protein concentrations in single functional cells, and enables the distributions of concentrations across a cell population to be measured. This could be useful in investigating several cellular processes that are mediated by proteins, especially where changes in protein concentration in a single cell in response to changes in the extracellular chemical environment are subtle and rapid and may be smaller than the variability across a cell population.

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.

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.