Metabolic cycle, cell cycle, and the finishing kick to Start

Temporal segregation of biosynthetic processes is responsible for metabolic oscillations during the budding yeast cell cycle

Many cell biological and biochemical mechanisms controlling the fundamental process of eukaryotic cell division have been identified; however, the temporal dynamics of biosynthetic processes during the cell division cycle are still elusive. Here, we show that key biosynthetic processes are temporally segregated along the cell cycle. Using budding yeast as a model and single-cell methods to dynamically measure metabolic activity, we observe two peaks in protein synthesis, in the G1 and S/G2/M phase, whereas lipid and polysaccharide synthesis peaks only once, during the S/G2/M phase. Integrating the inferred biosynthetic rates into a thermodynamic-stoichiometric metabolic model, we find that this temporal segregation in biosynthetic processes causes flux changes in primary metabolism, with an acceleration of glucose-uptake flux in G1 and phase-shifted oscillations of oxygen and carbon dioxide exchanges. Through experimental validation of the model predictions, we demonstrate that primary metabolism oscillates with cell-cycle periodicity to satisfy the changing demands of biosynthetic processes exhibiting unexpected dynamics during the cell cycle.

Using the AKAR3-EV biosensor to assess Sch9p- and PKA-signalling in budding yeast

Budding yeast uses the TORC1-Sch9p and cAMP-PKA signalling pathways to regulate adaptations to changing nutrient environments. Dynamic and single-cell measurements of the activity of these cascades will improve our understanding of the cellular adaptation of yeast. Here, we employed the AKAR3-EV biosensor developed for mammalian cells to measure the cellular phosphorylation status determined by Sch9p and PKA activity in budding yeast. Using various mutant strains and inhibitors, we show that AKAR3-EV measures the Sch9p- and PKA-dependent phosphorylation status in intact yeast cells. At the single-cell level, we found that the phosphorylation responses are homogenous for glucose, sucrose, and fructose, but heterogeneous for mannose. Cells that start to grow after a transition to mannose correspond to higher normalized Förster resonance energy transfer (FRET) levels, in line with the involvement of Sch9p and PKA pathways to stimulate growth-related processes. The Sch9p and PKA pathways have a relatively high affinity for glucose (K0.5 of 0.24 mM) under glucose-derepressed conditions. Lastly, steady-state FRET levels of AKAR3-EV seem to be independent of growth rates, suggesting that Sch9p- and PKA-dependent phosphorylation activities are transient responses to nutrient transitions. We believe that the AKAR3-EV sensor is an excellent addition to the biosensor arsenal for illuminating cellular adaptation in single yeast cells.

Universality of stable multi-cluster periodic solutions in a population model of the cell cycle with negative feedback

We study a population model where cells in one part of the cell cycle may affect the progress of cells in another part. If the influence, or feedback, from one part to another is negative, simulations of the model almost always result in multiple temporal clusters formed by groups of cells. We study regions in parameter space where periodic 'k-cyclic' solutions are stable. The regions of stability coincide with sub-triangles on which certain events occur in a fixed order. For boundary sub-triangles with order 'rs1', we prove that the k-cyclic periodic solution is asymptotically stable if the index of the sub-triangle is relatively prime with respect to the number of clusters k and neutrally stable otherwise. For negative linear feedback, we prove that the interior of the parameter set is covered by stable sub-triangles, i.e. a stable k-cyclic solution always exists for some k. We observe numerically that the result also holds for many forms of nonlinear feedback, but may break down in extreme cases.

Bend or break: how biochemically versatile molecules enable metabolic division of labor in clonal microbial communities

In fluctuating nutrient environments, isogenic microbial cells transition into "multicellular" communities composed of phenotypically heterogeneous cells, showing functional specialization. In fungi (such as budding yeast), phenotypic heterogeneity is often described in the context of cells switching between different morphotypes (e.g., yeast to hyphae/pseudohyphae or white/opaque transitions in Candida albicans). However, more fundamental forms of metabolic heterogeneity are seen in clonal Saccharomyces cerevisiae communities growing in nutrient-limited conditions. Cells within such communities exhibit contrasting, specialized metabolic states, and are arranged in distinct, spatially organized groups. In this study, we explain how such an organization can stem from self-organizing biochemical reactions that depend on special metabolites. These metabolites exhibit plasticity in function, wherein the same metabolites are metabolized and utilized for distinct purposes by different cells. This in turn allows cell groups to function as specialized, interdependent cross-feeding systems which support distinct metabolic processes. Exemplifying a system where cells exhibit either gluconeogenic or glycolytic states, we highlight how available metabolites can drive favored biochemical pathways to produce new, limiting resources. These new resources can themselves be consumed or utilized distinctly by cells in different metabolic states. This thereby enables cell groups to sustain contrasting, even apparently impossible metabolic states with stable transcriptional and metabolic signatures for a given environment, and divide labor in order to increase community fitness or survival. We speculate on possible evolutionary implications of such metabolic specialization and division of labor in isogenic microbial communities.

Evolution of opposing regulatory interactions underlies the emergence of eukaryotic cell cycle checkpoints

In eukaryotes the entry into mitosis is initiated by activation of cyclin-dependent kinases (CDKs), which in turn activate a large number of protein kinases to induce all mitotic processes. The general view is that kinases are active in mitosis and phosphatases turn them off in interphase. Kinases activate each other by cross- and self-phosphorylation, while phosphatases remove these phosphate groups to inactivate kinases. Crucial exceptions to this general rule are the interphase kinase Wee1 and the mitotic phosphatase Cdc25. Together they directly control CDK in an opposite way of the general rule of mitotic phosphorylation and interphase dephosphorylation. Here we investigate why this opposite system emerged and got fixed in almost all eukaryotes. Our results show that this reversed action of a kinase-phosphatase pair, Wee1 and Cdc25, on CDK is particularly suited to establish a stable G2 phase and to add checkpoints to the cell cycle. We show that all these regulators appeared together in LECA (Last Eukaryote Common Ancestor) and co-evolved in eukaryotes, suggesting that this twist in kinase-phosphatase regulation was a crucial step happening at the emergence of eukaryotes.

Differential scaling between G1 protein production and cell size dynamics promotes commitment to the cell division cycle in budding yeast

In the unicellular eukaryote Saccharomyces cerevisiae, Cln3-cyclin-dependent kinase activity enables Start, the irreversible commitment to the cell division cycle. However, the concentration of Cln3 has been paradoxically considered to remain constant during G1, due to the presumed scaling of its production rate with cell size dynamics. Measuring metabolic and biosynthetic activity during cell cycle progression in single cells, we found that cells exhibit pulses in their protein production rate. Rather than scaling with cell size dynamics, these pulses follow the intrinsic metabolic dynamics, peaking around Start. Using a viral-based bicistronic construct and targeted proteomics to measure Cln3 at the single-cell and population levels, we show that the differential scaling between protein production and cell size leads to a temporal increase in Cln3 concentration, and passage through Start. This differential scaling causes Start in both daughter and mother cells across growth conditions. Thus, uncoupling between two fundamental physiological parameters drives cell cycle commitment.

Metabolic rhythms: A framework for coordinating cellular function

Circadian clocks are widespread among eukaryotes and generally involve feedback loops coupled with metabolic processes and redox balance. The organising power of these oscillations has not only allowed organisms to anticipate day-night cycles, but also acts to temporally compartmentalise otherwise incompatible processes, enhance metabolic efficiency, make the system more robust to noise and propagate signals among cells. While daily rhythms and the function of the circadian transcription-translation loop have been the subject of extensive research over the past four decades, cycles of shorter period and respiratory oscillations, with which they are intertwined, have received less attention. Here, we describe features of yeast respiratory oscillations, which share many features with daily and 12 hr cellular oscillations in animal cells. This relatively simple system enables the analysis of dynamic rhythmic changes in metabolism, independent of cellular oscillations that are a product of the circadian transcription-translation feedback loop. Knowledge gained from studying ultradian oscillations in yeast will lead to a better understanding of the basic mechanistic principles and evolutionary origins of oscillatory behaviour among eukaryotes.

Instability of the steady state solution in cell cycle population structure models with feedback

We show that when cell-cell feedback is added to a model of the cell cycle for a large population of cells, then instability of the steady state solution occurs in many cases. We show this in the context of a generic agent-based ODE model. If the feedback is positive, then instability of the steady state solution is proved for all parameter values except for a small set on the boundary of parameter space. For negative feedback we prove instability for half the parameter space. We also show by example that instability in the other half may be proved on a case by case basis.

A minimal "push-pull" bistability model explains oscillations between quiescent and proliferative cell states

A minimal model for oscillating between quiescent and growth/proliferation states, dependent on the availability of a central metabolic resource, is presented. From the yeast metabolic cycles, metabolic oscillations in oxygen consumption are represented as transitions between quiescent and growth states. We consider metabolic resource availability, growth rates, and switching rates (between states) to model a relaxation oscillator explaining transitions between these states. This frustrated bistability model reveals a required communication between the metabolic resource that determines oscillations and the quiescent and growth state cells. Cells in each state reflect memory, or hysteresis of their current state, and “push–pull” cells from the other state. Finally, a parsimonious argument is made for a specific central metabolite as the controller of switching between quiescence and growth states. We discuss how an oscillator built around the availability of such a metabolic resource is sufficient to generally regulate oscillations between growth and quiescence through committed transitions.

Cyclin-Dependent Kinase Co-Ordinates Carbohydrate Metabolism and Cell Cycle in S. cerevisiae

Cyclin-dependent kinases (CDKs) control cell division in eukaryotes by phosphorylating proteins involved in division. But successful proliferation requires co-ordination between division and cellular growth in mass. Previous proteomic studies suggested that metabolic proteins, as well as cell division proteins, could potentially be substrates of cyclin-dependent kinases. Here we focus on two metabolic enzymes of the yeast S. cerevisiae, neutral trehalase (Nth1) and glycogen phosphorylase (Gph1), and show that their activities are likely directly controlled by CDK activity, thus allowing co-ordinate regulation of carbohydrate metabolism with cell division processes. In this case, co-ordinate regulation may optimize the decision to undertake a final cell division as nutrients are being exhausted. Co-regulation of cell division processes and metabolic processes by CDK activity may be a general phenomenon important for co-ordinating the cell cycle with growth.

The Yeast Cyclin-Dependent Kinase Routes Carbon Fluxes to Fuel Cell Cycle Progression

Cell division entails a sequence of processes whose specific demands for biosynthetic precursors and energy place dynamic requirements on metabolism. However, little is known about how metabolic fluxes are coordinated with the cell division cycle. Here, we examine budding yeast to show that more than half of all measured metabolites change significantly through the cell division cycle. Cell cycle-dependent changes in central carbon metabolism are controlled by the cyclin-dependent kinase (Cdk1), a major cell cycle regulator, and the metabolic regulator protein kinase A. At the G1/S transition, Cdk1 phosphorylates and activates the enzyme Nth1, which funnels the storage carbohydrate trehalose into central carbon metabolism. Trehalose utilization fuels anabolic processes required to reliably complete cell division. Thus, the cell cycle entrains carbon metabolism to fuel biosynthesis. Because the oscillation of Cdk activity is a conserved feature of the eukaryotic cell cycle, we anticipate its frequent use in dynamically regulating metabolism for efficient proliferation.

Taking chances and making mistakes: non-genetic phenotypic heterogeneity and its consequences for surviving in dynamic environments

Natural selection has shaped the strategies for survival and growth of microorganisms. The success of microorganisms depends not only on slow evolutionary tuning but also on the ability to adapt to unpredictable changes in their environment. In principle, adaptive strategies range from purely deterministic mechanisms to those that exploit the randomness intrinsic to many cellular and molecular processes. Depending on the environment and selective pressures, particular strategies can lie somewhere along this continuum. In recent years, non-genetic cell-to-cell differences have received a lot of attention, not least because of their potential impact on the ability of microbial populations to survive in dynamic environments. Using several examples, we describe the origins of spontaneous and induced mechanisms of phenotypic adaptation. We identify some of the commonalities of these examples and consider the potential role of chance and constraints in microbial phenotypic adaptation.

The molecular basis of metabolic cycles and their relationship to circadian rhythms

Metabolic cycles result from the partitioning of oxidative and reductive metabolism into rhythmic phases of gene expression and oscillating post-translational protein modifications. Relatively little is known about how these switches in gene expression are controlled, although recent studies have suggested that transcription itself may play a central role. This review explores the molecular basis of the metabolic and gene-expression oscillations in the yeast Saccharomyces cerevisiae, as well as how they relate to other biological time-keeping mechanisms, such as circadian rhythms.

Exploring potential biomarkers and determining the metabolic mechanism of type 2 diabetes mellitus using liquid chromatography coupled to high-resolution mass spectrometry

Diabetes mellitus has imposed a huge burden on modern society and is a serious threat to human health globally.

Autonomous Metabolic Oscillations Robustly Gate the Early and Late Cell Cycle

Eukaryotic cell division is known to be controlled by the cyclin/cyclin dependent kinase (CDK) machinery. However, eukaryotes have evolved prior to CDKs, and cells can divide in the absence of major cyclin/CDK components. We hypothesized that an autonomous metabolic oscillator provides dynamic triggers for cell-cycle initiation and progression. Using microfluidics, cell-cycle reporters, and single-cell metabolite measurements, we found that metabolism of budding yeast is a CDK-independent oscillator that oscillates across different growth conditions, both in synchrony with and also in the absence of the cell cycle. Using environmental perturbations and dynamic single-protein depletion experiments, we found that the metabolic oscillator and the cell cycle form a system of coupled oscillators, with the metabolic oscillator separately gating and maintaining synchrony with the early and late cell cycle. Establishing metabolism as a dynamic component within the cell-cycle network opens new avenues for cell-cycle research and therapeutic interventions for proliferative disorders.

13C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids

Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined ¹³C labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genome-wide acetyl-CoA balance study showed ATP citrate lyase from Yarrowia lipolytica as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for downregulation in terms of acetyl-CoA consumption. These genetic modifications were applied to S. cerevisiae WRY2, a strain that is capable of producing 460 mg/L of free fatty acids. With the addition of ATP citrate lyase and downregulation of malate synthase, the engineered strain produced 26% more free fatty acids. Further increases in free fatty acid production of 33% were obtained by knocking out the cytoplasmic glycerol-3-phosphate dehydrogenase, which flux analysis had shown was competing for carbon flux upstream with the carbon flux through the acetyl-CoA production pathway in the cytoplasm. In total, the genetic interventions applied in this work increased fatty acid production by ~70%.

The Malleable Nature of the Budding Yeast Nuclear Envelope: Flares, Fusion, and Fenestrations

In eukaryotes, the nuclear envelope (NE) physically separates nuclear components and activities from rest of the cell. The NE also provides rigidity to the nucleus and contributes to chromosome organization. At the same time, the NE is highly dynamic; it must change shape and rearrange its components during development and throughout the cell cycle, and its morphology can be altered in response to mutation and disease. Here we focus on the NE of budding yeast, Saccharomyces cerevisiae, which has several unique features: it remains intact throughout the cell cycle, expands symmetrically during interphase, elongates during mitosis and, expands asymmetrically during mitotic delay. Moreover, its NE is safely breached during mating and when large structures, such as nuclear pore complexes and the spindle pole body, are embedded into its double membrane. The budding yeast NE lacks lamins and yet the nucleus is capable of maintaining a spherical shape throughout interphase. Despite these eccentricities, studies of the budding yeast NE have uncovered interesting, and likely conserved, processes that contribute to NE dynamics. In particular, we discuss the processes that drive and enable NE expansion and the dramatic changes in the NE that lead to extensions and fenestrations. J. Cell. Physiol. 231: 2353-2360, 2016. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Stratification of yeast cells during chronological aging by size points to the role of trehalose in cell vitality

Cells of the budding yeast Saccharomyces cerevisiae undergo a process akin to differentiation during prolonged culture without medium replenishment. Various methods have been used to separate and determine the potential role and fate of the different cell species. We have stratified chronologically-aged yeast cultures into cells of different sizes, using centrifugal elutriation, and characterized these subpopulations physiologically. We distinguish two extreme cell types, very small (XS) and very large (L) cells. L cells display higher viability based on two separate criteria. They respire much more actively, but produce lower levels of reactive oxygen species (ROS). L cells are capable of dividing, albeit slowly, giving rise to XS cells which do not divide. L cells are more resistant to osmotic stress and they have higher trehalose content, a storage carbohydrate often connected to stress resistance. Depletion of trehalose by deletion of TPS2 does not affect the vital characteristics of L cells, but it improves some of these characteristics in XS cells. Therefore, we propose that the response of L and XS cells to the trehalose produced in the former differs in a way that lowers the vitality of the latter. We compare our XS- and L-fraction cell characteristics with those of cells isolated from stationary cultures by others based on density. This comparison suggests that the cells have some similarities but also differences that may prove useful in addressing whether it is the segregation or the response to trehalose that may play the predominant role in cell division from stationary culture.

Cell cycle Start is coupled to entry into the yeast metabolic cycle across diverse strains and growth rates

Cells have evolved oscillators with different frequencies to coordinate periodic processes. Here we studied the interaction of two oscillators, the cell division cycle (CDC) and the yeast metabolic cycle (YMC), in budding yeast. Previous work suggested that the CDC and YMC interact to separate high oxygen consumption (HOC) from DNA replication to prevent genetic damage. To test this hypothesis, we grew diverse strains in chemostat and measured DNA replication and oxygen consumption with high temporal resolution at different growth rates. Our data showed that HOC is not strictly separated from DNA replication; rather, cell cycle Start is coupled with the initiation of HOC and catabolism of storage carbohydrates. The logic of this YMC-CDC coupling may be to ensure that DNA replication and cell division occur only when sufficient cellular energy reserves have accumulated. Our results also uncovered a quantitative relationship between CDC period and YMC period across different strains. More generally, our approach shows how studies in genetically diverse strains efficiently identify robust phenotypes and steer the experimentalist away from strain-specific idiosyncrasies.

The Yeast GSK-3 Homologue Mck1 Is a Key Controller of Quiescence Entry and Chronological Lifespan

Upon starvation for glucose or any other core nutrient, yeast cells exit from the mitotic cell cycle and acquire a set of G0-specific characteristics to ensure long-term survival. It is not well understood whether or how cell cycle progression is coordinated with the acquisition of different G0-related features during the transition to stationary phase (SP). Here, we identify the yeast GSK-3 homologue Mck1 as a key regulator of G0 entry and reveal that Mck1 acts in parallel to Rim15 to activate starvation-induced gene expression, the acquisition of stress resistance, the accumulation of storage carbohydrates, the ability of early SP cells to exit from quiescence, and their chronological lifespan. FACS and microscopy imaging analyses indicate that Mck1 promotes mother-daughter cell separation and together with Rim15, modulates cell size. This indicates that the two kinases coordinate the transition-phase cell cycle, cell size and the acquisition of different G0-specific features. Epistasis experiments place MCK1, like RIM15, downstream of RAS2 in antagonising cell growth and activating stress resistance and glycogen accumulation. Remarkably, in the ras2∆ cells, deletion of MCK1 and RIM15 together, compared to removal of either of them alone, compromises respiratory growth and enhances heat tolerance and glycogen accumulation. Our data indicate that the nutrient sensor Ras2 may prevent the acquisition of G0-specific features via at least two pathways. One involves the negative regulation of the effectors of G0 entry such as Mck1 and Rim15, while the other likely to involve its functions in promoting respiratory growth, a phenotype also contributed by Mck1 and Rim15.

Bud-Localization of CLB2 mRNA Can Constitute a Growth Rate Dependent Daughter Sizer

Maintenance of cellular size is a fundamental systems level process that requires balancing of cell growth with proliferation. This is achieved via the cell division cycle, which is driven by the sequential accumulation and destruction of cyclins. The regulatory network around these cyclins, particularly in G1, has been interpreted as a size control network in budding yeast, and cell size as being decisive for the START transition. However, it is not clear why disruptions in the G1 network may lead to altered size rather than loss of size control, or why the S-G2-M duration also depends on nutrients. With a mathematical population model comprised of individually growing cells, we show that cyclin translation would suffice to explain the observed growth rate dependence of cell volume at START. Moreover, we assess the impact of the observed bud-localisation of the G2 cyclin CLB2 mRNA, and find that localised cyclin translation could provide an efficient mechanism for measuring the biosynthetic capacity in specific compartments: The mother in G1, and the growing bud in G2. Hence, iteration of the same principle can ensure that the mother cell is strong enough to grow a bud, and that the bud is strong enough for independent life. Cell sizes emerge in the model, which predicts that a single CDK-cyclin pair per growth phase suffices for size control in budding yeast, despite the necessity of the cell cycle network around the cyclins to integrate other cues. Size control seems to be exerted twice, where the G2/M control affects bud size through bud-localized translation of CLB2 mRNA, explaining the dependence of the S-G2-M duration on nutrients. Taken together, our findings suggest that cell size is an emergent rather than a regulatory property of the network linking growth and proliferation.

Topology and control of the cell-cycle-regulated transcriptional circuitry

Nearly 20% of the budding yeast genome is transcribed periodically during the cell division cycle. The precise temporal execution of this large transcriptional program is controlled by a large interacting network of transcriptional regulators, kinases, and ubiquitin ligases. Historically, this network has been viewed as a collection of four coregulated gene clusters that are associated with each phase of the cell cycle. Although the broad outlines of these gene clusters were described nearly 20 years ago, new technologies have enabled major advances in our understanding of the genes comprising those clusters, their regulation, and the complex regulatory interplay between clusters. More recently, advances are being made in understanding the roles of chromatin in the control of the transcriptional program. We are also beginning to discover important regulatory interactions between the cell-cycle transcriptional program and other cell-cycle regulatory mechanisms such as checkpoints and metabolic networks. Here we review recent advances and contemporary models of the transcriptional network and consider these models in the context of eukaryotic cell-cycle controls.

Physiological and transcriptional responses of anaerobic chemostat cultures of Saccharomyces cerevisiae subjected to diurnal temperature cycles

Diurnal temperature cycling is an intrinsic characteristic of many exposed microbial ecosystems. However, its influence on yeast physiology and the yeast transcriptome has not been studied in detail. In this study, 24-h sinusoidal temperature cycles, oscillating between 12°C and 30°C, were imposed on anaerobic, glucose-limited chemostat cultures of Saccharomyces cerevisiae. After three diurnal temperature cycles (DTC), concentrations of glucose and extracellular metabolites as well as CO2 production rates showed regular, reproducible circadian rhythms. DTC also led to waves of transcriptional activation and repression, which involved one-sixth of the yeast genome. A substantial fraction of these DTC-responsive genes appeared to respond primarily to changes in the glucose concentration. Elimination of known glucose-responsive genes revealed an overrepresentation of previously identified temperature-responsive genes as well as genes involved in the cell cycle and de novo purine biosynthesis. In-depth analysis demonstrated that DTC led to a partial synchronization of the cell cycle of the yeast populations in chemostat cultures, which was lost upon release from DTC. Comparison of DTC results with data from steady-state cultures showed that the 24-h DTC was sufficiently slow to allow S. cerevisiae chemostat cultures to acclimate their transcriptome and physiology at the DTC temperature maximum and to approach acclimation at the DTC temperature minimum. Furthermore, this comparison and literature data on growth rate-dependent cell cycle phase distribution indicated that cell cycle synchronization was most likely an effect of imposed fluctuations of the relative growth rate (μ/μmax) rather than a direct effect of temperature.

Uncovering by atomic force microscopy of an original circular structure at the yeast cell surface in response to heat shock

BACKGROUND

Atomic Force Microscopy (AFM) is a polyvalent tool that allows biological and mechanical studies of full living microorganisms, and therefore the comprehension of molecular mechanisms at the nanoscale level. By combining AFM with genetical and biochemical methods, we explored the biophysical response of the yeast Saccharomyces cerevisiae to a temperature stress from 30°C to 42°C during 1 h.

RESULTS

We report for the first time the formation of an unprecedented circular structure at the cell surface that takes its origin at a single punctuate source and propagates in a concentric manner to reach a diameter of 2-3 μm at least, thus significantly greater than a bud scar. Concomitantly, the cell wall stiffness determined by the Young's Modulus of heat stressed cells increased two fold with a concurrent increase of chitin. This heat-induced circular structure was not found either in wsc1Δ or bck1Δ mutants that are defective in the CWI signaling pathway, nor in chs1Δ, chs3Δ and bni1Δ mutant cells, reported to be deficient in the proper budding process. It was also abolished in the presence of latrunculin A, a toxin known to destabilize actin cytoskeleton.

CONCLUSIONS

Our results suggest that this singular morphological event occurring at the cell surface is due to a dysfunction in the budding machinery caused by the heat shock and that this phenomenon is under the control of the CWI pathway.

Acetyl-CoA induces transcription of the key G1 cyclin CLN3 to promote entry into the cell division cycle in Saccharomyces cerevisiae

In budding yeast cells, nutrient repletion induces rapid exit from quiescence and entry into a round of growth and division. The G1 cyclin CLN3 is one of the earliest genes activated in response to nutrient repletion. Subsequent to its activation, hundreds of cell-cycle genes can then be expressed, including the cyclins CLN1/2 and CLB5/6. Although much is known regarding how CLN3 functions to activate downstream targets, the mechanism through which nutrients activate CLN3 transcription in the first place remains poorly understood. Here we show that a central metabolite of glucose catabolism, acetyl-CoA, induces CLN3 transcription by promoting the acetylation of histones present in its regulatory region. Increased rates of acetyl-CoA synthesis enable the Gcn5p-containing Spt-Ada-Gcn5-acetyltransferase transcriptional coactivator complex to catalyze histone acetylation at the CLN3 locus alongside ribosomal and other growth genes to promote entry into the cell division cycle.

Driving the cell cycle through metabolism

For unicellular organisms, the decision to enter the cell cycle can be viewed most fundamentally as a metabolic problem. A cell must assess its nutritional and metabolic status to ensure it can synthesize sufficient biomass to produce a new daughter cell. The cell must then direct the appropriate metabolic outputs to ensure completion of the division process. Herein, we discuss the changes in metabolism that accompany entry to, and exit from, the cell cycle for the unicellular eukaryote Saccharomyces cerevisiae. Studies of budding yeast under continuous, slow-growth conditions have provided insights into the essence of these metabolic changes at unprecedented temporal resolution. Some of these mechanisms by which cell growth and proliferation are coordinated with metabolism are likely to be conserved in multicellular organisms. An improved understanding of the metabolic basis of cell cycle control promises to reveal fundamental principles governing tumorigenesis, metazoan development, niche expansion, and many additional aspects of cell and organismal growth control.

Cell size control in yeast

Cell size is an important adaptive trait that influences nearly all aspects of cellular physiology. Despite extensive characterization of the cell-cycle regulatory network, the molecular mechanisms coupling cell growth to division, and thereby controlling cell size, have remained elusive. Recent work in yeast has reinvigorated the size control field and suggested provocative mechanisms for the distinct functions of setting and sensing cell size. Further examination of size-sensing models based on spatial gradients and molecular titration, coupled with elucidation of the pathways responsible for nutrient-modulated target size, may reveal the fundamental principles of eukaryotic cell size control.

Clustering in cell cycle dynamics with general response/signaling feedback

Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call responsive/signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behavior of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as "uniform" solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments.

Coupling among growth rate response, metabolic cycle, and cell division cycle in yeast

We discovered that the relative durations of the phases of the yeast metabolic cycle change with the growth rate. These changes can explain mechanistically the transcriptional growth-rate responses of all yeast genes (25% of the genome) that we find to be the same across all studied nutrient limitations in either ethanol or glucose media.

We studied the steady-state responses to changes in growth rate of yeast when ethanol is the sole source of carbon and energy. Analysis of these data, together with data from studies where glucose was the carbon source, allowed us to distinguish a “universal” growth rate response (GRR) common to all media studied from a GRR specific to the carbon source. Genes with positive universal GRR include ribosomal, translation, and mitochondrial genes, and those with negative GRR include autophagy, vacuolar, and stress response genes. The carbon source–specific GRR genes control mitochondrial function, peroxisomes, and synthesis of vitamins and cofactors, suggesting this response may reflect the intensity of oxidative metabolism. All genes with universal GRR, which comprise 25% of the genome, are expressed periodically in the yeast metabolic cycle (YMC). We propose that the universal GRR may be accounted for by changes in the relative durations of the YMC phases. This idea is supported by oxygen consumption data from metabolically synchronized cultures with doubling times ranging from 5 to 14 h. We found that the high oxygen consumption phase of the YMC can coincide exactly with the S phase of the cell division cycle, suggesting that oxidative metabolism and DNA replication are not incompatible.

The proteomics of quiescent and nonquiescent cell differentiation in yeast stationary-phase cultures

As yeast cultures enter stationary phase in rich, glucose-based medium, differentiation of two major subpopulations of cells, termed quiescent and nonquiescent, is observed. Differences in mRNA abundance between exponentially growing and stationary-phase cultures and quiescent and nonquiescent cells are known, but little was known about protein abundance in these cells. To measure protein abundance in exponential and stationary-phase cultures, the yeast GFP-fusion library (4159 strains) was examined during exponential and stationary phases, using high-throughput flow cytometry (HyperCyt). Approximately 5% of proteins in the library showed twofold or greater changes in median fluorescence intensity (abundance) between the two conditions. We examined 38 strains exhibiting two distinct fluorescence-intensity peaks in stationary phase and determined that the two fluorescence peaks distinguished quiescent and nonquiescent cells, the two major subpopulations of cells in stationary-phase cultures. GFP-fusion proteins in this group were more abundant in quiescent cells, and half were involved in mitochondrial function, consistent with the sixfold increase in respiration observed in quiescent cells and the relative absence of Cit1p:GFP in nonquiescent cells. Finally, examination of quiescent cell-specific GFP-fusion proteins revealed symmetry in protein accumulation in dividing quiescent and nonquiescent cells after glucose exhaustion, leading to a new model for the differentiation of these cells.

Systems approaches for the study of metabolic cycles in yeast

Over four decades ago, the first oscillations in metabolism in yeast cells were reported. Since then, multiple forms of oscillatory behavior have been observed in yeast grown under a variety of continuous culturing environments. The remarkable synchrony of cells undergoing such oscillations has made them ideal subjects for investigation using systems-based approaches. Herein, we briefly summarize previous work on the characterization of such oscillations using systems approaches, and present the long-period, Yeast Metabolic Cycle as an excellent model system for deciphering the temporal organization of fundamental cellular and metabolic processes at unprecedented resolution.

Quantitative analysis of cellular metabolic dissipative, self-organized structures

One of the most important goals of the postgenomic era is understanding the metabolic dynamic processes and the functional structures generated by them. Extensive studies during the last three decades have shown that the dissipative self-organization of the functional enzymatic associations, the catalytic reactions produced during the metabolite channeling, the microcompartmentalization of these metabolic processes and the emergence of dissipative networks are the fundamental elements of the dynamical organization of cell metabolism. Here we present an overview of how mathematical models can be used to address the properties of dissipative metabolic structures at different organizational levels, both for individual enzymatic associations and for enzymatic networks. Recent analyses performed with dissipative metabolic networks have shown that unicellular organisms display a singular global enzymatic structure common to all living cellular organisms, which seems to be an intrinsic property of the functional metabolism as a whole. Mathematical models firmly based on experiments and their corresponding computational approaches are needed to fully grasp the molecular mechanisms of metabolic dynamical processes. They are necessary to enable the quantitative and qualitative analysis of the cellular catalytic reactions and also to help comprehend the conditions under which the structural dynamical phenomena and biological rhythms arise. Understanding the molecular mechanisms responsible for the metabolic dissipative structures is crucial for unraveling the dynamics of cellular life.

ODE, RDE and SDE models of cell cycle dynamics and clustering in yeast

Biologists have long observed periodic-like oxygen consumption oscillations in yeast populations under certain conditions, and several unsatisfactory explanations for this phenomenon have been proposed. These ‘autonomous oscillations’ have often appeared with periods that are nearly integer divisors of the calculated doubling time of the culture. We hypothesize that these oscillations could be caused by a form of cell cycle synchronization that we call clustering. We develop some novel ordinary differential equation models of the cell cycle. For these models, and for random and stochastic perturbations, we give both rigorous proofs and simulations showing that both positive and negative growth rate feedback within the cell cycle are possible agents that can cause clustering of populations within the cell cycle. It occurs for a variety of models and for a broad selection of parameter values. These results suggest that the clustering phenomenon is robust and is likely to be observed in nature. Since there are necessarily an integer number of clusters, clustering would lead to periodic-like behaviour with periods that are nearly integer divisors of the period of the cell cycle. Related experiments have shown conclusively that cell cycle clustering occurs in some oscillating yeast cultures.

Reverse engineering dynamic temporal models of biological processes and their relationships

Biological processes such as circadian rhythms, cell division, metabolism, and development occur as ordered sequences of events. The synchronization of these coordinated events is essential for proper cell function, and hence the determination of critical time points in biological processes is an important component of all biological investigations. In particular, such critical time points establish logical ordering constraints on subprocesses, impose prerequisites on temporal regulation and spatial compartmentalization, and situate dynamic reorganization of functional elements in preparation for subsequent stages. Thus, building temporal phenomenological representations of biological processes from genome-wide datasets is relevant in formulating biological hypotheses on: how processes are mechanistically regulated; how the regulations vary on an evolutionary scale, and how their inadvertent disregulation leads to a diseased state or fatality. This paper presents a general framework (GOALIE) to reconstruct temporal models of cellular processes from time-course gene expression data. We mathematically formulate the problem as one of optimally segmenting datasets into a succession of "informative" windows such that time points within a window expose concerted clusters of gene action whereas time points straddling window boundaries constitute points of significant restructuring. We illustrate here how GOALIE successfully brings out the interplay between multiple yeast processes, inferred from combined experimental datasets for the cell cycle and the metabolic cycle.

Trehalose is a key determinant of the quiescent metabolic state that fuels cell cycle progression upon return to growth

The disaccharide trehalose accumulates as yeast cells enter quiescence. Glucose equivalents in the form of trehalose and glycogen lead to an increase in the apparent density of the cell. Upon exit from quiescence, trehalose stores are initially metabolized in preference over other energy sources to help drive cell cycle progression.

When conditions are unfavorable, virtually all living cells have the capability of entering a resting state termed quiescence or G0. Many aspects of the quiescence program as well as the mechanisms governing the entry and exit from quiescence remain poorly understood. Previous studies using the budding yeast Saccharomyces cerevisiae have shown that upon entry into stationary phase, a quiescent cell population emerges that is heavier in density than nonquiescent cells. Here, we show that total intracellular trehalose and glycogen content exhibits substantial correlation with the density of individual cells both in stationary phase batch cultures and during continuous growth. During prolonged quiescence, trehalose stores are often maintained in favor over glycogen, perhaps to fulfill its numerous stress-protectant functions. Immediately upon exit from quiescence, cells preferentially metabolize trehalose over other fuel sources. Moreover, cells lacking trehalose initiate growth more slowly and frequently exhibit poor survivability. Together, our results support the view that trehalose, which is more stable than other carbohydrates, provides an enduring source of energy that helps drive cell cycle progression upon return to growth.

Metabolic cycling in single yeast cells from unsynchronized steady-state populations limited on glucose or phosphate

Oscillations in patterns of expression of a large fraction of yeast genes are associated with the "metabolic cycle," usually seen only in prestarved, continuous cultures of yeast. We used FISH of mRNA in individual cells to test the hypothesis that these oscillations happen in single cells drawn from unsynchronized cultures growing exponentially in chemostats. Gene-expression data from synchronized cultures were used to predict coincident appearance of mRNAs from pairs of genes in the unsynchronized cells. Quantitative analysis of the FISH results shows that individual unsynchronized cells growing slowly because of glucose limitation or phosphate limitation show the predicted oscillations. We conclude that the yeast metabolic cycle is an intrinsic property of yeast metabolism and does not depend on either synchronization or external limitation of growth by the carbon source.

Global self-regulation of the cellular metabolic structure

BACKGROUND

Different studies have shown that cellular enzymatic activities are able to self-organize spontaneously, forming a metabolic core of reactive processes that remain active under different growth conditions while the rest of the molecular catalytic reactions exhibit structural plasticity. This global cellular metabolic structure appears to be an intrinsic characteristic common to all cellular organisms. Recent work performed with dissipative metabolic networks has shown that the fundamental element for the spontaneous emergence of this global self-organized enzymatic structure could be the number of catalytic elements in the metabolic networks.

METHODOLOGY/PRINCIPAL FINDINGS

In order to investigate the factors that may affect the catalytic dynamics under a global metabolic structure characterized by the presence of metabolic cores we have studied different transitions in catalytic patterns belonging to a dissipative metabolic network. The data were analyzed using non-linear dynamics tools: power spectra, reconstructed attractors, long-term correlations, maximum Lyapunov exponent and Approximate Entropy; and we have found the emergence of self-regulation phenomena during the transitions in the metabolic activities.

CONCLUSIONS/SIGNIFICANCE

The analysis has also shown that the chaotic numerical series analyzed correspond to the fractional Brownian motion and they exhibit long-term correlations and low Approximate Entropy indicating a high level of predictability and information during the self-regulation of the metabolic transitions. The results illustrate some aspects of the mechanisms behind the emergence of the metabolic self-regulation processes, which may constitute an important property of the global structure of the cellular metabolism.

Growth-limiting intracellular metabolites in yeast growing under diverse nutrient limitations

Microbes tailor their growth rate to nutrient availability. Here, we measured, using liquid chromatography-mass spectrometry, >100 intracellular metabolites in steady-state cultures of Saccharomyces cerevisiae growing at five different rates and in each of five different limiting nutrients. In contrast to gene transcripts, where approximately 25% correlated with growth rate irrespective of the nature of the limiting nutrient, metabolite concentrations were highly sensitive to the limiting nutrient's identity. Nitrogen (ammonium) and carbon (glucose) limitation were characterized by low intracellular amino acid and high nucleotide levels, whereas phosphorus (phosphate) limitation resulted in the converse. Low adenylate energy charge was found selectively in phosphorus limitation, suggesting the energy charge may actually measure phosphorus availability. Particularly strong concentration responses occurred in metabolites closely linked to the limiting nutrient, e.g., glutamine in nitrogen limitation, ATP in phosphorus limitation, and pyruvate in carbon limitation. A simple but physically realistic model involving the availability of these metabolites was adequate to account for cellular growth rate. The complete data can be accessed at the interactive website http://growthrate.princeton.edu/metabolome.

The number of catalytic elements is crucial for the emergence of metabolic cores

Background

Different studies show evidence that several unicellular organisms display a cellular metabolic structure characterized by a set of enzymes which are always in an active state (metabolic core), while the rest of the molecular catalytic reactions exhibit on-off changing states. This self-organized enzymatic configuration seems to be an intrinsic characteristic of metabolism, common to all living cellular organisms. In a recent analysis performed with dissipative metabolic networks (DMNs) we have shown that this global functional structure emerges in metabolic networks with a relatively high number of catalytic elements, under particular conditions of enzymatic covalent regulatory activity.

Methodology/Principal Findings

Here, to investigate the mechanism behind the emergence of this supramolecular organization of enzymes, we have performed extensive DMNs simulations (around 15,210,000 networks) taking into account the proportion of the allosterically regulated enzymes and covalent enzymes present in the networks, the variation in the number of substrate fluxes and regulatory signals per catalytic element, as well as the random selection of the catalytic elements that receive substrate fluxes from the exterior. The numerical approximations obtained show that the percentages of DMNs with metabolic cores grow with the number of catalytic elements, converging to 100% for all cases.

Conclusions/Significance

The results show evidence that the fundamental factor for the spontaneous emergence of this global self-organized enzymatic structure is the number of catalytic elements in the metabolic networks. Our analysis corroborates and expands on our previous studies illustrating a crucial property of the global structure of the cellular metabolism. These results also offer important insights into the mechanisms which ensure the robustness and stability of living cells.

Identity of the growth-limiting nutrient strongly affects storage carbohydrate accumulation in anaerobic chemostat cultures of Saccharomyces cerevisiae

Accumulation of glycogen and trehalose in nutrient-limited cultures of Saccharomyces cerevisiae is negatively correlated with the specific growth rate. Additionally, glucose-excess conditions (i.e., growth limitation by nutrients other than glucose) are often implicated in high-level accumulation of these storage carbohydrates. The present study investigates how the identity of the growth-limiting nutrient affects accumulation of storage carbohydrates in cultures grown at a fixed specific growth rate. In anaerobic chemostat cultures (dilution rate, 0.10 h(-1)) of S. cerevisiae, the identity of the growth-limiting nutrient (glucose, ammonia, sulfate, phosphate, or zinc) strongly affected storage carbohydrate accumulation. The glycogen contents of the biomass from glucose- and ammonia-limited cultures were 10- to 14-fold higher than those of the biomass from cultures grown under the other three glucose-excess regimens. Trehalose levels were specifically higher under nitrogen-limited conditions. These results demonstrate that storage carbohydrate accumulation in nutrient-limited cultures of S. cerevisiae is not a generic response to excess glucose but instead is strongly dependent on the identity of the growth-limiting nutrient. While transcriptome analysis of wild-type and msn2Delta msn4Delta strains confirmed that transcriptional upregulation of glycogen and trehalose biosynthesis genes is mediated by Msn2p/Msn4p, transcriptional regulation could not quantitatively account for the drastic changes in storage carbohydrate accumulation. The results of assays of glycogen synthase and glycogen phosphorylase activities supported involvement of posttranscriptional regulation. Consistent with the high glycogen levels in ammonia-limited cultures, the ratio of glycogen synthase to glycogen phosphorylase in these cultures was up to eightfold higher than the ratio in the other glucose-excess cultures.

Quantitative physiology of Saccharomyces cerevisiae at near-zero specific growth rates

Growth at near-zero specific growth rates is a largely unexplored area of yeast physiology. To investigate the physiology of Saccharomyces cerevisiae under these conditions, the effluent removal pipe of anaerobic, glucose-limited chemostat culture (dilution rate, 0.025 h(-1)) was fitted with a 0.22-microm-pore-size polypropylene filter unit. This setup enabled prolonged cultivation with complete cell retention. After 22 days of cultivation, specific growth rates had decreased below 0.001 h(-1) (doubling time of >700 h). Over this period, viability of the retentostat cultures decreased to ca. 80%. The viable biomass concentration in the retentostats could be accurately predicted by a maintenance coefficient of 0.50 mmol of glucose g(-1) of biomass h(-1) calculated from anaerobic, glucose-limited chemostat cultures grown at dilution rates of 0.025 to 0.20 h(-1). This indicated that, in contrast to the situation in several prokaryotes, maintenance energy requirements in S. cerevisiae do not substantially change at near-zero specific growth rates. After 22 days of retentostat cultivation, glucose metabolism was predominantly geared toward alcoholic fermentation to meet maintenance energy requirements. The strict correlation between glycerol production and biomass formation observed at higher specific growth rates was not maintained at the near-zero growth rates reached in the retentostat cultures. In addition to glycerol, the organic acids acetate, d-lactate, and succinate were produced at low rates during prolonged retentostat cultivation. This study identifies robustness and by-product formation as key issues in attempts to uncouple growth and product formation in S. cerevisiae.

Simultaneously segmenting multiple gene expression time courses by analyzing cluster dynamics

We present a new approach to segmenting multiple time series by analyzing the dynamics of cluster formation and rearrangement around putative segment boundaries. This approach finds application in distilling large numbers of gene expression profiles into temporal relationships underlying biological processes. By directly minimizing information-theoretic measures of segmentation quality derived from Kullback-Leibler (KL) divergences, our formulation reveals clusters of genes along with a segmentation such that clusters show concerted behavior within segments but exhibit significant regrouping across segmentation boundaries. The results of the segmentation algorithm can be summarized as Gantt charts revealing temporal dependencies in the ordering of key biological processes. Applications to the yeast metabolic cycle and the yeast cell cycle are described.

mRNA stability and the unfolding of gene expression in the long-period yeast metabolic cycle

Background

In yeast, genome-wide periodic patterns associated with energy-metabolic oscillations have been shown recently for both short (approx. 40 min) and long (approx. 300 min) periods.

Results

The dynamical regulation due to mRNA stability is found to be an important aspect of the genome-wide coordination of the long-period yeast metabolic cycle. It is shown that for periodic genes, arranged in classes according either to expression profile or to function, the pulses of mRNA abundance have phase and width which are directly proportional to the corresponding turnover rates.

Conclusion

The cascade of events occurring during the yeast metabolic cycle (and their correlation with mRNA turnover) reflects to a large extent the gene expression program observable in other dynamical contexts such as the response to stresses/stimuli.

How Saccharomyces responds to nutrients

Yeast cells sense the amount and quality of external nutrients through multiple interconnected signaling networks, which allow them to adjust their metabolism, transcriptional profile and developmental program to adapt readily and appropriately to changing nutritional states. We present our current understanding of the nutritional sensing networks yeast cells rely on for perceiving the nutritional landscape, with particular emphasis on those sensitive to carbon and nitrogen sources. We describe the means by which these networks inform the cell's decision among the different developmental programs available to them-growth, quiescence, filamentous development, or meiosis/sporulation. We conclude that the highly interconnected signaling networks provide the cell with a highly nuanced view of the environment and that the cell can interpret that information through a sophisticated calculus to achieve optimum responses to any nutritional condition.

Growth temperature exerts differential physiological and transcriptional responses in laboratory and wine strains of Saccharomyces cerevisiae

Laboratory strains of Saccharomyces cerevisiae have been widely used as a model for studying eukaryotic cells and mapping the molecular mechanisms of many different human diseases. Industrial wine yeasts, on the other hand, have been selected on the basis of their adaptation to stringent environmental conditions and the organoleptic properties that they confer to wine. Here, we used a two-factor design to study the responses of a standard laboratory strain, CEN.PK113-7D, and an industrial wine yeast strain, EC1118, to growth temperatures of 15 degrees C and 30 degrees C in nitrogen-limited, anaerobic, steady-state chemostat cultures. Physiological characterization revealed that the growth temperature strongly impacted the biomass yield of both strains. Moreover, we found that the wine yeast was better adapted to mobilizing resources for biomass production and that the laboratory yeast exhibited higher fermentation rates. To elucidate mechanistic differences controlling the growth temperature response and underlying adaptive mechanisms between the strains, DNA microarrays and targeted metabolome analysis were used. We identified 1,007 temperature-dependent genes and 473 strain-dependent genes. The transcriptional response was used to identify highly correlated gene expression subnetworks within yeast metabolism. We showed that temperature differences most strongly affect nitrogen metabolism and the heat shock response. A lack of stress response element-mediated gene induction, coupled with reduced trehalose levels, indicated that there was a decreased general stress response at 15 degrees C compared to that at 30 degrees C. Differential responses among strains were centered on sugar uptake, nitrogen metabolism, and expression of genes related to organoleptic properties. Our study provides global insight into how growth temperature affects differential physiological and transcriptional responses in laboratory and wine strains of S. cerevisiae.

Genome-wide transcriptional responses of Escherichia coli K-12 to continuous osmotic and heat stresses

Osmotic stress is known to increase the thermotolerance and oxidative-stress resistance of bacteria by a mechanism that is not adequately understood. We probed the cross-regulation of continuous osmotic and heat stress responses by characterizing the effects of external osmolarity (0.3 M versus 0.0 M NaCl) and temperature (43 degrees C versus 30 degrees C) on the transcriptome of Escherichia coli K-12. Our most important discovery was that a number of genes in the SoxRS and OxyR oxidative-stress regulons were up-regulated by high osmolarity, high temperature, or a combination of both stresses. This result can explain the previously noted cross-protection of osmotic stress against oxidative and heat stresses. Most of the genes shown in previous studies to be induced during the early phase of adaptation to hyperosmotic shock were found to be also overexpressed under continuous osmotic stress. However, there was a poorer overlap between the heat shock genes that are induced transiently after high temperature shifts and the genes that we found to be chronically up-regulated at 43 degrees C. Supplementation of the high-osmolarity medium with the osmoprotectant glycine betaine, which reduces the cytoplasmic K(+) pool, did not lead to a universal reduction in the expression of osmotically induced genes. This finding does not support the hypothesis that K(+) is the central osmoregulatory signal in Enterobacteriaceae.