The rhythm of yeast

On the coupling of intracellular K + ${{\rm{K}}}^{+}$ to glycolytic oscillations in yeast

We have investigated the interplay between glycolytic oscillations and intracellularK + ${{\rm{K}}}^{+}$ concentration in the yeast Saccharomyces cerevisiae. IntracellularK + ${{\rm{K}}}^{+}$ concentration was measured using the fluorophore potassium-binding benzofuranisophthalate (PBFI). We found thatK + ${{\rm{K}}}^{+}$ is an essential ion for the occurrence of glycolytic oscillations and that intracellularK + ${{\rm{K}}}^{+}$ concentration oscillates synchronously with other variables such as nicotinamide adenine dinucleotide hydride (NADH), intracellular adenosine triphosphate (ATP), and mitochondrial membrane potential. We also investigated if glycolysis and intracellularK + ${{\rm{K}}}^{+}$ concentration oscillate in a number of yeast strains with mutations inK + ${{\rm{K}}}^{+}$ transporters in the plasma membrane, mitochondrial membrane and in the vacuolar membrane. Most of these strains are still capable of showing glycolytic oscillations, but two strains are not: (i) a strain with a deletion in the mitochondrial Mdm38pK + ∕ H + ${{\rm{K}}}^{+}\unicode{x02215}{{\rm{H}}}^{+}$ transporter and (ii) a strain with deletion of the late endosomal Nhx1pK + ∕ H + ${{\rm{K}}}^{+}\unicode{x02215}{{\rm{H}}}^{+}$ (Na + ∕ H + ${\text{Na}}^{+}\unicode{x02215}{{\rm{H}}}^{+}$ ) transporter. In these two mutant strains intracellularK + ${{\rm{K}}}^{+}$ concentration seems to be low, indicating that the two transporters may be involved in transport ofK + ${{\rm{K}}}^{+}$ into the cytosol. In the strain, Mdm38pΔ ${\rm{\Delta }}$ oscillations in glycolysis could be restored by addition of theK + ∕ H + ${{\rm{K}}}^{+}\unicode{x02215}{{\rm{H}}}^{+}$ exchange ionophore nigericin. Furthermore, in two nonoscillating mutant strains with a defective V-ATPase and deletion of the Arp1p protein the intracellularK + ${{\rm{K}}}^{+}$ is relatively high, suggesting that the V-ATPase is essential for transport ofK + ${{\rm{K}}}^{+}$ out of the cytosol and that the cytoskeleton may be involved in bindingK + ${{\rm{K}}}^{+}$ to reduce the concentration of free ion in the cytosol. Analyses of the time series of oscillations of NADH, ATP, mitochondrial membrane potential, and potassium concentration using data-driven modeling corroborate the conjecture thatK + ${{\rm{K}}}^{+}$ ion is essential for the emergence of oscillations and support the experimental findings using mutant strains.

Kinetic modelling of glycolytic oscillations

Glycolytic oscillations have been studied for well over 60 years, but aspects of their function, and mechanisms of regulation and synchronisation remain unclear. Glycolysis is amenable to mechanistic mathematical modelling, as its components have been well characterised, and the system can be studied at many organisational levels: in vitro reconstituted enzymes, cell free extracts, individual cells, and cell populations. In recent years, the emergence of individual cell analysis has opened new ways of studying this intriguing system.

From biological data to oscillator models using SINDy

Periodic changes in the concentration or activity of different molecules regulate vital cellular processes such as cell division and circadian rhythms. Developing mathematical models is essential to better understand the mechanisms underlying these oscillations. Recent data-driven methods like SINDy have fundamentally changed model identification, yet their application to experimental biological data remains limited. This study investigates SINDy's constraints by directly applying it to biological oscillatory data. We identify insufficient resolution, noise, dimensionality, and limited prior knowledge as primary limitations. Using various generic oscillator models of different complexity and/or dimensionality, we systematically analyze these factors. We then propose a comprehensive guide for inferring models from biological data, addressing these challenges step by step. Our approach is validated using glycolytic oscillation data from yeast.

Dynamic fluctuations in a bacterial metabolic network

The operation of the central metabolism is typically assumed to be deterministic, but dynamics and high connectivity of the metabolic network make it potentially prone to generating fluctuations. However, time-resolved measurements of metabolite levels in individual cells that are required to characterize such fluctuations remained a challenge, particularly in small bacterial cells. Here we use single-cell metabolite measurements based on Förster resonance energy transfer, combined with computer simulations, to explore the real-time dynamics of the metabolic network of Escherichia coli. We observe that steplike exposure of starved E. coli to glycolytic carbon sources elicits large periodic fluctuations in the intracellular concentration of pyruvate in individual cells. These fluctuations are consistent with predicted oscillatory dynamics of E. coli metabolic network, and they are primarily controlled by biochemical reactions around the pyruvate node. Our results further indicate that fluctuations in glycolysis propagate to other cellular processes, possibly leading to temporal heterogeneity of cellular states within a population.

Agent-based models for detecting the driving forces of biomolecular interactions

Agent-based modelling and simulation have been effectively applied to the study of complex biological systems, especially when composed of many interacting entities. Representing biomolecules as autonomous agents allows this approach to bring out the global behaviour of biochemical processes as resulting from local molecular interactions. In this paper, we leverage the capabilities of the agent paradigm to construct an in silico replica of the glycolytic pathway; the aim is to detect the role that long-range electrodynamic forces might have on the rate of glucose oxidation. Experimental evidences have shown that random encounters and short-range potentials might not be sufficient to explain the high efficiency of biochemical reactions in living cells. However, while the latest in vitro studies are limited by present-day technology, agent-based simulations provide an in silico support to the outcomes hitherto obtained and shed light on behaviours not yet well understood. Our results grasp properties hard to uncover through other computational methods, such as the effect of electromagnetic potentials on glycolytic oscillations.

Synchronisation of glycolytic activity in yeast cells

Glycolysis is the central metabolic pathway of almost every cell and organism. Under appropriate conditions, glycolytic oscillations may occur in individual cells as well as in entire cell populations or tissues. In many biological systems, glycolytic oscillations drive coherent oscillations of other metabolites, for instance in cardiomyocytes near anorexia, or in pancreas where they lead to a pulsatile release of insulin. Oscillations at the population or tissue level require the cells to synchronize their metabolism. We review the progress achieved in studying a model organism for glycolytic oscillations, namely yeast. Oscillations may occur on the level of individual cells as well as on the level of the cell population. In yeast, the cell-to-cell interaction is realized by diffusion-mediated intercellular communication via a messenger molecule. The present mini-review focuses on the synchronisation of glycolytic oscillations in yeast. Synchronisation is a quorum-sensing phenomenon because the collective oscillatory behaviour of a yeast cell population ceases when the cell density falls below a threshold. We review the question, under which conditions individual cells in a sparse population continue or cease to oscillate. Furthermore, we provide an overview of the pathway leading to the onset of synchronized oscillations. We also address the effects of spatial inhomogeneities (e.g., the formation of spatial clusters) on the collective dynamics, and also review the emergence of travelling waves of glycolytic activity. Finally, we briefly review the approaches used in numerical modelling of synchronized cell populations.

Omics analysis reveals mechanism underlying metabolic oscillation during continuous very-high-gravity ethanol fermentation by Saccharomyces cerevisiae

During continuous very-high-gravity (VHG) ethanol fermentation with Saccharomyces cerevisiae, the process exhibits sustained oscillation in residual glucose, ethanol, and biomass, raising a question: how do yeast cells respond to this phenomenon? In this study, the oscillatory behavior of yeast cells was characterized through transcriptome and metabolome analysis for one complete oscillatory period. By analyzing the accumulation of 26 intracellular metabolites and the expression of 90 genes related to central carbon metabolism and stress response, we confirmed that the process oscillation was attributed to intracellular metabolic oscillation with phase difference, and the expression of HXK1, HXT1,2,4, and PFK1 was significantly different from other genes in the Embden-Meyerhof-Parnas pathway, indicating that glucose transport and phosphorylation could be key nodes for regulating the intracellular metabolism under oscillatory conditions. Moreover, the expression of stress response genes was triggered and affected predominately by ethanol inhibition in yeast cells. This progress not only contributes to the understanding of mechanisms underlying the process oscillation observed for continuous VHG ethanol fermentation, but also provides insights for understanding unsteady state that might develop in other continuous fermentation processes operated under VHG conditions to increase product titers for robust production.

Leveraging autocatalytic reactions for chemical domain image classification

Autocatalysis is fundamental to many biological processes, and kinetic models of autocatalytic reactions have mathematical forms similar to activation functions used in artificial neural networks. Inspired by these similarities, we use an autocatalytic reaction, the copper-catalyzed azide-alkyne cycloaddition, to perform digital image recognition tasks. Images are encoded in the concentration of a catalyst across an array of liquid samples, and the classification is performed with a sequence of automated fluid transfers. The outputs of the operations are monitored using UV-vis spectroscopy. The growing interest in molecular information storage suggests that methods for computing in chemistry will become increasingly important for querying and manipulating molecular memory.

Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators

Networks of oscillating processes are a common occurrence in living systems. This is as true as anywhere in the energy metabolism of individual cells. Exchanges of molecules and common regulation operate throughout the metabolic processes of glycolysis and oxidative phosphorylation, making the consideration of each of these as a network a natural step. Oscillations are similarly ubiquitous within these processes, and the frequencies of these oscillations are never truly constant. These features make this system an ideal example with which to discuss an alternative approach to modeling living systems, which focuses on their thermodynamically open, oscillating, non-linear and non-autonomous nature. We implement this approach in developing a model of non-autonomous Kuramoto oscillators in two all-to-all weighted networks coupled to one another, and themselves driven by non-autonomous oscillators. Each component represents a metabolic process, the networks acting as the glycolytic and oxidative phosphorylative processes, and the drivers as glucose and oxygen supply. We analyse the effect of these features on the synchronization dynamics within the model, and present a comparison between this model, experimental data on the glycolysis of HeLa cells, and a comparatively mainstream model of this experiment. In the former, we find that the introduction of oscillator networks significantly increases the proportion of the model's parameter space that features some form of synchronization, indicating a greater ability of the processes to resist external perturbations, a crucial behavior in biological settings. For the latter, we analyse the oscillations of the experiment, finding a characteristic frequency of 0.01–0.02 Hz. We further demonstrate that an output of the model comparable to the measurements of the experiment oscillates in a manner similar to the measured data, achieving this with fewer parameters and greater flexibility than the comparable model.

Partial synchronisation of glycolytic oscillations in yeast cell populations

The transition between synchronized and asynchronous behaviour of immobilized yeast cells of the strain Saccharomyces carlsbergensis was investigated by monitoring the autofluorescence of the coenzyme NADH. In populations of intermediate cell densities the individual cells remained oscillatory, whereas on the level of the cell population both a partially synchronized and an asynchronous state were accessible for experimental studies. In the partially synchronized state, the mean oscillatory frequency was larger than that of the cells in the asynchronous state. This suggests that synchronisation occurred due to entrainment by the cells that oscillated more rapidly. This is typical for synchronisation due to phase advancement. Furthermore, the synchronisation of the frequency of the glycolytic oscillations preceded the synchronisation of their phases. However, the cells did not synchronize completely, as the distribution of the oscillatory frequencies only narrowed but did not collapse to a unique frequency. Cells belonging to spatially denser clusters showed a slightly enhanced local synchronisation during the episode of partial synchronisation. Neither the clusters nor a transition from partially synchronized glycolytic oscillations to travelling glycolytic waves did substantially affect the degree of partial synchronisation. Chimera states, i.e., the coexistence of a synchronized and an asynchronous part of the population, could not be found.

Non-histone protein acetylation by the evolutionarily conserved GCN5 and PCAF acetyltransferases

GCN5, conserved from yeast to humans, and the vertebrate specific PCAF, are lysine acetyltransferase enzymes found in large protein complexes. Both enzymes have well documented roles in the histone acetylation and the concomitant regulation of transcription. However, these enzymes also acetylate non-histone substrates to impact diverse aspects of cell physiology. Here, I review our current understanding of non-histone acetylation by GCN5 and PCAF across eukaryotes, from target identification to molecular mechanism and regulation. I focus mainly on budding yeast, where Gcn5 was first discovered, and mammalian systems, where the bulk of non-histone substrates have been characterized. I end the review by defining critical caveats and open questions that apply to all models.

PSK1 coordinates glucose metabolism and utilization and regulates energy-metabolism oscillation in Saccharomyces cerevisiae

Energy-metabolism oscillations (EMO) are ultradian biological rhythms observed in in aerobic chemostat cultures of Saccharomyces cerevisiae. EMO regulates energy metabolism such as glucose, carbohydrate storage, O₂ uptake, and CO₂ production. PSK1 is a nutrient responsive protein kinase involved in regulation of glucose metabolism, sensory response to light, oxygen, and redox state. The aim of this investigation was to assess the function of PSK1 in regulation of EMO. The mRNA levels of PSK1 fluctuated in concert with EMO, and deletion of PSK1 resulted in unstable EMO with disappearance of the fluctuations and reduced amplitude, compared with the wild type. Furthermore, the mutant PSK1Δ showed downregulation of the synthesis and breakdown of glycogen with resultant decrease in glucose concentrations. The redox state represented by NADH also decreased in PSK1Δ compared with the wild type. These data suggest that PSK1 plays an important role in the regulation of energy metabolism and stabilizes ultradian biological rhythms. These results enhance our understanding of the mechanisms of biorhythms in the budding yeast.

Emergence of collective oscillations in adaptive cells

Collective oscillations of cells in a population appear under diverse biological contexts. Here, we establish a set of common principles by categorising the response of individual cells against a time-varying signal. A positive intracellular signal relay of sufficient gain from participating cells is required to sustain the oscillations, together with phase matching. The two conditions yield quantitative predictions for the onset cell density and frequency in terms of measured single-cell and signal response functions. Through mathematical constructions, we show that cells that adapt to a constant stimulus fulfil the phase requirement by developing a leading phase in an active frequency window that enables cell-to-signal energy flow. Analysis of dynamical quorum sensing in several cellular systems with increasing biological complexity reaffirms the pivotal role of adaptation in powering oscillations in an otherwise dissipative cell-to-cell communication channel. The physical conditions identified also apply to synthetic oscillatory systems.

There are many examples of cell populations exhibiting density-dependent collective oscillatory behaviour. Here, the authors show that sustained collective oscillations emerge when cells anticipate variation in signal and attempt to amplify it, a property that can be linked to adaptation.

Coherence between oscillations in the cardiorespiratory system and tissue oxygen index in muscle recovering from intensive exercise in humans

It has been shown that the tissue oxygen index (TOI) measured by near-infrared spectroscopy oscillates at very low frequencies during recovery after exercise and that this oscillation is derived from interactions among biochemical substances involved in oxidative metabolism in skeletal muscle. As a further step, we examined whether TOI in muscle interacts through oscillation with factors related to oxygen in the cardiorespiratory system. For this examination, coherence and phase difference between the TOI in the vastus lateralis and heart rate (HR) and between TOI and arterial oxygen saturation (SpO₂) were sequentially determined during recovery (2-60 min) after severe cycle exercise with a workload of 7.5% of body weight for 20 s. Significant coherence between TOI and HR was obtained in the very low-frequency band (approximate range: 0.002-0.03 Hz) and in the low-frequency band (approximate range: 0.06-0.12 Hz). The phase difference was negative in the low-frequency band and positive in the very low-frequency band. The coherence between TOI and SpO₂ was significant in the very low-frequency band. The phase difference was negative. There were no sequential changes in these coherences and phase differences. The results suggest that TOI in skeletal muscle interrelates with factors related to the heart and lungs.

Diverse conditions support near-zero growth in yeast: Implications for the study of cell lifespan

Baker's yeast has a finite lifespan and ages in two ways: a mother cell can only divide so many times (its replicative lifespan), and a non-dividing cell can only live so long (its chronological lifespan). Wild and laboratory yeast strains exhibit natural variation for each type of lifespan, and the genetic basis for this variation has been generalized to other eukaryotes, including metazoans. To date, yeast chronological lifespan has chiefly been studied in relation to the rate and mode of functional decline among non-dividing cells in nutrient-depleted batch culture. However, this culture method does not accurately capture two major classes of long-lived metazoan cells: cells that are terminally differentiated and metabolically active for periods that approximate animal lifespan (e.g. cardiac myocytes), and cells that are pluripotent and metabolically quiescent (e.g. stem cells). Here, we consider alternative ways of cultivating Saccharomyces cerevisiae so that these different metabolic states can be explored in non-dividing cells: (i) yeast cultured as giant colonies on semi-solid agar, (ii) yeast cultured in retentostats and provided sufficient nutrients to meet minimal energy requirements, and (iii) yeast encapsulated in a semisolid matrix and fed ad libitum in bioreactors. We review the physiology of yeast cultured under each of these conditions, and explore their potential to provide unique insights into determinants of chronological lifespan in the cells of higher eukaryotes.

Quantitative Studies for Cell-Division Cycle Control

The cell-division cycle (CDC) is driven by cyclin-dependent kinases (CDKs). Mathematical models based on molecular networks, as revealed by molecular and genetic studies, have reproduced the oscillatory behavior of CDK activity. Thus, one basic system for representing the CDC is a biochemical oscillator (CDK oscillator). However, genetically clonal cells divide with marked variability in their total duration of a single CDC round, exhibiting non-Gaussian statistical distributions. Therefore, the CDK oscillator model does not account for the statistical nature of cell-cycle control. Herein, we review quantitative studies of the statistical properties of the CDC. Over the past 70 years, studies have shown that the CDC is driven by a cluster of molecular oscillators. The CDK oscillator is coupled to transcriptional and mitochondrial metabolic oscillators, which cause deterministic chaotic dynamics for the CDC. Recent studies in animal embryos have raised the possibility that the dynamics of molecular oscillators underlying CDC control are affected by allometric volume scaling among the cellular compartments. Considering these studies, we discuss the idea that a cluster of molecular oscillators embedded in different cellular compartments coordinates cellular physiology and geometry for successful cell divisions.

Phosphofructokinase controls the acetaldehyde-induced phase shift in isolated yeast glycolytic oscillators

The response of oscillatory systems to external perturbations is crucial for emergent properties such as synchronisation and phase locking and can be quantified in a phase response curve (PRC). In individual, oscillating yeast cells, we characterised experimentally the phase response of glycolytic oscillations for external acetaldehyde pulses and followed the transduction of the perturbation through the system. Subsequently, we analysed the control of the relevant system components in a detailed mechanistic model. The observed responses are interpreted in terms of the functional coupling and regulation in the reaction network. We find that our model quantitatively predicts the phase-dependent phase shift observed in the experimental data. The phase shift is in agreement with an adaptation leading to synchronisation with an external signal. Our model analysis establishes that phosphofructokinase plays a key role in the phase shift dynamics as shown in the PRC and adaptation time to external perturbations. Specific mechanism-based interventions, made possible through such analyses of detailed models, can improve upon standard trial and error methods, e.g. melatonin supplementation to overcome jet-lag, which are error-prone, specifically, since the effects are phase dependent and dose dependent. The models by Gustavsson and Goldbeter discussed in the text can be obtained from the JWS Online simulation database: (https://jjj.bio.vu.nl/models/gustavsson5 and https://jjj.bio.vu.nl/models/goldbeter1).

Oscillatory behaviour control in a continuous culture under double-substrate limitation

The paper discusses the possibility of using a mixture of two growth limiting substrates to induce or eliminate self-sustained oscillations in a continuous culture process. The proportion of both substrates in the mixture is treated as a new control variable. The presented approach is based on the assumption that the oscillatory behaviour occurs for selected substrates in some range of dilution rates. Because a double-substrate limitation may occur, the analysis is performed for two fundamental substrate utilization patterns: simultaneous consumption and diauxic growth. By using model simulations and bifurcation analysis, we show that an appropriate proportion of two substrates in the mixture allows for the control of the oscillatory behaviour.

Early redox activities modulate Xenopus tail regeneration

Redox state sustained by reactive oxygen species (ROS) is crucial for regeneration; however, the interplay between oxygen (O2), ROS and hypoxia-inducible factors (HIF) remains elusive. Here we observe, using an optic-based probe (optrode), an elevated and steady O2 influx immediately upon amputation. The spatiotemporal O2 influx profile correlates with the regeneration of Xenopus laevis tadpole tails. Inhibition of ROS production but not ROS scavenging decreases O2 influx. Inhibition of HIF-1α impairs regeneration and stabilization of HIF-1α induces regeneration in the refractory period. In the regeneration bud, hypoxia correlates with O2 influx, ROS production, and HIF-1α stabilization that modulate regeneration. Further analyses reveal that heat shock protein 90 is a putative downstream target of HIF-1α while electric current reversal is a de facto downstream target of HIF-1α. Collectively, the results show a mechanism for regeneration via the orchestration of O2 influx, ROS production, and HIF-1α stabilization.

Revisiting the role of metabolism during development

An emerging view emphasizes that metabolism is highly regulated in both time and space. In addition, it is increasingly being recognized that metabolic pathways are tightly connected to specific biological processes such as cell signaling, proliferation and differentiation. As we obtain a better view of this spatiotemporal regulation of metabolism, and of the molecular mechanisms that connect metabolism and signaling, we can now move from largely correlative to more functional studies. It is, therefore, a particularly promising time to revisit how metabolism can affect multiple aspects of animal development. In this Review, we discuss how metabolism is mechanistically linked to cellular and developmental programs through both its bioenergetic and metabolic signaling functions. We highlight how metabolism is regulated across various spatial and temporal scales, and discuss how this regulation can influence cellular processes such as cell signaling, gene expression, and epigenetic and post-translational modifications during embryonic development.

Systems and synthetic biology approaches in understanding biological oscillators

Background

Self-sustained oscillations are a ubiquitous and vital phenomenon in living systems. From primitive single-cellular bacteria to the most sophisticated organisms, periodicities have been observed in a broad spectrum of biological processes such as neuron firing, heart beats, cell cycles, circadian rhythms, etc. Defects in these oscillators can cause diseases from insomnia to cancer. Elucidating their fundamental mechanisms is of great significance to diseases, and yet challenging, due to the complexity and diversity of these oscillators.

Results

Approaches in quantitative systems biology and synthetic biology have been most effective by simplifying the systems to contain only the most essential regulators. Here, we will review major progress that has been made in understanding biological oscillators using these approaches. The quantitative systems biology approach allows for identification of the essential components of an oscillator in an endogenous system. The synthetic biology approach makes use of the knowledge to design the simplest, de novo oscillators in both live cells and cell-free systems. These synthetic oscillators are tractable to further detailed analysis and manipulations.

Conclusion

With the recent development of biological and computational tools, both approaches have made significant achievements.

Live Cell Imaging Reveals pH Oscillations in Saccharomyces cerevisiae During Metabolic Transitions

Addition of glucose to starved Saccharomyces cerevisiae initiates collective NADH dynamics termed glycolytic oscillations. Numerous questions remain about the extent to which single cells can oscillate, if oscillations occur in natural conditions, and potential physiological consequences of oscillations. In this paper, we report sustained glycolytic oscillations in single cells without the need for cyanide. Glucose addition to immobilized cells induced pH oscillations that could be imaged with fluorescent sensors. A population of cells had oscillations that were heterogeneous in frequency, start time, stop time, duration and amplitude. These changes in cytoplasmic pH were necessary and sufficient to drive changes in NADH. Oscillators had lower mitochondrial membrane potentials and budded more slowly than non-oscillators. We also uncovered a new type of oscillation during recovery from H₂O₂ challenge. Our data show that pH in S. cerevisiae changes over several time scales, and that imaging pH offers a new way to measure glycolytic oscillations on individual cells.

Physiology, ecology and industrial applications of aroma formation in yeast

Yeast cells are often employed in industrial fermentation processes for their ability to efficiently convert relatively high concentrations of sugars into ethanol and carbon dioxide. Additionally, fermenting yeast cells produce a wide range of other compounds, including various higher alcohols, carbonyl compounds, phenolic compounds, fatty acid derivatives and sulfur compounds. Interestingly, many of these secondary metabolites are volatile and have pungent aromas that are often vital for product quality. In this review, we summarize the different biochemical pathways underlying aroma production in yeast as well as the relevance of these compounds for industrial applications and the factors that influence their production during fermentation. Additionally, we discuss the different physiological and ecological roles of aroma-active metabolites, including recent findings that point at their role as signaling molecules and attractants for insect vectors.

Upregulation of an inward rectifying K+ channel can rescue slow Ca2+ oscillations in K(ATP) channel deficient pancreatic islets

Plasma insulin oscillations are known to have physiological importance in the regulation of blood glucose. In insulin-secreting β-cells of pancreatic islets, K(ATP) channels play a key role in regulating glucose-dependent insulin secretion. In addition, they convey oscillations in cellular metabolism to the membrane by sensing adenine nucleotides, and are thus instrumental in mediating pulsatile insulin secretion. Blocking K(ATP) channels pharmacologically depolarizes the β-cell plasma membrane and terminates islet oscillations. Surprisingly, when K(ATP) channels are genetically knocked out, oscillations in islet activity persist, and relatively normal blood glucose levels are maintained. Compensation must therefore occur to overcome the loss of K(ATP) channels in K(ATP) knockout mice. In a companion study, we demonstrated a substantial increase in Kir2.1 protein occurs in β-cells lacking K(ATP) because of SUR1 deletion. In this report, we demonstrate that β-cells of SUR1 null islets have an upregulated inward rectifying K⁺ current that helps to compensate for the loss of K(ATP) channels. This current is likely due to the increased expression of Kir2.1 channels. We used mathematical modeling to determine whether an ionic current having the biophysical characteristics of Kir2.1 is capable of rescuing oscillations that are similar in period to those of wild-type islets. By experimentally testing a key model prediction we suggest that Kir2.1 current upregulation is a likely mechanism for rescuing the oscillations seen in islets from mice deficient in K(ATP) channels.

Pulsatile insulin secretion is important for the proper regulation of blood glucose, and disruption of this pulsatility is a hallmark of type II diabetes. An ion channel was discovered more than three decades ago that conveys the metabolic state of insulin-secreting β-cells to the plasma membrane because it is blocked by ATP and opened by ADP, and thereby controls the activity of these electrically-excitable cells on a rapid time scale according to the prevailing blood glucose level. In addition to setting the appropriate level of insulin secretion, K(ATP) channels play a key role in generating the oscillations in cellular activity that underlie insulin pulsatility. It is therefore surprising that oscillations in activity persist in islets in which the K(ATP) channels are genetically knocked out. In this combined modeling and experimental study, we demonstrate that the role played by K(ATP) current in wild-type β-cells can be taken over by an inward-rectifying K⁺ current which, we show here, is upregulated in β-cells from SUR1 knockout mice. This result helps to resolve a mystery in the field that has remained elusive for more than a decade, since the first studies showing oscillations in SUR1^-/- islets.

Analysis of Raw Biofluids by Mass Spectrometry Using Microfluidic Diffusion-Based Separation

Elucidation and monitoring of biomarkers continues to expand because of their medical value and potential to reduce healthcare costs. For example, biomarkers are used extensively to track physiology associated with drug addiction, disease progression, aging, and industrial processes. While longitudinal analyses are of great value from a biological or healthcare perspective, the cost associated with replicate analyses is preventing the expansion of frequent routine testing. Frequent testing could deepen our understanding of disease emergence and aid adoption of personalized healthcare. To address this need, we have developed a system for measuring metabolite abundance from raw biofluids. Using a metabolite extraction chip (MEC), based upon diffusive extraction of small molecules and metabolites from biofluids using microfluidics, we show that biologically relevant markers can be measured in blood and urine. Previously it was shown that the MEC could be used to track metabolic changes in real-time. We now demonstrate that the device can be adapted to high-throughput screening using standard liquid chromatography mass spectrometry instrumentation (LCMS). The results provide insight into the sensitivity of the system and its application for the analysis of human biofluids. Quantitative analysis of clinical predictors including nicotine, caffeine, and glutathione are described.

Oscillation in tissue oxygen index during recovery from exercise

It was hypothesized that an oscillation of tissue oxygen index (TOI) determined by near-infrared spectroscopy during recovery from exercise occurs due to feedback control of adenosine triphosphate and that frequency of the oscillation is affected by blood pH. In order to examine these hypotheses, we aimed 1) to determine whether there is an oscillation of TOI during recovery from exercise and 2) to determine the effect of blood pH on frequency of the oscillation of TOI. Three exercises were performed with exercise intensities of 30 % and 70 % peak oxygen uptake (V(.)o(2)peak) for 12 min and with exercise intensity of 70 % V(.)o(2)peak for 30 s. TOI during recovery from the exercise was analyzed by fast Fourier transform in order to obtain power spectra density (PSD). There was a significant difference in the frequency at which maximal PSD of TOI appeared (Fmax) between the exercises with 70 % V(.)o(2)peak for 12 min (0.0039+/-0 Hz) and for 30 s (0.0061+/-0.0028 Hz). However, there was no significant difference in Fmax between the exercises with 30 % (0.0043+/-0.0013 Hz) and with 70 % V(.)o(2)peak for 12 min despite differences in blood pH and blood lactate from the warmed fingertips. It is concluded that there was an oscillation in TOI during recovery from the three exercises. It was not clearly shown that there was an effect of blood pH on Fmax.

The 6th International Conference on Analysis of Microbial Cells at the Single Cell Level, Retz, Austria, 19-22 July 2015

The 6th International Conference on Analysis of Microbial Cells at the Single Cell Level, held in Retz, Austria from 19 to 22 July 2015, brought together experts from different areas working with bacterial, yeast and mammalian cell systems. The conference highlighted the importance of dissecting cell behaviour down to the single cell level, as analysis of mixed populations can obscure crucial cell-to-cell variations. The sessions covered advances in the fields of image analysis and microscopy, flow cytometry and cell sorting as well as bioinformatics, including recent developments and new applications of existing tools. In addition, a high speed poster slam session contributed to the lively discussions and exchange of expertise among academic and industrial researchers.

Entrainment of heterogeneous glycolytic oscillations in single cells

Cell signaling, gene expression, and metabolism are affected by cell-cell heterogeneity and random changes in the environment. The effects of such fluctuations on cell signaling and gene expression have recently been studied intensively using single-cell experiments. In metabolism heterogeneity may be particularly important because it may affect synchronisation of metabolic oscillations, an important example of cell-cell communication. This synchronisation is notoriously difficult to describe theoretically as the example of glycolytic oscillations shows: neither is the mechanism of glycolytic synchronisation understood nor the role of cell-cell heterogeneity. To pin down the mechanism and to assess its robustness and universality we have experimentally investigated the entrainment of glycolytic oscillations in individual yeast cells by periodic external perturbations. We find that oscillatory cells synchronise through phase shifts and that the mechanism is insensitive to cell heterogeneity (robustness) and similar for different types of external perturbations (universality).

Tight coupling of metabolic oscillations and intracellular water dynamics in Saccharomyces cerevisiae

We detected very strong coupling between the oscillating concentration of ATP and the dynamics of intracellular water during glycolysis in Saccharomyces cerevisiae. Our results indicate that: i) dipolar relaxation of intracellular water is heterogeneous within the cell and different from dilute conditions, ii) water dipolar relaxation oscillates with glycolysis and in phase with ATP concentration, iii) this phenomenon is scale-invariant from the subcellular to the ensemble of synchronized cells and, iv) the periodicity of both glycolytic oscillations and dipolar relaxation are equally affected by D₂O in a dose-dependent manner. These results offer a new insight into the coupling of an emergent intensive physicochemical property of the cell, i.e. cell-wide water dipolar relaxation, and a central metabolite (ATP) produced by a robustly oscillating metabolic process.

Real-time digitization of metabolomics patterns from a living system using mass spectrometry

The real-time quantification of changes in intracellular metabolic activities has the potential to vastly improve upon traditional transcriptomics and metabolomics assays for the prediction of current and future cellular phenotypes. This is in part because intracellular processes reveal themselves as specific temporal patterns of variation in metabolite abundance that can be detected with existing signal processing algorithms. Although metabolite abundance levels can be quantified by mass spectrometry (MS), large-scale real-time monitoring of metabolite abundance has yet to be realized because of technological limitations for fast extraction of metabolites from cells and biological fluids. To address this issue, we have designed a microfluidic-based inline small molecule extraction system, which allows for continuous metabolomic analysis of living systems using MS. The system requires minimal supervision, and has been successful at real-time monitoring of bacteria and blood. Feature-based pattern analysis of Escherichia coli growth and stress revealed cyclic patterns and forecastable metabolic trajectories. Using these trajectories, future phenotypes could be inferred as they exhibit predictable transitions in both growth and stress related changes. Herein, we describe an interface for tracking metabolic changes directly from blood or cell suspension in real-time.

Oscillation in O2 uptake in impulse exercise

The purpose of the present study was to examine 1) whether O(2) uptake (VO(2)) oscillates during light exercise and 2) whether the oscillation is enhanced after impulse exercise. After resting for 1 min on a bicycle seat, subjects performed 5-min pre-exercise with 25 watts work load, 10-s impulse exercise with 200 watts work load and 15-min post exercise with 25 watts work load at 80 rpm. VO(2) during pre-exercise significantly increased during impulse exercise and suddenly decreased and re-increased until 23 s after impulse exercise. In the cross correlation between heart rate (HR) and VO(2) after impulse exercise, VO(2) strongly correlated to HR with a time delay of -4 s. Peak of power spectral density (PSD) in HR appeared at 0.0039 Hz and peak of PSD in VO(2) appeared at 0.019 Hz. The peak of the cross power spectrum between VO(2) and HR appeared at 0.0078 Hz. The results suggested that there is an oscillation in O(2) uptake during light exercise that is associated with the oscillation in O(2) consumption in active muscle. The oscillation is enhanced not only by change in O(2) consumption but also by O(2) content transported from active muscle to the lungs.

Allosteric regulation of phosphofructokinase controls the emergence of glycolytic oscillations in isolated yeast cells

Oscillations are widely distributed in nature and synchronization of oscillators has been described at the cellular level (e.g. heart cells) and at the population level (e.g. fireflies). Yeast glycolysis is the best known oscillatory system, although it has been studied almost exclusively at the population level (i.e. limited to observations of average behaviour in synchronized cultures). We studied individual yeast cells that were positioned with optical tweezers in a microfluidic chamber to determine the precise conditions for autonomous glycolytic oscillations. Hopf bifurcation points were determined experimentally in individual cells as a function of glucose and cyanide concentrations. The experiments were analyzed in a detailed mathematical model and could be interpreted in terms of an oscillatory manifold in a three-dimensional state-space; crossing the boundaries of the manifold coincides with the onset of oscillations and positioning along the longitudinal axis of the volume sets the period. The oscillatory manifold could be approximated by allosteric control values of phosphofructokinase for ATP and AMP.

DATABASE

The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.mib.ac.uk/webMathematica/UItester.jsp?modelName=gustavsson5. [Database section added 14 May 2014 after original online publication].

UVA-induced reset of hydroxyl radical ultradian rhythm improves temporal lipid production in Chlorella vulgaris

We report for the first time that the endogenous, pseudo-steady-state, specific intracellular levels of the hydroxyl radical (si-OH) oscillate in an ultradian fashion (model system: the microalga, Chlorella vulgaris), and also characterize the various rhythm parameters. The ultradian rhythm in the endogenous levels of the si-OH occurred with an approximately 6 h period in the daily cycle of light and darkness. Further, we expected that the rhythm reset to a shorter period could rapidly switch the cellular redox states that could favor lipid accumulation. We reset the endogenous rhythm through entrainment with UVA radiation, and generated two new ultradian rhythms with periods of approximately 2.97 h and 3.8 h in the light phase and dark phase, respectively. The reset increased the window of maximum lipid accumulation from 6 h to 12 h concomitant with the onset of the ultradian rhythms. Further, the saturated fatty acid content increased approximately to 80% of total lipid content, corresponding to the peak maxima of the hydroxyl radical levels in the reset rhythm.

Comparison of oscillations of skin blood flow and deoxygenation in vastus lateralis in light exercise

The purpose of the present study was to compare oscillation of skin blood flow with that of deoxygenation in muscle during light exercise in order to determine the physiological significance of oscillations in deoxygenation. Prolonged exercise with 50% of peak oxygen uptake was performed for 60 min. Skin blood flow (SBF) was measured using a laser blood flow meter on the right vastus lateralis muscle. Deoxygenated haemoglobin/myoglobin (DHb/Mb) concentration in the left vastus lateralis were measured using a near-infrared spectroscopy system. SBF and DHb/Mb during exercise were analysed by fast Fourier transform. We classified frequency bands according to previous studies (Kvernmo et al. 1999, Kvandal et al. 2006) into phase I (0.005-0.0095 and 0.0095-0.02 Hz), phase II (0.02-0.06 Hz: phase II) and phase III (0.06-0.16 Hz). The first peak of power spectra density (PSD) in SBF appeared at 0.0078 Hz in phase I. The second peak of PSD in SBF appeared at 0.035 Hz. The third peak of PSD in SBF appeared at 0.078 Hz. The first peak of PSD in DHb/Mb appeared at 0.0039 Hz, which was out of phase I. The second peak of PSD in DHb/Mb appeared at 0.016 Hz. The third peak of PSD in DHb/Mb appeared at 0.035 Hz. The coefficient of cross correlation was very low. Cross power spectra density showed peaks of 0.0039, 0.016 and 0.035 Hz. It is concluded that a peak of 0.016 Hz in oscillations of DHb/Mb observed in muscle during exercise is associated with endothelium-dependent vasodilation (phase I) and that a peak of 0.035 Hz in DHb/Mb is associated with sympathetic nerve activity (phase II). It is also confirmed that each peak of SBF oscillations is observed in each phase.

Cell cycle dynamics in a response/signalling feedback system with a gap

We consider a dynamical model of cell cycles of n cells in a culture in which cells in one specific phase (S for signalling) of the cell cycle produce chemical agents that influence the growth/cell cycle progression of cells in another phase (R for responsive). In the case that the feedback is negative, it is known that subpopulations of cells tend to become clustered in the cell cycle; while for a positive feedback, all the cells tend to become synchronized. In this paper, we suppose that there is a gap between the two phases. The gap can be thought of as modelling the physical reality of a time delay in the production and action of the signalling agents. We completely analyse the dynamics of this system when the cells are arranged into two cell cycle clusters. We also consider the stability of certain important periodic solutions in which clusters of cells have a cyclic arrangement and there are just enough clusters to allow interactions between them. We find that the inclusion of a small gap does not greatly alter the global dynamics of the system; there are still large open sets of parameters for which clustered solutions are stable. Thus, we add to the evidence that clustering can be a robust phenomenon in biological systems. However, the gap does effect the system by enhancing the stability of the stable clustered solutions. We explain this phenomenon in terms of contraction rates (Floquet exponents) in various invariant subspaces of the system. We conclude that in systems for which these models are reasonable, a delay in signalling is advantageous to the emergence of clustering.

Chemical computing based on Turing patterns in two coupled cells with equal transport coefficients

Two diffusively coupled reaction cells with a nonlinear reaction are used to perform chemical computing based on targeted perturbations switching between two Turing patterns defining two states of a logical device.

Response of end tidal CO2 pressure to impulse exercise

The purpose of the present study was to examine how end tidal CO(2) pressure (PETCO(2)) is controlled in impulse exercise. After pre-exercise at 25 watts for 5 min, impulse exercise for 10 sec with 200 watts followed by post exercise at 25 watts was performed. Ventilation (VE) significantly increased until the end of impulse exercise and significantly re-increased after a sudden decrease. Heart rate (HR) significantly increased until the end of impulse exercise and then decreased to the pre-exercise level. PETCO(2) remained constant during impulse exercise. PETCO(2) significantly increased momentarily after impulse exercise and then significantly decreased to the pre-exercise level. PETCO(2) showed oscillation. The average peak frequency of power spectral density in PETCO(2) appeared at 0.0078 Hz. Cross correlations were obtained after impulse exercise. The peak cross correlations between VE and PETCO(2), HR and PETCO(2), and VE and HR were 0.834 with a time delay of -7 sec, 0.813 with a time delay of 7 sec and 0.701 with a time delay of -15 sec, respectively. We demonstrated that PETCO(2) homeodynamics was interactively maintained by PETCO(2) itself, CO(2) transportation (product of cardiac output and mixed venous CO(2) content) into the lungs by heart pumping and CO(2) elimination by ventilation, and it oscillates as a result of their interactions.

Heterogeneity of glycolytic oscillatory behaviour in individual yeast cells

There are many examples of oscillations in biological systems and one of the most investigated is glycolytic oscillations in yeast. These oscillations have been studied since the 1950s in dense, synchronized populations and in cell-free extracts, but it has for long been unknown whether a high cell density is a requirement for oscillations to be induced, or if individual cells can oscillate also in isolation without synchronization. Here we present an experimental method and a detailed kinetic model for studying glycolytic oscillations in individual, isolated yeast cells and compare them to previously reported studies of single-cell oscillations. The importance of single-cell studies of this phenomenon and relevant future research questions are also discussed.

An experimental study of the regulation of glycolytic oscillations in yeast

We have studied oscillating glycolysis in the strain BY4743 and isogenic strains with deletions of genes encoding enzymes in glycolysis, mitochondrial electron transport and ATP synthesis. We found that deletion of the gene encoding the hexokinase 1 isoform does not affect the oscillations while deletion of the gene encoding the hexokinase 2 isoform results in oscillations with smaller amplitude. The latter is associated with an almost 50% decrease in hexokinase activity. Deletions in the genes encoding the α- and β-subunits of phosphofructokinase abolish the oscillations entirely. This loss in oscillatory activity is associated with a fourfold decrease in phosphofructokinase activity. Deletions of genes encoding subunits of the F1F0 ATPase also inhibit the oscillations in accordance with earlier studies using for example inhibitors. Finally, we identified an apparently new control point involving the mitochondrial cytochrome c oxidase. The latter is difficult to explain as oscillatory activity entails 100% inhibition of this enzyme. The mitochondria of this strain seem to have normal F1F0 ATPase activity. Overall these results support earlier experimental and model studies suggesting that in addition to processes within glycolysis also processes outside this pathway contribute to the control of the oscillatory behaviour.

Direct measurements of oscillatory glycolysis in pancreatic islet β-cells using novel fluorescence resonance energy transfer (FRET) biosensors for pyruvate kinase M2 activity

Pulses of insulin released from pancreatic β-cells maintain blood glucose in a narrow range, although the source of these pulses is unclear. We and others have proposed that positive feedback mediated by the glycolytic enzyme phosphofructokinase-1 (PFK1) enables β-cells to generate metabolic oscillations via autocatalytic activation by its product fructose 1,6-bisphosphate (FBP). Although much indirect evidence has accumulated in favor of this hypothesis, a direct measurement of oscillating glycolytic intermediates has been lacking. To probe glycolysis directly, we engineered a family of inter- and intramolecular FRET biosensors based on the glycolytic enzyme pyruvate kinase M2 (PKAR; pyruvate kinase activity reporter), which multimerizes and is activated upon binding FBP. When introduced into Min6 β-cells, PKAR FRET efficiency increased rapidly in response to glucose. Importantly, however, metabolites entering downstream of PFK1 (glyceraldehyde, pyruvate, and ketoisocaproate) failed to activate PKAR, consistent with sensor activation by FBP; the dependence of PKAR on FBP was further confirmed using purified sensor in vitro. Using a novel imaging modality for monitoring mitochondrial flavin fluorescence in mouse islets, we show that slow oscillations in mitochondrial redox potential stimulated by 10 mm glucose are in phase with glycolytic efflux through PKM2, measured simultaneously from neighboring islet β-cells expressing PKAR. These results indicate that PKM2 activity in β-cells is oscillatory and are consistent with pulsatile PFK1 being the mediator of slow glycolytic oscillations.

Oscillation of oxygenation in skeletal muscle at rest and in light exercise

The aim of the present study was to compare the frequency of oxygenation determined in the vastus lateralis by near-infrared spectroscopy (NIRS) in light exercise with that at rest. A subject rested in a recumbent position for 5 min and changed body position to a sitting position on a cycle ergometer for 9 min. Then exercise with low intensity (work rate of 60% of maximal oxygen uptake) was carried out for 30 min. Total hemoglobin and myoglobin (THb/Mb) suddenly decreased after the start of exercise and gradually increased for 6 min. Oxygenated hemoglobin and myoglobin (Hb/MbO2) suddenly decreased and returned to a steady-state after the start of exercise. The difference between Hb/MbO2 and THb/Mb showed a sudden decrease and then a steady-state. This difference was analyzed by fast Fourier transform. The peak frequencies of the power spectrum density (PSD) were 0.0169 ± 0.0076 Hz at rest and 0.0117 ± 0.0042 Hz in exercise. The peak frequency of PSD was significantly decreased in exercise. In exercise, the range of frequencies was expanded. It is concluded that there are oscillations at rest as well as in exercise and that the frequency of peak PSD becomes lower in exercise than at rest.

Comparison of oscillation of oxygenation in skeletal muscle between early and late phases in prolonged exercise

The aim of the present study was to compare the oscillations of oxygenation in skeletal muscle between early and late phases in prolonged exercise. During prolonged exercise at 60 % of peak oxygen uptake (V(.)o(2)) for 60 min and at rest, oxygenated hemoglobin/myoglobin (Hb/MbO(2)) and total Hb/Mb (THb/Mb) were determined by near-infrared spectroscopy in the vastus lateralis. Power spectra density (PSD) for the difference between Hb/MbO(2) and THb/Mb (-HHb/MbO(2): deoxygenation) was obtained by fast Fourier transform at rest, in the early phase (1-6 min) and in the late phase (55-60 min) in exercise. Peak PSD in the early phase was significantly higher than that at rest. There were at least three peaks of PSD in exercise. The highest peak was a band around 0.01 Hz, the next peak was a band around 0.04 Hz, and the lowest peak was a band around 0.06 Hz. PSD in the early phase was not significantly different from that in the late phase in exercise. Heart rate (HR) showed a continuous significant increase from 3 min in exercise until the end of exercise. Skin blood flow (SBF) around the early phase was significantly lower than that around the late phase. It was concluded that oscillation of oxygenation in the muscle oxygen system in the early phase is not different from that in the late phase in prolonged exercise despite cardiovascular drift.

Glycolytic oscillations in a model of a lactic acid bacterium metabolism

Glycolytic oscillations in yeast have been extensively studied. It is still unclear, if these oscillations are caused by the allosteric enzyme phosphofructokinase or the stoichiometry of glycolysis which contains an autocatalysis with respect to ATP. Bacterial glycolysis shows a different stoichiometry, however, also containing a stoichiometric autocatalysis. For Escherichia coli, the regulation of the enzyme phosphofructokinase is also assumed to be a major reason for oscillations to occur. We investigated glycolytic oscillations in a quantitative kinetic model for Streptococcus pyogenes set-up on the basis of experimental data. We found oscillations within physiologically feasible parameter ranges. We investigated the origin of these oscillations and conclude that, again, both the stoichiometry of the system, as well as its allosterically regulated enzymes can give rise to these oscillations. For the analysis we employed established and new optimization methods for finding oscillatory regimes and present these in the context of this study.

Telomerase-dependent generation of 70-nt-long telomeric single-stranded 3' overhangs in yeast

Telomeres, the chromatin structures at the ends of eukaryotic chromosomes, are essential for chromosome stability. The telomere terminates with a TG-rich 3' overhang, which is bound by sequence-specific proteins that both protect the end and regulate the telomerase elongation process. Here, we demonstrate the presence of 3' overhangs as long as 200 nt in asynchronously growing cells of the budding yeast Saccharomyces castellii. The 3' overhangs show a wide distribution of 14-200 nt in length, thus resembling the distribution found in human cells. A substantially large fraction of the 3' overhangs resides in the 70-200 nt range. Remarkably, we found an accumulation of a distinct class of 70-nt-long 3' overhangs in the S phase of the cell cycle. Cells without a functional telomerase showed the same wide distribution of 3' overhangs, but significantly, lacked the specific fraction of 70-nt 3' overhangs. Hence, our data show that the highly defined 70-nt 3' overhangs are generated by a telomerase-dependent mechanism, which is uncoupled to the mechanisms producing the bulk of the 3' overhangs. These data provide new insights that will be helpful for deciphering the complex interplay between the specialized telomere replication machinery and the conventional DNA replication.