A systems-level analysis of perfect adaptation in yeast osmoregulation

How Does Escherichia coli Allocate Proteome?

Microorganisms are shown to actively partition their intracellular resources, such as proteins, for growth optimization. Recent experiments have begun to reveal molecular components unpinning the partition; however, quantitatively, it remains unclear how individual parts orchestrate to yield precise resource allocation that is both robust and dynamic. Here, we developed a coarse-grained mathematical framework that centers on guanosine pentaphosphate (ppGpp)-mediated regulation and used it to systematically uncover the design principles of proteome allocation in Escherichia coli. Our results showed that the cellular ability of resource partition lies in an ultrasensitive, negative feedback-controlling topology with the ultrasensitivity arising from zero-order amino acid kinetics and the negative feedback from ppGpp-controlled ribosome synthesis. In addition, together with the time-scale separation between slow ribosome kinetics and fast turnovers of ppGpp and amino acids, the network topology confers the organism an optimization mechanism that mimics sliding mode control, a nonlinear optimization strategy that is widely used in man-made systems. We further showed that such a controlling mechanism is robust against parameter variations and molecular fluctuations and is also efficient for biomass production over time. This work elucidates the fundamental controlling mechanism of E. coli proteome allocation, thereby providing insights into quantitative microbial physiology as well as the design of synthetic gene networks.

Polysome collapse and RNA condensation fluidize the cytoplasm

The cell interior is packed with macromolecules of mesoscale size, and this crowded milieu significantly influences cellular physiology. Cellular stress responses almost universally lead to inhibition of translation, resulting in polysome collapse and release of mRNA. The released mRNA molecules condense with RNA-binding proteins to form ribonucleoprotein (RNP) condensates known as processing bodies and stress granules. Here, we show that polysome collapse and condensation of RNA transiently fluidize the cytoplasm, and coarse-grained molecular dynamic simulations support this as a minimal mechanism for the observed biophysical changes. Increased mesoscale diffusivity correlates with the efficient formation of quality control bodies (Q-bodies), membraneless organelles that compartmentalize misfolded peptides during stress. Synthetic, light-induced RNA condensation also fluidizes the cytoplasm. Together, our study reveals a functional role for stress-induced translation inhibition and formation of RNP condensates in modulating the physical properties of the cytoplasm to enable efficient response of cells to stress conditions.

Signal integration and integral feedback control with biochemical reaction networks

Biochemical reaction networks perform a variety of signal processing functions, one of which is computing the integrals of signal values. This is often used in integral feedback control, where it enables a system's output to respond to changing inputs, but to then return exactly back to some pre-determined setpoint value afterward. To gain a deeper understanding of how biochemical networks are able to both integrate signals and perform integral feedback control, we investigated these abilities for several simple reaction networks. We found imperfect overlap between these categories, with some networks able to perform both tasks, some able to perform integration but not integral feedback control, and some the other way around. Nevertheless, networks that could either integrate or perform integral feedback control shared key elements. In particular, they included a chemical species that was neutrally stable in the open loop system (no feedback), meaning that this species does not have a unique stable steady-state concentration. Neutral stability could arise from zeroth order decay reactions, binding to a partner that was produced at a constant rate (which occurs in antithetic control), or through a long chain of covalent cycles. Mathematically, it arose from rate equations for the reaction network that were underdetermined when evaluated at steady-state.

Yeast cell responses and survival during periodic osmotic stress are controlled by glucose availability

Natural environments of living organisms are often dynamic and multifactorial, with multiple parameters fluctuating over time. To better understand how cells respond to dynamically interacting factors, we quantified the effects of dual fluctuations of osmotic stress and glucose deprivation on yeast cells using microfluidics and time-lapse microscopy. Strikingly, we observed that cell proliferation, survival, and signaling depend on the phasing of the two periodic stresses. Cells divided faster, survived longer, and showed decreased transcriptional response when fluctuations of hyperosmotic stress and glucose deprivation occurred in phase than when the two stresses occurred alternatively. Therefore, glucose availability regulates yeast responses to dynamic osmotic stress, showcasing the key role of metabolic fluctuations in cellular responses to dynamic stress. We also found that mutants with impaired osmotic stress response were better adapted to alternating stresses than wild-type cells, showing that genetic mechanisms of adaptation to a persistent stress factor can be detrimental under dynamically interacting conditions.

Design patterns of biological cells

Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.

Phenotypic consequences of logarithmic signaling in MAPK stress response

How cells respond to dynamic environmental changes is crucial for understanding fundamental biological processes and cell physiology. In this study, we developed an experimental and quantitative analytical framework to explore how dynamic stress gradients that change over time regulate cellular volume, signaling activation, and growth phenotypes. Our findings reveal that gradual stress conditions substantially enhance cell growth compared to conventional acute stress. This growth advantage correlates with a minimal reduction in cell volume dependent on the dynamic of stress. We explain the growth phenotype with our finding of a logarithmic signal transduction mechanism in the yeast Mitogen-Activated Protein Kinase (MAPK) osmotic stress response pathway. These insights into the interplay between gradual environments, cell volume change, dynamic cell signaling, and growth, advance our understanding of fundamental cellular processes in gradual stress environments.

Development of chemically defined media for Lactococcus lactis subsp. lactis YF11 to eliminate the influence of hyperosmotic stress

Chemically defined media (CDM) can eliminate or lessen the interference that occurs in complex culture media (CCM) caused by the undefined substrate pools, and various CDM have been designed and employed for investigating microbial physiology and multiomics. Herein, using the measured amount of total amino acids in CCM and combined with the in vivo and in vitro amino acid content of Lactococcus lactis subsp. lactis YF11, new enriched CDM were designed and then optimized using a statistical design-of-experiment method coupling with fed-batch fermentation to eliminate or lessen the influence of hyperosmotic pressure. Cell volume was introduced as a target index to assess the performance of CDM, and average osmotic pressure (AOP) was employed to describe the osmotic pressure of CDM. The AOP was significantly decreased from 610 mOsm/kg·H2O in the initial CDM (I-CDM) to 360 mOsm/kg·H2O in fed-batch CDM (F-CDM), and the cell volume was increased from 0.142 ± 0.004 μm3 in I-CDM to 0.198 ± 0.008 μm3 in F-CDM, which was close to 0.206 ± 0.005 μm3 found in CCM, indicating that the strategy of designing and improving CDM followed by a statistical design-of-experiment coupling with fed-batch cultivation presented a promising pathway for extensive utilization of CDM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03788-5.

Optogenetic control of YAP reveals a dynamic communication code for stem cell fate and proliferation

YAP is a transcriptional regulator that controls pluripotency, cell fate, and proliferation. How cells ensure the selective activation of YAP effector genes is unknown. This knowledge is essential to rationally control cellular decision-making. Here we leverage optogenetics, live-imaging of transcription, and cell fate analysis to understand and control gene activation and cell behavior. We reveal that cells decode the steady-state concentrations and timing of YAP activation to control proliferation, cell fate, and expression of the pluripotency regulators Oct4 and Nanog. While oscillatory YAP inputs induce Oct4 expression and proliferation optimally at frequencies that mimic native dynamics, cellular differentiation requires persistently low YAP levels. We identify the molecular logic of the Oct4 dynamic decoder, which acts through an adaptive change sensor. Our work reveals how YAP levels and dynamics enable multiplexing of information transmission for the regulation of developmental decision-making and establishes a platform for the rational control of these behaviors.

Adhesion tunes speed and persistence by coordinating protrusions and extracellular matrix remodeling

Cell migration through 3D environments is essential to development, disease, and regeneration processes. Conceptual models of migration have been developed primarily on the basis of 2D cell behaviors, but a general understanding of 3D cell migration is still lacking due to the added complexity of the extracellular matrix. Here, using a multiplexed biophysical imaging approach for single-cell analysis of human cell lines, we show how the subprocesses of adhesion, contractility, actin cytoskeletal dynamics, and matrix remodeling integrate to produce heterogeneous migration behaviors. This single-cell analysis identifies three modes of cell speed and persistence coupling, driven by distinct modes of coordination between matrix remodeling and protrusive activity. The framework that emerges establishes a predictive model linking cell trajectories to distinct subprocess coordination states.

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

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

mRNA condensation fluidizes the cytoplasm

The intracellular environment is packed with macromolecules of mesoscale size, and this crowded milieu significantly influences cell physiology. When exposed to stress, mRNAs released after translational arrest condense with RNA binding proteins, resulting in the formation of membraneless RNA protein (RNP) condensates known as processing bodies (P-bodies) and stress granules (SGs). However, the impact of the assembly of these condensates on the biophysical properties of the crowded cytoplasmic environment remains unclear. Here, we find that upon exposure to stress, polysome collapse and condensation of mRNAs increases mesoscale particle diffusivity in the cytoplasm. Increased mesoscale diffusivity is required for the efficient formation of Q-bodies, membraneless organelles that coordinate degradation of misfolded peptides that accumulate during stress. Additionally, we demonstrate that polysome collapse and stress granule formation has a similar effect in mammalian cells, fluidizing the cytoplasm at the mesoscale. We find that synthetic, light-induced RNA condensation is sufficient to fluidize the cytoplasm, demonstrating a causal effect of RNA condensation. Together, our work reveals a new functional role for stress-induced translation inhibition and formation of RNP condensates in modulating the physical properties of the cytoplasm to effectively respond to stressful conditions.

Evolutionary Stability of Small Molecular Regulatory Networks That Exhibit Near-Perfect Adaptation

Large-scale protein regulatory networks, such as signal transduction systems, contain small-scale modules ('motifs') that carry out specific dynamical functions. Systematic characterization of the properties of small network motifs is therefore of great interest to molecular systems biologists. We simulate a generic model of three-node motifs in search of near-perfect adaptation, the property that a system responds transiently to a change in an environmental signal and then returns near-perfectly to its pre-signal state (even in the continued presence of the signal). Using an evolutionary algorithm, we search the parameter space of these generic motifs for network topologies that score well on a pre-defined measure of near-perfect adaptation. We find many high-scoring parameter sets across a variety of three-node topologies. Of all possibilities, the highest scoring topologies contain incoherent feed-forward loops (IFFLs), and these topologies are evolutionarily stable in the sense that, under 'macro-mutations' that alter the topology of a network, the IFFL motif is consistently maintained. Topologies that rely on negative feedback loops with buffering (NFLBs) are also high-scoring; however, they are not evolutionarily stable in the sense that, under macro-mutations, they tend to evolve an IFFL motif and may-or may not-lose the NFLB motif.

Positive feedback induces switch between distributive and processive phosphorylation of Hog1

Cellular decision making often builds on ultrasensitive MAPK pathways. The phosphorylation mechanism of MAP kinase has so far been described as either distributive or processive, with distributive mechanisms generating ultrasensitivity in theoretical analyses. However, the in vivo mechanism of MAP kinase phosphorylation and its activation dynamics remain unclear. Here, we characterize the regulation of the MAP kinase Hog1 in Saccharomyces cerevisiae via topologically different ODE models, parameterized on multimodal activation data. Interestingly, our best fitting model switches between distributive and processive phosphorylation behavior regulated via a positive feedback loop composed of an affinity and a catalytic component targeting the MAP kinase-kinase Pbs2. Indeed, we show that Hog1 directly phosphorylates Pbs2 on serine 248 (S248), that cells expressing a non-phosphorylatable (S248A) or phosphomimetic (S248E) mutant show behavior that is consistent with simulations of disrupted or constitutively active affinity feedback and that Pbs2-S248E shows significantly increased affinity to Hog1 in vitro. Simulations further suggest that this mixed Hog1 activation mechanism is required for full sensitivity to stimuli and to ensure robustness to different perturbations.

Two activating phosphorylation sites of Pbs2 MAP2K in the yeast HOG pathway are differentially dephosphorylated by four PP2C phosphatases Ptc1-Ptc4

To cope with an increased external osmolarity, the budding yeast Saccharomyces cerevisiae activates the Hog1 mitogen-activated kinase (MAPK) through the High-Osmolarity Glycerol (HOG) pathway, which governs adaptive responses to osmostress. In the HOG pathway, two apparently redundant upstream branches, termed SLN1 and SHO1, activate cognate MAP3Ks Ssk2/22 and Ste11, respectively. These MAP3Ks, when activated, phosphorylate and thus activate the Pbs2 MAP2K, which in turn phosphorylates and activates Hog1. Previous studies have shown that protein tyrosine phosphatases (PTP) and the serine/threonine protein phosphatases type 2C (PP2C) negatively regulate the HOG pathway to prevent its excessive and inappropriate activation, which is detrimental to cell growth. The tyrosine phosphatases Ptp2 and Ptp3 dephosphorylate Hog1 at Tyr-176, whereas the PP2Cs Ptc1 and Ptc2 dephosphorylate Hog1 at Thr-174. In contrast, the identities of phosphatases that dephosphorylate Pbs2 remained less clear. Here, we examined the phosphorylation status of Pbs2 at the activating phosphorylation sites Ser-514 and Thr-518 (S514 and T518) in various mutants, both in the unstimulated and osmostressed conditions. Thus, we found that Ptc1-Ptc4 collectively regulate Pbs2 negatively, but each Ptc acts differently to the two phosphorylation sites in Pbs2. T518 is predominantly dephosphorylated by Ptc1, whereas the effect of Ptc2-Ptc4 could be seen only when Ptc1 is absent. Conversely, S514 can be dephosphorylated by any of Ptc1-4 to an appreciable extent. We also show that Pbs2 dephosphorylation by Ptc1 requires the adaptor protein Nbp2 that recruits Ptc1 to Pbs2, thus highlighting the complex processes involved in regulating adaptive responses to osmostress.

Perfect adaptation achieved by transport limitations governs the inorganic phosphate response in S. cerevisiae

Cells cope with and adapt to ever-changing environmental conditions. Sophisticated regulatory networks allow cells to adjust to these fluctuating environments. One such archetypal system is the Saccharomyces cerevisiae Pho regulon. When external inorganic phosphate (P_i) concentration is low, the Pho regulon activates, expressing genes that scavenge external and internal P_i. However, the precise mechanism controlling this regulon remains elusive. We conducted a systems analysis of the Pho regulon on the single-cell level under well-controlled environmental conditions. This analysis identified a robust, perfectly adapted Pho regulon state in intermediate P_i conditions, and we identified an intermediate nuclear localization state of the transcriptional master regulator Pho4p. The existence of an intermediate nuclear Pho4p state unifies and resolves outstanding incongruities associated with the Pho regulon, explains the observed programmatic states of the Pho regulon, and improves our general understanding of how nature evolves and controls sophisticated gene regulatory networks. We further propose that robustness and perfect adaptation are not achieved through complex network-centric control but by simple transport biophysics. The ubiquity of multitransporter systems suggests that similar mechanisms could govern the function of other regulatory networks as well.

Protein-protein complexes can undermine ultrasensitivity-dependent biological adaptation

Robust perfect adaptation (RPA) is a ubiquitously observed signalling response across all scales of biological organization. A major class of network architectures that drive RPA in complex networks is the Opposer module-a feedback-regulated network into which specialized integral-computing 'opposer node(s)' are embedded. Although ultrasensitivity-generating chemical reactions have long been considered a possible mechanism for such adaptation-conferring opposer nodes, this hypothesis has relied on simplified Michaelian models, which neglect the presence of protein-protein complexes. Here we develop complex-complete models of interlinked covalent-modification cycles with embedded ultrasensitivity, explicitly capturing all molecular interactions and protein complexes. Strikingly, we demonstrate that the presence of protein-protein complexes thwarts the network's capacity for RPA in any 'free' active protein form, conferring RPA capacity instead on the concentration of a larger protein pool consisting of two distinct forms of a single protein. We further show that the presence of enzyme-substrate complexes, even at comparatively low concentrations, play a crucial and previously unrecognized role in controlling the RPA response-significantly reducing the range of network inputs for which RPA can obtain, and imposing greater parametric requirements on the RPA response. These surprising results raise fundamental new questions as to the biochemical requirements for adaptation-conferring Opposer modules within complex cellular networks.

Rate thresholds in cell signaling have functional and phenotypic consequences in non-linear time-dependent environments

All cells employ signal transduction pathways to respond to physiologically relevant extracellular cytokines, stressors, nutrient levels, hormones, morphogens, and other stimuli that vary in concentration and rate in healthy and diseased states. A central unsolved fundamental question in cell signaling is whether and how cells sense and integrate information conveyed by changes in the rate of extracellular stimuli concentrations, in addition to the absolute difference in concentration. We propose that different environmental changes over time influence cell behavior in addition to different signaling molecules or different genetic backgrounds. However, most current biomedical research focuses on acute environmental changes and does not consider how cells respond to environments that change slowly over time. As an example of such environmental change, we review cell sensitivity to environmental rate changes, including the novel mechanism of rate threshold. A rate threshold is defined as a threshold in the rate of change in the environment in which a rate value below the threshold does not activate signaling and a rate value above the threshold leads to signal activation. We reviewed p38/Hog1 osmotic stress signaling in yeast, chemotaxis and stress response in bacteria, cyclic adenosine monophosphate signaling in Amoebae, growth factors signaling in mammalian cells, morphogen dynamics during development, temporal dynamics of glucose and insulin signaling, and spatio-temproral stressors in the kidney. These reviewed examples from the literature indicate that rate thresholds are widespread and an underappreciated fundamental property of cell signaling. Finally, by studying cells in non-linear environments, we outline future directions to understand cell physiology better in normal and pathophysiological conditions.

Design Principles Underlying Robust Adaptation of Complex Biochemical Networks

Biochemical networks are often characterized by tremendous complexity-both in terms of the sheer number of interacting molecules ("nodes") and in terms of the varied and incompletely understood interactions among these molecules ("interconnections" or "edges"). Strikingly, the vast and intricate networks of interacting proteins that exist within each living cell have the capacity to perform remarkably robustly, and reproducibly, despite significant variations in concentrations of the interacting components from one cell to the next and despite mutability over time of biochemical parameters. Here we consider the ubiquitously observed and fundamentally important signalling response known as robust perfect adaptation (RPA). We have recently shown that all RPA-capable networks, even the most complex ones, must satisfy an extremely rigid set of design principles, and are modular, being decomposable into just two types of network building-blocks-opposer modules and balancer modules. Here we present an overview of the design principles that characterize all RPA-capable network topologies through a detailed examination of a collection of simple examples. We also introduce a diagrammatic method for studying the potential of a network to exhibit RPA, which may be applied without a detailed knowledge of the complex mathematical principles governing RPA.

Reconstructing gene regulatory networks of biological function using differential equations of multilayer perceptrons

BACKGROUND

Building biological networks with a certain function is a challenge in systems biology. For the functionality of small (less than ten nodes) biological networks, most methods are implemented by exhausting all possible network topological spaces. This exhaustive approach is difficult to scale to large-scale biological networks. And regulatory relationships are complex and often nonlinear or non-monotonic, which makes inference using linear models challenging.

RESULTS

In this paper, we propose a multi-layer perceptron-based differential equation method, which operates by training a fully connected neural network (NN) to simulate the transcription rate of genes in traditional differential equations. We verify whether the regulatory network constructed by the NN method can continue to achieve the expected biological function by verifying the degree of overlap between the regulatory network discovered by NN and the regulatory network constructed by the Hill function. And we validate our approach by adapting to noise signals, regulator knockout, and constructing large-scale gene regulatory networks using link-knockout techniques. We apply a real dataset (the mesoderm inducer Xenopus Brachyury expression) to construct the core topology of the gene regulatory network and find that Xbra is only strongly expressed at moderate levels of activin signaling.

CONCLUSION

We have demonstrated from the results that this method has the ability to identify the underlying network topology and functional mechanisms, and can also be applied to larger and more complex gene network topologies.

Universal structural requirements for maximal robust perfect adaptation in biomolecular networks

Adaptation is a running theme in biology. It allows a living system to survive and thrive in the face of unpredictable environments by maintaining key physiological variables at their desired levels through tight regulation. When one such variable is maintained at a certain value at the steady state despite perturbations to a single input, this property is called robust perfect adaptation (RPA). Here we address and solve the fundamental problem of maximal RPA (maxRPA), whereby, for a designated output variable, RPA is achieved with respect to perturbations in virtually all network parameters. In particular, we show that the maxRPA property imposes certain structural constraints on the network. We then prove that these constraints are fully characterized by simple linear algebraic stoichiometric conditions which differ between deterministic and stochastic descriptions of the dynamics. We use our results to derive a new internal model principle (IMP) for biomolecular maxRPA networks, akin to the celebrated IMP in control theory. We exemplify our results through several known biological examples of robustly adapting networks and construct examples of such networks with the aid of our linear algebraic characterization. Our results reveal the universal requirements for maxRPA in all biological systems, and establish a foundation for studying adaptation in general biomolecular networks, with important implications for both systems and synthetic biology.

CyberSco.Py an open-source software for event-based, conditional microscopy

Timelapse fluorescence microscopy imaging is routinely used in quantitative cell biology. However, microscopes could become much more powerful investigation systems if they were endowed with simple unsupervised decision-making algorithms to transform them into fully responsive and automated measurement devices. Here, we report CyberSco.Py, Python software for advanced automated timelapse experiments. We provide proof-of-principle of a user-friendly framework that increases the tunability and flexibility when setting up and running fluorescence timelapse microscopy experiments. Importantly, CyberSco.Py combines real-time image analysis with automation capability, which allows users to create conditional, event-based experiments in which the imaging acquisition parameters and the status of various devices can be changed automatically based on the image analysis. We exemplify the relevance of CyberSco.Py to cell biology using several use case experiments with budding yeast. We anticipate that CyberSco.Py could be used to address the growing need for smart microscopy systems to implement more informative quantitative cell biology experiments.

Dynamics and Sensitivity of Signaling Pathways

Purpose of Review

Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are frequently associated with cancer and can result in cells acquiring an ability to divide and grow uncontrollably. Because signaling pathways play such a significant role in cancer initiation and advancement, their constituent proteins are attractive therapeutic targets. In this review, we discuss how signaling pathway modeling can assist with identifying effective drugs for treating diseases, such as cancer. An achievement that would facilitate the use of such models is their ability to identify controlling biochemical parameters in signaling pathways, such as molecular abundances and chemical reaction rates, because this would help determine effective points of attack by therapeutics.

Recent Findings

We summarize the current state of understanding the sensitivity of phosphorylation cycles with and without sequestration. We also describe some basic properties of regulatory motifs including feedback and feedforward regulation.

Summary

Although much recent work has focused on understanding the dynamics and particularly the sensitivity of signaling networks in eukaryotic systems, there is still an urgent need to build more scalable models of signaling networks that can appropriately represent their complexity across different cell types and tumors.

A roadmap to understanding diversity and function of coral reef-associated fungi

Tropical coral reefs are hotspots of marine productivity, owing to the association of reef-building corals with endosymbiotic algae and metabolically diverse bacterial communities. However, the functional importance of fungi, well-known for their contribution to shaping terrestrial ecosystems and global nutrient cycles, remains underexplored on coral reefs. We here conceptualize how fungal functional traits may have facilitated the spread, diversification, and ecological adaptation of marine fungi on coral reefs. We propose that functions of reef-associated fungi may be diverse and go beyond their hitherto described roles of pathogens and bioeroders, including but not limited to reef-scale biogeochemical cycles and the structuring of coral-associated and environmental microbiomes via chemical mediation. Recent technological and conceptual advances will allow the elucidation of the physiological, ecological, and chemical contributions of understudied marine fungi to coral holobiont and reef ecosystem functioning and health and may help provide an outlook for reef management actions.

A genetic mammalian proportional-integral feedback control circuit for robust and precise gene regulation

To survive in the harsh environments they inhabit, cells have evolved sophisticated regulatory mechanisms that can maintain a steady internal milieu or homeostasis. This robustness, however, does not generally translate to engineered genetic circuits, such as the ones studied by synthetic biology. Here, we introduce an implementation of a minimal and universal gene regulatory motif that produces robust perfect adaptation for mammalian cells, and we improve on it by enhancing the precision of its regulation.

The processes that keep a cell alive are constantly challenged by unpredictable changes in its environment. Cells manage to counteract these changes by employing sophisticated regulatory strategies that maintain a steady internal milieu. Recently, the antithetic integral feedback motif has been demonstrated to be a minimal and universal biological regulatory strategy that can guarantee robust perfect adaptation for noisy gene regulatory networks in Escherichia coli. Here, we present a realization of the antithetic integral feedback motif in a synthetic gene circuit in mammalian cells. We show that the motif robustly maintains the expression of a synthetic transcription factor at tunable levels even when it is perturbed by increased degradation or its interaction network structure is perturbed by a negative feedback loop with an RNA-binding protein. We further demonstrate an improved regulatory strategy by augmenting the antithetic integral motif with additional negative feedback to realize antithetic proportional–integral control. We show that this motif produces robust perfect adaptation while also reducing the variance of the regulated synthetic transcription factor. We demonstrate that the integral and proportional–integral feedback motifs can mitigate the impact of gene expression burden, and we computationally explore their use in cell therapy. We believe that the engineering of precise and robust perfect adaptation will enable substantial advances in industrial biotechnology and cell-based therapeutics.

Transcription feedback dynamics in the wake of cytoplasmic mRNA degradation shutdown

In the last decade, multiple studies demonstrated that cells maintain a balance of mRNA production and degradation, but the mechanisms by which cells implement this balance remain unknown. Here, we monitored cells' total and recently-transcribed mRNA profiles immediately following an acute depletion of Xrn1-the main 5'-3' mRNA exonuclease-which was previously implicated in balancing mRNA levels. We captured the detailed dynamics of the adaptation to rapid degradation of Xrn1 and observed a significant accumulation of mRNA, followed by a delayed global reduction in transcription and a gradual return to baseline mRNA levels. We found that this transcriptional response is not unique to Xrn1 depletion; rather, it is induced earlier when upstream factors in the 5'-3' degradation pathway are perturbed. Our data suggest that the mRNA feedback mechanism monitors the accumulation of inputs to the 5'-3' exonucleolytic pathway rather than its outputs.

A hierarchy of biomolecular proportional-integral-derivative feedback controllers for robust perfect adaptation and dynamic performance

Proportional-Integral-Derivative (PID) feedback controllers are the most widely used controllers in industry. Recently, the design of molecular PID-controllers has been identified as an important goal for synthetic biology and the field of cybergenetics. In this paper, we consider the realization of PID-controllers via biomolecular reactions. We propose an array of topologies offering a compromise between simplicity and high performance. We first demonstrate that different biomolecular PI-controllers exhibit different performance-enhancing capabilities. Next, we introduce several derivative controllers based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop, which can be augmented by PI-components to yield PID-controllers. We demonstrate that PID-controllers can enhance stability and dynamic performance, and can also reduce stochastic noise. Finally, we provide an experimental demonstration using a hybrid setup where in silico PID-controllers regulate a genetic circuit in single yeast cells.

Synthetic robust perfect adaptation achieved by negative feedback coupling with linear weak positive feedback

Unlike their natural counterparts, synthetic genetic circuits are usually fragile in the face of environmental perturbations and genetic mutations. Several theoretical robust genetic circuits have been designed, but their performance under real-world conditions has not yet been carefully evaluated. Here, we designed and synthesized a new robust perfect adaptation circuit composed of two-node negative feedback coupling with linear positive feedback on the buffer node. As a key feature, the linear positive feedback was fine-tuned to evaluate its necessity. We found that the desired function was robustly achieved when genetic parameters were varied by systematically perturbing all interacting parts within the topology, and the necessity of the completeness of the topological structures was evaluated by destroying key circuit features. Furthermore, different environmental perturbances were imposed onto the circuit by changing growth rates, carbon metabolic strategies and even chassis cells, and the designed perfect adaptation function was still achieved under all conditions. The successful design of a robust perfect adaptation circuit indicated that the top-down design strategy is capable of predictably guiding bottom-up engineering for robust genetic circuits. This robust adaptation circuit could be integrated as a motif into more complex circuits to robustly implement more sophisticated and critical biological functions.

Hyperosmotic stress-induced microtubule disassembly in Chlamydomonas reinhardtii

BACKGROUND

Land plants respond to drought and salinity by employing multitude of sophisticated mechanisms with physiological and developmental consequences. Abscisic acid-mediated signaling pathways have evolved as land plant ancestors explored their habitats toward terrestrial dry area, and now play major roles in hyperosmotic stress responses in flowering plants. Green algae living in fresh water habitat do not possess abscisic acid signaling pathways but need to cope with increasing salt concentrations or high osmolarity when challenged with adverse aquatic environment. Hyperosmotic stress responses in green algae are largely unexplored.

RESULTS

In this study, we characterized hyperosmotic stress-induced cytoskeletal responses in Chlamydomonas reinhardtii, a fresh water green algae. The Chlamydomonas PROPYZAMIDE-HYPERSENSITEVE 1 (PHS1) tubulin kinase quickly and transiently phosphorylated a large proportion of cellular α-tubulin at Thr349 in G1 phase and during mitosis, which resulted in transient disassembly of microtubules, when challenged with > 0.2 M sorbitol or > 0.1 M NaCl. By using phs1 loss-of-function algal mutant cells, we demonstrated that transient microtubule destabilization by sorbitol did not affect cell growth in G1 phase but delayed mitotic cell cycle progression. Genome sequence analyses indicate that PHS1 genes evolved in ancestors of the Chlorophyta. Interestingly, PHS1 genes are present in all sequenced genomes of freshwater Chlorophyta green algae (including Chlamydomonas) but are absent in some marine algae of this phylum.

CONCLUSION

PHS1-mediated tubulin phosphorylation was found to be partly responsible for the efficient stress-responsive mitotic delay in Chlamydomonas cells. Ancient hyperosmotic stress-triggered cytoskeletal remodeling responses thus emerged when the PHS1 tubulin kinase gene evolved in freshwater green algae.

The high osmolarity glycerol (HOG) pathway in fungi†

While fungi are widely occupying nature, many species are responsible for devastating mycosis in humans. Such niche diversity explains how quick fungal adaptation is necessary to endow the capacity of withstanding fluctuating environments and to cope with host-imposed conditions. Among all the molecular mechanisms evolved by fungi, the most studied one is the activation of the phosphorelay signalling pathways, of which the high osmolarity glycerol (HOG) pathway constitutes one of the key molecular apparatus underpinning fungal adaptation and virulence. In this review, we summarize the seminal knowledge of the HOG pathway with its more recent developments. We specifically described the HOG-mediated stress adaptation, with a particular focus on osmotic and oxidative stress, and point out some lags in our understanding of its involvement in the virulence of pathogenic species including, the medically important fungi Candida albicans, Cryptococcus neoformans, and Aspergillus fumigatus, compared to the model yeast Saccharomyces cerevisiae. Finally, we also highlighted some possible applications of the HOG pathway modifications to improve the fungal-based production of natural products in the industry.

Rapid prototyping and design of cybergenetic single-cell controllers

The design and implementation of synthetic circuits that operate robustly in the cellular context is fundamental for the advancement of synthetic biology. However, their practical implementation presents challenges due to low predictability of synthetic circuit design and time-intensive troubleshooting. Here, we present the Cyberloop, a testing framework to accelerate the design process and implementation of biomolecular controllers. Cellular fluorescence measurements are sent in real-time to a computer simulating candidate stochastic controllers, which in turn compute the control inputs and feed them back to the controlled cells via light stimulation. Applying this framework to yeast cells engineered with optogenetic tools, we examine and characterize different biomolecular controllers, test the impact of non-ideal circuit behaviors such as dilution on their operation, and qualitatively demonstrate improvements in controller function with certain network modifications. From this analysis, we derive conditions for desirable biomolecular controller performance, thereby avoiding pitfalls during its biological implementation.

A novel two-layer-integrated microfluidic device for high-throughput yeast proteomic dynamics analysis at the single-cell level

Current microfluidic methods for studying multicell strains (e.g., m-types) with multienvironments (e.g., n-types) require large numbers of inlets/outlets (m*n), a complicated procedure or expensive machinery. Here, we developed a novel two-layer-integrated method to combine different PDMS microchannel layers with different functions into one chip by a PDMS through-hole array, which improved the design of a PDMS-based microfluidic system. Using this method, we succeeded in converting 2 × m × n inlets/outlets into m + n inlets/outlets and reduced the time cost of loading processing (from m × n to m) of the device for studying multicell strains (e.g., m-types) in varied multitemporal environments (i.e., n-types). Using this device, the dynamic behavior of the cell-stress-response proteins was studied when the glucose concentration decreased from 2% to a series of lower concentrations. Our device could also be widely used in high-throughput studies of various stress responses, and the new concept of a multilayer-integrated fabrication method could greatly improve the design of PDMS-based microfluidic systems.

T cells selectively filter oscillatory signals on the minutes timescale

T cells experience complex temporal patterns of stimulus via receptor-ligand-binding interactions with surrounding cells. From these temporal patterns, T cells are able to pick out antigenic signals while establishing self-tolerance. Although features such as duration of antigen binding have been examined, our understanding of how T cells interpret signals with different frequencies or temporal stimulation patterns is relatively unexplored. We engineered T cells to respond to light as a stimulus by building an optogenetically controlled chimeric antigen receptor (optoCAR). We discovered that T cells respond to minute-scale oscillations of activation signal by stimulating optoCAR T cells with tunable pulse trains of light. Systematically scanning signal oscillation period from 1 to 150 min revealed that expression of CD69, a T cell activation marker, reached a local minimum at a period of ∼25 min (corresponding to 5 to 15 min pulse widths). A combination of inhibitors and genetic knockouts suggest that this frequency filtering mechanism lies downstream of the Erk signaling branch of the T cell response network and may involve a negative feedback loop that diminishes Erk activity. The timescale of CD69 filtering corresponds with the duration of T cell encounters with self-peptide-presenting APCs observed via intravital imaging in mice, indicating a potential functional role for temporal filtering in vivo. This study illustrates that the T cell signaling machinery is tuned to temporally filter and interpret time-variant input signals in discriminatory ways.

Ultrasensitivity and bistability in covalent-modification cycles with positive autoregulation

Switch-like behaviours in biochemical networks are of fundamental significance in biological signal processing, and exist as two distinct types: ultra-sensitivity and bistability. Here we propose two new models of a reversible covalent-modification cycle with positive autoregulation (PAR), a motif structure that is thought to be capable of both ultrasensitivity and bistability in different parameter regimes. These new models appeal to a modelling framework that we call complex-complete, which accounts fully for the molecular complexities of the underlying signalling mechanisms. Each of the two new models encodes a specific molecular mechanism for PAR. We demonstrate that the modelling simplifications for PAR models that have been used in previous work, which rely on Michaelian approximations, are unable to accurately recapitulate the qualitative signalling responses supported by our detailed models. Strikingly, we show that complex-complete PAR models are capable of new qualitative responses such as one-way switches and a 'prozone' effect, depending on the specific PAR-encoding mechanism, which are not supported by Michaelian simplifications. Our results highlight the critical importance of accurately representing the molecular details of biochemical signalling mechanisms, and strongly suggest that the Michaelian approximation is inadequate for predictive models of enzyme-mediated chemical reactions with added regulations such as PAR.

Effect of Osmotic Stress on the Growth, Development and Pathogenicity of Setosphaeria turcica

Osmotic stress is a severe condition frequently encountered by microorganisms; however, there is limited knowledge on the influence of hyperosmotic stress on the growth, development and pathogenicity of phytopathogenic fungi. Here, three osmotic conditions (0.4 M NaCl, 0.4 M KCl, and 0.6 M sorbitol supplemented in potato dextrose agar medium) were used to identify the effect of osmotic stress on the growth, development and pathogenicity of Setosphaeria turcica which is a plant pathogenic fungus and causes northern corn leaf blight disease in maize, sorghum, and related grasses. In osmotic stress, the growth rate of mycelium was decreased, and the number of vesicular structures and flocculent secretion outside the hypha cell wall were significantly increased. The qRT-PCR results showed that the osmotic stress quickly activated the HOG-MAPK pathway, up-regulated the expression of the downstream genes, and these genes were most highly expressed within 30 min of exposure to osmotic stress. Furthermore, the germination rate and the yield of conidia were significantly higher under osmotic stress than in the control. A pathogenicity analysis confirmed that pathogenicity of the conidia which were cultured under osmotic stress was significantly enhanced. By analyzing the knock-out mutants of an osmotic stress responsed gene StFPS1, an aquaglyceroporin downstream of the HOG-MAPK pathway, we found that StFPS1 was involved in the formation of appressorium and penetration peg, which affected the penetration ability of S. turcica. In summary, our work explained the correlation between osmotic stress and growth, development, and pathogenicity in S. turcica.

Building predictive signaling models by perturbing yeast cells with time-varying stimulations resulting in distinct signaling responses

This protocol provides a step-by-step approach to perturb single cells with time-varying stimulation profiles, collect distinct signaling responses, and use these to infer a system of ordinary differential equations to capture and predict dynamics of protein-protein regulation in signal transduction pathways. The models are validated by predicting the signaling activation upon new cell stimulation conditions. In comparison to using standard step-like stimulations, application of diverse time-varying cell stimulations results in better inference of model parameters and substantially improves model predictions.

For complete details on the use and results of this protocol, please refer to Jashnsaz et al. (2020).

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Diverse time-varying cell stimulations result in distinct signaling activation dynamics

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Signaling models fit step stimuli responses well but result in poor predictions

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Distinct responses upon diverse time-varying stimulations improve model predictions

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Temporal stimulation of pathways result in novel signaling dynamics and mechanisms

An engineered protein-phosphorylation toggle network with implications for endogenous network discovery

Synthetic biological networks comprising fast, reversible reactions could enable engineering of new cellular behaviors that are not possible with slower regulation. Here, we created a bistable toggle switch in Saccharomyces cerevisiae using a cross-repression topology comprising 11 protein-protein phosphorylation elements. The toggle is ultrasensitive, can be induced to switch states in seconds, and exhibits long-term bistability. Motivated by our toggle's architecture and size, we developed a computational framework to search endogenous protein pathways for other large and similar bistable networks. Our framework helped us to identify and experimentally verify five formerly unreported endogenous networks that exhibit bistability. Building synthetic protein-protein networks will enable bioengineers to design fast sensing and processing systems, allow sophisticated regulation of cellular processes, and aid discovery of endogenous networks with particular functions.

Increased xerotolerance of Saccharomyces cerevisiae during an osmotic pressure ramp over several generations

Although mechanisms involved in response of Saccharomyces cerevisiae to osmotic challenge are well described for low and sudden stresses, little is known about how cells respond to a gradual increase of the osmotic pressure (reduced water activity; aw ) over several generations as it could encounter during drying in nature or in food processes. Using glycerol as a stressor, we propagated S. cerevisiae through a ramp of the osmotic pressure (up to high molar concentrations to achieve testing-to-destruction) at the rate of 1.5 MPa day-1 from 1.38 to 58.5 MPa (0.990-0.635 aw ). Cultivability (measured at 1.38 MPa and at the harvest osmotic pressure) and glucose consumption compared with the corresponding sudden stress showed that yeasts were able to grow until about 10.5 MPa (0.926 aw ) and to survive until about 58.5 MPa, whereas glucose consumption occurred until 13.5 MPa (about 0.915 aw ). Nevertheless, the ramp conferred an advantage since yeasts harvested at 10.5 and 34.5 MPa (0.778 aw ) showed a greater cultivability than glycerol-shocked cells after a subsequent shock at 200 MPa (0.234 aw ) for 2 days. FTIR analysis revealed structural changes in wall and proteins in the range 1.38-10.5 MPa, which would be likely to be involved in the resistance at extreme osmotic pressure.

Perfect adaptation in biology

A distinctive feature of many biological systems is their ability to adapt to persistent stimuli or disturbances that would otherwise drive them away from a desirable steady state. The resulting stasis enables organisms to function reliably while being subjected to very different external environments. This perspective concerns a stringent type of biological adaptation, robust perfect adaptation (RPA), that is resilient to certain network and parameter perturbations. As in engineered control systems, RPA requires that the regulating network satisfy certain structural constraints that cannot be avoided. We elucidate these ideas using biological examples from systems and synthetic biology. We then argue that understanding the structural constraints underlying RPA allows us to look past implementation details and offers a compelling means to unravel regulatory biological complexity.

Control engineering and synthetic biology: working in synergy for the analysis and control of microbial systems

The implementation of novel functionalities in living cells is a key aspect of synthetic biology. In the last decade, the field of synthetic biology has made progress working in synergy with control engineering, whose solid framework has provided concepts and tools to analyse biological systems and guide their design. In this review, we briefly highlight recent work focused on the application of control theoretical concepts and tools for the analysis and design of synthetic biology systems in microbial cells.

An Automated Tabletop Continuous Culturing System with Multicolor Fluorescence Monitoring for Microbial Gene Expression and Long-Term Population Dynamics

Real-time monitoring of gene expression dynamics and population levels in a multispecies microbial community could enable the study of the role of changing gene expression patterns on eco-evolutionary outcomes. Here we report the design and validation of a unique experimental platform with an in situ fluorescence measurement system that has high dynamic range and temporal resolution and is capable of monitoring multiple fluorophores for long-term gene expression and population dynamics experiments. We demonstrate the capability of our system to capture gene expression dynamics in response to external perturbations in two synthetic genetic systems: a simple inducible genetic circuit and a bistable toggle switch. Finally, in exploring the population dynamics of a two species microbial community, we show that our system can capture the switch between competitive exclusion and long-term coexistence in response to different nutrient conditions.

Energy-Based Modeling of the Feedback Control of Biomolecular Systems With Cyclic Flow Modulation

Energy-based modelling brings engineering insight to the understanding of biomolecular systems. It is shown how well-established control engineering concepts, such as loop-gain, arise from energy feedback loops and are therefore amenable to control engineering insight. In particular, a novel method is introduced to allow the transfer function based approach of classical linear control to be utilised in the analysis of feedback systems modelled by network thermodynamics and thus amalgamate energy-based modelling with control systems analysis. The approach is illustrated using a class of metabolic cycles with activation and inhibition leading to the concept of Cyclic Flow Modulation.

Stress-induced growth rate reduction restricts metabolic resource utilization to modulate osmo-adaptation time

A near-constant feature of stress responses is a downregulation or arrest of the cell cycle, resulting in transient growth slowdown. To investigate the role of growth slowdown in the hyperosmotic shock response of S. cerevisiae, we perturbed the G1/S checkpoint protein Sic1 to enable osmo-stress response activation with diminished growth slowdown. We document that in this mutant, adaptation to stress is accelerated rather than delayed. This accelerated recovery of the mutant proceeds by liquidation of internal glycogen stores, which are then shunted into the osmo-shock response. Therefore, osmo-adaptation in wild-type cells is delayed because growth slowdown prevents full accessibility to cellular glycogen stores. However, faster adaptation comes at the cost of acute sensitivity to subsequent osmo-stresses. We suggest that stress-induced growth slowdown acts as an arbiter to regulate the resources devoted to osmo-shock, balancing short-term adaptation with long-term robustness.

Stochastic models for single-cell data: Current challenges and the way forward

Although the quantity and quality of single-cell data have progressed rapidly, making quantitative predictions with single-cell stochastic models remains challenging. The stochastic nature of cellular processes leads to at least three challenges in building models with single-cell data: (a) because variability in single-cell data can be attributed to multiple different sources, it is difficult to rule out conflicting mechanistic models that explain the same data equally well; (b) the distinction between interesting biological variability and experimental variability is sometimes ambiguous; (c) the nonstandard distributions of single-cell data can lead to violations of the assumption of symmetric errors in least-squares fitting. In this review, we first discuss recent studies that overcome some of the challenges or set up a promising direction and then introduce some powerful statistical approaches utilized in these studies. We conclude that applying and developing statistical approaches could lead to further progress in building stochastic models for single-cell data.

Ultrasensitive molecular controllers for quasi-integral feedback

Feedback control has enabled the success of automated technologies by mitigating the effects of variability, unknown disturbances, and noise. While it is known that biological feedback loops reduce the impact of noise and help shape kinetic responses, many questions remain about how to design molecular integral controllers. Here, we propose a modular strategy to build molecular quasi-integral feedback controllers, which involves following two design principles. The first principle is to utilize an ultrasensitive response, which determines the gain of the controller and influences the steady-state error. The second is to use a tunable threshold of the ultrasensitive response, which determines the equilibrium point of the system. We describe a reaction network, named brink controller, that satisfies these conditions by combining molecular sequestration and an activation/deactivation cycle. With computational models, we examine potential biological implementations of brink controllers, and we illustrate different example applications.

Kinetics of osmotic stress regulate a cell fate switch of cell survival

Exposure of cells to diverse types of stressful environments differentially regulates cell fate. Although many types of stresses causing this differential regulation are known, it is unknown how changes over time of the same stressor regulate cell fate. Changes in extracellular osmolarity are critically involved in physiological and pathophysiological processes in several tissues. We observe that human cells survive gradual but not acute hyperosmotic stress. We find that stress, caspase, and apoptosis signaling do not activate during gradual stress in contrast to acute treatments. Contrary to the current paradigm, we see a substantial accumulation of proline in cells treated with gradual but not acute stresses. We show that proline can protect cells from hyperosmotic stress similar to the osmoprotection in plants and bacteria. Our studies found a cell fate switch that enables cells to survive gradually changing stress environments by preventing caspase activation and protect cells through proline accumulation.

A rate threshold mechanism regulates MAPK stress signaling and survival

Cells are exposed to changes in extracellular stimulus concentration that vary as a function of rate. However, how cells integrate information conveyed from stimulation rate along with concentration remains poorly understood. Here, we examined how varying the rate of stress application alters budding yeast mitogen-activated protein kinase (MAPK) signaling and cell behavior at the single-cell level. We show that signaling depends on a rate threshold that operates in conjunction with stimulus concentration to determine the timing of MAPK signaling during rate-varying stimulus treatments. We also discovered that the stimulation rate threshold and stimulation rate-dependent cell survival are sensitive to changes in the expression levels of the Ptp2 phosphatase, but not of another phosphatase that similarly regulates osmostress signaling during switch-like treatments. Our results demonstrate that stimulation rate is a regulated determinant of cell behavior and provide a paradigm to guide the dissection of major stimulation rate dependent mechanisms in other systems.

Diverse Cell Stimulation Kinetics Identify Predictive Signal Transduction Models

Computationally understanding the molecular mechanisms that give rise to cell signaling responses upon different environmental, chemical, and genetic perturbations is a long-standing challenge that requires models that fit and predict quantitative responses for new biological conditions. Overcoming this challenge depends not only on good models and detailed experimental data but also on the rigorous integration of both. We propose a quantitative framework to perturb and model generic signaling networks using multiple and diverse changing environments (hereafter "kinetic stimulations") resulting in distinct pathway activation dynamics. We demonstrate that utilizing multiple diverse kinetic stimulations better constrains model parameters and enables predictions of signaling dynamics that would be impossible using traditional dose-response or individual kinetic stimulations. To demonstrate our approach, we use experimentally identified models to predict signaling dynamics in normal, mutated, and drug-treated conditions upon multitudes of kinetic stimulations and quantify which proteins and reaction rates are most sensitive to which extracellular stimulations.

Age-dependent decline in stress response capacity revealed by proteins dynamics analysis

The aging process is regarded as the progressive loss of physiological integrity, leading to impaired biological functions and the increased vulnerability to death. Among various biological functions, stress response capacity enables cells to alter gene expression patterns and survive when facing internal and external stresses. Here, we explored changes in stress response capacity during the replicative aging of Saccharomyces cerevisiae. To this end, we used a high-throughput microfluidic device to deliver intermittent pulses of osmotic stress and tracked the dynamic changes in the production of downstream stress-responsive proteins, in a large number of individual aging cells. Cells showed a gradual decline in stress response capacity of these osmotic-related downstream proteins during the aging process after the first 5 generations. Among the downstream stress-responsive genes and unrelated genes tested, the residual level of response capacity of Trehalose-6-Phosphate Synthase (TPS2) showed the best correlation with the cell remaining lifespan. By monitor dynamics of the upstream transcription factors and mRNA of Tps2, it was suggested that the decline in downstream stress response capacity was caused by the decline of translational rate of these proteins during aging.

Single-particle imaging of stress-promoters induction reveals the interplay between MAPK signaling, chromatin and transcription factors

Precise regulation of gene expression in response to environmental changes is crucial for cell survival, adaptation and proliferation. In eukaryotic cells, extracellular signal integration is often carried out by Mitogen-Activated Protein Kinases (MAPK). Despite a robust MAPK signaling activity, downstream gene expression can display a great variability between single cells. Using a live mRNA reporter, here we monitor the dynamics of transcription in Saccharomyces cerevisiae upon hyper-osmotic shock. We find that the transient activity of the MAPK Hog1 opens a temporal window where stress-response genes can be activated. We show that the first minutes of Hog1 activity are essential to control the activation of a promoter. Chromatin repression on a locus slows down this transition and contributes to the variability in gene expression, while binding of transcription factors increases the level of transcription. However, soon after Hog1 activity peaks, negative regulators promote chromatin closure of the locus and transcription progressively stops.