Summary Information about environmental stimuli is often transmitted using common signalling molecules, but the mechanisms that ensure signalling specificity are not entirely known. Here we show that the identities and intensities of different stresses are transmitted by modulation of the amplitude, duration or frequency of nuclear translocation of the budding yeast general stress responsive transcription factor Msn2. Through artificial control of the dynamics of Msn2 translocation, we reveal how distinct dynamical schemes differentially affect reporter gene expression. Using a simple model, we predict stress-induced reporter gene expression from single-cell translocation dynamics. We then demonstrate that the response of natural target genes to dynamical modulation of Msn2 translocation is influenced by differences in the kinetics of promoter transitions and transcription factor binding properties. Thus, multiple environmental signals can trigger qualitatively different dynamics of a single transcription factor, and influence gene expression patterns.

Signaling pathways can induce different dynamics of transcription factor (TF) activation. We explored how TFs process signaling inputs to generate diverse dynamic responses. The budding yeast general stress responsive TF Msn2 acted as a tunable signal processor that could track, filter, or integrate signals in an input dependent manner. This tunable signal processing appears to originate from dual regulation of both nuclear import and export by phosphorylation, as mutants with one form of regulation sustained only one signal processing function. Versatile signal processing by Msn2 is crucial for generating distinct dynamic responses to different natural stresses. Our findings reveal how complex signal processing functions are integrated into a single molecule and provide a guide for the design of TFs with “programmable” signal processing functions.

Cell differentiation requires the ability to detect and respond appropriately to a variety of extracellular signals. Here we investigate a differentiation switch induced by changes in the concentration of a single stimulus. Yeast cells exposed to high doses of mating pheromone undergo cell division arrest. Cells at intermediate doses become elongated and divide in the direction of a pheromone gradient (chemotropic growth). Either of the pheromone-responsive MAP kinases, Fus3 and Kss1, promotes cell elongation, but only Fus3 promotes chemotropic growth. Whereas Kss1 is activated rapidly and with a graded dose-response profile, Fus3 is activated slowly and exhibits a steeper dose-response relationship (ultrasensitivity). Fus3 activity requires the scaffold protein Ste5; when binding to Ste5 is abrogated, Fus3 behaves like Kss1, and the cells no longer respond to a gradient or mate efficiently with distant partners. We propose that scaffold proteins serve to modulate the temporal and dose-response behavior of the MAP kinase.

We perform a systematic analysis of mechanisms of feedback regulation that underlie short-term adaptation in intracellular signaling systems. Upon receiving an external cue, these systems generate a transient response that quickly returns to basal levels even if the stimulus persists. Signaling pathways capable of short-term adaptation are found in systems as diverse as the high osmolarity response of yeast, gradient sensing in Dictyostelium, and the cytokine response in vertebrates. Using mathematical analysis and computational experiments, we compare different feedback architectures in terms of response amplitude and duration, ability to adapt, and response to variable stimulus levels. Our analysis reveals three important features of these systems: 1), multiple step signaling cascades improve sensitivity to low doses by an effect distinct from signal amplification; 2), some feedback architectures act as signal transducers converting stimulus strength into response duration; and 3), feedback deactivation acts as a dose-dependent switch between transient and sustained responses. Finally, we present characteristic features for each form of feedback regulation that can aid in their identification.

Chromatin instability and mitochondrial decline are conserved processes that contribute to cellular aging. Although both processes have been explored individually in the context of their distinct signaling pathways, the mechanism that determines which process dominates during aging of individual cells is unknown. We show that interactions between the chromatin silencing and mitochondrial pathways lead to an epigenetic landscape of yeast replicative aging with multiple equilibrium states that represent different types of terminal states of aging. The structure of the landscape drives single-cell differentiation toward one of these states during aging, whereby the fate is determined quite early and is insensitive to intracellular noise. Guided by a quantitative model of the aging landscape, we genetically engineered a long-lived equilibrium state characterized by an extended life span.

Many different signaling pathways share common components but nevertheless invoke distinct physiological responses. In yeast, the adaptor protein Ste50 functions in multiple mitogen-activated protein (MAP) kinase pathways, each with unique dynamical and developmental properties. Although Kss1 activity is sustained and promotes invasive growth, Hog1 activity is transient and promotes cell adaptation to osmotic stress. Here we show that osmotic stress activates Kss1 as well as Hog1. We show further that Hog1 phosphorylates Ste50 and that phosphorylation of Ste50 limits the duration of Kss1 activation and prevents invasive growth under high osmolarity growth conditions. Thus feedback regulation of a shared component can restrict the activity of a competing MAP kinase to ensure signal fidelity.All living organisms respond to specific external cues and initiate the appropriate developmental or metabolic responses. In many cases, extracellular stimuli lead to activation of MAP 2 kinases, which in turn initiate distinct, and often mutually exclusive, cellular behaviors including cell growth, movement, differentiation, and death. Therefore the regulation and coordination of multiple kinases are essential for the cell to respond appropriately to a changing environment (1). However, the underlying mechanisms ensuring pathway fidelity are not well understood.The MAP kinases in yeast Saccharomyces cerevisiae provide a powerful model to study the mechanisms of signal specificity. Two different MAP kinases, Fus3 and Kss1, function in the mating-response pathway leading to fusion of haploid a-and ␣-type cells. In this case, pheromone stimulation leads to activation of a protein kinase cascade that includes Ste20, Ste11, Ste7, and ultimately Fus3 and Kss1 (2).Nutrient-poor conditions lead to activation of the same kinase components, with the exception of Fus3 (3, 4). In this alternate developmental pathway, the cells exhibit altered budding, formation of long branching filaments, as well as increased adherence and invasion of the substratum. A third pathway leads to activation of the high osmolarity glycerol (HOG) response kinase Hog1 (5, 6). The HOG response is initiated by stimulation of two putative osmosensing proteins, Sln1 and Sho1 (7,8). Sln1 activates two partially redundant kinases, Ssk2 and Ssk22, which then activate the MAP kinase kinase Pbs2 and ultimately Hog1. Sho1 recruits a distinct kinase Ste11 to activate Pbs2 and Hog1. In either case, Hog1 induces production of glycerol that serves to balance intracellular osmotic pressure with the external environment and thereby enables cell survival (9 -11).Thus Ste11 is required for signaling by Sho1 as well as by mating pheromones. Another shared component is Ste50, which forms a stable complex with Ste11 (12-17). Although the Sho1 branch of the Hog1 pathway shares components with the Fus3 and Kss1 pathways, osmotic stimulation does not normally induce mating or invasive growth. If Hog1 expression or catalytic activity is abrogated, however, osmotic stimulation leads to ...

These findings reveal a novel phosphorylation-dependent feedback loop leading to diminished cellular responses to an osmotic-stress stimulus.

Cellular aging plays an important role in many diseases, such as cancers, metabolic syndromes, and neurodegenerative disorders. There has been steady progress in identifying aging-related factors such as reactive oxygen species and genomic instability, yet an emerging challenge is to reconcile the contributions of these factors with the fact that genetically identical cells can age at significantly different rates. Such complexity requires single-cell analyses designed to unravel the interplay of aging dynamics and cell-to-cell variability. Here we use microfluidic technologies to track the replicative aging of single yeast cells and reveal that the temporal patterns of heterochromatin silencing loss regulate cellular life span. We found that cells show sporadic waves of silencing loss in the heterochromatic ribosomal DNA during the early phases of aging, followed by sustained loss of silencing preceding cell death. Isogenic cells have different lengths of the early intermittent silencing phase that largely determine their final life spans. Combining computational modeling and experimental approaches, we found that the intermittent silencing dynamics is important for longevity and is dependent on the conserved Sir2 deacetylase, whereas either sustained silencing or sustained loss of silencing shortens life span. These findings reveal that the temporal patterns of a key molecular process can directly influence cellular aging, and thus could provide guidance for the design of temporally controlled strategies to extend life span.replicative aging | single-cell analysis | microfluidics | chromatin silencing | computational modeling C ellular aging is generally driven by the accumulation of genetic and cellular damage (1, 2). Although much progress has been made in identifying molecular factors that influence life span, what remains sorely missing is an understanding of how these factors interact and change dynamically during the aging process. This is in part because aging is a complex process wherein isogenic cells have various intrinsic causes of aging and widely different rates of aging. As a result, static population-based approaches could be insufficient to fully reveal sophisticated dynamic changes during aging. Recent developments in single-cell analyses to unravel the interplay of cellular dynamics and variability hold the promise to answer that challenge (3-5). Here we chose the replicative aging of yeast S. cerevisiae as a model and exploited quantitative biology technologies to study the dynamics of molecular processes that control aging at the single-cell level.