RESUMEN
Populations of isogenic cells often respond coherently to signals, despite differences in protein abundance and cell state. Previously, we uncovered processes in the Saccharomyces cerevisiae pheromone response system (PRS) that reduced cell-to-cell variability in signal strength and cellular response. Here, we screened 1,141 non-essential genes to identify 50 "variability genes". Most had distinct, separable effects on strength and variability of the PRS, defining these quantities as genetically distinct "axes" of system behavior. Three genes affected cytoplasmic microtubule function: BIM1, GIM2, and GIM4 We used genetic and chemical perturbations to show that, without microtubules, PRS output is reduced but variability is unaffected, while, when microtubules are present but their function is perturbed, output is sometimes lowered, but its variability is always high. The increased variability caused by microtubule perturbations required the PRS MAP kinase Fus3 and a process at or upstream of Ste5, the membrane-localized scaffold to which Fus3 must bind to be activated. Visualization of Ste5 localization dynamics demonstrated that perturbing microtubules destabilized Ste5 at the membrane signaling site. The fact that such microtubule perturbations cause aberrant fate and polarity decisions in mammals suggests that microtubule-dependent signal stabilization might also operate throughout metazoans.
Asunto(s)
Sistema de Señalización de MAP Quinasas/genética , Proteínas de Microtúbulos/genética , Microtúbulos/genética , Análisis de la Célula Individual , Proteínas Adaptadoras Transductoras de Señales/genética , Proteínas de Ciclo Celular/genética , Microtúbulos/metabolismo , Proteínas Quinasas Activadas por Mitógenos/genética , Feromonas/genética , Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/genética , Transducción de Señal/genéticaRESUMEN
Many cell signaling systems, including the yeast pheromone response system, exhibit "dose-response alignment" (DoRA), in which output of one or more downstream steps closely matches the fraction of occupied receptors. DoRA can improve the fidelity of transmitted dose information. Here, we searched systematically for biochemical network topologies that produced DoRA. Most networks, including many containing feedback and feedforward loops, could not produce DoRA. However, networks including "push-pull" mechanisms, in which the active form of a signaling species stimulates downstream activity and the nominally inactive form reduces downstream activity, enabled perfect DoRA. Networks containing feedbacks enabled DoRA, but only if they also compared feedback to input and adjusted output to match. Our results establish push-pull as a non-feedback mechanism to align output with variable input and maximize information transfer in signaling systems. They also suggest genetic approaches to determine whether particular signaling systems use feedback or push-pull control.
Asunto(s)
Transducción de Señal , Simulación por Computador , Retroalimentación Fisiológica , Saccharomyces cerevisiaeRESUMEN
Study of signal transduction in live cells benefits from the ability to visualize and quantify light emitted by fluorescent proteins (XFPs) fused to different signaling proteins. However, because cell signaling proteins are often present in small numbers, and because the XFPs themselves are poor fluorophores, the amount of emitted light, and the observable signal in these studies, is often small. An XFP's fluorescence lifetime contains additional information about the immediate environment of the fluorophore that can augment the information from its weak light signal. Here, we constructed and expressed in Saccharomyces cerevisiae variants of Teal Fluorescent Protein (TFP) and Citrine that were isospectral but had shorter fluorescence lifetimes, â¼ 1.5 ns vs â¼ 3 ns. We modified microscopic and flow cytometric instruments to measure fluorescence lifetimes in live cells. We developed digital hardware and a measure of lifetime called a "pseudophasor" that we could compute quickly enough to permit sorting by lifetime in flow. We used these abilities to sort mixtures of cells expressing TFP and the short-lifetime TFP variant into subpopulations that were respectively 97% and 94% pure. This work demonstrates the feasibility of using information about fluorescence lifetime to help quantify cell signaling in living cells at the high throughput provided by flow cytometry. Moreover, it demonstrates the feasibility of isolating and recovering subpopulations of cells with different XFP lifetimes for subsequent experimentation.
Asunto(s)
Citometría de Flujo/métodos , Proteínas Luminiscentes/metabolismo , Transducción de Señal/fisiología , Citometría de Flujo/instrumentación , Fluorescencia , Colorantes Fluorescentes , Saccharomyces cerevisiaeRESUMEN
Participants studied naturalistic pictures presented for varying brief durations and then received a recognition test on which they indicated whether each picture was old or new and rated their confidence. In 1 experiment they indicated whether each "old"/"new" response was based on memory for a specific feature in the picture or instead on the picture's general familiarity; in another experiment, we defined pictures that tended to elicit feature versus familiarity responses. Thus, feature/familiarity was a dependent variable in 1 experiment and an independent variable in the other. In both experiments feature-based responses were more accurate than those that were familiarity based, and confidence and accuracy increased with duration for both response types. However, when confidence was controlled for, mean accuracy was higher for familiarity-based than for feature-based responses. The theoretical implication is that confidence and accuracy arise from different underlying information. The applied implication is that confidence differences should not be taken as implying accuracy differences when the phenomenal basis of the memory reports differ.