Richard C. Yu

Negative feedback that improves information transmission in yeast signalling

Haploid Saccharomyces cerevisiae yeast cells use a prototypic cell signaling system to transmit information about the extracellular concentration of mating pheromone secreted by potential mating partners. The ability for cells to respond distinguishably to different pheromone concentrations depends on how much information about pheromone concentration the system can transmit. Here we show that the MAPK Fus3 mediates fast-acting negative feedback that adjusts the dose-response of downstream system response to match that of receptor-ligand binding. This “dose-response alignment”, defined by a linear relationship between receptor occupancy and downstream response, can improve the fidelity of information transmission by making downstream responses corresponding to different receptor occupancies more distinguishable and reducing amplification of stochastic noise during signal transmission. We also show that one target of the feedback is a novel signal-promoting function of the RGS protein Sst2. Our work suggests that negative feedback is a general mechanism used in signaling systems to align dose-responses and thereby increase the fidelity of information transmission.Haploid Saccharomyces cerevisiae yeast cells use a prototypic cell signalling system to transmit information about the extracellular concentration of mating pheromone secreted by potential mating partners. The ability of cells to respond distinguishably to different pheromone concentrations depends on how much information about pheromone concentration the system can transmit. Here we show that the mitogen-activated protein kinase Fus3 mediates fast-acting negative feedback that adjusts the dose response of the downstream system response to match the dose response of receptor-ligand binding. This ‘dose–response alignment’, defined by a linear relationship between receptor occupancy and downstream response, can improve the fidelity of information transmission by making downstream responses corresponding to different receptor occupancies more distinguishable and reducing amplification of stochastic noise during signal transmission. We also show that one target of the feedback is a previously uncharacterized signal-promoting function of the regulator of G-protein signalling protein Sst2. Our work suggests that negative feedback is a general mechanism used in signalling systems to align dose responses and thereby increase the fidelity of information transmission.

Scaffold number in yeast signaling system sets tradeoff between system output and dynamic range

Although the proteins comprising many signaling systems are known, less is known about their numbers per cell. Existing measurements often vary by more than 10-fold. Here, we devised improved quantification methods to measure protein abundances in the Saccharomyces cerevisiae pheromone response pathway, an archetypical signaling system. These methods limited variation between independent measurements of protein abundance to a factor of two. We used these measurements together with quantitative models to identify and investigate behaviors of the pheromone response system sensitive to precise abundances. The difference between the maximum and basal signaling output (dynamic range) of the pheromone response MAPK cascade was strongly sensitive to the abundance of Ste5, the MAPK scaffold protein, and absolute system output depended on the amount of Fus3, the MAPK. Additional analysis and experiment suggest that scaffold abundance sets a tradeoff between maximum system output and system dynamic range, a prediction supported by recent experiments.

Negative feedback confers mutational robustness in yeast transcription factor regulation

Organismal fitness depends on the ability of gene networks to function robustly in the face of environmental and genetic perturbations. Understanding the mechanisms of this stability is one of the key aims of modern systems biology. Dissecting the basis of robustness to mutation has proven a particular challenge, with most experimental models relying on artificial DNA sequence variants engineered in the laboratory. In this work, we hypothesized that negative regulatory feedback could stabilize gene expression against the disruptions that arise from natural genetic variation. We screened yeast transcription factors for feedback and used the results to establish ROX1 (Repressor of hypOXia) as a model system for the study of feedback in circuit behaviors and its impact across genetically heterogeneous populations. Mutagenesis experiments revealed the mechanism of Rox1 as a direct transcriptional repressor at its own gene, enabling a regulatory program of rapid induction during environmental change that reached a plateau of moderate steady-state expression. Additionally, in a given environmental condition, Rox1 levels varied widely across genetically distinct strains; the ROX1 feedback loop regulated this variation, in that the range of expression levels across genetic backgrounds showed greater spread in ROX1 feedback mutants than among strains with the ROX1 feedback loop intact. Our findings indicate that the ROX1 feedback circuit is tuned to respond to perturbations arising from natural genetic variation in addition to its role in induction behavior. We suggest that regulatory feedback may be an important element of the network architectures that confer mutational robustness across biology.

Using Cell‐ID 1.4 with R for Microscope‐Based Cytometry

This unit describes a method for quantifying various cellular features (e.g., volume, total and subcellular fluorescence localization) from sets of microscope images of individual cells. It includes procedures for tracking cells over time. One purposely defocused transmission image (sometimes referred to as bright‐field or BF) is acquired to segment the image and locate each cell. Fluorescence images (one for each of the color channels to be analyzed) are then acquired by conventional wide‐field epifluorescence or confocal microscopy. This method uses the image‐processing capabilities of Cell‐ID and data analysis by the statistical programming framework R, which is supplemented with a package of routines for analyzing Cell‐ID output. Both Cell‐ID and the analysis package are open‐source. Curr. Protoc. Mol. Biol. 100:14.18.1‐14.18.26.

Cell-ID Software for Microscope-Based Cytometry

This unit describes a method for quantifying various cellular parameters (e.g., volume, total and subcellular fluorescence localization) from sets of microscope images of individual cells. It includes procedures for tracking cells over time. One purposefully defocused transmission image (sometimes referred to as bright‐field or BF) is acquired to locate each cell. Fluorescent images (one for each of the color channels to be analyzed) are then acquired by conventional wide‐field epifluorescence or confocal microscopy. This method uses the image processing capabilities of Cell‐ID (Gordon et al., 2007) and data analysis by the statistical programming framework R (R‐Development‐Team, 2008), which we have supplemented with a package tailored to analyze Cell‐ID output. Both programs are open‐source software packages. Curr. Protoc. Mol. Biol. 84:14.18.1‐14.18.27.

Single‐cell profiling screen identifies microtubule‐dependent reduction of variability in signaling

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.

Cell-to-cell variability in the yeast pheromone response: high throughput screen identifies genes with different effects on transmitted signal and response

Populations of isogenic cells often respond coherently to signals despite differences in protein abundance and cell state. Our previous work in the Saccharomyces cerevisiae pheromone response system (PRS) uncovered processes that reduced cell-to-cell variation in signal and response. To understand these and other processes that controlled variation, we generated a whole-genome collection of haploid strains with deletions in non-essential genes and used high-throughput flow cytometry to screen more than 1000. We identified 50 “variation genes” required for normal cell-to-cell variability in signal and response. Some genes affected only signal variability, signal strength, or system output, defining these quantities as separable “axes” of system behavior. Two genes affected cytoplasmic microtubule function.