Compartmentalization of a bistable switch enables memory to cross a feedback-driven transition.

Cells make accurate decisions in the face of molecular noise and environmental fluctuations by relying not only on present pathway activity, but also on their memory of past signaling dynamics. Once a decision is made, cellular transitions are often rapid and switch-like due to positive feedback loops in the regulatory network. While positive feedback loops are good at promoting switch-like transitions, they are not expected to retain information to inform subsequent decisions. However, this expectation is based on our current understanding of network motifs that accounts for temporal, but not spatial, dynamics. Here, we show how spatial organization of the feedback-driven yeast G1/S switch enables the transmission of memory of past pheromone exposure across this transition. We expect this to be one of many examples where the exquisite spatial organization of the eukaryotic cell enables previously well-characterized network motifs to perform new and unexpected signal processing functions.

When yeast cells change their mind: cell cycle "Start" is reversible under starvation.

Eukaryotic cells decide in late G1 phase of the cell cycle whether to commit to another round of division. This point of cell cycle commitment is termed "Restriction Point" in mammals and "Start" in the budding yeast Saccharomyces cerevisiae. At Start, yeast cells integrate multiple signals such as pheromones and nutrients, and will not pass Start if nutrients are lacking. However, how cells respond to nutrient depletion after the Start decision remains poorly understood. Here, we analyze how post-Start cells respond to nutrient depletion, by monitoring Whi5, the cell cycle inhibitor whose export from the nucleus determines Start. Surprisingly, we find that cells that have passed Start can re-import Whi5 into the nucleus. In these cells, the positive feedback loop activating G1/S transcription is interrupted, and the Whi5 repressor re-binds DNA. Cells which re-import Whi5 become again sensitive to mating pheromone, like pre-Start cells, and CDK activation can occur a second time upon replenishment of nutrients. These results demonstrate that upon starvation, the commitment decision at Start can be reversed. We therefore propose that cell cycle commitment in yeast is a multi-step process, similar to what has been suggested for mammalian cells.

Integration of Multiple Metabolic Signals Determines Cell Fate Prior to Commitment.

Cell-fate decisions are central to the survival and development of both uni- and multicellular organisms. It remains unclear when and to what degree cells can decide on future fates prior to commitment. This uncertainty stems from experimental and theoretical limitations in measuring and integrating multiple signals at the single-cell level during a decision process. Here, we combine six-color live-cell imaging with the Bayesian method of statistical evidence to study the meiosis/quiescence decision in budding yeast. Integration of multiple upstream metabolic signals predicts individual cell fates with high probability well before commitment. Cells "decide" their fates before birth, well before the activation of pathways characteristic of downstream cell fates. This decision, which remains stable through several cell cycles, occurs when multiple metabolic parameters simultaneously cross cell-fate-specific thresholds. Taken together, our results show that cells can decide their future fates long before commitment mechanisms are activated.

A Precise Cdk Activity Threshold Determines Passage through the Restriction Point.

At the restriction point (R), mammalian cells irreversibly commit to divide. R has been viewed as a point in G1 that is passed when growth factor signaling initiates a positive feedback loop of Cdk activity. However, recent studies have cast doubt on this model by claiming R occurs prior to positive feedback activation in G1 or even before completion of the previous cell cycle. Here we reconcile these results and show that whereas many commonly used cell lines do not exhibit a G1 R, primary fibroblasts have a G1 R that is defined by a precise Cdk activity threshold and the activation of cell-cycle-dependent transcription. A simple threshold model, based solely on Cdk activity, predicted with more than 95% accuracy whether individual cells had passed R. That a single measurement accurately predicted cell fate shows that the state of complex regulatory networks can be assessed using a few critical protein activities.

Feedforward regulation ensures stability and rapid reversibility of a cellular state.

Cellular transitions are important for all life. Such transitions, including cell fate decisions, often employ positive feedback regulation to establish and stabilize new cellular states. However, positive feedback is unlikely to underlie stable cell-cycle arrest in yeast exposed to mating pheromone because the signaling pathway is linear, rather than bistable, over a broad range of extracellular pheromone concentration. We show that the stability of the pheromone-arrested state results from coherent feedforward regulation of the cell-cycle inhibitor Far1. This network motif is effectively isolated from the more complex regulatory network in which it is embedded. Fast regulation of Far1 by phosphorylation allows rapid cell-cycle arrest and reentry, whereas slow Far1 synthesis reinforces arrest. We expect coherent feedforward regulation to be frequently implemented at reversible cellular transitions because this network motif can achieve the ostensibly conflicting aims of arrest stability and rapid reversibility without loss of signaling information.

Functional interrelationships between carbohydrate and lipid storage, and mitochondrial activity during sporulation in Saccharomyces cerevisiae.

In Saccharomyces cerevisiae under conditions of nutrient stress, meiosis precedes the formation of spores. Although the molecular mechanisms that regulate meiosis, such as meiotic recombination and nuclear divisions, have been extensively studied, the metabolic factors that determine the efficiency of sporulation are less understood. Here, we have directly assessed the relationship between metabolic stores and sporulation in S. cerevisiae by genetically disrupting the synthetic pathways for the carbohydrate stores, glycogen (gsy1/2Δ cells), trehalose (tps1Δ cells), or both (gsy1/2Δ and tps1Δ cells). We show that storage carbohydrate-deficient strains are highly inefficient in sporulation. Although glycogen and trehalose stores can partially compensate for each other, they have differential effects on sporulation rate and spore number. Interestingly, deletion of the G1 cyclin, CLN3, which resulted in an increase in cell size, mitochondria and lipid stores, partially rescued meiosis progression and spore ascus formation but not spore number in storage carbohydrate-deficient strains. Sporulation efficiency in the carbohydrate-deficient strain exhibited a greater dependency on mitochondrial activity and lipid stores than wild-type yeast. Taken together, our results provide new insights into the complex crosstalk between metabolic factors that support gametogenesis.

Distinct interactions select and maintain a specific cell fate.

The ability to specify and maintain discrete cell fates is essential for development. However, the dynamics underlying selection and stability of distinct cell types remain poorly understood. Here, we provide a quantitative single-cell analysis of commitment dynamics during the mating-mitosis switch in budding yeast. Commitment to division corresponds precisely to activating the G1 cyclin positive feedback loop in competition with the cyclin inhibitor Far1. Cyclin-dependent phosphorylation and inhibition of the mating pathway scaffold Ste5 are required to ensure exclusive expression of the mitotic transcriptional program after cell cycle commitment. Failure to commit exclusively results in coexpression of both cell cycle and pheromone-induced genes, and a morphologically mixed inviable cell fate. Thus, specification and maintenance of a cellular state are performed by distinct interactions, which are likely a consequence of disparate reaction rates and may be a general feature of the interlinked regulatory networks responsible for selecting cell fates.

A processive phosphorylation circuit with multiple kinase inputs and mutually diversional routes controls G1/S decision.

Studies on multisite phosphorylation networks of cyclin-dependent kinase (CDK) targets have opened a new level of signaling complexity by revealing signal processing routes encoded into disordered proteins. A model target, the CDK inhibitor Sic1, contains linear phosphorylation motifs, docking sites, and phosphodegrons to empower an N-to-C terminally directed phosphorylation process. Here, we uncover a signal processing mechanism involving multi-step competition between mutually diversional phosphorylation routes within the S-CDK-Sic1 inhibitory complex. Intracomplex phosphorylation plays a direct role in controlling Sic1 degradation, and provides a mechanism to sequentially integrate both the G1- and S-CDK activities while keeping S-CDK inhibited towards other targets. The competing phosphorylation routes prevent premature Sic1 degradation and demonstrate how integration of MAPK from the pheromone pathway allows one to tune the competition of alternative phosphorylation paths. The mutually diversional phosphorylation circuits may be a general way for processing multiple kinase signals to coordinate cellular decisions in eukaryotes.

A fully-automated, robust, and versatile algorithm for long-term budding yeast segmentation and tracking.

Live cell time-lapse microscopy, a widely-used technique to study gene expression and protein dynamics in single cells, relies on segmentation and tracking of individual cells for data generation. The potential of the data that can be extracted from this technique is limited by the inability to accurately segment a large number of cells from such microscopy images and track them over long periods of time. Existing segmentation and tracking algorithms either require additional dyes or markers specific to segmentation or they are highly specific to one imaging condition and cell morphology and/or necessitate manual correction. Here we introduce a fully automated, fast and robust segmentation and tracking algorithm for budding yeast that overcomes these limitations. Full automatization is achieved through a novel automated seeding method, which first generates coarse seeds, then automatically fine-tunes cell boundaries using these seeds and automatically corrects segmentation mistakes. Our algorithm can accurately segment and track individual yeast cells without any specific dye or biomarker. Moreover, we show how existing channels devoted to a biological process of interest can be used to improve the segmentation. The algorithm is versatile in that it accurately segments not only cycling cells with smooth elliptical shapes, but also cells with arbitrary morphologies (e.g. sporulating and pheromone treated cells). In addition, the algorithm is independent of the specific imaging method (bright-field/phase) and objective used (40X/63X/100X). We validate our algorithm's performance on 9 cases each entailing a different imaging condition, objective magnification and/or cell morphology. Taken together, our algorithm presents a powerful segmentation and tracking tool that can be adapted to numerous budding yeast single-cell studies.

A regulatory circuit of two lncRNAs and a master regulator directs cell fate in yeast.

Transcription of long noncoding RNAs (lncRNAs) regulates local gene expression in eukaryotes. Many examples of how a single lncRNA controls the expression of an adjacent or nearby protein-coding gene have been described. Here we examine the regulation of a locus consisting of two contiguous lncRNAs and the master regulator for entry into yeast meiosis, IME1. We find that the cluster of two lncRNAs together with several transcription factors form a regulatory circuit by which IME1 controls its own promoter and thereby promotes its own expression. Inhibition or stimulation of this unusual feedback circuit affects timing and rate of IME1 accumulation, and hence the ability for cells to enter meiosis. Our data demonstrate that orchestrated transcription through two contiguous lncRNAs promotes local gene expression and determines a critical cell fate decision.

Noise resistance in the spindle assembly checkpoint.

Genetically identical cells vary in the amount of expressed proteins even when growing under the same conditions. It is not yet clear how cellular information processing copes with such stochastic fluctuations in protein levels. Here we examine the capacity of the spindle assembly checkpoint to buffer temporal fluctuations in the expression of Cdc20, a critical checkpoint target whose activity is inhibited to prevent premature cell cycle progression. Using mathematical modeling, we demonstrate that the checkpoint can buffer significant fluctuations in Cdc20 production rate. Critical to this buffering capacity is the use of sequestering-based mechanism for inhibiting Cdc20, as apposed to inhibition by enhancing protein degradation. We propose that the design of biological networks is limited by the need to overcome noise in gene expression.

Switch-like Transitions Insulate Network Motifs to Modularize Biological Networks.

Cellular decisions are made by complex networks that are difficult to analyze. Although it is common to analyze smaller sub-networks known as network motifs, it is unclear whether this is valid, because these motifs are embedded in complex larger networks. Here, we address the general question of modularity by examining the S. cerevisiae pheromone response. We demonstrate that the feedforward motif controlling the cell-cycle inhibitor Far1 is insulated from cell-cycle dynamics by the positive feedback switch that drives reentry to the cell cycle. Before cells switch on positive feedback, the feedforward motif model predicts the behavior of the larger network. Conversely, after the switch, the feedforward motif is dismantled and has no discernable effect on the cell cycle. When insulation is broken, the feedforward motif no longer predicts network behavior. This work illustrates how, despite the interconnectivity of networks, the activity of motifs can be insulated by switches that generate well-defined cellular states.

An algorithm to automate yeast segmentation and tracking.

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation.

Reverse engineering of the spindle assembly checkpoint.

The Spindle Assembly Checkpoint (SAC) is an intracellular mechanism that ensures proper chromosome segregation. By inhibiting Cdc20, a co-factor of the Anaphase Promoting Complex (APC), the checkpoint arrests the cell cycle until all chromosomes are properly attached to the mitotic spindle. Inhibition of Cdc20 is mediated by a conserved network of interacting proteins. The individual functions of these proteins are well characterized, but understanding of their integrated function is still rudimentary. We here describe our attempts to reverse-engineer the SAC network based on gene deletion phenotypes. We begun by formulating a general model of the SAC which enables us to predict the rate of chromosomal missegregation for any putative set of interactions between the SAC proteins. Next the missegregation rates of seven yeast strains are measured in response to the deletion of one or two checkpoint proteins. Finally, we searched for the set of interactions that correctly predicted the observed missegregation rates of all deletion mutants. Remarkably, although based on only seven phenotypes, the consistent network we obtained successfully reproduces many of the known properties of the SAC. Further insights provided by our analysis are discussed.

Evaluating putative mechanisms of the mitotic spindle checkpoint.

The mitotic spindle checkpoint halts the cell cycle until all chromosomes are attached to the mitotic spindles. Evidence suggests that the checkpoint prevents cell-cycle progression by inhibiting the activity of the APC-Cdc20 complex, but the precise mechanism underlying this inhibition is not yet known. Here, we use mathematical modeling to compare several mechanisms that could account for this inhibition. We describe the interplay between the capacities to strongly inhibit cell-cycle progression before spindle attachment on one hand and to rapidly resume cell-cycle progression once the last kinetochore is attached on the other hand. We find that inhibition that is restricted to the kinetochore region is not sufficient for supporting both requirements when realistic diffusion constants are considered. A mechanism that amplifies the checkpoint signal through autocatalyzed inhibition is also insufficient. In contrast, amplifying the signal through the release of a diffusible inhibitory complex can support reliable checkpoint function. Our results suggest that the design of the spindle checkpoint network is limited by physical constraints imposed by realistic diffusion constants and the relevant spatial and temporal dimensions where computation is performed.