Coherence and Timing of Cell Cycle Start Examined at Single-Cell Resolution

Oscillatory dynamics of cell cycle proteins in single yeast cells analyzed by imaging cytometry

Progression through the cell division cycle is orchestrated by a complex network of interacting genes and proteins. Some of these proteins are known to fluctuate periodically during the cell cycle, but a systematic study of the fluctuations of a broad sample of cell-cycle proteins has not been made until now. Using time-lapse fluorescence microscopy, we profiled 16 strains of budding yeast, each containing GFP fused to a single gene involved in cell cycle regulation. The dynamics of protein abundance and localization were characterized by extracting the amplitude, period, and other indicators from a series of images. Oscillations of protein abundance could clearly be identified for Cdc15, Clb2, Cln1, Cln2, Mcm1, Net1, Sic1, and Whi5. The period of oscillation of the fluorescently tagged proteins is generally in good agreement with the inter-bud time. The very strong oscillations of Net1 and Mcm1 expression are remarkable since little is known about the temporal expression of these genes. By collecting data from large samples of single cells, we quantified some aspects of cell-to-cell variability due presumably to intrinsic and extrinsic noise affecting the cell cycle.

A low number of SIC1 mRNA molecules ensures a low noise level in cell cycle progression of budding yeast

The budding yeast genome comprises roughly 6000 genes generating a number of about 10 000 mRNA copies, which gives a general estimation of 1-2 mRNA copies generated per gene. What does this observation implicate for cellular processes and their regulation? Whether the number of mRNA molecules produced is important for setting the amount of proteins implicated in a particular function is at present unknown. In this context, we studied cell cycle control as one of the highly fine tuned processes that guarantee the precise timing of events essential for cell growth. Here, we developed a stochastic model that addresses the effect of varying the mRNA amount of Sic1, inhibitor of the Cdk1-Clb5 kinase activity, and the resulting noise on Sic1/Clb5 balance at the G1/S transition. We considered a range of SIC1 transcripts number according to our experimental data derived from the MS2 mRNA tagging system. Computational simulation revealed that an increased amount of SIC1 mRNAs lead to an amplified dispersion of Sic1 protein levels, suggesting mRNA control being critical to set timing of Sic1 downregulation and, therefore, S phase onset. Moreover, Sic1/Clb5 balance is strongly influenced by Clb5 production in both daughter and mother cells in order to maintain the characteristic time of S phase entry overall the population. Furthermore, CLB5 mRNA molecules calculated to reproduce temporal dynamics of Sic1 and Clb5 for daughter and mother cells agree with recent data obtained from more complex networks. Thus, the results presented here provide novel insights into the influence that the mRNA amount and, indirectly, the transcription process exploit on cell cycle progression.

Multiple sequence-specific factors generate the nucleosome-depleted region on CLN2 promoter

Nucleosome-depleted regions (NDRs) are ubiquitous on eukaryotic promoters. The formation of many NDRs cannot be readily explained by previously proposed mechanisms. Here, we carry out a focused study on a physiologically important NDR in the yeast CLN2 promoter (CLN2pr). We show that this NDR does not result from intrinsically unfavorable histone-DNA interaction. Instead, we identified eight conserved factor binding sites, including that of Reb1, Mcm1, and Rsc3, that cause the local nucleosome depletion. These nucleosome-depleting factors (NDFs) work redundantly, and simultaneously mutating all their binding sites eliminates CLN2pr NDR. The loss of the NDR induces unreliable "on/off" expression in individual cell cycles, but in the presence of the NDR, NDFs have little direct effect on transcription. We present bioinformatic evidence that the formation of many NDRs across the genome involves multiple NDFs. Our findings also provide significant insight into the composition and spatial organization of functional promoters.

High-throughput tracking of single yeast cells in a microfluidic imaging matrix

Time-lapse live cell imaging is a powerful tool for studying signaling network dynamics and complexity and is uniquely suited to single cell studies of response dynamics, noise, and heritable differences. Although conventional imaging formats have the temporal and spatial resolution needed for such studies, they do not provide the simultaneous advantages of cell tracking, experimental throughput, and precise chemical control. This is particularly problematic for system-level studies using non-adherent model organisms such as yeast, where the motion of cells complicates tracking and where large-scale analysis under a variety of genetic and chemical perturbations is desired. We present here a high-throughput microfluidic imaging system capable of tracking single cells over multiple generations in 128 simultaneous experiments with programmable and precise chemical control. High-resolution imaging and robust cell tracking are achieved through immobilization of yeast cells using a combination of mechanical clamping and polymerization in an agarose gel. The channel and valve architecture of our device allows for the formation of a matrix of 128 integrated agarose gel pads, each allowing for an independent imaging experiment with fully programmable medium exchange via diffusion. We demonstrate our system in the combinatorial and quantitative analysis of the yeast pheromone signaling response across 8 genotypes and 16 conditions, and show that lineage-dependent effects contribute to observed variability at stimulation conditions near the critical threshold for cellular decision making.

Multisite phosphorylation provides an effective and flexible mechanism for switch-like protein degradation

Phosphorylation-triggered degradation is a common strategy for elimination of regulatory proteins in many important cell signaling processes. Interesting examples include cyclin-dependent kinase inhibitors such as p27 in human and Sic1 in yeast, which play crucial roles during the G1/S transition in the cell cycle. In this work, we have modeled and analyzed the dynamics of multisite-phosphorylation-triggered protein degradation systematically. Inspired by experimental observations on the Sic1 protein and a previous intriguing theoretical conjecture, we develop a model to examine in detail the degradation dynamics of a protein featuring multiple phosphorylation sites and a threshold site number for elimination in response to a kinase signal. Our model explains the role of multiple phosphorylation sites, compared to a single site, in the regulation of protein degradation. A single-site protein cannot convert a graded input of kinase increase to much sharper output, whereas multisite phosphorylation is capable of generating a highly switch-like temporal profile of the substrate protein with two characteristics: a temporal threshold and rapid decrease beyond the threshold. We introduce a measure termed temporal response coefficient to quantify the extent to which a response in the time domain is switch-like and further investigate how this property is determined by various factors including the kinase input, the total number of sites, the threshold site number for elimination, the order of phosphorylation, the kinetic parameters, and site preference. Some interesting and experimentally verifiable predictions include that the non-degradable fraction of the substrate protein exhibits a more switch-like temporal profile; a sequential system is more switch-like, while a random system has the advantage of increased robustness; all the parameters, including the total number of sites, the threshold site number for elimination and the kinetic parameters synergistically determine the exact extent to which the degradation profile is switch-like. Our results suggest design principles for protein degradation switches which might be a widespread mechanism for precise regulation of cellular processes such as cell cycle progression.

Frequency control of cell cycle oscillators

The cell cycle oscillator, based on a core negative feedback loop and modified extensively by positive feedback, cycles with a frequency that is regulated by environmental and developmental programs to encompass a wide range of cell cycle times. We discuss how positive feedback allows frequency tuning, how size and morphogenetic checkpoints regulate oscillator frequency, and how extrinsic oscillators such as the circadian clock gate cell cycle frequency. The master cell cycle regulatory oscillator in turn controls the frequency of peripheral oscillators controlling essential events. A recently proposed phase-locking model accounts for this coupling.

Measuring growth rate in high-throughput growth phenotyping

Growth rate is an important variable and parameter in biology with a central role in evolutionary, functional genomics, and systems biology studies. In this review the pros and cons of the different technologies presently available for high-throughput measurements of growth rate are discussed. Growth rate can be measured in liquid microcultivation of individual strains, in competition between strains, as growing colonies on agar, as division of individual cells, and estimated from molecular reporters. Irrespective of methodology, statistical issues such as spatial biases and batch effects are crucial to investigate and correct for to ensure low false discovery rates. The rather low correlations between studies indicate that cross-laboratory comparison and standardization are pressing issue to assure high-quality and comparable growth-rate data.

Timing control in regulatory networks by multisite protein modifications

Computational and experimental studies have yielded quantitative insights into the role for multisite phosphorylation, and other protein modifications, in cell function. This work has emphasized the creation of thresholds and switches for cellular decisions. To date, the dynamics of phosphorylation events have been disregarded yet could be equally relevant for cell function. Here, we discuss theoretical predictions about the kinetic functions of multisite phosphorylation in regulatory networks and how these predictions relate to experimental findings. Using DNA replication as an example, we demonstrate that multisite phosphorylations can support coherent origin firing and robustness against rereplication. We suggest that multisite protein modifications provide a molecular mechanism to robustly time cellular events in the cell cycle, the circadian clock and signal transduction.

Stochastic E2F activation and reconciliation of phenomenological cell-cycle models

A new, stochastic model of entry into the mammalian cell cycle provides a mechanistic understanding of the temporal variability observed across populations of cells and reconciles previously proposed phenomenological cell-cycle models.

The transition of the mammalian cell from quiescence to proliferation is a highly variable process. Over the last four decades, two lines of apparently contradictory, phenomenological models have been proposed to account for such temporal variability. These include various forms of the transition probability (TP) model and the growth control (GC) model, which lack mechanistic details. The GC model was further proposed as an alternative explanation for the concept of the restriction point, which we recently demonstrated as being controlled by a bistable Rb-E2F switch. Here, through a combination of modeling and experiments, we show that these different lines of models in essence reflect different aspects of stochastic dynamics in cell cycle entry. In particular, we show that the variable activation of E2F can be described by stochastic activation of the bistable Rb-E2F switch, which in turn may account for the temporal variability in cell cycle entry. Moreover, we show that temporal dynamics of E2F activation can be recast into the frameworks of both the TP model and the GC model via parameter mapping. This mapping suggests that the two lines of phenomenological models can be reconciled through the stochastic dynamics of the Rb-E2F switch. It also suggests a potential utility of the TP or GC models in defining concise, quantitative phenotypes of cell physiology. This may have implications in classifying cell types or states.

Mammalian cells enter the division cycle in response to appropriate growth signals. For each cell, the decision to do so is critically dependent on the interplay between environmental cues and the internal state of the cell and is influenced by random fluctuations in cellular processes. Indeed, experimental evidence indicates that cell cycle entry is highly variable from cell to cell, even within a clonal population. To account for such variability, a number of phenomenological models have been previously proposed. These models primarily fall into two types depending on their fundamental assumptions on the origin of the variability. “Transition probability” models presume that variability in cell cycle entry originates from the fact that entry in each individual cell is random but also governed by a fixed probability. In contrast, “growth-controlled” models assume that the growth rates across a population are variable and result in cells that are out of phase developmentally. While both kinds of models provide a good fit to experimental data, their lack of mechanistic details limits their predictive power and has led to unresolved debate between their practitioners. In this study, we developed a mechanistically based stochastic model of the temporal dynamics of activation of the E2F transcription factor, which is used here as a marker of the transition of cells from quiescence to active cell cycling. Using this model, we show that “transition probability” and “growth-controlled” models can be reconciled by incorporation of a small number of basic cellular parameters related to protein synthesis and turnover, protein modification, stochasticity, and the like. Essentially our work shows that each kind of phenomenological model holds true for describing a particular aspect of the cell cycle transition. We suggest that incorporation of basic cellular parameters in this manner into phenomenological models may constitute a broadly applicable approach to defining concise, quantitative phenotypes of cell physiology.

A conserved G₁ regulatory circuit promotes asynchronous behavior of nuclei sharing a common cytoplasm

Synthesis and accumulation of conserved cell cycle regulators such as cyclins are thought to promote G₁/S and G₂/M transitions in most eukaryotes. When cells at different stages of the cell cycle are fused to form heterokaryons, the shared complement of regulators in the cytoplasm induces the nuclei to become synchronized. However, multinucleate fungi often display asynchronous nuclear division cycles, even though the nuclei inhabit a shared cytoplasm. Similarly, checkpoints can induce nuclear asynchrony in multinucleate cells by arresting only the nucleus that receives damage. The cell biological basis for nuclear autonomy in a common cytoplasm is not known. Here we show that in the filamentous fungus Ashbya gossypii, sister nuclei born from one mitosis immediately lose synchrony in the subsequent G₁ interval. A conserved G₁ transcriptional regulatory circuit involving the Rb-analogue Whi5p promotes the asynchronous behavior yet Whi5 protein is uniformly distributed among nuclei throughout the cell cycle. The homologous Whi5p circuit in S. cerevisiae employs positive feedback to promote robust and coherent entry into the cell cycle. We propose that positive feedback in this same circuit generates timing variability in a multinucleate cell. These unexpected findings indicate that a regulatory program whose products (mRNA transcripts) are translated in a common cytoplasm can nevertheless promote variability in the individual behavior of sister nuclei.

Periodic cyclin-Cdk activity entrains an autonomous Cdc14 release oscillator

One oscillation of Cyclin-dependent kinase (Cdk) activity, largely driven by periodic synthesis and destruction of cyclins, is tightly coupled to a single complete eukaryotic cell division cycle. Tight linkage of different steps in diverse cell-cycle processes to Cdk activity has been proposed to explain this coupling. Here, we demonstrate an intrinsically oscillatory module controlling nucleolar release and resequestration of the Cdc14 phosphatase, which is essential for mitotic exit in budding yeast. We find that this Cdc14 release oscillator functions at constant and physiological cyclin-Cdk levels, and is therefore independent of the Cdk oscillator. However, the frequency of the release oscillator is regulated by cyclin-Cdk activity. This observation together with its mechanism suggests that the intrinsically autonomous Cdc14 release cycles are locked at once-per-cell-cycle through entrainment by the Cdk oscillator in wild-type cells. This concept may have broad implications for the structure and evolution of eukaryotic cell-cycle control.

Nucleosome-depleted regions in cell-cycle-regulated promoters ensure reliable gene expression in every cell cycle

Many promoters in eukaryotes have nucleosome-depleted regions (NDRs) containing transcription factor binding sites. However, the functional significance of NDRs is not well understood. Here, we examine NDR function in two cell cycle-regulated promoters, CLN2pr and HOpr, by varying nucleosomal coverage of the binding sites of their activator, Swi4/Swi6 cell-cycle box (SCB)-binding factor (SBF), and probing the corresponding transcriptional activity in individual cells with time-lapse microscopy. Nucleosome-embedded SCBs do not significantly alter peak expression levels. Instead, they induce bimodal, "on/off" activation in individual cell cycles, which displays short-term memory, or epigenetic inheritance, from the mother cycle. In striking contrast, the same SCBs localized in NDR lead to highly reliable activation, once in every cell cycle. We further demonstrate that the high variability in Cln2p expression induced by the nucleosomal SCBs reduces cell fitness. Therefore, we propose that the NDR function in limiting stochasticity in gene expression promotes the ubiquity and conservation of promoter NDR. PAPERCLIP:

Requirements and reasons for effective inhibition of the anaphase promoting complex activator CDH1

Inhibitory phosphorylation of Cdh1 by CDK and Polo kinase has been proposed to inactivate APC-Cdh1. Through an exact gene replacement approach, we find CDK, but not Polo, phosphorylation of Cdh1 to be a critical regulatory mechanism. APC-Cdh1 inhibits multiple aspects of spindle morphogenesis, and its activity is modulated by endogenous ACM1.

Anaphase promoting complex (APC)-Cdh1 targets multiple mitotic proteins for degradation upon exit from mitosis into G1; inhibitory phosphorylation of Cdh1 by cyclin-dependent kinase (CDK) and Polo kinase has been proposed to prevent the premature degradation of substrates in the ensuing cell cycle. Here, we demonstrate essentiality of CDK phosphorylation of Cdh1 in Saccharomyces cerevisiae by exact endogenous gene replacement of CDH1 with CDK-unphosphorylatable CDH1-m11; in contrast, neither Cdh1 polo kinase sites nor polo interaction motifs are required. CDH1-m11 cells arrest in the first cycle with replicated DNA and sustained polarized growth; most cells have monopolar spindles. Blocking proteolysis of the Cin8 kinesin in CDH1-m11 cells does not promote spindle pole body (SPB) separation. In contrast, expression of undegradable mitotic cyclin results in both SPB separation and the restoration of isotropic growth. A minority of CDH1-m11 cells arrest with short bipolar spindles that fail to progress to anaphase; this can be accounted for by a failure to accumulate Cdc20 and consequent failure to cleave cohesin. Bipolar spindle assembly in CDH1-m11 cells is strikingly sensitive to gene dosage of the stoichiometric Cdh1 inhibitor ACM1. Thus, different spindle-regulatory pathways have distinct sensitivities to Cdh1, and ACM1 may buffer essential CDK phosphorylation of Cdh1.

Origin of irreversibility of cell cycle start in budding yeast

Budding yeast cells irreversibly commit to a new division cycle at a regulatory transition called Start. This essential decision-making step involves the activation of the SBF/MBF transcription factors. SBF/MBF promote expression of the G1 cyclins encoded by CLN1 and CLN2. Cln1,2 can activate their own expression by inactivating the Whi5 repressor of SBF/MBF. The resulting transcriptional positive feedback provides an appealing, but as yet unproven, candidate for generating irreversibility of Start. Here, we investigate the logic of the Start regulatory module by quantitative single-cell time-lapse microscopy, using strains in which expression of key regulators is efficiently controlled by changes of inducers in a microfluidic chamber. We show that Start activation is ultrasensitive to G1 cyclin. In the absence of CLN1,2-dependent positive feedback, we observe that Start transit is reversible, due to reactivation of the Whi5 transcriptional repressor. Introduction of the positive feedback loop makes Whi5 inactivation and Start activation irreversible, which therefore guarantees unidirectional entry into S phase. A simple mathematical model to describe G1 cyclin turn on at Start, entirely constrained by empirically measured parameters, shows that the experimentally measured ultrasensitivity and transcriptional positive feedback are necessary and sufficient dynamical characteristics to make the Start transition a bistable and irreversible switch. Our study thus demonstrates that Start irreversibility is a property that arises from the architecture of the system (Whi5/SBF/Cln2 loop), rather than the consequence of the regulation of a single component (e.g., irreversible protein degradation).

Daughter-specific transcription factors regulate cell size control in budding yeast

The asymmetric localization of cell fate determinants results in asymmetric cell cycle control in budding yeast.

In budding yeast, asymmetric cell division yields a larger mother and a smaller daughter cell, which transcribe different genes due to the daughter-specific transcription factors Ace2 and Ash1. Cell size control at the Start checkpoint has long been considered to be a main regulator of the length of the G1 phase of the cell cycle, resulting in longer G1 in the smaller daughter cells. Our recent data confirmed this concept using quantitative time-lapse microscopy. However, it has been proposed that daughter-specific, Ace2-dependent repression of expression of the G1 cyclin CLN3 had a dominant role in delaying daughters in G1. We wanted to reconcile these two divergent perspectives on the origin of long daughter G1 times. We quantified size control using single-cell time-lapse imaging of fluorescently labeled budding yeast, in the presence or absence of the daughter-specific transcriptional regulators Ace2 and Ash1. Ace2 and Ash1 are not required for efficient size control, but they shift the domain of efficient size control to larger cell size, thus increasing cell size requirement for Start in daughters. Microarray and chromatin immunoprecipitation experiments show that Ace2 and Ash1 are direct transcriptional regulators of the G1 cyclin gene CLN3. Quantification of cell size control in cells expressing titrated levels of Cln3 from ectopic promoters, and from cells with mutated Ace2 and Ash1 sites in the CLN3 promoter, showed that regulation of CLN3 expression by Ace2 and Ash1 can account for the differential regulation of Start in response to cell size in mothers and daughters. We show how daughter-specific transcriptional programs can interact with intrinsic cell size control to differentially regulate Start in mother and daughter cells. This work demonstrates mechanistically how asymmetric localization of cell fate determinants results in cell-type-specific regulation of the cell cycle.

Asymmetric cell division is a universal mechanism for generating differentiated cells. The progeny of such divisions can often display differential cell cycle regulation. This study addresses how differential regulation of gene expression in the progeny of a single division can alter cell cycle control. In budding yeast, asymmetric cell division yields a bigger ‘mother’ cell and a smaller ‘daughter’ cell. Regulation of gene expression is also asymmetric because two transcription factors, Ace2 and Ash1, are specifically localized to the daughter. Cell size has long been proposed as important for the regulation of the cell cycle in yeast. Our work shows that Ace2 and Ash1 regulate size control in daughter cells: daughters ‘interpret’ their size as smaller, making size control more stringent and delaying cell cycle commitment relative to mother cells of the same size. This asymmetric interpretation of cell size is associated with differential regulation of the G1 cyclin CLN3 by Ace2 and Ash1, at least in part via direct binding of these factors to the CLN3 promoter. CLN3 is the most upstream regulator of Start, the initiation point of the yeast cell cycle, and differential regulation of CLN3 accounts for most or all asymmetric regulation of Start in budding yeast mother and daughter cells.

Positive-feedback loops in cell cycle progression

A positive-feedback loop is a simple motif that is ubiquitous to the modules and networks that comprise cellular signaling systems. Signaling behaviors that are synonymous with positive feedback include amplification and rapid switching, maintenance, and the coherence of outputs. Recent advances have been made towards understanding how positive-feedback loops function, as well as their mechanistic basis in controlling eukaryotic cell cycle progression. Some of these advances will be reviewed here, including: how cyclin controls passage through Start and maintains coherence of G1/S regulon expression in yeast; how Polo-like kinase 1 activation is driven by Bora and Aurora A, and its expression is stimulated by Forkhead Box M1 in mammalian cells; and how some of the various dynamic behaviors of spindle assembly and anaphase onset can be produced.

Specific genetic interactions between spindle assembly checkpoint proteins and B-Type cyclins in Saccharomyces cerevisiae

The B-type cyclin Clb5 is involved primarily in control of DNA replication in Saccharomyces cerevisiae. We conducted a synthetic genetic array (SGA) analysis, testing for synthetic lethality between the clb5 deletion and a selected 87 deletions related to diverse aspects of cell cycle control based on GO annotations. Deletion of the spindle checkpoint genes BUB1 and BUB3 caused synthetic lethality with clb5. The spindle checkpoint monitors the attachment of spindles to the kinetochore or spindle tension during early mitosis. However, another spindle checkpoint gene, MAD2, could be deleted without ill effects in the absence of CLB5, suggesting that the bub1/3 clb5 synthetic lethality reflected some function other than the spindle checkpoint of Bub1 and Bub3. To characterize the lethality of bub3 clb5 cells, we constructed a temperature-sensitive clb5 allele. At nonpermissive temperature, bub3 clb5-ts cells showed defects in spindle elongation and cytokinesis. High-copy plasmid suppression of bub3 clb5 lethality identified the C-terminal fragment of BIR1, the yeast homolog of survivin; cytologically, the BIR1 fragment rescued the growth and cytokinesis defects. Bir1 interacts with IplI (Aurora B homolog), and the addition of bub3 clb5-ts significantly enhanced the lethality of the temperature-sensitive ipl1-321. Overall, we conclude that the synthetic lethality between clb5 and bub1 or bub3 is likely related to functions of Bub1/3 unrelated to their spindle checkpoint function. We tested requirements for other B-type cyclins in the absence of spindle checkpoint components. In the absence of the related CLB3 and CLB4 cyclins, the spindle integrity checkpoint becomes essential, since bub3 or mad2 deletion is lethal in a clb3 clb4 background. clb3 clb4 mad2 cells accumulated with unseparated spindle pole bodies. Thus, different B-type cyclins are required for distinct aspects of spindle morphogenesis and function, as revealed by differential genetic interactions with spindle checkpoint components.

IQGAP1 regulates cell proliferation through a novel CDC42-mTOR pathway

Cell proliferation requires close coordination of cell growth and division to ensure constant cell size through the division cycles. IQGAP1, an effector of CDC42 GTPase has been implicated in the modulation of cell architecture, regulation of exocytosis and in human cancers. The precise mechanism underlying these activities is unclear. Here, we show that IQGAP1 regulates cell proliferation, which requires phosphorylation of IQGAP1 and binding to CDC42. Expression of the C-terminal region of IQGAP1 enhanced cellular transformation and migration, but reduced the cell size, whereas expression of the N-terminus increased the cell size, but inhibited cell transformation and migration. The N-terminus of IQGAP1 interacts with mTOR, which is required for IQGAP1-mediated cell proliferation. These findings are consistent with a model where IQGAP1 serves as a phosphorylation-sensitive conformation switch to regulate the coupling of cell growth and division through a novel CDC42-mTOR pathway, dysregulation of which generates cellular transformation.

Sin3 is involved in cell size control at Start in Saccharomyces cerevisiae

Saccharomyces cerevisiae cells control their cell size at a point in late G(1) called Start. Here, we describe a negative role for the Sin3/Rpd3 histone deacetylase complex in the regulation of cell size at Start. Initiation of G(1)/S-specific transcription of CLN1, CLN2 and PCL1 in a sin3Delta strain occurs at a reduced cell size compared with a wild-type strain. In addition, inactivation of the transcriptional regulator SIN3 partially suppressed a cln3Delta mutant, causing sin3Deltacln3Delta double mutants to start the cell cycle at wild-type size. Chromatin immunoprecipitation results demonstrate that Sin3 and Rpd3 are recruited to promoters of SBF (Swi4/Swi6)-regulated genes, and reveal that binding of Sin3 to SBF-specific promoters is cell-cycle regulated. We observe that transcriptional repression of SBF-dependent genes in early G(1) coincides with the recruitment of Sin3 to specific promoters, whereas binding of Sin3 is abolished from Swi4/Swi6-regulated promoters when transcription is activated at the G(1) to S phase transition. We conclude that the Sin3/Rpd3 histone deacetylase complex helps to prevent premature activation of the S phase in daughter cells.

Using movies to analyse gene circuit dynamics in single cells

Many bacterial systems rely on dynamic genetic circuits to control crucial biological processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages 'wash out' crucial dynamics that are either unsynchronized between cells or are driven by fluctuations, or 'noise', in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems.

Forced periodic expression of G1 cyclins phase-locks the budding yeast cell cycle

Phase-locking (frequency entrainment) of an oscillator, in which a periodic extrinsic signal drives oscillations at a frequency different from the unperturbed frequency, is a useful property for study of oscillator stability and structure. The cell cycle is frequently described as a biochemical oscillator; however, because this oscillator is tied to key biological events such as DNA replication and segregation, and to cell growth (cell mass increase), it is unclear whether phase locking is possible for the cell cycle oscillator. We found that forced periodic expression of the G(1) cyclin CLN2 phase locks the cell cycle of budding yeast over a range of extrinsic periods in an exponentially growing monolayer culture. We characterize the behavior of cells in a pedigree using a return map to determine the efficiency of entrainment to the externally controlled pulse. We quantify differences between mothers and daughters and how synchronization of an expanding population differs from synchronization of a single oscillator. Mothers only lock intermittently whereas daughters lock completely and in a different period range than mothers. We can explain quantitative features of phase locking in both cell types with an analytically solvable model based on cell size control and how mass is partitioned between mother and daughter cells. A key prediction of this model is that size control can occur not only in G(1), but also later in the cell cycle under the appropriate conditions; this prediction is confirmed in our experimental data. Our results provide quantitative insight into how cell size is integrated with the cell cycle oscillator.

Computational systems biology of the cell cycle

One of the early success stories of computational systems biology was the work done on cell-cycle regulation. The earliest mathematical descriptions of cell-cycle control evolved into very complex, detailed computational models that describe the regulation of cell division in many different cell types. On the way these models predicted several dynamical properties and unknown components of the system that were later experimentally verified/identified. Still, research on this field is far from over. We need to understand how the core cell-cycle machinery is controlled by internal and external signals, also in yeast cells and in the more complex regulatory networks of higher eukaryotes. Furthermore, there are many computational challenges what we face as new types of data appear thanks to continuing advances in experimental techniques. We have to deal with cell-to-cell variations, revealed by single cell measurements, as well as the tremendous amount of data flowing from high throughput machines. We need new computational concepts and tools to handle these data and develop more detailed, more precise models of cell-cycle regulation in various organisms. Here we review past and present of computational modeling of cell-cycle regulation, and discuss possible future directions of the field.

Mitotic exit in the absence of separase activity

In budding yeast, three interdigitated pathways regulate mitotic exit (ME): mitotic cyclin-cyclin-dependent kinase (Cdk) inactivation; the Cdc14 early anaphase release (FEAR) network, including a nonproteolytic function of separase (Esp1); and the mitotic exit network (MEN) driven by interaction between the spindle pole body and the bud cortex. Here, we evaluate the contributions of these pathways to ME kinetics. Reducing Cdk activity is critical for ME, and the MEN contributes strongly to ME efficiency. Esp1 contributes to ME kinetics mainly through cohesin cleavage: the Esp1 requirement can be largely bypassed if cells are provided Esp1-independent means of separating sister chromatids. In the absence of Esp1 activity, we observed only a minor ME delay consistent with a FEAR defect. Esp1 overexpression drives ME in Cdc20-depleted cells arrested in metaphase. We have found that this activity of overexpressed Esp1 depended on spindle integrity and the MEN. We defined the first quantitative measure for Cdc14 release based on colocalization with the Net1 nucleolar anchor. This measure indicates efficient Cdc14 release upon MEN activation; release driven by Esp1 in the absence of microtubules was inefficient and incapable of driving ME. We also found a novel role for the MEN: activating Cdc14 nuclear export, even in the absence of Net1.

Quantitative time-lapse fluorescence microscopy in single cells

The cloning of green fluorescent protein (GFP) 15 years ago revolutionized cell biology by permitting visualization of a wide range of molecular mechanisms within living cells. Though initially used to make largely qualitative assessments of protein levels and localizations, fluorescence microscopy has since evolved to become highly quantitative and high-throughput. Computational image analysis has catalyzed this evolution, enabling rapid and automated processing of large datasets. Here, we review studies that combine time-lapse fluorescence microscopy and automated image analysis to investigate dynamic events at the single-cell level. We highlight examples where single-cell analysis provides unique mechanistic insights into cellular processes that cannot be otherwise resolved in bulk assays. Additionally, we discuss studies where quantitative microscopy facilitates the assembly of detailed 4D lineages in developing organisms. Finally, we describe recent advances in imaging technology, focusing especially on platforms that allow the simultaneous perturbation and quantitative monitoring of biological systems.

Huxley's revenge: cell-cycle entry, positive feedback, and the G1 cyclins

In a recent issue of Nature, Skotheim et al. (2008) show that a transcriptional positive feedback loop plays a key role in the commitment to enter the yeast cell cycle.

Image analysis algorithms for cell contour recognition in budding yeast

Quantification of protein abundance and subcellular localization dynamics from fluorescence microscopy images is of high contemporary interest in cell and molecular biology. For large-scale studies of cell populations and for time-lapse studies, such quantitative analysis can not be performed effectively without some kind of automated image analysis tool. Here, we present fast algorithms for automatic cell contour recognition in bright field images, optimized to the model organism budding yeast (Saccharomyces cerevisiae). The cell contours can be used to effectively quantify cell morphology parameters as well as protein abundance and subcellular localization from overlaid fluorescence data.

The stochastic nature of biochemical networks

Cell behaviour and the cellular environment are stochastic. Phenotypes vary across isogenic populations and in individual cells over time. Here we will argue that to understand the abilities of cells we need to understand their stochastic nature. New experimental techniques allow gene expression to be followed in single cells over time and reveal stochastic bursts of both mRNA and protein synthesis in many different types of organisms. Stochasticity has been shown to be exploited by bacteria and viruses to decide between different behaviours. In fluctuating environments, cells that respond stochastically can out-compete those that sense environmental changes, and stochasticity may even have contributed to chromosomal gene order. We will focus on advances in modelling stochasticity, in understanding its effects on evolution and cellular design, and on means by which it may be exploited in biotechnology and medicine.

Spatio-temporal protein dynamics in single living cells

The development and application of single cell optical imaging has identified dynamic and oscillatory signalling processes in individual cells. This requires single cell analyses since the processes may otherwise be masked by the population average. These oscillations range in timing from seconds/minutes (e.g. calcium) to minutes/hours (e.g. NF-kappaB, Notch/Wnt and p53) and hours/days (e.g. circadian clock and cell cycle). Quantitative live cell measurement of the protein processes underlying these complex networks will allow characterisation of the core mechanisms that drive these signalling pathways and control cell function. Ultimately, such studies can be applied to develop predictive models of whole tissues and organisms.

Positive feedback of G1 cyclins ensures coherent cell cycle entry

In budding yeast, Saccharomyces cerevisiae, the Start checkpoint integrates multiple internal and external signals into an all-or-none decision to enter the cell cycle. Here we show that Start behaves like a switch due to systems-level feedback in the regulatory network. In contrast to current models proposing a linear cascade of Start activation, transcriptional positive feedback of the G1 cyclins Cln1 and Cln2 induces the near-simultaneous expression of the approximately 200-gene G1/S regulon. Nuclear Cln2 drives coherent regulon expression, whereas cytoplasmic Cln2 drives efficient budding. Cells with the CLN1 and CLN2 genes deleted frequently arrest as unbudded cells, incurring a large fluctuation-induced fitness penalty due to both the lack of cytoplasmic Cln2 and insufficient G1/S regulon expression. Thus, positive-feedback-amplified expression of Cln1 and Cln2 simultaneously drives robust budding and rapid, coherent regulon expression. A similar G1/S regulatory network in mammalian cells, comprised of non-orthologous genes, suggests either conservation of regulatory architecture or convergent evolution.

Robust, tunable biological oscillations from interlinked positive and negative feedback loops

A simple negative feedback loop of interacting genes or proteins has the potential to generate sustained oscillations. However, many biological oscillators also have a positive feedback loop, raising the question of what advantages the extra loop imparts. Through computational studies, we show that it is generally difficult to adjust a negative feedback oscillator's frequency without compromising its amplitude, whereas with positive-plus-negative feedback, one can achieve a widely tunable frequency and near-constant amplitude. This tunability makes the latter design suitable for biological rhythms like heartbeats and cell cycles that need to provide a constant output over a range of frequencies. Positive-plus-negative oscillators also appear to be more robust and easier to evolve, rationalizing why they are found in contexts where an adjustable frequency is unimportant.

Cell-to-cell stochastic variation in gene expression is a complex genetic trait

The genetic control of common traits is rarely deterministic, with many genes contributing only to the chance of developing a given phenotype. This incomplete penetrance is poorly understood and is usually attributed to interactions between genes or interactions between genes and environmental conditions. Because many traits such as cancer can emerge from rare events happening in one or very few cells, we speculate an alternative and complementary possibility where some genotypes could facilitate these events by increasing stochastic cell-to-cell variations (or ‘noise’). As a very first step towards investigating this possibility, we studied how natural genetic variation influences the level of noise in the expression of a single gene using the yeast S. cerevisiae as a model system. Reproducible differences in noise were observed between divergent genetic backgrounds. We found that noise was highly heritable and placed under a complex genetic control. Scanning the genome, we mapped three Quantitative Trait Loci (QTL) of noise, one locus being explained by an increase in noise when transcriptional elongation was impaired. Our results suggest that the level of stochasticity in particular molecular regulations may differ between multicellular individuals depending on their genotypic background. The complex genetic architecture of noise buffering couples genetic to non-genetic robustness and provides a molecular basis to the probabilistic nature of complex traits.

Although most inter-individual phenotypic variabilities are largely attributable to DNA differences, a wealth of examples illustrate how a single biological system can vary stochastically over time and between individuals. Identical twins are not identical, and similarly, clonal microbial cells differ in many aspects even when grown simultaneously in a common environment. Using yeast as a model system, we show that a population of isogenic cells all carrying genotype A showed higher cell-to-cell heterogeneity in gene expression than a population of isogenic cells of genotype B. We considered this level of intra-clonal heterogeneity as a quantitative trait and performed genetic linkage (on AxB) to search for regulators of it. This led to the demonstration that transcriptional elongation impairment increases stochastic variation in gene expression in vivo. Our results show that the two levels of inter-individual diversity, genetic and stochastic, are connected by a complex control of the former on the latter. We invite the community to revisit the interpretation of incomplete penetrance, which defines cases where a mutation does not cause the associated phenotype in all its carriers. We propose that, in the case of cancer or other diseases triggered by single cells, such mutations might increase stochastic molecular fluctuations and thereby the fraction of deviant cellular phenotypes in a human body.

A bistable Rb-E2F switch underlies the restriction point

The restriction point (R-point) marks the critical event when a mammalian cell commits to proliferation and becomes independent of growth stimulation. It is fundamental for normal differentiation and tissue homeostasis, and seems to be dysregulated in virtually all cancers. Although the R-point has been linked to various activities involved in the regulation of G1-S transition of the mammalian cell cycle, the underlying mechanism remains unclear. Using single-cell measurements, we show here that the Rb-E2F pathway functions as a bistable switch to convert graded serum inputs into all-or-none E2F responses. Once turned ON by sufficient serum stimulation, E2F can memorize and maintain this ON state independently of continuous serum stimulation. We further show that, at critical concentrations and duration of serum stimulation, bistable E2F activation correlates directly with the ability of a cell to traverse the R-point.

A microfluidic device for temporally controlled gene expression and long-term fluorescent imaging in unperturbed dividing yeast cells

BACKGROUND

Imaging single cells with fluorescent markers over multiple cell cycles is a powerful tool for unraveling the mechanism and dynamics of the cell cycle. Over the past ten years, microfluidic techniques in cell biology have emerged that allow for good control of growth environment. Yet the control and quantification of transient gene expression in unperturbed dividing cells has received less attention.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we describe a microfluidic flow cell to grow Saccharomyces Cerevisiae for more than 8 generations (approximately 12 hrs) starting with single cells, with controlled flow of the growth medium. This setup provides two important features: first, cells are tightly confined and grow in a remarkably planar array. The pedigree can thus be determined and single-cell fluorescence measured with 3 minutes resolution for all cells, as a founder cell grows to a micro-colony of more than 200 cells. Second, we can trigger and calibrate rapid and transient gene expression using reversible administration of inducers that control the GAL1 or MET3 promoters. We then show that periodic 10-20 minutes gene induction pulses can drive many cell division cycles with complete coherence across the cell cluster, with either a G1/S trigger (cln1 cln2 cln3 MET3-CLN2) or a mitotic trigger (cdc20 GALL-CDC20).

CONCLUSIONS/SIGNIFICANCE

In addition to evident cell cycle applications, this device can be used to directly measure the amount and duration of any fluorescently scorable signal-transduction or gene-induction response over a long time period. The system allows direct correlation of cell history (e.g., hysteresis or epigenetics) or cell cycle position with the measured response.

Phenotypic variability of growing cellular populations

The dynamics and diversity of proliferating cellular populations are governed by the interplay between the growth and death rates among the various phenotypes within a colony. In addition, epigenetic multistability can cause cells to spontaneously switch from one phenotype to another. By examining a generalized form of the relative variance of populations and classifying it into intracolony and cross-colony contributions, we study the origins and consequences of cellular population variability. We find that the variability can depend highly on the initial conditions and the constraints placed on the population by the growth environment. We construct a two-phenotype model system and examine, analytically and numerically, its time-dependent variability in both unbounded and population-limited growth environments. We find that in unbounded growth environments the overall variability is strictly governed by the initial conditions. In contrast, when the overall population is limited by the environment, the system eventually relaxes to a unique fixed point regardless of the initial conditions. However, the transient decay to the fixed point depends highly on initial conditions, and the time scale over which the variability decays can be very long, depending on the intrinsic time scales of the system. These results provide insights into the origins of population variability and suggest mechanisms in which variability can arise in commonly used experimental approaches.

Cell encapsulating droplet vitrification

The capability to encapsulate single cells in droplets while retaining high cell viability (>90%) has great impact on tissue engineering, high-throughput screening, as well as clinical diagnostics and therapeutics. We demonstrate a novel method to vitrify a small number of cells using cell-encapsulating droplets. The method allows vitrification at low cryoprotectant concentration (1.5 M propanediol and 0.5 M trehalose), similar to that used in slow freezing protocols. The method was successfully applied to five different mammalian cell types: AML-12 hepatocytes, NIH-3T3 fibroblasts, HL-1 cardiomyocytes, mouse embryonic stem cells, and RAJI cells.

Single cell epitaxy by acoustic picolitre droplets

The capability to encapsulate single to few cells with micrometre precision, high viability, and controlled directionality via a nozzleless ejection technology using a gentle acoustic field would have great impact on tissue engineering, high throughput screening, and clinical diagnostics. We demonstrate encapsulation of single cells (or a few cells) ejected from an open pool in acoustic picolitre droplets. We have developed this technology for the specific purpose of printing cells in various biological fluids, including PBS and agarose hydrogels used in tissue engineering. We ejected various cell types, including mouse embryonic stem cells, fibroblasts, AML-12 hepatocytes, human Raji cells, and HL-1 cardiomyocytes encapsulated in acoustic picolitre droplets of around 37 microm in diameter at rates varying from 1 to 10,000 droplets per second. At such high throughput levels, we demonstrated cell viabilities of over 89.8% across various cell types. Moreover, this ejection method is readily adaptable to other biological applications, such as extracting data from single cells and generating large cell populations from single cells. The technique described in the current study may also be applied to investigate stem cell differentiation at the single cell level, to direct tissue printing, and to isolating pure RNA or DNA from a single cell at the picolitre level. Overall, the techniques described have the potential for widespread impact on many high-throughput testing applications in the biological and health sciences.

The effects of molecular noise and size control on variability in the budding yeast cell cycle

Molecular noise in gene expression can generate substantial variability in protein concentration. However, its effect on the precision of a natural eukaryotic circuit such as the control of cell cycle remains unclear. We use single-cell imaging of fluorescently labelled budding yeast to measure times from division to budding (G1) and from budding to the next division. The variability in G1 decreases with the square root of the ploidy through a 1N/2N/4N ploidy series, consistent with simple stochastic models for molecular noise. Also, increasing the gene dosage of G1 cyclins decreases the variability in G1. A new single-cell reporter for cell protein content allows us to determine the contribution to temporal G1 variability of deterministic size control (that is, smaller cells extending G1). Cell size control contributes significantly to G1 variability in daughter cells but not in mother cells. However, even in daughters, size-independent noise is the largest quantitative contributor to G1 variability. Exit of the transcriptional repressor Whi5 from the nucleus partitions G1 into two temporally uncorrelated and functionally distinct steps. The first step, which depends on the G1 cyclin gene CLN3, corresponds to noisy size control that extends G1 in small daughters, but is of negligible duration in mothers. The second step, whose variability decreases with increasing CLN2 gene dosage, is similar in mothers and daughters. This analysis decomposes the regulatory dynamics of the Start transition into two independent modules, a size sensing module and a timing module, each of which is predominantly controlled by a different G1 cyclin.

Phosphorylation of the Sic1 inhibitor of B-type cyclins in Saccharomyces cerevisiae is not essential but contributes to cell cycle robustness

In budding yeast, B-type cyclin (Clb)-dependent kinase activity is essential for S phase and mitosis. In newborn G(1) cells, Clb kinase accumulation is blocked, in part because of the Sic1 stoichiometric inhibitor. Previous results strongly suggested that G(1) cyclin-dependent Sic1 phosphorylation, and its consequent degradation, is essential for S phase. However, cells containing a precise endogenous gene replacement of SIC1 with SIC1-0P (all nine phosphorylation sites mutated) were fully viable. Unphosphorylatable Sic1 was abundant and nuclear throughout the cell cycle and effectively inhibited Clb kinase in vitro. SIC1-0P cells had a lengthened G(1) and increased G(1) cyclin transcriptional activation and variable delays in the budded part of the cell cycle. SIC1-0P was lethal when combined with deletion of CLB2, CLB3, or CLB5, the major B-type cyclins. Sic1 phosphorylation provides a sharp link between G(1) cyclin activation and Clb kinase activation, but failure of Sic1 phosphorylation and proteolysis imposes a variable cell cycle delay and extreme sensitivity to B-type cyclin dosage, rather than a lethal cell cycle block.

Noise in timing and precision of gene activities in a genetic cascade

The timing of events along the induction cascade of bacteriophage lambda is independent of UV dose and displays increased relative temporal precision with cascade progression.

This behavior is reproduced by a model of a cascade consisting of independent steps that shows that higher temporal precision can be attained by a cascade consisting of a large number of fast steps.

The observed cell-cell variability in cascade timing is not due to differences in uniform dilation of intervals between events among cells, but rather to the independent distribution of interval durations within the cascade, consistently with the modular architecture of the lambda genome.

The single-cell time lapse study reveals a bistable regime at low UV doses in which some cells are induced while others are not, evidence for a commitment point beyond which lysis will occur, and an unexpected shutoff of the lambda pR promoter.

Stochasticity or noise, an inherent property of all biological networks, is often manifested by different phenotypic behaviors in clonal populations of cells (Raser and O'Shea, 2005). Noise can arise, for instance, from sources such as cell–cell variations in small numbers of regulatory molecules or from the stochastic nature of molecular interactions (Paulsson, 2005). Besides affecting the number of molecules in a cell, noise may also lead to variability in timing of particular events along a given pathway. In this work, we studied temporal noise in the induction cascade of phage lambda.

Infection of a bacterial cell by bacteriophage lambda can lead to two different fates (Ptashne, 2004; Dodd et al, 2005; Oppenheim et al, 2005): the phage can either multiply inside the host leading to its eventual lysis and the generation of progeny virions (the lytic pathway) or, alternatively, it can integrate its genome into the host's genome (prophage state), replicating passively with the latter (the lysogenic pathway). The prophage state is highly stable, being maintained by a phage-encoded repressor, which shuts off phage genes leading to lytic growth. However, the lytic pathway can be induced in a lysogenic cell, through the activation of the bacterial SOS response to DNA damage (Little, 1996), for example by UV irradiation. Once activated, the SOS response results in cleavage of the lambda repressor, leading to expression of the phage early and late genes, and culminating in the lysis of the host cell.

The lambda induction cascade has been extensively characterized over the years. We built upon this knowledge to tap the cascade at different points and quantitatively analyze the progressive loss of temporal coherence between cells, as different stages along the cascade are executed, following synchronous induction. Using time-lapse microscopy, we monitored the time of activation of early and late genes in individual cells using lambda pR and pR′-tR′ promoter-GFP fusions, respectively, by means of reporter plasmids, and finally the time of lysis. Sample results are shown in Figure 2.

At low UV levels (5 J/m²), the network exhibits bistability: only approximately 40% of the bacteria lyse, whereas the others continue to divide, following a lag period. At high UV levels (20 J/m²), almost all bacteria lyse. We found that the timing of events in cells that lyse is independent of UV dose. This is in contrast to the known behavior of the SOS network (Friedman et al, 2005), indicating that these two networks proceed independently. Following induction, a surprising shutoff in the activity of the pR promoter is observed in all cells (see Figure 2). Furthermore, the data show that whereas early genes are expressed in all cells irrespective of cell fate, late genes are expressed only in the lysing cells, indicating that similar to infection, a specific commitment checkpoint is operating.

To characterize the temporal variability in a cell population, we used the coefficient of variation, defined as the non-dimensional ratio of the standard deviation and the mean time of occurrence of a particular event. We studied the changes in both standard deviation and coefficient of variation in timing of various events along the lambda induction cascade, from the expression of the early genes to the ultimate lysis of the cells. As shown in Figure 6, the absolute noise as measured by the standard deviation increases as the cascade progresses. In contrast, the coefficient of variation, which measures variability relative to the time of occurrence, decreases. Simple theoretical considerations described in the text yield a necessary and sufficient condition for a monotonic decrease in the coefficient of variation. Higher temporal precision can be achieved when the cascade is composed of a large number of fast steps.

Further support for the independence of network modules is furnished by a correlation analysis of the times of occurrence of different steps along the lytic cascade. This analysis also indicates that the variability in lysis time is not due to differences in the global rate of cascade progression, but probably to random fluctuations in the execution time of the various cascade stages. Indeed, phage lambda gene expression architecture is well known to have evolved from a number of independent regulatory modules (Hendrix, 2003).

Biological developmental pathways require proper timing of gene expression. We investigated timing variations of defined steps along the lytic cascade of bacteriophage λ. Gene expression was followed in individual lysogenic cells, after induction with a pulse of UV irradiation. At low UV doses, some cells undergo partial induction and eventually divide, whereas others follow the lytic pathway. The timing of events in cells committed to lysis is independent of the level of activation of the SOS response, suggesting that the lambda network proceeds autonomously after induction. An increased loss of temporal coherence of specific events from prophage induction to lysis is observed, even though the coefficient of variation of timing fluctuations decreases. The observed temporal variations are not due to cell factors uniformly dilating the timing of execution of the cascade. This behavior is reproduced by a simple model composed of independent stages, which for a given mean duration predicts higher temporal precision, when a cascade consists of a large number of steps. Evidence for the independence of regulatory modules in the network is presented.

Ribosome biogenesis is sensed at the Start cell cycle checkpoint

In the yeast Saccharomyces cerevisiae it has long been thought that cells must reach a critical cell size, called the "setpoint," in order to allow the Start cell cycle transition. Recent evidence suggests that this setpoint is lowered when ribosome biogenesis is slowed. Here we present evidence that yeast can sense ribosome biogenesis independently of mature ribosome levels and protein synthetic capacity. Our results suggest that ribosome biogenesis directly promotes passage through Start through Whi5, the yeast functional equivalent to the human tumor suppressor Rb. When ribosome biogenesis is inhibited, a Whi5-dependent mechanism inhibits passage through Start before significant decreases in both the number of ribosomes and in overall translation capacity of the cell become evident. This delay at Start in response to decreases in ribosome biogenesis occurs independently of Cln3, the major known Whi5 antagonist. Thus ribosome biogenesis may be sensed at multiple steps in Start regulation. Ribosome biogenesis may thus both delay Start by increasing the cell size setpoint and independently may promote Start by inactivating Whi5.

Dynamics of single-cell gene expression

Cellular behavior has traditionally been investigated by utilizing bulk-scale methods that measure average values for a population of cells. Such population-wide studies mask the behavior of individual cells and are often insufficient for characterizing biological processes in which cellular heterogeneity plays a key role. A unifying theme of many recent studies has been a focus on the development and utilization of single-cell experimental techniques that are capable of probing key biological phenomena in individual living cells. Recently, novel information about gene expression dynamics has been obtained from single-cell experiments that draw upon the unique capabilities of fluorescent reporter proteins.

Eavesdropping on the cytoskeleton: progress and controversy in the yeast morphogenesis checkpoint

The morphogenesis checkpoint provides a link between bud formation and mitosis in yeast. In this pathway, insults affecting the actin or septin cytoskeleton trigger a cell cycle arrest, mediated by the Wee1 homolog Swe1p, which catalyzes the inhibitory phosphorylation of the mitosis-promoting cyclin-dependent kinase (CDK) on a conserved tyrosine residue. Analyses of Swe1p phosphorylation have mapped 61 sites targeted by CDKs and Polo-related kinases, which control both Swe1p activity and Swe1p degradation. Although the sites themselves are not evolutionarily conserved, the control of Swe1p degradation exhibits many conserved features, and is linked to DNA-responsive checkpoints in vertebrate cells. At the 'sensing' end of the checkpoint, recent work has begun to shed light on how septins are organized and how they impact Swe1p regulators. However, the means by which Swe1p responds to actin perturbations once a bud has formed remains controversial.

Microbial cell individuality and the underlying sources of heterogeneity

Single cells in genetically homogeneous microbial cultures exhibit marked phenotypic individuality, a biological phenomenon that is considered to bolster the fitness of populations. Major phenotypes that are characterized by heterogeneity span the breadth of microbiology, in fields ranging from pathogenicity to ecology. The cell cycle, cell ageing and epigenetic regulation are proven drivers of heterogeneity in several of the best-known phenotypic examples. However, the full contribution of factors such as stochastic gene expression is yet to be realized.