Mitotic control in the absence of cdc25 mitotic inducer in fission yeast

Implications of differential size-scaling of cell-cycle regulators on cell size homeostasis

Accurate timing of division and size homeostasis is crucial for cells. A potential mechanism for cells to decide the timing of division is the differential scaling of regulatory protein copy numbers with cell size. However, it remains unclear whether such a mechanism can lead to robust growth and division, and how the scaling behaviors of regulatory proteins influence the cell size distribution. Here we study a mathematical model combining gene expression and cell growth, in which the cell-cycle activators scale superlinearly with cell size while the inhibitors scale sublinearly. The cell divides once the ratio of their concentrations reaches a threshold value. We find that the cell can robustly grow and divide within a finite range of the threshold value with the cell size proportional to the ploidy. In a stochastic version of the model, the cell size at division is uncorrelated with that at birth. Also, the more differential the cell-size scaling of the cell-cycle regulators is, the narrower the cell-size distribution is. Intriguingly, our model with multiple regulators rationalizes the observation that after the deletion of a single regulator, the coefficient of variation of cell size remains roughly the same though the average cell size changes significantly. Our work reveals that the differential scaling of cell-cycle regulators provides a robust mechanism of cell size control.

Characterizing non-exponential growth and bimodal cell size distributions in fission yeast: An analytical approach

Unlike many single-celled organisms, the growth of fission yeast cells within a cell cycle is not exponential. It is rather characterized by three distinct phases (elongation, septation, and reshaping), each with a different growth rate. Experiments also showed that the distribution of cell size in a lineage can be bimodal, unlike the unimodal distributions measured for the bacterium Escherichia coli. Here we construct a detailed stochastic model of cell size dynamics in fission yeast. The theory leads to analytic expressions for the cell size and the birth size distributions, and explains the origin of bimodality seen in experiments. In particular, our theory shows that the left peak in the bimodal distribution is associated with cells in the elongation phase, while the right peak is due to cells in the septation and reshaping phases. We show that the size control strategy, the variability in the added size during a cell cycle, and the fraction of time spent in each of the three cell growth phases have a strong bearing on the shape of the cell size distribution. Furthermore, we infer all the parameters of our model by matching the theoretical cell size and birth size distributions to those from experimental single-cell time-course data for seven different growth conditions. Our method provides a much more accurate means of determining the size control strategy (timer, adder or sizer) than the standard method based on the slope of the best linear fit between the birth and division sizes. We also show that the variability in added size and the strength of size control in fission yeast depend weakly on the temperature but strongly on the culture medium. More importantly, we find that stronger size homeostasis and larger added size variability are required for fission yeast to adapt to unfavorable environmental conditions.

Advances in microscopy enable us to follow single cells over long timescales from which we can understand how their size varies with time and the nature of innate strategies developed to control cell size. These data show that in many cell types, growth is exponential and the distribution of cell size has one peak, namely there is a single characteristic cell size. However data for fission yeast show remarkable differences: growth is non-exponential and the distribution of cell sizes has two peaks, corresponding to different growth phases. Here we construct a detailed stochastic mathematical model of this organism; by solving the model analytically, we show that it is able to predict the two peaked distributions of cell size seen in data and provide an explanation for each peak in terms of various growth phases of the single-celled organism. Furthermore, by fitting the model to the data, we infer values for the rates of all microscopic processes in our model. This method is shown to provide a much more reliable inference than current methods and shed light on how the strategy used by fission yeast cells to control their size varies with external conditions.

Cell Length Growth in the Fission Yeast Cell Cycle: Is It (Bi)linear or (Bi)exponential?

Fission yeast is commonly used as a model organism in eukaryotic cell growth studies. To describe the cells’ length growth patterns during the mitotic cycle, different models have been proposed previously as linear, exponential, bilinear and biexponential ones. The task of discriminating among these patterns is still challenging. Here, we have analyzed 298 individual cells altogether, namely from three different steady-state cultures (wild-type, wee1-50 mutant and pom1Δ mutant). We have concluded that in 190 cases (63.8%) the bilinear model was more adequate than either the linear or the exponential ones. These 190 cells were further examined by separately analyzing the linear segments of the best fitted bilinear models. Linear and exponential functions have been fitted to these growth segments to determine whether the previously fitted bilinear functions were really correct. The majority of these growth segments were found to be linear; nonetheless, a significant number of exponential ones were also detected. However, exponential ones occurred mainly in cases of rather short segments (<40 min), where there were not enough data for an accurate model fitting. By contrast, in long enough growth segments (≥40 min), linear patterns highly dominated over exponential ones, verifying that overall growth is probably bilinear.

Robust mitotic entry is ensured by a latching switch

Cell cycle events are driven by Cyclin dependent kinases (CDKs) and by their counter-acting phosphatases. Activation of the Cdk1:Cyclin B complex during mitotic entry is controlled by the Wee1/Myt1 inhibitory kinases and by Cdc25 activatory phosphatase, which are themselves regulated by Cdk1:Cyclin B within two positive circuits. Impairing these two feedbacks with chemical inhibitors induces a transient entry into M phase referred to as mitotic collapse. The pathology of mitotic collapse reveals that the positive circuits play a significant role in maintaining the M phase state. To better understand the function of these feedback loops during G2/M transition, we propose a simple model for mitotic entry in mammalian cells including spatial control over Greatwall kinase phosphorylation. After parameter calibration, the model is able to recapture the complex and non-intuitive molecular dynamics reported by Potapova et al. (Potapova et al., 2011). Moreover, it predicts the temporal patterns of other mitotic regulators which have not yet been experimentally tested and suggests a general design principle of cell cycle control: latching switches buffer the cellular stresses which accompany cell cycle processes to ensure that the transitions are smooth and robust.

Mathematical modeling of fission yeast Schizosaccharomyces pombe cell cycle: exploring the role of multiple phosphatases

Cell cycle is the central process that regulates growth and division in all eukaryotes. Based on the environmental condition sensed, the cell lies in a resting phase G0 or proceeds through the cyclic cell division process (G1→S→G2→M). These series of events and phase transitions are governed mainly by the highly conserved Cyclin dependent kinases (Cdks) and its positive and negative regulators. The cell cycle regulation of fission yeast Schizosaccharomyces pombe is modeled in this study. The study exploits a detailed molecular interaction map compiled based on the published model and experimental data. There are accumulating evidences about the prominent regulatory role of specific phosphatases in cell cycle regulations. The current study emphasizes the possible role of multiple phosphatases that governs the cell cycle regulation in fission yeast S. pombe. The ability of the model to reproduce the reported regulatory profile for the wild-type and various mutants was verified though simulations.

ELECTRONIC SUPPLEMENTARY MATERIAL

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Protein tyrosine kinase Wee1B is essential for metaphase II exit in mouse oocytes

Waves of cyclin synthesis and degradation regulate the activity of Cdc2 protein kinase during the cell cycle. Cdc2 inactivation by Wee1B-mediated phosphorylation is necessary for arrest of the oocyte at G2-prophase, but it is unclear whether this regulation functions later during the metaphase-to-anaphase transition. We show that reactivation of a Wee1B pathway triggers the decrease in Cdc2 activity during egg activation. When Wee1B is down-regulated, oocytes fail to form a pronucleus in response to Ca(2+) signals. Calcium-calmodulin-dependent kinase II (CaMKII) activates Wee1B, and CaMKII-driven exit from metaphase II is inhibited by Wee1B down-regulation, demonstrating that exit from metaphase requires not only a proteolytic degradation of cyclin B but also the inhibitory phosphorylation of Cdc2 by Wee1B.

Computational analysis of mammalian cell division gated by a circadian clock: quantized cell cycles and cell size control

Cell cycle and circadian rhythms are conserved from cyanobacteria to humans with robust cyclic features. Recently, molecular links between these two cyclic processes have been discovered. Core clock transcription factors, Bmal1 and Clock (Clk), directly regulate Wee1 kinase, which inhibits entry into the mitosis. We investigate the effect of this connection on the timing of mammalian cell cycle processes with computational modeling tools. We connect a minimal model of circadian rhythms, which consists of transcription-translation feedback loops, with a modified mammalian cell cycle model from Novak and Tyson (2004). As we vary the mass doubling time (MDT) of the cell cycle, stochastic simulations reveal quantized cell cycles when the activity of Wee1 is influenced by clock components. The quantized cell cycles disappear in the absence of coupling or when the strength of this link is reduced. More intriguingly, our simulations indicate that the circadian clock triggers critical size control in the mammalian cell cycle. A periodic brake on the cell cycle progress via Wee1 enforces size control when the MDT is quite different from the circadian period. No size control is observed in the absence of coupling. The issue of size control in the mammalian system is debatable, whereas it is well established in yeast. It is possible that the size control is more readily observed in cell lines that contain circadian rhythms, since not all cell types have a circadian clock. This would be analogous to an ultradian clock intertwined with quantized cell cycles (and possibly cell size control) in yeast. We present the first coupled model between the mammalian cell cycle and circadian rhythms that reveals quantized cell cycles and cell size control influenced by the clock.

Irreversible cell-cycle transitions are due to systems-level feedback

The irreversibility of cell-cycle transitions is commonly thought to derive from the irreversible degradation of certain regulatory proteins. We argue that irreversible transitions in the cell cycle (or in any other molecular control system) cannot be attributed to a single molecule or reaction, but that they derive from feedback signals in reaction networks. This systems-level view of irreversibility is supported by many experimental observations.

The time-profile of cell growth in fission yeast: model selection criteria favoring bilinear models over exponential ones

BACKGROUND

There is considerable controversy concerning the exact growth profile of size parameters during the cell cycle. Linear, exponential and bilinear models are commonly considered, and the same model may not apply for all species. Selection of the most adequate model to describe a given data-set requires the use of quantitative model selection criteria, such as the partial (sequential) F-test, the Akaike information criterion and the Schwarz Bayesian information criterion, which are suitable for comparing differently parameterized models in terms of the quality and robustness of the fit but have not yet been used in cell growth-profile studies.

RESULTS

Length increase data from representative individual fission yeast (Schizosaccharomyces pombe) cells measured on time-lapse films have been reanalyzed using these model selection criteria. To fit the data, an extended version of a recently introduced linearized biexponential (LinBiExp) model was developed, which makes possible a smooth, continuously differentiable transition between two linear segments and, hence, allows fully parametrized bilinear fittings. Despite relatively small differences, essentially all the quantitative selection criteria considered here indicated that the bilinear model was somewhat more adequate than the exponential model for fitting these fission yeast data.

CONCLUSION

A general quantitative framework was introduced to judge the adequacy of bilinear versus exponential models in the description of growth time-profiles. For single cell growth, because of the relatively limited data-range, the statistical evidence is not strong enough to favor one model clearly over the other and to settle the bilinear versus exponential dispute. Nevertheless, for the present individual cell growth data for fission yeast, the bilinear model seems more adequate according to all metrics, especially in the case of wee1Delta cells.

Dynamics of the cell cycle: checkpoints, sizers, and timers

We have developed a generic mathematical model of a cell cycle signaling network in higher eukaryotes that can be used to simulate both the G1/S and G2/M transitions. In our model, the positive feedback facilitated by CDC25 and wee1 causes bistability in cyclin-dependent kinase activity, whereas the negative feedback facilitated by SKP2 or anaphase-promoting-complex turns this bistable behavior into limit cycle behavior. The cell cycle checkpoint is a Hopf bifurcation point. These behaviors are coordinated by growth and division to maintain normal cell cycle and size homeostasis. This model successfully reproduces sizer, timer, and the restriction point features of the eukaryotic cell cycle, in addition to other experimental findings.

Effects of stochasticity in models of the cell cycle: from quantized cycle times to noise-induced oscillations

Noise and fluctuations are ubiquitous in living systems. Still, the interaction between complex biochemical regulatory systems and the inherent fluctuations ('noise') is only poorly understood. As a paradigmatic example, we study the implications of noise on a recently proposed model of the eukaryotic cell cycle, representing a complex network of interactions between several genes and proteins. The purpose of this work is twofold: First, we show that the inclusion of noise into the description of the system accounts for several recent experimental findings, as e.g. the existence of quantized cycle times in wee1- cdc25delta double-mutant cells of fission yeast. In the main part, we then focus on more general aspects of the interplay between noise and the dynamics of the system. In particular, we demonstrate that a stochastic description leads to qualitative changes in the dynamics, such as the emergence of noise-induced oscillations. These findings will be discussed in the light of an ongoing debate on models of cell division as limit-cycle oscillators versus checkpoint mechanisms.

Growth during the cell cycle

During the cell cycle, major bulk parameters such as volume, dry mass, total protein, and total RNA double and such growth is a fundamental property of the cell cycle. The patterns of growth in volume and total protein or RNA provide an "envelope" that contains and may restrict the gear wheels. The main parameters of cell cycle growth were established in the earlier work when people moved from this field to the reductionist approaches of molecular biology, but very little is known on the patterns of metabolism. Most of the bulk properties of cells show a continuous increase during the cell cycle, although the exact pattern of this increase may vary. Since the earliest days, there have been two popular models, based on an exponential increase and linear increase. In the first, there is no sharp change in the rate of increase through the cycle but a smooth increase by a factor of two. In the second, the rate of increase stays constant through much of the cycle but it doubles sharply at a rate change point (RCP). It is thought that the exponential increase is caused by the steady growth of ribosome numbers and the linear pattern is caused by a doubling of the structural genes during the S period giving an RCP--a "gene dosage" effect. In budding yeast, there are experiments fitting both models but on balance slightly favoring "gene dosage." In fission yeast, there is no good evidence of exponential increase. All the bulk properties, except O2 consumption, appear to follow linear patterns with an RCP during the short S period. In addition, there is in wild-type cells a minor RCP in G2 where the rate increases by 70%. In mammalian cells, there is good but not extensive evidence of exponential increase. In Escherichia coli, exponential increase appears to be the pattern. There are two important points: First, some proteins do not show peaks of periodic synthesis. If they show patterns of exponential increase both they and the total protein pattern will not be cell cycle regulated. However, if the total protein pattern is not exponential, then a majority of the individual proteins will be so regulated. If this majority pattern is linear, then it can be detected from rate measurements on total protein. However, it would be much harder at the level of individual proteins where the methods are at present not sensitive enough to detect a rate change by a factor of two. At a simple level, it is only the exponential increase that is not cell cycle regulated in a synchronous culture. The existence of a "size control" is well known and the control has been studied for a long time, but it has been remarkably resistant to molecular analysis. The attainment of a critical size triggers the periodic events of the cycle such as the S period and mitosis. This control acts as a homeostatic effector that maintains a constant "average" cell size at division through successive cycles in a growing culture. It is a vital link coordinating cell growth with periodic events of the cycle. A size control is present in all the systems and appears to operate near the start of S or of mitosis when the cell has reached a critical size, but the molecular mechanism by which size is measured remains both obscure and a challenge. A simple version might be for the cell to detect a critical concentration of a gene product.

Regularities and irregularities in the cell cycle of the fission yeast, Schizosaccharomyces pombe (a review)

In an exponentially growing wild-type fission yeast culture a size control mechanism ensures that mitosis is executed only if the cells have reached a critical size. However, there is some scattering both in cell length at birth (BL) and in cycle time (CT). By computational simulations we show here that this scattering cannot be explained solely by asymmetric cell division, therefore we assume that nuclear division is a stochastic, asymmetric process as well. We introduce an appropriate stochastic variable into a mathematical model and prove that this assumption is suitable to describe the CT vs. BL graph in a wild-type fission yeast population. In a double mutant of fission yeast (namely wee1-50 cdc25 delta) this CT vs. BL plot is even more curious: cycle time splits into three different values resulting in three clusters in this coordinate system. We show here that it is possible to describe these quantized cycles by choosing the appropriate values of the key parameters of mitotic entry and exit and even more the clustered behavior may be simulated by applying a further stochastic parameter.

Checking cell size in yeast

To remain viable, cells have to coordinate cell growth with cell division. In yeast, this occurs at two control points: the boundaries between G1 and S phases, also known as Start, and between G2 and M phases. Theoretically, coordination can be achieved by independent regulation of growth and division, or by participation of surveillance mechanisms in which cell size feeds back into cell-cycle control. This article discusses recent advances in the identification of sizing mechanisms in budding and in fission yeast, and how these mechanisms integrate with environmental stimuli. A comparison of the G1-S and G2-M size-control modules in the two species reveals a degree of conservation higher than previously thought. This reinforces the notion that internal sizing could be a conserved feature of cell-cycle control throughout eukaryotes.

G2/M arrest caused by actin disruption is a manifestation of the cell size checkpoint in fission yeast

In budding yeast, actin disruption prevents nuclear division. This has been explained as activation of a morphogenesis checkpoint monitoring the integrity of the actin cytoskeleton. The checkpoint operates through inhibitory tyrosine phosphorylation of Cdc28, the budding yeast Cdc2 homolog. Wild-type Schizosaccharomyces pombe cells also arrest before mitosis after actin depolymerization. Oversized cells, however, enter mitosis uninhibited. We carried out a careful analysis of the kinetics of mitotic initiation after actin disruption in undersized and oversized cells. We show that an inability to reach the mitotic size threshold explains the arrest in smaller cells. Among the regulators that control the level of the inhibitory Cdc2-Tyr15 phosphorylation, the Cdc25 protein tyrosine phosphatase is required to link cell size monitoring to mitotic control. This represents a novel function of the Cdc25 phosphatase. Furthermore, we demonstrate that this cell size-monitoring system fulfills the formal criteria of a cell cycle checkpoint.

A stochastic, molecular model of the fission yeast cell cycle: role of the nucleocytoplasmic ratio in cycle time regulation

We propose a stochastic version of a recently published, deterministic model of the molecular mechanism regulating the mitotic cell cycle of fission yeast, Schizosaccharomyces pombe. Stochasticity is introduced in two ways: (i) by considering the known asymmetry of cell division, which produces daughter cells of slightly different sizes; and (ii) by assuming that the nuclear volumes of the two newborn cells may also differ. In this model, the accumulation of cyclins in the nucleus is proportional to the ratio of cytoplasmic to nuclear volumes. We have simulated the cell-cycle statistics of populations of wild-type cells and of wee1(-) mutant cells. Our results are consistent with well known experimental observations.

Flp1, a fission yeast orthologue of theS. cerevisiae CDC14gene, is not required for cyclin degradation or rum1p stabilisation at the end of mitosis

In Saccharomyces cerevisiae, the phosphoprotein phosphatase Cdc14p plays a central role in exit from mitosis, by promoting B-type cyclin degradation and allowing accumulation of the cyclin-dependent kinase inhibitor Sic1p. Cdc14p is sequestered in the nucleolus during interphase, from where it is released at the end of mitosis, dependent upon mitotic exit network function. The CDC14 gene is essential and loss-of-function mutants arrest at the end of mitosis. We have identified a fission yeast orthologue of CDC14 through database searches. A Schizosaccharomyces pombe flp1 (cdc fourteen-like-phosphatase) null mutant is viable, divides at a reduced size and shows defects in septation. flp1p is not the essential effector of the S. pombe septation initiation network, but may potentiate signalling of the onset of septation. In contrast to S. cerevisiae Cdc14p, flp1p is not required for the accumulation or destruction of the B-type cyclin cdc13p, the cyclin-dependent kinase inhibitor rum1p, or for dephosphorylation of the APC/C specificity factor ste9p in G1. Like its budding yeast counterpart, flp1p is restricted to the nucleolus until mitosis, when it is dispersed through the nucleus. In contrast to S. cerevisiae Cdc14p, flp1p is also present on the mitotic spindle and contractile ring. The potential roles of flp1p in cell cycle control are discussed.

Mathematical model of the cell division cycle of fission yeast

Much is known about the genes and proteins controlling the cell cycle of fission yeast. Can these molecular components be spun together into a consistent mechanism that accounts for the observed behavior of growth and division in fission yeast cells? To answer this question, we propose a mechanism for the control system, convert it into a set of 14 differential and algebraic equations, study these equations by numerical simulation and bifurcation theory, and compare our results to the physiology of wild-type and mutant cells. In wild-type cells, progress through the cell cycle (G1-->S-->G2-->M) is related to cyclic progression around a hysteresis loop, driven by cell growth and chromosome alignment on the metaphase plate. However, the control system operates much differently in double-mutant cells, wee1(-) cdc25Delta, which are defective in progress through the latter half of the cell cycle (G2 and M phases). These cells exhibit "quantized" cycles (interdivision times clustering around 90, 160, and 230 min). We show that these quantized cycles are associated with a supercritical Hopf bifurcation in the mechanism, when the wee1 and cdc25 genes are disabled. (c) 2001 American Institute of Physics.

Genetic control of cell size

Over the past 25 years, the genetic control of cell size has mainly been addressed in yeast, a single-celled organism. Recent insights from Drosophila have shed light on the signalling pathways responsible for adjusting and maintaining cell size in metazoans. Evidence is emerging for a signalling cascade conserved in evolution that links external nutrient sources to cell size.

Modeling the fission yeast cell cycle: quantized cycle times in wee1- cdc25Delta mutant cells

A detailed mathematical model for the fission yeast mitotic cycle is developed based on positive and negative feedback loops by which Cdc13/Cdc2 kinase activates and inactivates itself. Positive feedbacks are created by Cdc13/Cdc2-dependent phosphorylation of specific substrates: inactivating its negative regulators (Rum1, Ste9 and Wee1/Mik1) and activating its positive regulator (Cdc25). A slow negative feedback loop is turned on during mitosis by activation of Slp1/anaphase-promoting complex (APC), which indirectly re-activates the negative regulators, leading to a drop in Cdc13/Cdc2 activity and exit from mitosis. The model explains how fission yeast cells can exit mitosis in the absence of Ste9 (Cdc13 degradation) and Rum1 (an inhibitor of Cdc13/Cdc2). We also show that, if the positive feedback loops accelerating the G(2)/M transition (through Wee1 and Cdc25) are weak, then cells can reset back to G(2) from early stages of mitosis by premature activation of the negative feedback loop. This resetting can happen more than once, resulting in a quantized distribution of cycle times, as observed experimentally in wee1(-) cdc25Delta mutant cells. Our quantitative description of these quantized cycles demonstrates the utility of mathematical modeling, because these cycles cannot be understood by intuitive arguments alone.

The G(2) DNA damage checkpoint targets both Wee1 and Cdc25

The onset of mitosis is controlled by the cyclin dependent kinase Cdc2p. Cdc2p activity is controlled through the balance of phosphorylation and dephosphorylation of tyrosine-15 (Y15) by the Wee1p kinase and Cdc25p phosphatase. In the fission yeast Schizosaccharomyces pombe, detection of DNA damage in G(2) activates a checkpoint that prevents entry into mitosis through the maintenance of Y15 phosphorylation of Cdc2p, thus ensuring DNA repair precedes chromosome segregation. The protein kinase Chk1p is the endpoint of this checkpoint pathway. We have previously reported that overexpression of Chk1p causes a wee1(+)-dependent G(2) arrest, and this or irradiation leads to hyperphosphorylation of Wee1p. Moreover, Chk1p directly phosphorylates Wee1p in vitro. These data suggested that Wee1p is a key target of Chk1p action in checkpoint control. However, cells lacking wee1(+) are checkpoint proficient and sustained Chk1p overexpression arrests cell cycle progression independently of Wee1p. Therefore, up-regulation of Wee1p alone cannot enforce a checkpoint arrest. Chk1p can also phosphorylate Cdc25p in vitro. These phosphorylation events are thought to promote the interaction with 14–3-3 proteins the cytoplasmic retention of the 14–3-3/Cdc25p complexes. However, we show here that the G(2) DNA damage checkpoint is intact in cells that regulate mitotic entry independently of Cdc25p. Further, these cells are still sensitive to Chk1p-mediated arrest, and so down-regulation of Cdc25p is also insufficient to regulate checkpoint arrest. Conversely, inactivation of both wee1(+) and cdc25(+)abolishes checkpoint control. We also show that activation of the G(2) DNA damage checkpoint induces a transient increase in Wee1p levels. We conclude that the G(2) DNA damage checkpoint simultaneously signals via both up-regulation of Wee1p and down-regulation of Cdc25p, thus providing a double-lock mechanism to ensure cell cycle arrest and genomic stability.

Ultradian clocks in eukaryotic microbes: from behavioural observation to functional genomics

Period homeostasis is the defining characteristic of a biological clock. Strict period homeostasis is found for the ultradian clocks of eukaryotic microbes. In addition to being temperature-compensated, the period of these rhythms is unaffected by differences in nutrient composition or changes in other environmental variables. The best-studied examples of ultradian clocks are those of the ciliates Paramecium tetraurelia and Tetrahymena sp. and of the fission yeast, Schizosaccharomyces pombe. In these single cell eukaryotes, up to seven different parameters display ultradian rhythmicity with the same, species- and strain-specific period. In fission yeast, the molecular genetic analysis of ultradian clock mechanisms has begun with the systematic analysis of mutants in identified candidate genes. More than 40 "clock mutants" have already been identified, most of them affected in components of major regulatory and signalling pathways. These results indicate a high degree of complexity for a eukaryotic clock mechanism. BioEssays 22:16-22, 2000.

Felix Hoppe-Seyler Lecture 1999. Cyclin dependent kinases and regulation of the fission yeast cell cycle

The cyclin dependent kinases (CDKs), formed by complexes between Cdc2p and the B-cyclins Cig2p and Cdc13p, have a central role in regulating the fission yeast cell cycle and maintaining genomic stability. The CDK Cig2p/Cdc2p controls the onset of S-phase and the CDK Cdc13p/Cdc2p controls the onset of mitosis and ensures that there is only one S-phase in each cell. Cdc13p/Cdc2p can replace Cig2p/Cdc2p forthe onset of S-phase, suggesting that the increasing activity of a single CDK during the cell cycle is sufficient to drive a cell in an orderly fashion into S-phase and into mitosis. If S-phase is incomplete, then inhibition of Cdc13p/ Cdc2p prevents cells with unreplicated DNA from undergoing a catastrophic entry into mitosis. Control of CDK activity is also important to allow cells to exit the cell cycle and accumulate in G1 in response to nutritional deprivation and the presence of pheromone.