A yeast cell cycle model integrating stress, signaling, and physiology.

The cell division cycle in eukaryotic cells is a series of highly coordinated molecular interactions that ensure that cell growth, duplication of genetic material, and actual cell division are precisely orchestrated to give rise to two viable progeny cells. Moreover, the cell cycle machinery is responsible for incorporating information about external cues or internal processes that the cell must keep track of to ensure a coordinated, timely progression of all related processes. This is most pronounced in multicellular organisms, but also a cardinal feature in model organisms such as baker's yeast. The complex and integrative behavior is difficult to grasp and requires mathematical modeling to fully understand the quantitative interplay of the single components within the entire system. Here, we present a self-oscillating mathematical model of the yeast cell cycle that comprises all major cyclins and their main regulators. Furthermore, it accounts for the regulation of the cell cycle machinery by a series of external stimuli such as mating pheromones and changes in osmotic pressure or nutrient quality. We demonstrate how the external perturbations modify the dynamics of cell cycle components and how the cell cycle resumes after adaptation to or relief from stress.

Bud-Localization of CLB2 mRNA Can Constitute a Growth Rate Dependent Daughter Sizer.

Maintenance of cellular size is a fundamental systems level process that requires balancing of cell growth with proliferation. This is achieved via the cell division cycle, which is driven by the sequential accumulation and destruction of cyclins. The regulatory network around these cyclins, particularly in G1, has been interpreted as a size control network in budding yeast, and cell size as being decisive for the START transition. However, it is not clear why disruptions in the G1 network may lead to altered size rather than loss of size control, or why the S-G2-M duration also depends on nutrients. With a mathematical population model comprised of individually growing cells, we show that cyclin translation would suffice to explain the observed growth rate dependence of cell volume at START. Moreover, we assess the impact of the observed bud-localisation of the G2 cyclin CLB2 mRNA, and find that localised cyclin translation could provide an efficient mechanism for measuring the biosynthetic capacity in specific compartments: The mother in G1, and the growing bud in G2. Hence, iteration of the same principle can ensure that the mother cell is strong enough to grow a bud, and that the bud is strong enough for independent life. Cell sizes emerge in the model, which predicts that a single CDK-cyclin pair per growth phase suffices for size control in budding yeast, despite the necessity of the cell cycle network around the cyclins to integrate other cues. Size control seems to be exerted twice, where the G2/M control affects bud size through bud-localized translation of CLB2 mRNA, explaining the dependence of the S-G2-M duration on nutrients. Taken together, our findings suggest that cell size is an emergent rather than a regulatory property of the network linking growth and proliferation.

SensA: web-based sensitivity analysis of SBML models.

SUMMARY: SensA is a web-based application for sensitivity analysis of mathematical models. The sensitivity analysis is based on metabolic control analysis, computing the local, global and time-dependent properties of model components. Interactive visualization facilitates interpretation of usually complex results. SensA can contribute to the analysis, adjustment and understanding of mathematical models for dynamic systems. AVAILABILITY AND IMPLEMENTATION: SensA is available at http://gofid.biologie.hu-berlin.de/ and can be used with any modern browser. The source code can be found at https://bitbucket.org/floettma/sensa/ (MIT license)

Size homeostasis can be intrinsic to growing cell populations and explained without size sensing or signalling.

The cell division cycle orchestrates cellular growth and division. The machinery underpinning the cell division cycle is well characterized, but the actual cue(s) driving the cell division cycle remains unknown. In rapidly growing and dividing yeast cells, this cue has been proposed to be cell size. Presumably, a mechanism communicating cell size acts as gatekeeper for the cell division cycle via the G(1) network, which triggers G(1) exit only when a critical size has been reached. Here, we evaluate this hypothesis with a minimal core model linking metabolism, growth and the cell division cycle. Using this model, we (a) present support for coordinated regulation of G(1)/S and G(2)/M transition in Saccharomyces cerevisiae in response to altered growth conditions, (b) illustrate the intrinsic antagonism between G(1) progression and cell size and (c) provide evidence that the coupling of growth and division is sufficient to allow for size homeostasis without directly communicating or measuring cell size. We show that even with a rudimentary version of the G(1) network consisting of a single unregulated cyclin, size homeostasis is maintained in populations during autocatalytic growth when the geometric constraint on nutrient supply is considered. Taken together, our results support the notion that cell size is a consequence rather than a regulator of growth and division.

Replication origins and timing of temporal replication in budding yeast: how to solve the conundrum?

Similarly to metazoans, the budding yeast Saccharomyces cereviasiae replicates its genome with a defined timing. In this organism, well-defined, site-specific origins, are efficient and fire in almost every round of DNA replication. However, this strategy is neither conserved in the fission yeast Saccharomyces pombe, nor in Xenopus or Drosophila embryos, nor in higher eukaryotes, in which DNA replication initiates asynchronously throughout S phase at random sites. Temporal and spatial controls can contribute to the timing of replication such as Cdk activity, origin localization, epigenetic status or gene expression. However, a debate is going on to answer the question how individual origins are selected to fire in budding yeast. Two opposing theories were proposed: the "replicon paradigm" or "temporal program" vs. the "stochastic firing". Recent data support the temporal regulation of origin activation, clustering origins into temporal blocks of early and late replication. Contrarily, strong evidences suggest that stochastic processes acting on origins can generate the observed kinetics of replication without requiring a temporal order. In mammalian cells, a spatiotemporal model that accounts for a partially deterministic and partially stochastic order of DNA replication has been proposed. Is this strategy the solution to reconcile the conundrum of having both organized replication timing and stochastic origin firing also for budding yeast? In this review we discuss this possibility in the light of our recent study on the origin activation, suggesting that there might be a stochastic component in the temporal activation of the replication origins, especially under perturbed conditions.

What influences DNA replication rate in budding yeast?

BACKGROUND: DNA replication begins at specific locations called replication origins, where helicase and polymerase act in concert to unwind and process the single DNA filaments. The sites of active DNA synthesis are called replication forks. The density of initiation events is low when replication forks travel fast, and is high when forks travel slowly. Despite the potential involvement of epigenetic factors, transcriptional regulation and nucleotide availability, the causes of differences in replication times during DNA synthesis have not been established satisfactorily, yet. METHODOLOGY/PRINCIPAL FINDINGS: Here, we aimed at quantifying to which extent sequence properties contribute to the DNA replication time in budding yeast. We interpreted the movement of the replication machinery along the DNA template as a directed random walk, decomposing influences on DNA replication time into sequence-specific and sequence-independent components. We found that for a large part of the genome the elongation time can be well described by a global average replication rate, thus by a single parameter. However, we also showed that there are regions within the genomic landscape of budding yeast with highly specific replication rates, which cannot be explained by global properties of the replication machinery. CONCLUSION/SIGNIFICANCE: Computational models of DNA replication in budding yeast that can predict replication dynamics have rarely been developed yet. We show here that even beyond the level of initiation there are effects governing the replication time that can not be explained by the movement of the polymerase along the DNA template alone. This allows us to characterize genomic regions with significantly altered elongation characteristics, independent of initiation times or sequence composition.

Kinetic modelling of DNA replication initiation in budding yeast.

DNA replication is restricted to a specific time window of the cell cycle, called S phase. Successful progression through S phase requires replication to be properly regulated to ensure that the entire genome is duplicated exactly once, without errors, in a timely fashion. As a result, DNA replication has evolved into a tightly regulated process involving the coordinated action of numerous factors that function in all phases of the cell cycle. Biochemical mechanisms driving the eukaryotic cell division cycle have been the subject of a number of mathematical models. However, cell cycle networks reported in literature so far have not addressed the steps of DNA replication events. In particular, the assembly of the replication machinery is crucial for the timing of S phase. This event, called "initiation", which occurs in late M / early G1 of the cell cycle, starts with the assembly of the pre-replicative complex (pre-RC) at the origins of replication on the DNA. Its activation depends on the availability of different kinase complexes, cyclin-dependent kinases (CDKs) and Dbf-dependent kinase (DDK), which phosphorylate specific components of the pre-RC to convert it into the pre-initiation complex (pre-IC). We have developed an ODE-based model of the network responsible for this process in budding yeast by using mass-action kinetics. We considered all steps from the assembly of the first components at the DNA replication origin up to the active replisome that recruits the polymerases and verified the computational dynamics with the available literature data. Our results highlighted the link between activation of CDK and DDK and the step-by-step formation of both pre-RC and pre-IC, suggesting S-CDK (Cdk1-Clb5,6) to be the main regulator of the process.

Different groups of metabolic genes cluster around early and late firing origins of replication in budding yeast.

DNA replication is a fundamental process that is tightly regulated during the cell cycle. In budding yeast it starts from multiple origins of replication and proceeds in a timely fashion according to a reproducible temporal program until the entire DNA is replicated exactly once per cell cycle. In this program an origin seems to have an inherent firing probability at a specific time in S-phase that is conserved over the population. However, what exactly determines the origin initiation time remains obscure. In this work, we analyze the gene content that clusters around replication origins following the assumption that inherent origin properties that determine staggered initiation times could potentially be mirrored in the close origin proximity. We perform a Gene Ontology term enrichment test and find that metabolic genes are significantly over-represented in the regions that are close to the starting points of DNA replication. Furthermore, functional analysis also reveals that catabolic genes cluster around early firing origins, whereas anabolic genes can rather be found in the proximity of late firing origins of replication. We speculate that, in budding yeast, gene function around replication origins correlates with their intrinsic probability to initiate DNA replication at a given point in S-phase.