Whi5 phosphorylation embedded in the G1/S network dynamically controls critical cell size and cell fate

Influence of cell volume on the gene transcription rate

Cells vary in volume throughout their life cycle and in many other circumstances, while their genome remains identical. Hence, the RNA production factory must adapt to changing needs, while maintaining the same production lines. This paradox is resolved by different mechanisms in distinct cells and circumstances. RNA polymerases have evolved to cope with the particular circumstances of each case and the different characteristics of the several RNA molecule types, especially their stabilities. Here we review current knowledge on these issues. We focus on the yeast Saccharomyces cerevisiae, where many of the studies have been performed, although we compare and discuss the results obtained in other eukaryotes and propose several ideas and questions to be tested and solved in the future. TAKE AWAY.

Data integration strategies for whole-cell modeling

Data makes the world go round-and high quality data is a prerequisite for precise models, especially for whole-cell models (WCM). Data for WCM must be reusable, contain information about the exact experimental background, and should-in its entirety-cover all relevant processes in the cell. Here, we review basic requirements to data for WCM and strategies how to combine them. As a species-specific resource, we introduce the Yeast Cell Model Data Base (YCMDB) to illustrate requirements and solutions. We discuss recent standards for data as well as for computational models including the modeling process as data to be reported. We outline strategies for constructions of WCM despite their inherent complexity.

The Warburg Effect Explained: Integration of Enhanced Glycolysis with Heterogeneous Mitochondria to Promote Cancer Cell Proliferation

The Warburg effect is the long-standing riddle of cancer biology. How does aerobic glycolysis, inefficient in producing ATP, confer a growth advantage to cancer cells? A new evaluation of a large set of literature findings covering the Warburg effect and its yeast counterpart, the Crabtree effect, led to an innovative working hypothesis presented here. It holds that enhanced glycolysis partially inactivates oxidative phosphorylation to induce functional rewiring of a set of TCA cycle enzymes to generate new non-canonical metabolic pathways that sustain faster growth rates. The hypothesis has been structured by constructing two metabolic maps, one for cancer metabolism and the other for the yeast Crabtree effect. New lines of investigation, suggested by these maps, are discussed as instrumental in leading toward a better understanding of cancer biology in order to allow the development of more efficient metabolism-targeted anticancer drugs.

Involvement of the High-Osmolarity Glycerol Pathway of Saccharomyces Cerevisiae in Protection against Copper Toxicity

Although essential for life, copper is also potentially toxic in concentrations that surpass physiological thresholds. The high-osmolarity glycerol pathway of yeast is the main regulator of adaptive responses and is known to play crucial roles in the responses to various stressors. The objective of this research is to determine whether the HOG pathway could be activated and to investigate the possible interplay of the HOG pathway and oxidative stress due to copper exposure. In this research, we demonstrate that copper could induce oxidative stress, including the elevated concentrations of reactive oxygen species (ROS) and malondialdehyde (MDA). Increased combination with GSH, increased intracellular SOD activity, and the up-regulation of relevant genes can help cells defend themselves against oxidative toxicity. The results show that copper treatment triggers marked and prolonged Hog1 phosphorylation. Significantly, oxidative stress generated by copper toxicity is essential for the activation of Hog1. Activated Hog1 is translocated to the nucleus to regulate the expressions of genes such as CTT1, GPD1, and HSP12, among others. Furthermore, copper exposure induced significant G1-phase cell cycle arrest, while Hog1 partially participated in the regulation of cell cycle progression. These novel findings reveal another role for Hog1 in the regulation of copper-induced cellular stress.

Interactions, structural aspects, and evolutionary perspectives of the yeast 'START'-regulatory network

Molecular signal transduction networks which conduct transcription at the G1 to S phase transition of the eukaryotic cell division cycle have been identified in diverse taxa from mammals to baker´s yeast with analogous functional organization. However, regarding some network components, such as the transcriptional regulators STB1 and WHI5, only few orthologs exist which are confined to individual Saccharomycotina species. While Whi5 has been characterized as yeast analog of human Rb protein, in the particular case of Stb1 (Sin three binding protein 1) identification of functional analogs emerges as difficult because to date its exact functionality still remains obscured. By aiming to resolve Stb1´s enigmatic role this Perspectives article especially surveys works covering relations between Cyclin/CDKs, the heteromeric transcription factor complexes SBF (Swi4/Swi6) and MBF (Mbp1/Swi6), as well as additional coregulators (Whi5, Sin3, Rpd3, Nrm1) which are collectively associated with the orderly transcription at 'Start' of the Saccharomyces cerevisiae cell cycle. In this context, interaction capacities of the Sin3-scaffold protein are widely surveyed because its four PAH domains (Paired Amphiphatic Helix) represent a 'recruitment-code' for gene-specific targeting of repressive histone deacetylase activity (Rpd3) via different transcription factors. Here Stb1 plays a role in Sin3´s action on transcription at the G1/S-boundary. Through bioinformatic analyses a potential Sin3-interaction domain (SID) was detected in Stb1, and beyond that, connections within the G1/S-regulatory network are discussed in structural and evolutionary context thereby providing conceptual perspectives.

The Double Phospho/Dephosphorylation Cycle as a Benchmark to Validate an Effective Taylor Series Method to Integrate Ordinary Differential Equations

The double phosphorylation/dephosphorylation cycle consists of a symmetric network of biochemical reactions of paramount importance in many intracellular mechanisms. From a network perspective, they consist of four enzymatic reactions interconnected in a specular way. The general approach to model enzymatic reactions in a deterministic fashion is by means of stiff Ordinary Differential Equations (ODEs) that are usually hard to integrate according to biologically meaningful parameter settings. Indeed, the quest for model simplification started more than one century ago with the seminal works by Michaelis and Menten, and their Quasi Steady-State Approximation methods are still matter of investigation nowadays. This work proposes an effective algorithm based on Taylor series methods that manages to overcome the problems arising in the integration of stiff ODEs, without settling for model approximations. The double phosphorylation/dephosphorylation cycle is exploited as a benchmark to validate the methodology from a numerical viewpoint.

The budding yeast Start repressor Whi7 differs in regulation from Whi5, emerging as a major cell cycle brake in response to stress

Start is the main decision point in the eukaryotic cell cycle at which cells commit to a new round of cell division. It involves the irreversible activation of a transcriptional programme through the inactivation of Start transcriptional repressors: the retinoblastoma family in mammals, or Whi5 and its recently identified paralogue Whi7 (also known as Srl3) in budding yeast. Here, we provide a comprehensive comparison of Whi5 and Whi7 that reveals significant qualitative differences. Indeed, the expression, subcellular localization and functionality of Whi7 and Whi5 are differentially regulated. Importantly, Whi7 shows specific properties in its association with promoters not shared by Whi5, and for the first time, we demonstrate that Whi7, and not Whi5, can be the main contributor to Start inhibition such as it occurs in the response to cell wall stress. Our results help to improve understanding of the interplay between multiple differentially regulated Start repressors in order to face specific cellular conditions.

Highlighted Article: Cells can use the interplay between functionally redundant but differentially regulated cell-cycle repressors in order to confer new repression capabilities and to respond to specific cellular conditions.

Tumor suppressor stars in yeast G1/S transition

Yeast is one of the best-understood biological systems for genetic research. Over the last 40 years, geneticists have striven to search for homologues of tumor suppressors in yeast to simplify cancer research. The star tumor suppressor p21, downstream target of p53, is one of the primary factors on the START point through negatively regulating CycD/E-CDK, the yeast counterpart Cln3-Cdk1. Not like yeast Whi5 that was identified as the analog of the retinoblastoma tumor suppressor protein (Rb) and hence promoted to uncover the mechanism of its cancer suppression, homologue of p21 had not been found in yeast. Our lab identified Cip1 in budding yeast as a novel negative regulator of G1-Cdk1 and proposed that Cip1 is an analog of human p21. Recently, we demonstrated a dual repressive function of Cip1 on START timing via the redundant Cln3 and Ccr4 pathways. This work in yeast may help clarify the complex regulation in human p53-p21 signaling cascade. In this review, we will discuss the yeast paralogs of star tumor suppressors in the control of G1/S transition and present the new findings in this field.

Dual Repressive Function by Cip1, a Budding Yeast Analog of p21, in Cell-Cycle START Regulation

Cip1, a newly identified yeast analog of p21, is a Cln3-CDK inhibitor that negatively regulates cell-cycle START. However, its function remains poorly understood. In this study, we found that deletion of CLN3 did not result in bypass of G1-phase arrest caused by Cip1 overexpression. Cip1 depletion in cln3-null mutants significantly advanced the timing of Cln2 expression, supporting the idea that Cip1 represses START in a Cln3-independent manner. We set to search for novel Cip1 interacting proteins and found that Ccr4, a known START regulator, and its associated factor Caf120, interact with Cip1. Ccr4-Caf120 acts redundantly with Cdk1-Cln3 to inhibit Whi5-mediated regulation of START. This interaction was conserved between human Ccr4 and p21. In addition, deletion of WHI5 robustly suppressed G1-phase arrest caused by Cip1 overexpression. We conclude that Cip1 negatively regulates START by acting as a dual repressor of Ccr4 in parallel with Cln3.

Random Parametric Perturbations of Gene Regulatory Circuit Uncover State Transitions in Cell Cycle

Many biological processes involve precise cellular state transitions controlled by complex gene regulation. Here, we use budding yeast cell cycle as a model system and explore how a gene regulatory circuit encodes essential information of state transitions. We present a generalized random circuit perturbation method for circuits containing heterogeneous regulation types and its usage to analyze both steady and oscillatory states from an ensemble of circuit models with random kinetic parameters. The stable steady states form robust clusters with a circular structure that are associated with cell cycle phases. This circular structure in the clusters is consistent with single-cell RNA sequencing data. The oscillatory states specify the irreversible state transitions along cell cycle progression. Furthermore, we identify possible mechanisms to understand the irreversible state transitions from the steady states. We expect this approach to be robust and generally applicable to unbiasedly predict dynamical transitions of a gene regulatory circuit.

Critical slowing down and attractive manifold: A mechanism for dynamic robustness in the yeast cell-cycle process

Biological processes that execute complex multiple functions, such as the cell cycle, must ensure the order of sequential events and maintain dynamic robustness against various fluctuations. Here, we examine the mechanisms and fundamental structure that achieve these properties in the cell cycle of the budding yeast Saccharomyces cerevisiae. We show that this process behaves like an excitable system containing three well-decoupled saddle-node bifurcations to execute DNA replication and mitosis events. The yeast cell-cycle regulatory network can be divided into three modules-the G1/S phase, early M phase, and late M phase-wherein both positive feedback loops in each module and interactions among modules play important roles. Specifically, when the cell-cycle process operates near the critical points of the saddle-node bifurcations, a critical slowing down effect takes place. Such interregnum then allows for an attractive manifold and sufficient duration for cell-cycle events, within which to assess the completion of DNA replication and mitosis, e.g., spindle assembly. Moreover, such arrangement ensures that any fluctuation in an early module or event will not transmit to a later module or event. Thus, our results suggest a possible dynamical mechanism of the cell-cycle process to ensure event order and dynamic robustness and give insight into the evolution of eukaryotic cell-cycle processes.

Challenges and opportunities for strain verification by whole-genome sequencing

Laboratory strains, cell lines, and other genetic materials change hands frequently in the life sciences. Despite evidence that such materials are subject to mix-ups, contamination, and accumulation of secondary mutations, verification of strains and samples is not an established part of many experimental workflows. With the plummeting cost of next generation technologies, it is conceivable that whole genome sequencing (WGS) could be applied to routine strain and sample verification in the future. To demonstrate the need for strain validation by WGS, we sequenced haploid yeast segregants derived from a popular commercial mutant collection and identified several unexpected mutations. We determined that available bioinformatics tools may be ill-suited for verification and highlight the importance of finishing reference genomes for commonly used laboratory strains.

Competition in the chaperone-client network subordinates cell-cycle entry to growth and stress

The precise coordination of growth and proliferation has a universal prevalence in cell homeostasis. As a prominent property, cell size is modulated by the coordination between these processes in bacterial, yeast, and mammalian cells, but the underlying molecular mechanisms are largely unknown. Here, we show that multifunctional chaperone systems play a concerted and limiting role in cell-cycle entry, specifically driving nuclear accumulation of the G1 Cdk-cyclin complex. Based on these findings, we establish and test a molecular competition model that recapitulates cell-cycle-entry dependence on growth rate. As key predictions at a single-cell level, we show that availability of the Ydj1 chaperone and nuclear accumulation of the G1 cyclin Cln3 are inversely dependent on growth rate and readily respond to changes in protein synthesis and stress conditions that alter protein folding requirements. Thus, chaperone workload would subordinate Start to the biosynthetic machinery and dynamically adjust proliferation to the growth potential of the cell.

A comprehensive, mechanistically detailed, and executable model of the cell division cycle in Saccharomyces cerevisiae

Understanding how cellular functions emerge from the underlying molecular mechanisms is a key challenge in biology. This will require computational models, whose predictive power is expected to increase with coverage and precision of formulation. Genome-scale models revolutionised the metabolic field and made the first whole-cell model possible. However, the lack of genome-scale models of signalling networks blocks the development of eukaryotic whole-cell models. Here, we present a comprehensive mechanistic model of the molecular network that controls the cell division cycle in Saccharomyces cerevisiae. We use rxncon, the reaction-contingency language, to neutralise the scalability issues preventing formulation, visualisation and simulation of signalling networks at the genome-scale. We use parameter-free modelling to validate the network and to predict genotype-to-phenotype relationships down to residue resolution. This mechanistic genome-scale model offers a new perspective on eukaryotic cell cycle control, and opens up for similar models-and eventually whole-cell models-of human cells.

Whi2 signals low leucine availability to halt yeast growth and cell death

Cells are exquisitely tuned to environmental ques. Amino acid availability is rapidly sensed, allowing cells to adjust molecular processes and implement short or long-term metabolic shifts accordingly. How levels of most individual amino acids may be sensed and subsequently signaled to inform cells of their nutrient status is largely unknown. We made the unexpected observation that small changes in the levels of specific amino acids can have a profound effect on yeast cell growth, leading to the identification of yeast Whi2 as a negative regulator of cell growth in low amino acids. Although Whi2 was originally thought to be fungi-specific, Whi2 appears to share a conserved structural domain found in a family of 25 largely uncharacterized human genes encoding the KCTD (potassium channel tetramerization domain) protein family. Insights gained from yeast Whi2 are likely to be revealing about human KCTDs, many of which have been implicated or demonstrated to cause disease when mutated. Here we report new evidence that Whi2 responds to specific amino acids in the medium, particularly low leucine levels. We also discuss the known pathways of amino acid signaling and potential points of regulation by Whi2 in nutrient signaling in yeast and mammals.

Scaling of G1 Duration with Population Doubling Time by a Cyclin in Saccharomyces cerevisiae

The longer cells stay in particular phases of the cell cycle, the longer it will take these cell populations to increase. However, the above qualitative description has very little predictive value, unless it can be codified mathematically. A quantitative relation that defines the population doubling time (Td) as a function of the time eukaryotic cells spend in specific cell cycle phases would be instrumental for estimating rates of cell proliferation and for evaluating introduced perturbations. Here, we show that in human cells, the length of the G1 phase (TG1) regressed on Td with a slope of ≈0.75, while in the yeast Saccharomyces cerevisiae, the slope was slightly smaller, at ≈0.60. On the other hand, cell size was not strongly associated with Td or TG1 in cell cultures that were proliferating at different rates. Furthermore, we show that levels of the yeast G1 cyclin Cln3p were positively associated with rates of cell proliferation over a broad range, at least in part through translational control mediated by a short upstream ORF (uORF) in the CLN3 transcript. Cln3p was also necessary for the proper scaling between TG1 and Td In contrast, yeast lacking the Whi5p transcriptional repressor maintained the scaling between TG1 and Td These data reveal fundamental scaling relationships between the duration of eukaryotic cell cycle phases and rates of cell proliferation, point to the necessary role of Cln3p in these relationships in yeast, and provide a mechanistic basis linking Cln3p levels to proliferation rates and the scaling of G1 with doubling time.

Candida glabrata Med3 Plays a Role in Altering Cell Size and Budding Index To Coordinate Cell Growth

Candida glabrata is a promising microorganism for the production of organic acids. Here, we report deletion and quantitative-expression approaches to elucidate the role of C. glabrata Med3AB (CgMed3AB), a subunit of the mediator transcriptional coactivator, in regulating cell growth. Deletion of CgMed3AB caused an 8.6% decrease in final biomass based on growth curve plots and 10.5% lower cell viability. Based on transcriptomics data, the reason for this growth defect was attributable to changes in expression of genes involved in pyruvate and acetyl-coenzyme A (CoA)-related metabolism in a Cgmed3abΔ strain. Furthermore, the mRNA level of acetyl-CoA synthetase was downregulated after deleting Cgmed3ab, resulting in 22.8% and 21% lower activity of acetyl-CoA synthetase and cellular acetyl-CoA, respectively. Additionally, the mRNA level of CgCln3, whose expression depends on acetyl-CoA, was 34% lower in this strain. As a consequence, the cell size and budding index in the Cgmed3abΔ strain were both reduced. Conversely, overexpression of Cgmed3ab led to 16.8% more acetyl-CoA and 120% higher CgCln3 mRNA levels, as well as 19.1% larger cell size and a 13.3% higher budding index than in wild-type cells. Taken together, these results suggest that CgMed3AB regulates cell growth in C. glabrata by coordinating homeostasis between cellular acetyl-CoA and CgCln3.IMPORTANCE This study demonstrates that CgMed3AB can regulate cell growth in C. glabrata by coordinating the homeostasis of cellular acetyl-CoA metabolism and the cell cycle cyclin CgCln3. Specifically, we report that CgMed3AB regulates the cellular acetyl-CoA level, which induces the transcription of Cgcln3, finally resulting in alterations to the cell size and budding index. In conclusion, we report that CgMed3AB functions as a wheel responsible for driving cellular acetyl-CoA metabolism, indirectly inducing the transcription of Cgcln3 and coordinating cell growth. We propose that Mediator subunits may represent a vital regulatory target modulating cell growth in C. glabrata.

Identifying robust hysteresis in networks

We present a new modeling and computational tool that computes rigorous summaries of network dynamics over large sets of parameter values. These summaries, organized in a database, can be searched for observed dynamics, e.g., bistability and hysteresis, to discover parameter regimes over which they are supported. We illustrate our approach on several networks underlying the restriction point of the cell cycle in humans and yeast. We rank networks by how robustly they support hysteresis, which is the observed phenotype. We find that the best 6-node human network and the yeast network share similar topology and robustness of hysteresis, in spite of having no homology between the corresponding nodes of the network. Our approach provides a new tool linking network structure and dynamics.

To summarize our understanding of how genes, their products and other cellular actors interact with each other, we often employ networks to describe their interactions. However, networks do not fully specify how the underlying biological system behaves in different conditions, nor how such response evolves in time. We present a new modeling and computational approach that allows us to compute and collect summaries of network dynamics for large sets of parameter values. We can then search these summaries for all observed behavior. We illustrate our approach on networks that govern entry to the cell cycle in humans and yeast. We rank networks based on how robustly they exhibit the experimentally observed behavior of hysteresis. We find similarities in network structure of the best ranked networks in yeast and humans, which are not explained by a common ancestry. Our approach provides a tool linking network structure and the behavior of the underlying system.

Controlling cell size through sizer mechanisms

Cell size is partly determined through coordination between cell growth and division. How this coordination is achieved mechanistically remains mostly unknown. However, quantitative experiments together with computational modelling have reinvigorated the field and are elucidating underlying molecular processes. Size homeostasis may be achieved through different modes of regulation, including "sizers", "adders" and "timers." For sizer regulation, the cell division cycle does not proceed until a minimal size has been reached, requiring that the cell monitors its own size. Here, we highlight progress in defining sizer mechanisms in fission and budding yeasts showing how accumulation or dilution of key molecules can be used to monitor cell size during growth. We also discuss a potential role for sizers in bacterial size control.

Whi7 is an unstable cell-cycle repressor of the Start transcriptional program

Start is the main decision point in eukaryotic cell cycle in which cells commit to a new round of cell division. It involves the irreversible activation of a transcriptional program by G1 CDK-cyclin complexes through the inactivation of Start transcriptional repressors, Whi5 in yeast or Rb in mammals. Here we provide novel keys of how Whi7, a protein related at sequence level to Whi5, represses Start. Whi7 is an unstable protein, degraded by the SCF^Grr1 ubiquitin-ligase, whose stability is cell cycle regulated by CDK1 phosphorylation. Importantly, Whi7 associates to G1/S gene promoters in late G1 acting as a repressor of SBF-dependent transcription. Our results demonstrate that Whi7 is a genuine paralog of Whi5. In fact, both proteins collaborate in Start repression bringing to light that yeast cells, as occurs in mammalian cells, rely on the combined action of multiple transcriptional repressors to block Start transition.

The commitment of cells to a new cycle of division involves inactivation of the Start transcriptional repressor Whi5. Here the authors show that the sequence related protein Whi7 associates to G1/S gene promoters in late G1 and collaborates with Whi5 in Start repression.

A simple molecular mechanism explains multiple patterns of cell-size regulation

Increasingly accurate and massive data have recently shed light on the fundamental question of how cells maintain a stable size trajectory as they progress through the cell cycle. Microbes seem to use strategies ranging from a pure sizer, where the end of a given phase is triggered when the cell reaches a critical size, to pure adder, where the cell adds a constant size during a phase. Yet the biological origins of the observed spectrum of behavior remain elusive. We analyze a molecular size-control mechanism, based on experimental data from the yeast S. cerevisiae, that gives rise to behaviors smoothly interpolating between adder and sizer. The size-control is obtained from the accumulation of an activator protein that titrates an inhibitor protein. Strikingly, the size-control is composed of two different regimes: for small initial cell size, the size-control is a sizer, whereas for larger initial cell size, it is an imperfect adder, in agreement with recent experiments. Our model thus indicates that the adder and critical size behaviors may just be different dynamical regimes of a single simple biophysical mechanism.

Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models

The eukaryotic cell cycle is robustly designed, with interacting molecules organized within a definite topology that ensures temporal precision of its phase transitions. Its underlying dynamics are regulated by molecular switches, for which remarkable insights have been provided by genetic and molecular biology efforts. In a number of cases, this information has been made predictive, through computational models. These models have allowed for the identification of novel molecular mechanisms, later validated experimentally. Logical modeling represents one of the youngest approaches to address cell cycle regulation. We summarize the advances that this type of modeling has achieved to reproduce and predict cell cycle dynamics. Furthermore, we present the challenge that this type of modeling is now ready to tackle: its integration with intracellular networks, and its formalisms, to understand crosstalks underlying systems level properties, ultimate aim of multi-scale models. Specifically, we discuss and illustrate how such an integration may be realized, by integrating a minimal logical model of the cell cycle with a metabolic network.