Cell cycle control by a minimal Cdk network

The bistable mitotic switch in fission yeast

In favorable conditions, eukaryotic cells proceed irreversibly through the cell division cycle (G1-S-G2-M) in order to produce two daughter cells with the same number and identity of chromosomes of their progenitor. The integrity of this process is maintained by "checkpoints" that hold a cell at particular transition points of the cycle until all requisite events are completed. The crucial functions of these checkpoints seem to depend on irreversible bistability of the underlying checkpoint control systems. Bistability of cell cycle transitions has been confirmed experimentally in frog egg extracts, budding yeast cells and mammalian cells. For fission yeast cells, a recent paper by Patterson et al. (2021) provides experimental evidence for an abrupt transition from G2 phase into mitosis, and we show that these data are consistent with a stochastic model of a bistable switch governing the G2/M checkpoint. Interestingly, our model suggests that their experimental data could also be explained by a reversible/sigmoidal switch, and stochastic simulations confirm this supposition. We propose a simple modification of their experimental protocol that could provide convincing evidence for (or against) bistability of the G2/M transition in fission yeast.

R-loop and diseases: the cell cycle matters

The cell cycle is a crucial biological process that is involved in cell growth, development, and reproduction. It can be divided into G1, S, G2, and M phases, and each period is closely regulated to ensure the production of two similar daughter cells with the same genetic material. However, many obstacles influence the cell cycle, including the R-loop that is formed throughout this process. R-loop is a triple-stranded structure, composed of an RNA: DNA hybrid and a single DNA strand, which is ubiquitous in organisms from bacteria to mammals. The existence of the R-loop has important significance for the regulation of various physiological processes. However, aberrant accumulation of R-loop due to its limited resolving ability will be detrimental for cells. For example, DNA damage and genomic instability, caused by the R-loop, can activate checkpoints in the cell cycle, which in turn induce cell cycle arrest and cell death. At present, a growing number of factors have been proven to prevent or eliminate the accumulation of R-loop thereby avoiding DNA damage and mutations. Therefore, we need to gain detailed insight into the R-loop resolution factors at different stages of the cell cycle. In this review, we review the current knowledge of factors that play a role in resolving the R-loop at different stages of the cell cycle, as well as how mutations of these factors lead to the onset and progression of diseases.

Live-cell imaging defines a threshold in CDK activity at the G2/M transition

Cyclin-dependent kinase (CDK) determines the temporal ordering of the cell cycle phases. However, despite significant progress in studying regulators of CDK and phosphorylation patterns of CDK substrates at the population level, it remains elusive how CDK regulators coordinately affect CDK activity at the single-cell level and how CDK controls the temporal order of cell cycle events. Here, we elucidate the dynamics of CDK activity in fission yeast and mammalian cells by developing a CDK activity biosensor, Eevee-spCDK. We find that although CDK activity does not necessarily correlate with cyclin levels, it converges to the same level around mitotic onset in several mutant backgrounds, including pom1Δ cells and wee1 or cdc25 overexpressing cells. These data provide direct evidence that cells enter the M phase when CDK activity reaches a high threshold, consistent with the quantitative model of cell cycle progression in fission yeast.

Artificial Modulation and Rewiring of Cell Cycle Progression Using Synthetic Circuits in Fission Yeast

Cell cycle control is a central aspect of the biology of proliferating eukaryotic cells. However, progression through the cell cycle relies on a highly complex network, making it difficult to unravel the core design principles underlying the mechanisms that sustain cell proliferation and the ways in which they interact with other cellular pathways. In this context, the use of a synthetic approach to simplify the cell cycle network in unicellular genetic models such as fission yeast has opened the door to studying the biology of proliferating cells from unique perspectives. Here, we provide a series of methods based on a minimal cell cycle module in the fission yeast Schizosaccharomyces pombe that allows for an unprecedented artificial control of cell cycle events, enabling the rewiring and remodeling of cell cycle progression.

Quercetin attenuates angiotensin II-induced proliferation of vascular smooth muscle cells and p53 pathway activation in vitro and in vivo

Quercetin is an essential flavonoid mostly found in herbal plants, fruits, and vegetables, which exhibits anti-hypertension properties. However, its pharmacological impact on angiotensin II (Ang II) induced the increase of blood pressure along with in-depth mechanism needs further exploration. The present study pointed out the anti-hypertensive role of quercetin and its comprehensive fundamental mechanisms. Our data showed that quercetin treatment substantially reduced the increase in blood pressure, pulse wave velocity, and aortic thickness of abdominal aorta in Ang II-infused C57BL/6 mice. RNA sequencing revealed that quercetin treatment reversed 464 differentially expressed transcripts in the abdominal aorta of Ang II-infused mice. Moreover, overlapping KEGG-enriched signaling pathways identified multiple common pathways between the comparison of Ang II versus control and Ang II + quercetin versus Ang II. Likewise, these pathways included cell cycle as well as p53 pathways. Transcriptome was further validated by immunohistochemistry, indicating that quercetin treatment significantly decreased the Ang II-induced expression of proliferating cell nuclear antigen (PCNA), cyclin-dependent kinase-4 (CDK4), and cyclin D1, while increased protein expression of p53, and p21 in abdominal aortic tissues of mice. In vitro, quercetin treatment meaningfully decreased the cell viability, arrested cell cycle at G0/G1 phase, and up-regulated the p53 and p21 proteins expression, as well as down-regulated the protein expression of cell cycle-related markers, for example, CDK4, cyclin D1 in Ang II stimulated vascular smooth muscle cells (VSMCs). This study addresses pharmacologic and mechanistic perspectives of quercetin against Ang-II-induced vascular injury and the increase of blood pressure.

Time-keeping and decision-making in the cell cycle

Cell growth, DNA replication, mitosis and division are the fundamental processes by which life is passed on from one generation of eukaryotic cells to the next. The eukaryotic cell cycle is intrinsically a periodic process but not so much a ‘clock’ as a ‘copy machine’, making new daughter cells as warranted. Cells growing under ideal conditions divide with clock-like regularity; however, if they are challenged with DNA-damaging agents or mitotic spindle disrupters, they will not progress to the next stage of the cycle until the damage is repaired. These ‘decisions’ (to exit and re-enter the cell cycle) are essential to maintain the integrity of the genome from generation to generation. A crucial challenge for molecular cell biologists in the 1990s was to unravel the genetic and biochemical mechanisms of cell cycle control in eukaryotes. Central to this effort were biochemical studies of the clock-like regulation of ‘mitosis promoting factor’ during synchronous mitotic cycles of fertilized frog eggs and genetic studies of the switch-like regulation of ‘cyclin-dependent kinases' in yeast cells. In this review, we uncover some secrets of cell cycle regulation by mathematical modelling of increasingly more complex molecular regulatory networks of cell cycle ‘clocks’ and ‘switches’.

Cyclin/Forkhead-mediated coordination of cyclin waves: an autonomous oscillator rationalizing the quantitative model of Cdk control for budding yeast

Networks of interacting molecules organize topology, amount, and timing of biological functions. Systems biology concepts required to pin down 'network motifs' or 'design principles' for time-dependent processes have been developed for the cell division cycle, through integration of predictive computer modeling with quantitative experimentation. A dynamic coordination of sequential waves of cyclin-dependent kinases (cyclin/Cdk) with the transcription factors network offers insights to investigate how incompatible processes are kept separate in time during the eukaryotic cell cycle. Here this coordination is discussed for the Forkhead transcription factors in light of missing gaps in the current knowledge of cell cycle control in budding yeast. An emergent design principle is proposed where cyclin waves are synchronized by a cyclin/Cdk-mediated feed-forward regulation through the Forkhead as a transcriptional timer. This design is rationalized by the bidirectional interaction between mitotic cyclins and the Forkhead transcriptional timer, resulting in an autonomous oscillator that may be instrumental for a well-timed progression throughout the cell cycle. The regulation centered around the cyclin/Cdk-Forkhead axis can be pivotal to timely coordinate cell cycle dynamics, thereby to actuate the quantitative model of Cdk control.

The fission yeast S-phase cyclin Cig2 can drive mitosis

Commitment to mitosis is regulated by cyclin-dependent kinase (CDK) activity. In the fission yeast Schizosaccharomyces pombe, the major B-type cyclin, Cdc13, is necessary and sufficient to drive mitotic entry. Furthermore, Cdc13 is also sufficient to drive S phase, demonstrating that a single cyclin can regulate alternating rounds of replication and mitosis, and providing the foundation of the quantitative model of CDK function. It has been assumed that Cig2, a B-type cyclin expressed only during S phase and incapable of driving mitosis in wild-type cells, was specialized for S-phase regulation. Here, we show that Cig2 is capable of driving mitosis. Cig2/CDK activity drives mitotic catastrophe-lethal mitosis in inviably small cells-in cells that lack CDK inhibition by tyrosine-phosphorylation. Moreover, Cig2/CDK can drive mitosis in the absence of Cdc13/CDK activity and constitutive expression of Cig2 can rescue loss of Cdc13 activity. These results demonstrate that in fission yeast, not only can the presumptive M-phase cyclin drive S phase, but the presumptive S-phase cyclin can drive M phase, further supporting the quantitative model of CDK function. Furthermore, these results provide an explanation, previously proposed on the basis of computational analyses, for the surprising observation that cells expressing a single-chain Cdc13-Cdc2 CDK do not require Y15 phosphorylation for viability. Their viability is due to the fact that in such cells, which lack Cig2/CDK complexes, Cdc13/CDK activity is unable to drive mitotic catastrophe.

WIPI1 promotes osteosarcoma cell proliferation by inhibiting CDKN1A

Detection of TCGA data revealed that WIPI1 is highly expressed in osteosarcoma cells. So we explore the mechanisms of WIPI1 affecting the proliferation of osteosarcoma cells through Affymetrix microarray analysis. Functional analysis of differentially expressed genes shows that the classical signaling pathways affecting tumor formation and development have changed significantly. By fitting analysis, it is speculated that the WIPI1 may function in the direction of osteosarcoma by regulating the expression of multiple cell cycle-related genes such as CDKN1A, CDK4 and CCND1. Therefore, the key genes are selected for RT-PCR and Western-blot verification. Combined with flow and other means, WIPI1 may affect the cell cycle and the osteosarcoma by regulating the expression of CDKN1A, CDK4 and CCND1. To verify the results, the effect of WIPI1 on cell proliferation was quantified by MTT, cell counts and nude mouse tumorigenicity assay. The results showed that WIPI1 promotes osteosarcoma cell proliferation.

Adaptive behaviour and learning in slime moulds: the role of oscillations

The slime mould Physarum polycephalum, an aneural organism, uses information from previous experiences to adjust its behaviour, but the mechanisms by which this is accomplished remain unknown. This article examines the possible role of oscillations in learning and memory in slime moulds. Slime moulds share surprising similarities with the network of synaptic connections in animal brains. First, their topology derives from a network of interconnected, vein-like tubes in which signalling molecules are transported. Second, network motility, which generates slime mould behaviour, is driven by distinct oscillations that organize into spatio-temporal wave patterns. Likewise, neural activity in the brain is organized in a variety of oscillations characterized by different frequencies. Interestingly, the oscillating networks of slime moulds are not precursors of nervous systems but, rather, an alternative architecture. Here, we argue that comparable information-processing operations can be realized on different architectures sharing similar oscillatory properties. After describing learning abilities and oscillatory activities of P. polycephalum, we explore the relation between network oscillations and learning, and evaluate the organism's global architecture with respect to information-processing potential. We hypothesize that, as in the brain, modulation of spontaneous oscillations may sustain learning in slime mould. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.

Computational modeling of chromosome re-replication in mutant strains of fission yeast

Typically cells replicate their genome only once per division cycle, but under some circumstances, both natural and unnatural, cells synthesize an overabundance of DNA, either in a disorganized manner (“overreplication”) or by a systematic doubling of chromosome number (“endoreplication”). These variations on the theme of DNA replication and division have been studied in strains of fission yeast, Schizosaccharomyces pombe, carrying mutations that interfere with the function of mitotic cyclin-dependent kinase (Cdk1:Cdc13) without impeding the roles of DNA-replication loading factor (Cdc18) and S-phase cyclin-dependent kinase (Cdk1:Cig2). Some of these mutations support endoreplication, and some overreplication. In this paper, we propose a dynamical model of the interactions among the proteins governing DNA replication and cell division in fission yeast. By computational simulations of the mathematical model, we account for the observed phenotypes of these re-replicating mutants, and by theoretical analysis of the dynamical system, we provide insight into the molecular distinctions between overreplicating and endoreplicating cells. In the case of induced overproduction of regulatory proteins, our model predicts that cells first switch from normal mitotic cell cycles to growth-controlled endoreplication, and ultimately to disorganized overreplication, parallel to the slow increase of protein to very high levels.

Anti-tumor Drug Targets Analysis: Current Insight and Future Prospect

The incidence and mortality of malignant tumors are on the rise, which has become the second leading cause of death in the world. At present, anti-tumor drugs are one of the most common methods for treating cancer. In recent years, with the in-depth study of tumor biology and related disciplines, it has been gradually discovered that the essence of cell carcinogenesis is the infinite proliferation of cells caused by the disorder of cell signal transduction pathways, followed by a major shift in the concept of anti-tumor drugs research and development. The focus of research and development is shifting from traditional cytotoxic drugs to a new generation of anti-tumor drugs targeted at abnormal signaling system targets in tumor cells. In this review, we summarize the targets of anti-tumor drugs and analyse the molecular mechanisms of their effects, which lay a foundation for subsequent treatment, research and development.

Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology

Computer-aided design (CAD) for synthetic biology promises to accelerate the rational and robust engineering of biological systems. It requires both detailed and quantitative mathematical and experimental models of the processes to (re)design biology, and software and tools for genetic engineering and DNA assembly. Ultimately, the increased precision in the design phase will have a dramatic impact on the production of designer cells and organisms with bespoke functions and increased modularity. CAD strategies require quantitative models of cells that can capture multiscale processes and link genotypes to phenotypes. Here, we present a perspective on how whole-cell, multiscale models could transform design-build-test-learn cycles in synthetic biology. We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems. We also discuss several challenges for the realization of our vision. The possibility to describe and build whole-cells in silico offers an opportunity to develop increasingly automatized, precise and accessible CAD tools and strategies.

Clb3-centered regulations are recurrent across distinct parameter regions in minimal autonomous cell cycle oscillator designs

Some biological networks exhibit oscillations in their components to convert stimuli to time-dependent responses. The eukaryotic cell cycle is such a case, being governed by waves of cyclin-dependent kinase (cyclin/Cdk) activities that rise and fall with specific timing and guarantee its timely occurrence. Disruption of cyclin/Cdk oscillations could result in dysfunction through reduced cell division. Therefore, it is of interest to capture properties of network designs that exhibit robust oscillations. Here we show that a minimal yeast cell cycle network is able to oscillate autonomously, and that cyclin/Cdk-mediated positive feedback loops (PFLs) and Clb3-centered regulations sustain cyclin/Cdk oscillations, in known and hypothetical network designs. We propose that Clb3-mediated coordination of cyclin/Cdk waves reconciles checkpoint and oscillatory cell cycle models. Considering the evolutionary conservation of the cyclin/Cdk network across eukaryotes, we hypothesize that functional ("healthy") phenotypes require the capacity to oscillate autonomously whereas dysfunctional (potentially "diseased") phenotypes may lack this capacity.

Network mechanisms and dysfunction within an integrated computational model of progression through mitosis in the human cell cycle

The cellular protein-protein interaction network that governs cellular proliferation (cell cycle) is highly complex. Here, we have developed a novel computational model of human mitotic cell cycle, integrating diverse cellular mechanisms, for the purpose of generating new hypotheses and predicting new experiments designed to help understand complex diseases. The pathogenic state investigated is infection by a human herpesvirus. The model starts at mitotic entry initiated by the activities of Cyclin-dependent kinase 1 (CDK1) and Polo-like kinase 1 (PLK1), transitions through Anaphase-promoting complex (APC/C) bound to Cell division cycle protein 20 (CDC20), and ends upon mitotic exit mediated by APC/C bound to CDC20 homolog 1 (CDH1). It includes syntheses and multiple mechanisms of degradations of the mitotic proteins. Prior to this work, no such comprehensive model of the human mitotic cell cycle existed. The new model is based on a hybrid framework combining Michaelis-Menten and mass action kinetics for the mitotic interacting reactions. It simulates temporal changes in 12 different mitotic proteins and associated protein complexes in multiple states using 15 interacting reactions and 26 ordinary differential equations. We have defined model parameter values using both quantitative and qualitative data and using parameter values from relevant published models, and we have tested the model to reproduce the cardinal features of human mitosis determined experimentally by numerous laboratories. Like cancer, viruses create dysfunction to support infection. By simulating infection of the human herpesvirus, cytomegalovirus, we hypothesize that virus-mediated disruption of APC/C is necessary to establish a unique mitotic collapse with sustained CDK1 activity, consistent with known mechanisms of virus egress. With the rapid discovery of cellular protein-protein interaction networks and regulatory mechanisms, we anticipate that this model will be highly valuable in helping us to understand the network dynamics and identify potential points of therapeutic interventions.

Double or Nothing? Cell Division and Cell Size Control

Size is a fundamental property that must be tightly regulated to ensure that cells and tissues function efficiently. Dynamic size control allows unicellular organisms to adapt to environmental changes, but cell size is also integral to multicellular development, affecting tissue size and structure. Despite clear evidence for homeostatic cell size maintenance, we are only now beginning to understand cell size regulation in the actively dividing meristematic tissues of higher plants. We discuss here how coupled advances in live cell imaging and modelling are uncovering dynamic mechanisms for size control mediated at the cellular level. We argue that integrated models of cell growth and division will be necessary to predict cell size and fully understand multicellular growth and development.

A Mathematical Model for the Effect of Low-Dose Radiation on the G2/M Transition

We develop a mathematical model to study the immediate effect of low-dose radiation on the G2 checkpoint and the G2/M transition of the cell cycle via a radiation pathway (the ATM-Chk2 pathway) of an individual mammalian cell. The model consists of a system of nonlinear differential equations describing the dynamics of a network of regulatory proteins that play key roles in the G2/M transition, cell cycle oscillations, and the radiation pathway. We simulate the application of a single pulse of low-dose radiation at different intensities ([Formula: see text] 0-0.4 Gy) and times during the latter part of the G2-phase. We use bifurcation analysis to characterize the effect of radiation on the G2/M transition via the ATM-Chk2 pathway. We show that radiation between 0.1 and 0.3 Gy can delay the G2/M transition, and radiation higher than 0.3 Gy can fully activate the G2 checkpoint. Also, our results show that radiation can be low enough to neither delay the G2/M transition nor activate the G2 checkpoint ([Formula: see text] 0.1 Gy). Our model supports the idea that the cell response to radiation during G2-phase explains hyper-radiosensitivity and increased radioresistance (HRS/IRR) observed at low dose.

Noisy Cell-Size-Correlated Expression of Cyclin B Drives Probabilistic Cell-Size Homeostasis in Fission Yeast

How cells correct deviations from a mean cell size at mitosis remains uncertain. Classical cell-size homeostasis models are the sizer, timer, and adder [1]. Sizers postulate that cells divide at some threshold size; timers, that cells grow for a set time; and adders, that cells add a constant volume before division. Here, we show that a size-based probabilistic model of cell-size control at the G2/M transition (P(Div)) can generate realistic cell-size homeostasis in silico. In fission yeast cells, Cyclin B^Cdc13 scales with size, and we propose that this increases the likelihood of mitotic entry, while molecular noise in its expression adds a probabilistic component to the model. Varying Cdc13 expression levels exogenously using a newly developed tetracycline inducible promoter shows that both the level and variability of its expression influence cell size at division. Our results demonstrate that as cells grow larger, their probability of dividing increases, and this is sufficient to generate cell-size homeostasis. Size-correlated Cdc13 expression forms part of the molecular circuitry of this system.

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A size-correlated division probability can generate cell-size homeostasis

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Cyclin B concentration scales noisily with size in fission yeast

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Cells with stochastically suprathreshold cyclin B are the ones that divide

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A new tetracycline inducible promoter with linear dose response is developed

A checkpoint-oriented cell cycle simulation model

Modeling and in silico simulations are of major conceptual and applicative interest in studying the cell cycle and proliferation in eukaryotic cells. In this paper, we present a cell cycle checkpoint-oriented simulator that uses agent-based simulation modeling to reproduce the dynamics of a cancer cell population in exponential growth. Our in silico simulations were successfully validated by experimental in vitro supporting data obtained with HCT116 colon cancer cells. We demonstrated that this model can simulate cell confluence and the associated elongation of the G1 phase. Using nocodazole to synchronize cancer cells at mitosis, we confirmed the model predictivity and provided evidence of an additional and unexpected effect of nocodazole on the overall cell cycle progression. We anticipate that this cell cycle simulator will be a potential source of new insights and research perspectives.

Adding phosphorylation events to the core oscillator driving the cell cycle of fission yeast

Much is known about the regulatory elements controlling the cell cycle in fission yeast (Schizosaccharomyces pombe). This regulation is mainly done by the (cyclin-dependent kinase/cyclin) complex (Cdc2/Cdc13) that activates specific target genes and proteins via phosphorylation events during the cell cycle in a time-dependent manner. However, more work is still needed to complement the existing gaps in the current fission yeast gene regulatory network to be able to overcome abnormalities in its growth, repair and development, i.e. explain many phenomena including mitotic catastrophe. In this work we complement the previously presented core oscillator of the cell cycle of fission yeast by selected phosphorylation events and study their effects on the temporal evolution of the core oscillator based Boolean network. Thereby, we attempt to establish a regulatory link between the autonomous cell cycle oscillator and the remainder of the cell. We suggest the unclear yet regulatory effect of phosphorylation on the added components, and discuss many unreported points regarding the temporal evolution of the cell cycle and its components. To better visualize the results regardless of the programming background we developed an Android application that can be used to run the core and extended model of the fission yeast cell cycle step by step.

Revisiting a skeleton model for the mammalian cell cycle: From bistability to Cdk oscillations and cellular heterogeneity

A network of cyclin-dependent kinases (Cdks) regulated by multiple negative and positive feedback loops controls progression in the mammalian cell cycle. We previously proposed a detailed computational model for this network, which consists of four coupled Cdk modules. Both this detailed model and a reduced, skeleton version show that the Cdk network is capable of temporal self-organization in the form of sustained Cdk oscillations, which correspond to the orderly progression along the different cell cycle phases G1, S (DNA replication), G2 and M (mitosis). We use the skeleton model to revisit the role of positive feedback (PF) loops on the dynamics of the mammalian cell cycle by showing that the multiplicity of PF loops extends the range of bistability in the isolated Cdk modules controlling the G1/S and G2/M transitions. Resorting to stochastic simulations we show that, through their effect on the range of bistability, multiple PF loops enhance the robustness of Cdk oscillations with respect to molecular noise. The model predicts that a rise in the total level of Cdk1 also enlarges the domain of bistability in the isolated Cdk modules as well as the range of oscillations in the full Cdk network. Surprisingly, stochastic simulations indicate that Cdk1 overexpression reduces the robustness of Cdk oscillations towards molecular noise; this result is due to the increased distance between the two branches of the bistable switch at higher levels of Cdk1. At intermediate levels of growth factor stochastic simulations show that cells may randomly switch between cell cycle arrest and cell proliferation, as a consequence of fluctuations. In the presence of Cdk1 overexpression, these transitions occur even at low levels of growth factor. Extending stochastic simulations from single cells to cell populations suggests that stochastic switches between cell cycle arrest and proliferation may provide a source of heterogeneity in a cell population, as observed in cancer cells characterized by Cdk1 overexpression.

Degradation of cyclin B is critical for nuclear division in Trypanosoma brucei

Kinetoplastids have a nucleus that contains the nuclear genome and a kinetoplast that contains the mitochondrial genome. These single-copy organelles must be duplicated and segregated faithfully to daughter cells at each cell division. In Trypanosoma brucei, although duplication of both organelles starts around the same time, segregation of the kinetoplast precedes that of the nucleus. Cytokinesis subsequently takes place so that daughter cells inherit a single copy of each organelle. Very little is known about the molecular mechanism that governs the timing of these events. Furthermore, it is thought that T. brucei lacks a spindle checkpoint that delays the onset of nuclear division in response to spindle defects. Here we show that a mitotic cyclin CYC6 has a dynamic localization pattern during the cell cycle, including kinetochore localization. Using CYC6 as a molecular cell cycle marker, we confirmed that T. brucei cannot delay the onset of anaphase in response to a bipolar spindle assembly defect. Interestingly, expression of a stabilized form of CYC6 caused the nucleus to arrest in a metaphase-like state without preventing cytokinesis. We propose that trypanosomes have an ability to regulate the timing of nuclear division by modulating the CYC6 protein level, without a spindle checkpoint.

Cyclin Y Modulates the Proliferation, Invasion, and Metastasis of Hepatocellular Carcinoma Cells

Background

Cyclin Y (CCNY) is a member of the cyclin family of proteins that regulate the cell cycle. The aims of this study were to compare the expression of CCNY in normal liver and human hepatocellular carcinoma (HCC), in normal and HCC cell lines, and in mouse HCC tumor xenografts.

Material/Methods

Tumor tissues from 55 patients diagnosed with HCC were studied for CCNY expression. Human HCC cell lines, SK-Hep1, HepG2, HEP3B, HuH7 and L02 were studied using the MTT cell proliferation assay, cell apoptosis, transwell and wound healing assays. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot were used to measure CCNY expression. Indirect immunofluorescence was used to assess cell apoptosis. In vivo xenograft mouse model was constructed and examined histologically.

Results

Expression of CCNY in human HCC tumor tissues was significantly increased when compared with adjacent normal liver (all P<0.05). HCC cells grown in vitro showed significantly increased expression of CCNY, cell proliferation, and migration, and a reduced rate of apoptosis, compared with cells with CCNY knockdown (siRNA) (all P<0.05). In the xenograft mouse model, tumor volume and weight in the CCNY overexpression group were significantly increased, compared with CCNY knockdown (siRNA) group (all P<0.05).

Conclusions

In tissue samples of human HCC, and human HCC cell lines, increased expression of CCNY was significantly associated with cell proliferation and migration. Further studies are recommended to evaluate the role of CCNY as a potential diagnostic biomarker or target for treatment in human HCC.

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

Clinical role and biological function of CDK5 in hepatocellular carcinoma: A study based on immunohistochemistry, RNA-seq and in vitro investigation

To investigate the clinical role and biological function of cyclin-dependent kinase 5 (CDK5) in hepatocellular carcinoma (HCC), 412 surgically resected tissue samples (HCC, n=171; non-HCC=241) were obtained and analyzed with immunohistochemistry. The diagnostic and prognostic values of CDK5 expression levels in HCC were clarified. Moreover, RNA-seq data or microarray datasets from The Cancer Genome Atlas (TCGA) (HCC, n=374; normal, n=50) or other public databases (HCC, n=1864; non-tumor=1995) regarding CDK5 in HCC were extracted and examined. Several bioinformatic methods were performed to identify CDK5-regulated pathways. In vitro experiments were adopted to measure proliferation and apoptosis in HCC cells after CDK5 mRNA was inhibited in the HCC cell lines HepG2 and HepB3. Based on immunohistochemistry, CDK5 expression levels were notably increased in HCC tissues (n=171) compared with normal (n=33, P<0.001), cirrhosis (n=37, P<0.001), and adjacent non-cancerous liver (n=171, P<0.001) tissues. The up-regulation of CDK5 was associated with higher differentiation (P<0.001), metastasis (P<0.001), advanced clinical TNM stages (P<0.001), portal vein tumor embolus (P=0.003) and vascular invasion (P=0.004). Additionally, TCGA data analysis also revealed significantly increased CDK5 expression in HCC compared with non-cancerous hepatic tissues (P<0.001). The pooled standard mean deviation (SMD) based on 36 included datasets (HCC, n=2238; non-cancerous, n=2045) indicated that CDK5 was up-regulated in HCC (SMD=1.23, 95% CI: 1.00-1.45, P<0.001). The area under the curve (AUC) of the summary receiver operating characteristic (SROC) curve was 0.88. Furthermore, CDK5 knock-down inhibited proliferation and promoted apoptosis. In conclusion, CDK5 plays an essential role in the initiation and progression of HCC, most likely via accelerating proliferation and suppressing apoptosis in HCC cells by regulating the cell cycle and DNA replication pathways.

Cell-size dependent progression of the cell cycle creates homeostasis and flexibility of plant cell size

Mean cell size at division is generally constant for specific conditions and cell types, but the mechanisms coupling cell growth and cell cycle control with cell size regulation are poorly understood in intact tissues. Here we show that the continuously dividing fields of cells within the shoot apical meristem of Arabidopsis show dynamic regulation of mean cell size dependent on developmental stage, genotype and environmental signals. We show cell size at division and cell cycle length is effectively predicted using a two-stage cell cycle model linking cell growth and two sequential cyclin dependent kinase (CDK) activities, and experimental results concur in showing that progression through both G1/S and G2/M is size dependent. This work shows that cell-autonomous co-ordination of cell growth and cell division previously observed in unicellular organisms also exists in intact plant tissues, and that cell size may be an emergent rather than directly determined property of cells.

A Clb/Cdk1-mediated regulation of Fkh2 synchronizes CLB expression in the budding yeast cell cycle

Precise timing of cell division is achieved by coupling waves of cyclin-dependent kinase (Cdk) activity with a transcriptional oscillator throughout cell cycle progression. Although details of transcription of cyclin genes are known, it is unclear which is the transcriptional cascade that modulates their expression in a timely fashion. Here, we demonstrate that a Clb/Cdk1-mediated regulation of the Fkh2 transcription factor synchronizes the temporal mitotic CLB expression in budding yeast. A simplified kinetic model of the cyclin/Cdk network predicts a linear cascade where a Clb/Cdk1-mediated regulation of an activator molecule drives CLB3 and CLB2 expression. Experimental validation highlights Fkh2 as modulator of CLB3 transcript levels, besides its role in regulating CLB2 expression. A Boolean model based on the minimal number of interactions needed to capture the information flow of the Clb/Cdk1 network supports the role of an activator molecule in the sequential activation, and oscillatory behavior, of mitotic Clb cyclins. This work illustrates how transcription and phosphorylation networks can be coupled by a Clb/Cdk1-mediated regulation that synchronizes them.

A dynamic coupling of cyclin-dependent kinase with transcription factors in yeast offers insights into the timely cell cycle progression. An international team lead by Matteo Barberis from University of Amsterdam in The Netherlands studied the molecular mechanisms responsible for the coordination of DNA replication with cell division. The researchers have demonstrated how the sequential order of waves of mitotic cyclins activating cyclin-dependent kinase, or Cdk, is achieved by synchronizing Cdk with transcriptional activities. They have generated a mathematical model that predicts a cyclin/Cdk-mediated regulation of an activator molecule to stimulate mitotic cyclin expression. This prediction was successfully validated experimentally, identifying Forkhead transcription factors, or Fkh, as pivotal molecules. Cyclin waves are temporally synchronized by Fkh, and a mitotic Clb/Cdk1-mediated regulation of Fkh modulates cyclin expression. The findings reveal a novel principle of design, with kinase and transcription activities interlocked to guarantee a timely cell cycle.

To senesce or not to senesce: how primary human fibroblasts decide their cell fate after DNA damage

Excessive DNA damage can induce an irreversible cell cycle arrest, called senescence, which is generally perceived as an important tumour-suppressor mechanism. However, it is unclear how cells decide whether to senesce or not after DNA damage. By combining experimental data with a parameterized mathematical model we elucidate this cell fate decision at the G1-S transition. Our model provides a quantitative and conceptually new understanding of how human fibroblasts decide whether DNA damage is beyond repair and senesce. Model and data imply that the G1-S transition is regulated by a bistable hysteresis switch with respect to Cdk2 activity, which in turn is controlled by the Cdk2/p21 ratio rather than cyclin abundance. We experimentally confirm the resulting predictions that to induce senescence i) in healthy cells both high initial and elevated background DNA damage are necessary and sufficient, and ii) in already damaged cells much lower additional DNA damage is sufficient. Our study provides a mechanistic explanation of a) how noise in protein abundances allows cells to overcome the G1-S arrest even with substantial DNA damage, potentially leading to neoplasia, and b) how accumulating DNA damage with age increasingly sensitizes cells for senescence.

Seed maturation: Simplification of control networks in plants

Networks controlling developmental or metabolic processes in plants are often complex as a consequence of the duplication and specialisation of the regulatory genes as well as the numerous levels of transcriptional and post-transcriptional controls added during evolution. Networks serve to accommodate multicellular complexity and increase robustness to environmental changes. Mathematical simplification by regrouping genes or pathways in a limited number of hubs has facilitated the construction of models for complex traits. In a complementary approach, a biological simplification can be achieved by using genetic modification to understand the core and singular ancestral function of the network, which is likely to be more prevalent within the plant kingdom rather than specific to a species. With this viewpoint, we review examples of simplification successfully undertaken in yeast and other organisms. A strategy of progressive complementation of single, double and triple mutants of seed maturation confirmed the fundamental role of the AFL sub-family of B3 transcription factors as master regulators of seed maturation, illustrating that biological simplification of complex networks could be more widely applied in plants. Defining minimal control networks will facilitate evolutionary comparisons of regulatory processes and the identification of an essential gene set for synthetic biology.

Stochastic multi-scale models of competition within heterogeneous cellular populations: Simulation methods and mean-field analysis

We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated proliferation rate. Our formulation is based on an age-dependent stochastic process. Cells within the population are characterised by their age (i.e. time elapsed since they were born). The age-dependent (oxygen-regulated) birth rate is given by a stochastic model of oxygen-dependent cell cycle progression. Once the birth rate is determined, we formulate an age-dependent birth-and-death process, which dictates the time evolution of the cell population. The population is under a feedback loop which controls its steady state size (carrying capacity): cells consume oxygen which in turn fuels cell proliferation. We show that our stochastic model of cell cycle progression allows for heterogeneity within the cell population induced by stochastic effects. Such heterogeneous behaviour is reflected in variations in the proliferation rate. Within this set-up, we have established three main results. First, we have shown that the age to the G1/S transition, which essentially determines the birth rate, exhibits a remarkably simple scaling behaviour. Besides the fact that this simple behaviour emerges from a rather complex model, this allows for a huge simplification of our numerical methodology. A further result is the observation that heterogeneous populations undergo an internal process of quasi-neutral competition. Finally, we investigated the effects of cell-cycle-phase dependent therapies (such as radiation therapy) on heterogeneous populations. In particular, we have studied the case in which the population contains a quiescent sub-population. Our mean-field analysis and numerical simulations confirm that, if the survival fraction of the therapy is too high, rescue of the quiescent population occurs. This gives rise to emergence of resistance to therapy since the rescued population is less sensitive to therapy.

Maintaining Genome Stability in Defiance of Mitotic DNA Damage

The implementation of decisions affecting cell viability and proliferation is based on prompt detection of the issue to be addressed, formulation and transmission of a correct set of instructions and fidelity in the execution of orders. While the first and the last are purely mechanical processes relying on the faithful functioning of single proteins or macromolecular complexes (sensors and effectors), information is the real cue, with signal amplitude, duration, and frequency ultimately determining the type of response. The cellular response to DNA damage is no exception to the rule. In this review article we focus on DNA damage responses in G2 and Mitosis. First, we set the stage describing mitosis and the machineries in charge of assembling the apparatus responsible for chromosome alignment and segregation as well as the inputs that control its function (checkpoints). Next, we examine the type of issues that a cell approaching mitosis might face, presenting the impact of post-translational modifications (PTMs) on the correct and timely functioning of pathways correcting errors or damage before chromosome segregation. We conclude this essay with a perspective on the current status of mitotic signaling pathway inhibitors and their potential use in cancer therapy.

Insights from synthetic yeasts

Synthetic biology is one of the most exciting strategies for the investigation of living organisms and lies at the intersection of biology and engineering. Originally developed in prokaryotes, the idea of deciphering biological phenomena through building artificial genetic circuits and studying their behaviours has rapidly demonstrated its potential in a broad range of fields in the life sciences. From the assembly of synthetic genomes to the generation of novel biological functions, yeast cells have imposed themselves as the most powerful eukaryotic model for this approach. However, we are only beginning to explore the possibilities of synthetic biology, and the perspectives it offers in a genetically amenable system such as yeasts are endless. Copyright © 2016 John Wiley & Sons, Ltd.

Cdk1 activity acts as a quantitative platform for coordinating cell cycle progression with periodic transcription

Cell proliferation is regulated by cyclin-dependent kinases (Cdks) and requires the periodic expression of particular gene clusters in different cell cycle phases. However, the interplay between the networks that generate these transcriptional oscillations and the core cell cycle machinery remains largely unexplored. In this work, we use a synthetic regulable Cdk1 module to demonstrate that periodic expression is governed by quantitative changes in Cdk1 activity, with different clusters directly responding to specific activity levels. We further establish that cell cycle events neither participate in nor interfere with the Cdk1-driven transcriptional program, provided that cells are exposed to the appropriate Cdk1 activities. These findings contrast with current models that propose self-sustained and Cdk1-independent transcriptional oscillations. Our work therefore supports a model in which Cdk1 activity serves as a quantitative platform for coordinating cell cycle transitions with the expression of critical genes to bring about proper cell cycle progression.

Cell proliferation is regulated by cyclin-dependent kinases (Cdks) and relies on periodic gene cluster expression according to cell cycle phases. Here the authors use a synthetic regulatable Cdk1 module to demonstrate that periodic expression is governed by quantitative changes in Cdk1 activity.

An immunohistochemical study of cyclin-dependent kinase 5 (CDK5) expression in non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC): a possible prognostic biomarker

Background

Cyclin-dependent kinase 5 (CDK5) is an atypical CDK which plays a vital role in several cancers via regulating migration and motility of cancer cells. However, the clinicopathological impact and function of CDK5 in lung cancer remain poorly understood. The present study was aimed at exploring expression and clinicopathological significance of CDK5 in lung cancer.

Methods

There were 395 samples of lung tissue including 365 lung tumors (339 non-small cell lung cancers and 26 small cell lung cancers) and 30 samples of normal lung. CDK5 expression was detected by immunohistochemistry on lung tissue microarrays.

Results

Over expression was detected in lung cancer compared with normal lung tissues (P = 0.001). Furthermore, area under curve (AUC) of receiver operating characteristic (ROC) of CDK5 was 0.685 (95 % CI 0.564~0.751, P = 0.004). In lung cancer, we also discovered close correlations between CDK5 and pathological grading (r = 0.310, P < 0.001), TNM stage (r = 0.155, P = 0.003), and lymph node metastasis (r = 0.279, P < 0.001) by using Spearman analysis. In two subgroups of non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), the expression of CDK5 was also higher than that of normal lung tissue, respectively (P = 0.001 and P = 0.004). Moreover, in NSCLCs, Spearman analysis revealed that expression of CDK5 was correlated with TNM stages (r = 0.129, P = 0.017), lymph node metastasis (r = 0.365, P < 0.001), and pathological grading (r = 0.307, P < 0.001), respectively. The significant correlation was also found between CDK5 expression and TNM stages (r = 0.415, P = 0.049) and lymphatic metastasis (r = 0.469, P = 0.024) in SCLCs.

Conclusions

The results of this present study suggest that the CDK5 expression is associated with several clinicopathological factors linked with poorer prognosis.

Model-Based Analysis of Cell Cycle Responses to Dynamically Changing Environments

Cell cycle progression is carefully coordinated with a cell's intra- and extracellular environment. While some pathways have been identified that communicate information from the environment to the cell cycle, a systematic understanding of how this information is dynamically processed is lacking. We address this by performing dynamic sensitivity analysis of three mathematical models of the cell cycle in Saccharomyces cerevisiae. We demonstrate that these models make broadly consistent qualitative predictions about cell cycle progression under dynamically changing conditions. For example, it is shown that the models predict anticorrelated changes in cell size and cell cycle duration under different environments independently of the growth rate. This prediction is validated by comparison to available literature data. Other consistent patterns emerge, such as widespread nonmonotonic changes in cell size down generations in response to parameter changes. We extend our analysis by investigating glucose signalling to the cell cycle, showing that known regulation of Cln3 translation and Cln1,2 transcription by glucose is sufficient to explain the experimentally observed changes in cell cycle dynamics at different glucose concentrations. Together, these results provide a framework for understanding the complex responses the cell cycle is capable of producing in response to dynamic environments.

Quantitative imaging with Fucci and mathematics to uncover temporal dynamics of cell cycle progression

Cell cycle progression is strictly coordinated to ensure proper tissue growth, development, and regeneration of multicellular organisms. Spatiotemporal visualization of cell cycle phases directly helps us to obtain a deeper understanding of controlled, multicellular, cell cycle progression. The fluorescent ubiquitination-based cell cycle indicator (Fucci) system allows us to monitor, in living cells, the G1 and the S/G2/M phases of the cell cycle in red and green fluorescent colors, respectively. Since the discovery of Fucci technology, it has found numerous applications in the characterization of the timing of cell cycle phase transitions under diverse conditions and various biological processes. However, due to the complexity of cell cycle dynamics, understanding of specific patterns of cell cycle progression is still far from complete. In order to tackle this issue, quantitative approaches combined with mathematical modeling seem to be essential. Here, we review several studies that attempted to integrate Fucci technology and mathematical models to obtain quantitative information regarding cell cycle regulatory patterns. Focusing on the technological development of utilizing mathematics to retrieve meaningful information from the Fucci producing data, we discuss how the combined methods advance a quantitative understanding of cell cycle regulation.

Timing in the Testis

The testis provides not just one but several models of temporal organization. The complexity of its rhythmic function arises in part from its compartmentalization and diversity of cell types: not only does the testis produce gametes, but it also serves as the major source of circulating androgens. Within the seminiferous tubules, the germ cells divide and differentiate while in intimate contact with Sertoli cells. The tubule is highly periodic: a spermatogenic wave travels along its length to determine the timing of the commitment of spermatogonia to differentiate, the phases of meiotic division, and the rate of differentiation of the postmeiotic germ cells. Recent evidence indicates that oscillations of retinoic acid play a major role in determining periodicity of the seminiferous epithelium. In the interstitial space, Leydig cells produce the steroid hormones required both for the completion of spermatogenesis and the development and maintenance of male sexual characteristics throughout the body. This endocrine output also oscillates; although the pulse generator lies outside the gonad, the steroidogenic function of Leydig cells is tuned to a regular episodic input. While the oscillations of the intratubular and interstitial cells have multihour (ultradian) and multiday (infradian) periodicities, respectively, the functions of both compartments also display dramatic seasonal rhythms. Furthermore, circadian rhythms are evident in some of the cell types, although their amplitude and pervasiveness are not as great as in many other tissues of the same organism, and their detection may require methods that recognize the heterogeneity of the testis. This review examines the periodicity of testicular function along multiple time scales.

Dynamics of the mammalian cell cycle in physiological and pathological conditions

A network of cyclin-dependent kinases (Cdks) controls progression along the successive phases G1, S, G2, and M of the mammalian cell cycle. Deregulations in the expression of molecular components in this network often lead to abusive cell proliferation and cancer. Given the complex nature of the Cdk network, it is fruitful to resort to computational models to grasp its dynamical properties. Investigated by means of bifurcation diagrams, a detailed computational model for the Cdk network shows how the balance between quiescence and proliferation is affected by activators (oncogenes) and inhibitors (tumor suppressors) of cell cycle progression, as well as by growth factors and other external factors such as the extracellular matrix (ECM) and cell contact inhibition. Suprathreshold changes in all these factors can trigger a switch in the dynamical behavior of the network corresponding to a bifurcation between a stable steady state, associated with cell cycle arrest, and sustained oscillations of the various cyclin/Cdk complexes, corresponding to cell proliferation. The model for the Cdk network accounts for the dependence or independence of cell proliferation on serum and/or cell anchorage to the ECM. Such computational approach provides an integrated view of the control of cell proliferation in physiological or pathological conditions. Whether the balance is tilted toward cell cycle arrest or cell proliferation depends on the direction in which the threshold associated with the bifurcation is passed once the cell integrates the multiple signals, internal or external to the Cdk network, that promote or impede progression in the cell cycle.

The principles of whole-cell modeling

Whole-cell models which comprehensively predict how phenotypes emerge from genotype promise to enable rational bioengineering and precision medicine. Here, we outline the key principles of whole-cell modeling which have emerged from our work developing bacterial whole-cell models: single-cellularity; functional, genetic, molecular, and temporal completeness; biophysical realism including temporal dynamics and stochastic variation; species-specificity; and model integration and reproducibility. We also outline the whole-cell model construction process, highlighting existing resources. Numerous challenges remain to achieving fully complete models including developing new experimental tools to more completely characterize cells and developing a strong theoretical understanding of hybrid mathematics. Solving these challenges requires collaboration among computational and experimental biologists, biophysicists, biochemists, applied mathematicians, computer scientists, and software engineers.

Complex, non-monotonic dose-response curves with multiple maxima: Do we (ever) sample densely enough?

We usually expect the dose-response curves of biological responses to quantifiable stimuli to be simple, either monotonic or exhibiting a single maximum or minimum. Deviations are often viewed as experimental noise. However, detailed measurements in plant primary tissue cultures (stem pith explants of kale and tobacco) exposed to varying doses of sucrose, cytokinins (BA or kinetin) or auxins (IAA or NAA) revealed that growth and several biochemical parameters exhibit multiple reproducible, statistically significant maxima over a wide range of exogenous substance concentrations. This results in complex, non-monotonic dose-response curves, reminiscent of previous reports of analogous observations in both metazoan and plant systems responding to diverse pharmacological treatments. These findings suggest the existence of a hitherto neglected class of biological phenomena resulting in dose-response curves exhibiting periodic patterns of maxima and minima, whose causes remain so far uncharacterized, partly due to insufficient sampling frequency used in many studies.