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Review on CDC42 (cell division cycle 42 (GTP binding protein, 25kDa)), with data on DNA, on the protein encoded, and where the gene is implicated.

Review on CDC20 (cell division cycle 20 homolog (S. cerevisiae)), with data on DNA, on the protein encoded, and where the gene is implicated.

In fungi, cellular morphogenesis is driven by localized membrane expansion and cell wall deposition. Variation in the geometry of fungal cells likely arises through the precise temporal and spatial regulation of these processes. Nevertheless, these modes of regulation are not well understood in filamentous fungi. This review focuses on three key aspects of fungal cellular morphogenesis: symmetry breaking, polarity maintenance, and septum formation. The mechanisms underlying cellular morphogenesis are summarized, with an emphasis on comparison to the model yeasts. In addition, mechanisms that coordinate morphogenesis with the yeast cell division cycle are briefly outlined. It is proposed that to some extent, analogous mechanisms function during fungal development to alter cell shape and size.

Review on CDC73 (cell division cycle 73, Paf1/RNA polymerase II complex component, homolog (S. cerevisiae)), with data on DNA, on the protein encoded, and where the gene is implicated.

The Circadian Timing System (CTS) controls cellular proliferation and drug metabolism over a 24-h period through molecular clocks in each cell. These cellular clocks are coordinated by a hypothalamic pacemaker, the suprachiasmatic nuclei, which generate or control circadian physiology. The CTS down-regulates malignant growth in experimental models and in cancer patients. It also generates large and predictable 24-h changes in toxicity and efficacy of experimental and clinical anticancer treatments, which have been validated in randomized studies. Modelling of the interactions between circadian clocks, cell division cycle and pharmacology pathways reveals why the same circadian timing jointly optimizes the tolerability and efficacy of a given anticancer drug, both in experimental models and in cancer patients. Thus, an automaton model for the cell cycle shows the critical roles of variability in circadian entrainment, cell cycle length, and phase durations, which determine the success of cancer chronotherapeutics. Stochastic and deterministic models further confirm the poor therapeutic value of constant-rate infusion or wrongly-timed chronomodulated infusion. The integration of the circadian clock into the algorithms of anticancer treatments represents a critical step towards the tailoring of optimal chronotherapeutic delivery. The adjustment of mathematical models of circadian and cell cycle clocks to relevant clinical factors such as circadian biomarkers and gender constitutes an innovative and promising approach for personalized cancer medicine.

We study proliferation in tissues from the point of view of physiologically structured partial differential models, focusing on age synchronisation in the cell division cycle in cell populations and its control at phase transition checkpoints. We show how a recent fluorescence‐based technique (FUCCI) performed at the single cell level in proliferating cell populations allows identifying model parameters and how it may be applied to investigate healthy and cancer cell populations. We show how this modelling approach allows designing original optimisation methods for cancer chronotherapeutics, by controlling eigenvalues of differential operators underlying proliferation dynamics, in tumour and in healthy cell populations.

The time structure of a biological system is at least as intricate as its spatial structure. Whereas we have detailed information about the latter, our understanding of the former is still rudimentary. As techniques for monitoring intracellular processes continuously in single cells become more refined, it becomes increasingly evident that periodic behaviour abounds in all time domains. Timekeeping is essential for synchronization and coordination of intracellular processes. The presence of a temperature-compensated oscillator provides such a timer. The coupled outputs (epigenetic oscillations) of this ultradian clock constitute a special class of ultradian rhythm. These are undamped and endogenously driven by a device which shows biochemical properties characteristic of transcriptional and translational elements. Energy-yielding processes, protein turnover, motility, and the timing of the cell division cycle processes, are all controlled by the ultradian clock. Different periods 30 min-4h characterize different species.

Seventy-five 1,5,6,7-tetrahydro-pyrrolo[3,2-C]pyridinone derivatives displaying potent activities against Cdc7 kinase were selected to establish 3D-QSAR models using CoMFA and CoMSIA methods. Internal and external cross-validation techniques were investigated as well as some measures including region focusing, progressive scrambling, bootstraping and leave-group-out. The satisfactory CoMFA model predicted a q (2) value of 0.836 and an r (2) value of 0.950, indicating that electrostatic and steric properties play a significant role in potency. The best CoMSIA model, based on a combination of steric, electrostatic and H-bond acceptor effects, predicted a q (2) value of 0.636 and an r (2) value of 0.907. The models were graphically interpreted using contour plots which provided insight into the structural requirements for increasing the activity of a compound. The final 3D-QSAR results could be used for rational design of potent inhibitors against Cdc7 kinase.

Contrary to the situation in animal systems, plant shape and size are predominantly determined by developmental programs that govern the timely initiation and outgrowth of meristems. In plants, meristematic zones almost exclusively constitute the regions of dividing cells. The role of mitotic cell division in morphogenetic and developmental processes has been the subject of intense debate, but the present view seems to acknowledge the importance of proper cell division regulation for the correct elaboration and execution of developmental programs (29)

The biological problem of identifying the active genes during the cell division process is addressed. The cell division ensures the proliferation of cells, which is drastically aberrant in cancer cells. The studied genes are described by their expression profiles during the cell division cycle. Commonly, the identification process is a supervised approach based on an a priori set of reference genes, assumed as well-characterizing the cell cycle phases. Each studied gene is then classified by its peak similarity to one pre-specified reference gene. This classical approach suffers from two limitations. On the one hand, there is no consensus between biologists about the set of reference genes to consider for the identification process. On the other hand, the proximity measures used for genes expression profiles are unjustified and mainly based on the expression values regardless of the genes expression behavior. To identify genes expression profiles, a new adaptive clustering approach is proposed which consists of two main points. First, it allows in an unsupervised way the selection of a well-justified set of reference genes, to be compared with the pre-specified ones. Secondly, it enables the users to learn the appropriate proximity measure to use for genes expression data, a measure which will cover both proximity on values and on behavior. The adaptive clustering method is compared to a correlation-based approach through public and simulated genes expression data.

This paper addresses the clustering and classification of active genes during the process of cell division. Cell division ensures the proliferation of cells, but becomes drastically aberrant in cancer cells. The studied genes are described by their expression profiles (i.e. time series) during the cell division cycle. This work focuses on evaluating the efficiency of four major metrics for clustering and classifying gene expression profiles. The study is based on a random-periods model for the expression of cell-cycle genes. The model accounts for the observed attenuation in cycle amplitude or duration, variations in the initial amplitude, and drift in the expression profiles.

Cdc7 kinase has recently emerged as an attractive target for cancer therapy and low-molecular-weight inhibitors of Cdc7 kinase have been found to be effective in the inhibition of tumor growth in animal models. In this paper, we describe synthesis and structure-activity relationships of new 1H-pyrrolo[2,3-b]pyridine derivatives identified as inhibitors of Cdc7 kinase. Progress from (Z)-2-phenyl-5-(1H-pyrrolo[2,3-b]pyridin-3-ylmethylene)-3,5-dihydro-4H-imidazol-4-one (1) to [(Z)-2-(benzylamino)-5-(1H-pyrrolo[2,3-b]pyridin-3-ylmethylene)-1,3-thiazol-4(5H)-one] (42), a potent ATP mimetic inhibitor of Cdc7 kinase with IC(50) value of 7 nM, is also reported.

We researched on Dendrobium candidium, which was stimulated by sound wave stress to find out the differentially expressed genes responding to sound wave stress. Extracting and analyzing the genes. And then four differentially expressed genes responding to sound wave stress appearing stable repetition, Clone-SA8, Clone-SA5, Clone-SG6, and Clone-CC7, were obtained by way of traditionary molecular biology techniques. It was conjectured that Clone-SA8 lengthen cell division cycle, Clone-SA5 make the expression of alpha-tubulin more strongly and Clone-SG6 increase the activity of H+-ATPase enzyme based on softwares: DNAMAN program, BLASTP program.

From general considerations of the basic physiological properties of the cell division cycle, we deduce what the dynamical properties of the underlying molecular control system must be. Then, taking a few hints from the biochemistry of cyclin-dependent kinases (the master regulators of the eukaryotic cell cycle), we guess what molecular mechanisms must be operating to produce the desired dynamical properties of the control system.

We study the growth rate of a cell population that follows an age-structured PDE with time-periodic coefficients. Our motivation comes from the comparison between experimental tumor growth curves in mice endowed with intact or disrupted circadian clocks, known to exert their influence on the cell division cycle. We compare the growth rate of the model controlled by a time-periodic control on its coefficients with the growth rate of stationary models of the same nature, but with averaged coefficients. We firstly derive a delay differential equation which allows us to prove several inequalities and equalities on the growth rates. We also discuss about the necessity to take into account the structure of the cell division cycle for chronotherapy modeling. Numerical simulations illustrate the results., 26 pages

While the original septin mutants were identified more than 30 years ago for their role in cytokinesis [Hartwell, LH: Genetic control of the cell division cycle in yeast. IV. Genes controlling bud emergence and cytokinesis. Exp Cell Res 1971, 69: 265-276], the architecture of septin complexes and higher order structures has remained a mystery up until very recently. Over the last few months a number of converging approaches have suddenly provided a wealth of structural information about the different levels of septin organization. Here, we review these advancements and highlight their functional consequences.

O ciclo de divisão celular compreende uma seqüência de fenômenos controlados por una complexa rede de regulação gênica muito estável e robusta. Aplicamos as Redes Genéticas Probabilísticas (PGNs) para construir um modelo cuja dinâmica e robustez se assemelham às observadas no ciclo celular biológico. A estrutura de nosso modelo PGN foi inspirada em fatos biológicos bem estabelecidos tais como a existência de subsistemas integradores, realimentação negativa e positiva e caminhos de sinalização redundantes. Nosso modelo representa as interações entre genes como processos estocásticos e apresenta uma forte robustez na presença de ruido e variações moderadas dos parâmetros. Um modelo determinístico recentemente publicado do ciclo celular da levedura não resiste a condições de ruido que nosso modelo suporta bem. A adição de mecanismos de auto excitação, permite a nosso modelo apresentar uma atividade oscilatória similar à observada no ciclo celular embrionário. Nossa abordagem de modelar e simular o comportamento observado usando mecanismos de controle biológico conhecidos fornece hipóteses plausíveis de como a regulação subjacente pode ser realizada na célula. A pesquisa atualmente em curso procura identificar tais mecanismos de regulação no ciclo celular da levedura, usando dados de expressão gênica provenientes de medições seqüenciais de microarray. The cell division cycle comprises a sequence of phenomena controlled by a stable and robust genetic network. We applied a Probabilistic Genetic Network (PGN) to construct an hypothetical model with dynamical behaviour and robustness typical of the biological cell-cycle. The structure of our PGN model was inspired in well established biological facts such as the existence of integrator subsystems, negative and positive feedback loops and redundant signaling pathways. Our model represents genes\' interactions as stochastic processes and presents strong robustness in the presence of moderate noise and parameters fluctuations. A recently published deterministic yeast cell-cycle model collapses upon noise conditions that our PGN model supports well. In addition, self stimulatory mechanisms can give our PGN model the possibility of having a pacemaker activity similar to the observed in the oscillatory embryonic cell cycle. Our approach of modeling and simulating the observed behavior by known biological control mechanisms provides plausible hypotheses of how the underlying regulation may be performed in the cell. The ongoing research is lead to identify such regulation mechanisms in the yeast cell-cycle from time-series microarray gene expression data.

Publisher Summary The first international yeast meeting at Carbondale in 1961 acknowledged the importance of the yeast research community that at that time had already become established. Since then, the yeast community has moved from classical genetics through the molecular age and finally into the post-genomic era. Along the way, the number of researchers using yeast as their model organism has expanded far beyond anyone's expectation and the tools that have been developed have brought yeast to the point where it is arguably the most powerful eukaryotic model system available for studying basic cellular processes. Studies in yeast have made major contributions to the understanding of a wide variety of fundamental processes, including the cell division cycle and protein targeting to name just two. The post-genomic era has enabled both genomewide and focused studies in yeast to advance at an amazing pace; yet the knowledge of yeast is still far from complete. There is still much to learn and the wide varieties of techniques that can be used now add to the power of yeast as an experimental system.

application/pdf, Little is known about the photoreceptors involved in the photoperiodism of unicellular organisms, which we elucidated by deriving their action spectra. The flagellated alga Euglena gracilis exhibits photoperiodism, with a long-day response in cell reproduction. The underlying clock is a circadian rhythm with photoinductive capability, peaking at subjective dusk and occurring at the 26th hour in continuous darkness (DD) when transferred from continuous light (LL); it regulates photoinduction, a high-irradiance response (HIR), of a dark-capability of progressing through cell division. We derived the action spectra by irradiating E. gracilis with monochromatic light for 3 h at around the 26th hour; the action maxima occurred at 380, 450–460, 480, 610, 640, 660, 680, and 740 nm. Except for the maximum at 450–460 nm, which was always a major maximum, the maxima greatly depended on the red (R)/far-red (FR) ratio of the prior LL. The high R/FR ratio resulted in a dominant major peak at 640 nm and minor peaks at 480 and 680 nm, whereas the low ratio resulted in dominant major peaks at 610 and 740 nm and minor peaks at 380 and 660 nm; the critical fluence was minimally about 60 mmol m–2. These HIRs resulted from the accumulation of corresponding low-fluence responses (LFRs) because we found that repetition of a 3-min light/dark cycle, with critical fluences of 1 mmol m–2, lasting for 3 h resulted in the same photoinduction as the continuous 3-h irradiation. Moreover, these LFRs expressed photoreversibility. Thus, photoperiodic photoinduction involves Euglena-phytochrome (640 and 740 nm) and blue photoreceptor (460 nm). Although 380, 480, 610, 660, and 680 nm may also represent Euglena-phytochrome, a definite conclusion awaits further study.

Cellular senescence permanently arrests the cell division cycle and has long been thought to prevent the growth of cells at risk for transformation into cancer cells. In her Perspective, [Campisi][1] discusses recent evidence that cellular senescence indeed limits the development of malignant cancers in mice and humans. [1]: http://www.sciencemag.org/cgi/content/full/309/5736/886

In this paper, we study the mathematical properties of a family of models of Eukaryotic cell cycle, which extend the qualitative model proposed by Tyson [Proc. Natl. Acad. Sci. 88 (1991) 7328–7332]. By means of some recent results in the theory of Lienard's systems, conditions for the uniqueness of the limit cycle and on the global asymptotic stability of the unique equilibrium (idest of the arrest of the cell division) are given.

A key phenomenon in the dynamics of genetic networks is the cell cycle. In the study of this phenomenon, an important task is to understand how many processes, acting on different temporal and spatial scales, interact in the cell. In this paper we deal with the problem of modelling cell cycles. We start our analysis from the Novak-Tyson model and apply this deterministic model to simulate relative protein concentrations in several different living systems, including Schixosaccharomyces pombe to validate the results. Then we generalize the model to account for the nonlinear dynamics of a cell division cycle, and in particular for special events of cell cycles. We discuss the obtained results and their implications on designing engineered regulatory genetic networks and new biological technologies.

The discovery of the cell division cycle opened new avenues for the understanding of cancer as well as in the search for therapy. However, the implications of the discovery had a more profound effect on biological research than anticipated at the time. We can now clearly distinguish between the activation of the cell division cycle and cell division itself. We also have closer understanding of the differences between senescence, quiescence and terminal differentiation. Furthermore the elucidation of the mechanisms that regulate the cell cycle also means that we have now begun to understand the mechanisms that link cell division and cell death.

The presence of microcystins (MCY) in the cyanobacteria Microcystis panniformis Komarek et al. is reported for the first time. This strain of cyanobacterium has been isolated from Barra Bonita, an eutrophicated water reservoir in Sao Paulo state, Brazil. The identification of M. panniformis was confirmed by both traditional morphological analysis and the phycocyanin intergenic spacer sequences. MCY-LR and [Asp3]-MCY-LR were identified in this strain after HPLC purification and extensive ESI-MS/MS analysis. Their levels in this strain were determined by HPLC and ranged from 0.25 to 2.75 and 0.08 to 0.75 fmol/cell, respectively. Analyzing the levels of MCY-LR and [Asp3]-MCY-LR in different times during the light:dark (L:D) cycle, it was found that levels of MCYs per cell were at least threefold as high during the day-phase than during the night-phase. This may be associated to the biological clock since prokaryotic cyanobacteria express robust circadian (daily) rhythms under the control of a timing mechanism that is independent of the cell division cycle. Our findings also showed the same pattern under light:light (L:L) cycle.

Meiosis can be considered an elaboration of the cell division cycle in the sense that meiosis combines cell-cycle processes with programs specific to meiosis. Each phase of the cell division cycle is driven forward by cell-cycle kinases (Cdk) and coordinated with other phases of the cycle through checkpoint functions (Hartwell and Weinert [1989]: Science. 246:629–634). Meiotic differentiation is also controlled by these two types of regulation (Murakami and Nurse [2000]: Biochem J. 349:1–12; Roeder and Bailis [2000]: Trends Genet. 16:395–403); however, recent study in the budding yeast S. cerevisiae indicates that progression of meiosis is also controlled by a master regulator specific to meiosis, namely the Ime2p kinase (Benjamin et al. [2003]: Genes Dev. 17:1–16; Schindler et al. [2003]: Mol Cell Biol 23:8718–8728). Below, I describe the overlapping roles of Ime2p and Cdk during meiosis in yeast and speculate on how these two kinases cooperate to drive the progression of meiosis. © 2004 Wiley-Liss, Inc.

Intense industrial development and population growth have been altering the quality of water and innumerous studies have been undertaken to analyze their effects on humans. Due to rivers contamination with agrotoxics, herbicides, pesticides, excess of farming chemical additives and through sewers spilling not properly treated industrial waste, investigating cytotoxic and mutagenic activity of river water becomes all-important. Bone marrow cells of Wistar rats ( Rattus norvegicus ), treated in vivo , through gavage, in subchronic treatment (7 days), were used as experimental animal test system to investigate the effects of well water and water from the rivers Ficha and Minas Gerais, close to the municipality of Ubirata, State of Parana, southern Brazil. Cell division index and metaphase chromosomes were analyzed. The statistical analysis showed that the experiment's water failed to alter cell division cycle of Wistar rats and did not increase number of chromosome aberrations. No cytotoxic and clastogenic effects ensued from this treatment

Human somatic cells undergo only a limited number of divisions in vitro before they withdraw from the cell division cycle and enter a permanent state of proliferation arrest. This arrest is accompanied by a variety of morphological and biochemical changes in the cells, and the arrest state is referred to as senescence. The in vitro senescence process has been widely studied as a model for in vivo cellular aging [1].

A model of artificial chemistry in which both genotypic and phenotypic strings mingle together and react with each other is presented. A cell that includes a string set for the replication and translation of genetic information is designed on this system, and the cells are reproduced by cell division cycles. From experiments that emulate cell selection, it is shown that a complete set of genes constituting the designed system can be stably transmitted to the offspring cells if they are put into a long single chromosome or the gene replication is strictly regulated and the replicated genes are transferred to the two daughter cells by a spindle.

In October 2001, Sir Paul Nurse and Dr Tim Hunt of the Imperial Cancer Research Fund became the first Britons since 1988 to win the Nobel prize for Physiology or Medicine. The prize was shared with Dr Leland Hartwell, director of the Fred Hutchinson Cancer Research Center in Seattle, and acknowledged the extraordinary progress made by the three scientists in identifying the molecules that orchestrate the growth and division of cells. Two British scientists winning a Nobel prize is reason enough to celebrate, but what made this achievement particularly pleasing was that many of the key experiments were carried out in fungi. In the early 1970's, Hartwell recognised the potential for studying the cell cycle with genetic methods, using as his model the baker's yeast, Saccharomyces cerevisiae (Hartwell, Culotti & Reid, 1970). He isolated yeast cells in which genes controlling the cell cycle were mutated and thereby identified over 100 "CDC" (cell division cycle) genes. One of these (CDC28) was shown to control a key step in the progression from G1 to S-phase, a point known as 'Start' (Fig 1). Inspired by Hartwell's work, Paul Nurse took a similar approach using another fungal model, the fission yeast Schizosaccharomyces pombe (Nurse, Thuriaux & Nasmyth, 1976). In the mid-1970's, he showed that a gene dubbed cdc2 had a key function in controlling the transition from G2 to M-phase. DNA sequencing of the gene revealed that cdc2 was very similar to the CDC28 gene that Hartwell had shown to control the transition through Start. In other words, a single gene regulates progression through two key points in the cell cycle in organisms that separated from each other during evolution more than one billion years ago.

Circadian Rhythms Studies of coupled oscillators started in the 1600s, when the man who invented the pendulum clock set a pair of clocks side by side in a single case and noticed that they started ticking in unison. In mammalian cells, the machinery that controls the cell division cycle turns out to be similarly synchronized with the daily circadian clock, which allows cells to get on the same seasonal and day-night schedules. Feillet et al. imaged single live mammalian cells in culture and performed mathematical modeling. They showed that the daily circadian clock and the cell division cycle oscillate together at the same frequency. This may have clinical relevance: Circadian disruption is a risk factor for some cancers. Proc. Natl. Acad. Sci. U.S.A. 10.1073pnas.1320474111 (2014).

53molecules. (a) 53 NSGM (G1-G12) were examined for growth in monolayer and spheroid conditions (Screen 1) followed by primary versus secondary/tertiary growth (Screen 2). The dual tandem screen identified three ‘lead' NSGMs (G2.2, G11.1 and G12.2) that selectively target self-renewing colorectal CSCs. Two structural analogues of G2.2 (G1.4 & G4.1) were also chosen for studying molecular specificity of inhibition. (b) 20 NSGMs (4 active scaffold G2, G4, G11 and G12, identified in screen 1), were examined for primary spheroid growth in HCT-116 and HT-29 cell with distinct genetic backgrounds. (c) 11 NSGMs (arrows in (B)) that showed >50% inhibition in both cell lines (p

Both cell growth (cell mass increase) and progression through the cell division cycle are required for sustained cell proliferation. Proliferating cells in culture tend to double in mass before each division, but it is not known how growth and division rates are co-ordinated to ensure that cell size is maintained. The prevailing view is that coordination is achieved because cell growth is rate-limiting for cell-cycle progression. Here, we challenge this view. We have investigated the relationship between cell growth and cell-cycle progression in purified rat Schwann cells, using two extracellular signal proteins that are known to influence these cells. We find that glial growth factor (GGF) can stimulate cell-cycle progression without promoting cell growth. We have used this restricted action of GGF to show that, for cultured Schwann cells, cell growth rate alone does not determine the rate of cell-cycle progression and that cell size at division is variable and depends on the concentrations of extracellular signal proteins that stimulate cell-cycle progression, cell growth, or both.