Dynamical modeling of the network controlling meiotic divisions

Mitosis and meiosis are both controlled by oscillations in the activities of cyclin- dependent kinase 1 (Cdk1) and the anaphase-promoting complex/cyclosome (APC/C). Nevertheless, these types of cell division differ in fundamental aspects. In mitosis, Cdk1 and APC/C-Cdc20 form a cyclical system whereby each cycle recreates the starting conditions for the next one. As a result, chromosomes duplication during S-phase alternates with chromosome segregation during M-phase. By contrast, meiosis is a linear pathway of precisely two waves of Cdk1 and APC/C-Cdc20 activity that govern the progression through one S-phase followed by two M-phases and a differentiation program dedicated to the formation of gametes or spores. Despite recent advances in our understanding of meiosis, it is unclear how the mitotic cell cycle engine is modified to regulate the two meiotic divisions. Therefore, we combined mathematical modeling with experimental studies on budding yeast to describe the general mechanism of progression through meiotic divisions with special emphasis on the regulation of the exit from meiosis II. We showed that progression through meiotic divisions is driven by a well conserved Cdk1-APC/C-Cdc20 oscillator complemented by a set of meiotic regulators in order to perform two, and only two, meiotic divisions. The machinery that terminates the oscillations after completion of meiosis II consists of a meiosis I-specific mechanism that unleashes the irreversible inactivation of M-phase regulators after the second wave of APC/C-Cdc20 activity, thereby preventing cells from undergoing an additional third division. Here, we describe the roles of the two main APC/C co- activators, Ama1 and Cdc20, in triggering the exit from meiosis and in terminating the oscillations. We show that Ama1 acts as a terminator of the meiotic oscillations, while Cdc20 is important for the proper timing of the exit from meiosis II. We propose that in the absence of Ama1, the properties of the system change, allowing Cdc20 to adopt the function of the terminator precisely after meiosis II. In addition, we evaluate an APC/C-independent mechanisms, which might be important for preventing a third meiotic division

Briefly Bound to Activate: Transient Binding of a Second Catalytic Magnesium Activates the Structure and Dynamics of CDK2 Kinase for Catalysis

SummaryWe have determined high-resolution crystal structures of a CDK2/Cyclin A transition state complex bound to ADP, substrate peptide, and MgF3−. Compared to previous structures of active CDK2, the catalytic subunit of the kinase adopts a more closed conformation around the active site and now allows observation of a second Mg2+ ion in the active site. Coupled with a strong [Mg2+] effect on in vitro kinase activity, the structures suggest that the transient binding of the second Mg2+ ion is necessary to achieve maximum rate enhancement of the chemical reaction, and Mg2+ concentration could represent an important regulator of CDK2 activity in vivo. Molecular dynamics simulations illustrate how the simultaneous binding of substrate peptide, ATP, and two Mg2+ ions is able to induce a more rigid and closed organization of the active site that functions to orient the phosphates, stabilize the buildup of negative charge, and shield the subsequently activated γ-phosphate from solvent

Transcriptional Regulation Is a Major Controller of Cell Cycle Transition Dynamics

DNA replication, mitosis and mitotic exit are critical transitions of the cell cycle which normally occur only once per cycle. A universal control mechanism was proposed for the regulation of mitotic entry in which Cdk helps its own activation through two positive feedback loops. Recent discoveries in various organisms showed the importance of positive feedbacks in other transitions as well. Here we investigate if a universal control system with transcriptional regulation(s) and post-translational positive feedback(s) can be proposed for the regulation of all cell cycle transitions. Through computational modeling, we analyze the transition dynamics in all possible combinations of transcriptional and post-translational regulations. We find that some combinations lead to ‘sloppy’ transitions, while others give very precise control. The periodic transcriptional regulation through the activator or the inhibitor leads to radically different dynamics. Experimental evidence shows that in cell cycle transitions of organisms investigated for cell cycle dependent periodic transcription, only the inhibitor OR the activator is under cyclic control and never both of them. Based on these observations, we propose two transcriptional control modes of cell cycle regulation that either STOP or let the cycle GO in case of a transcriptional failure. We discuss the biological relevance of such differences

Translational Oncogenomics and Human Cancer Interactome Networks

An overview of translational, human oncogenomics, transcriptomics and cancer interactomic networks is presented together with basic concepts and potential, new applications to Oncology and Integrative Cancer Biology. Novel translational oncogenomics research is rapidly expanding through the application of advanced technology, research findings and computational tools/models to both pharmaceutical and clinical problems. A self-contained presentation is adopted that covers both fundamental concepts and the most recent biomedical, as well as clinical, applications. Sample analyses in recent clinical studies have shown that gene expression data can be employed to distinguish between tumor types as well as to predict outcomes. Potentially important applications of such results are individualized human cancer therapies or, in general, ‘personalized medicine’. Several cancer detection techniques are currently under development both in the direction of improved detection sensitivity and increased time resolution of cellular events, with the limits of single molecule detection and picosecond time resolution already reached. The urgency for the complete mapping of a human cancer interactome with the help of such novel, high-efficiency / low-cost and ultra-sensitive techniques is also pointed out

A STAT3-inhibitory hairpin decoy oligodeoxynucleotide discriminates between STAT1 and STAT3 and induces death in a human colon carcinoma cell line

<p>Abstract</p> <p>Background</p> <p>The Signal Transducer and Activator of Transcription 3 (STAT3) is activated in tumor cells, and STAT3-inhibitors are able to induce the death of those cells. Decoy oligodeoxynucleotides (dODNs), which bind to the DNA Binding Domain (DBD) of STAT3, are efficient inhibitors. However, they also inhibit STAT1, whose activity is essential not only to resistance to pathogens, but also to cell growth inhibition and programmed cell death processes. The aim of this study was to design STAT3-specific dODNs which do not affect STAT1-mediated processes.</p> <p>Results</p> <p>New dODNs with a hairpin (hpdODNs) were designed. Modifications were introduced, based on the comparison of STAT3- and STAT1-DBD interactions with DNA using 3D structural analyses. The designed hpdODNs were tested for their ability to inhibit STAT3 but not STAT1 by determining: i) cell death in the active STAT3-dependent SW480 colon carcinoma cell line, ii) absence of inhibition of interferon (IFN) γ-dependent cell death, iii) expression of STAT1 targets, and iv) nuclear location of STAT3 and STAT1. One hpdODN was found to efficiently induce the death of SW480 cells without interfering with IFNγ-activated STAT1. This hpdODN was found in a complex with STAT3 but not with STAT1 using an original in-cell pull-down assay; this hpdODN also did not inhibit IFNγ-induced STAT1 phosphorylation, nor did it inhibit the expression of the STAT1-target IRF1. Furthermore, it prevented the nuclear transfer of STAT3 but not that of IFNγ-activated STAT1.</p> <p>Conclusions</p> <p>Comparative analyses at the atomic level revealed slight differences in STAT3 and STAT1 DBDs' interaction with their DNA target. These were sufficient to design a new discriminating hpdODN that inhibits STAT3 and not STAT1, thereby inducing tumor cell death without interfering with STAT1-dependent processes. Preferential interaction with STAT3 depends on oligodeoxynucleotide sequence modifications but might also result from DNA shape changes, known to modulate protein/DNA interactions. The finding of a STAT3-specific hpdODN establishes the first rational basis for designing STAT3 DBD-specific inhibitors.</p

Towards a systems biology approach to mammalian cell cycle: modeling the entrance into S phase of quiescent fibroblasts after serum stimulation

Background: The cell cycle is a complex process that allows eukaryotic cells to replicate chromosomal DNA and partition it into two daughter cells. A relevant regulatory step is in the G0/G1phase, a point called the restriction (R) point where intracellular and extracellular signals are monitored and integrated. Results: Subcellular localization of cell cycle proteins is increasingly recognized as a major factor that regulates cell cycle transitions. Nevertheless, current mathematical models of the G1/S networks of mammalian cells do not consider this aspect. Hence, there is a need for a computational model that incorporates this regulatory aspect that has a relevant role in cancer, since altered localization of key cell cycle players, notably of inhibitors of cyclin-dependent kinases, has been reported to occur in neoplastic cells and to be linked to cancer aggressiveness. Conclusion: The network of the model components involved in the G1to S transition process was identified through a literature and web-based data mining and the corresponding wiring diagram of the G1to S transition drawn with Cell Designer notation. The model has been implemented in Mathematica using Ordinary Differential Equations. Time-courses of level and of sub-cellular localization of key cell cycle players in mouse fibroblasts re-entering the cell cycle after serum starvation/re-feeding have been used to constrain network design and parameter determination. The model allows to recapitulate events from growth factor stimulation to the onset of S phase. The R point estimated by simulation is consistent with the R point experimentally determined. The major element of novelty of our model of the G1to S transition is the explicit modeling of cytoplasmic/nuclear shuttling of cyclins, cyclin-dependent kinases, their inhibitor and complexes. Sensitivity analysis of the network performance newly reveals that the biological effect brought about by Cki overexpression is strictly dependent on whether the Cki is promoting nuclear translocation of cyclin/Cdk containing complexes. © 2009 Alfieri et al; licensee BioMed Central Ltd

Stochastic modulation evidences a transitory EGF-Ras-ERK MAPK activity induced by PRMT5

The extracellular signal-regulated kinase (ERK) mitogen-activated protein kinase (MAPK) pathway involves a three-step cascade of kinases that transduce signals and promote processes such as cell growth, development, and apoptosis. An aberrant response of this pathway is related to the proliferation of cell diseases and tumors. By using simulation modeling, we document that the protein arginine methyltransferase 5 (PRMT5) modulates the MAPK pathway and thus avoids an aberrant behavior. PRMT5 methylates the Raf kinase, reducing its catalytic activity and thereby, reducing the activation of ERK in time and amplitude. Two minimal computational models of the epidermal growth factor (EGF)-Ras-ERK MAPK pathway influenced by PRMT5 were proposed: a first model in which PRMT5 is activated by EGF and a second one in which PRMT5 is stimulated by the cascade response. The reported results show that PRMT5 reduces the time duration and the expression of the activated ERK in both cases, but only in the first model PRMT5 limits the EGF range that generates an ERK activation. Based on our data, we propose the protein PRMT5 as a regulatory factor to develop strategies to fight against an excessive activity of the MAPK pathway, which could be of use in chronic diseases and cancer

Computational modelling of meiotic entry and commitment

In response to developmental and environmental conditions, cells exit the mitotic cell cycle and enter the meiosis program to generate haploid gametes from diploid germ cells. Once cells decide to enter the meiosis program they become irreversibly committed to the completion of meiosis irrespective of the presence of cue signals. How meiotic entry and commitment occur due to the dynamics of the regulatory network is not well understood. Therefore, we constructed a mathematical model of the regulatory network that controls the transition from mitosis to meiosis in Schizosaccharomyces pombe. Upon nitrogen starvation, yeast cells exit mitosis and undergo conjugation and meiotic entry. The model includes the regulation of Mei2, an RNA binding protein required for conjugation and meiotic entry, by multiple feedback loops involving Pat1, a kinase that keeps cells in mitosis, and Ste11, a transcription activator required for the sexual differentiation. The model accounts for various experimental observations and demonstrates that the activation of Mei2 is bistable, which ensures the irreversible commitment to meiosis. Further, we show by integrating the meiosis-specific regulation with a cell cycle model, the dynamics of cell cycle exit, G1 arrest and entry into meiosis under nitrogen starvation. © 2017 The Author(s)

The modular systems biology approach to investigate the control of apoptosis in Alzheimer's disease neurodegeneration

Apoptosis is a programmed cell death that plays a critical role during the development of the nervous system and in many chronic neurodegenerative diseases, including Alzheimer's disease (AD). This pathology, characterized by a progressive degeneration of cholinergic function resulting in a remarkable cognitive decline, is the most common form of dementia with high social and economic impact. Current therapies of AD are only symptomatic, therefore the need to elucidate the mechanisms underlying the onset and progression of the disease is surely needed in order to develop effective pharmacological therapies. Because of its pivotal role in neuronal cell death, apoptosis has been considered one of the most appealing therapeutic targets, however, due to the complexity of the molecular mechanisms involving the various triggering events and the many signaling cascades leading to cell death, a comprehensive understanding of this process is still lacking. Modular systems biology is a very effective strategy in organizing information about complex biological processes and deriving modular and mathematical models that greatly simplify the identification of key steps of a given process. This review aims at describing the main steps underlying the strategy of modular systems biology and briefly summarizes how this approach has been successfully applied for cell cycle studies. Moreover, after giving an overview of the many molecular mechanisms underlying apoptosis in AD, we present both a modular and a molecular model of neuronal apoptosis that suggest new insights on neuroprotection for this disease