Yukihiro Eguchi

DEVELOPMENT OF A SYSTEM FOR THE INFERENCE OF LARGE SCALE GENETIC NETWORKS

We propose a system named AIGNET (Algorithms for Inference of Genetic Networks), and introduce two top-down approaches for the inference of interrelated mechanism among genes in genetic network that is based on the steady state and temporal analyses of gene expression patterns against some kinds of gene perturbations such as disruption or overexpression. The former analysis is performed by a static Boolean network model based on multi-level digraph, and the latter one is by S-system model. By integrating these two analyses, we show our strategy is flexible and rich in structure to treat gene expression patterns; we applied our strategy to the inference of a genetic network that is composed of 30 genes as a case study. Given the gene expression time-course data set under the conditions of wild-type and the deletion of one gene, our system enabled us to reconstruct the same network architecture as original one.

Mathematical modeling and sensitivity analysis of G1/S phase in the cell cycle including the DNA-damage signal transduction pathway

The cell cycle has checkpoint systems, which control G1/S, G2/M and G0/G1 phase transitions. When a normal cell suffers from DNA-damage, the signal transduction of DNA-damage causes the cell cycle arrest by using the checkpoint systems. Therefore, the elucidation of interaction between the signal transduction of DNA-damage and the checkpoint systems is an important problem. In this study, we constructed a novel mathematical model (proposed model) which integrated G1/S-checkpoint model with a signal transduction of DNA damage model and performed some numerical simulations. The proposed model realized some biological findings of G1/S phase with or without DNA-damage, which suggested that proposed model is biologically appropriate. Moreover, the results of sensitivity analysis of the proposed model indicated the predominant factors of G1/S phase and some factors concerned with the transformation of cells.

Mathematical modeling of cell cycle regulation in response to DNA damage: Exploring mechanisms of cell-fate determination

After DNA damage, cells activate p53, a tumor suppressor gene, and select a cell fate (e.g., DNA repair, cell cycle arrest, or apoptosis). Recently, a p53 oscillatory behavior was observed following DNA damage. However, the relationship between this p53 oscillation and cell-fate selection is unclear. Here, we present a novel model of the DNA damage signaling pathway that includes p53 and whole cell cycle regulation and explore the relationship between p53 oscillation and cell fate selection. The simulation run without DNA damage qualitatively realized experimentally observed data from several cell cycle regulators, indicating that our model was biologically appropriate. Moreover, the comprehensive sensitivity analysis for the proposed model was implemented by changing the values of all kinetic parameters, which revealed that the cell cycle regulation system based on the proposed model has robustness on a fluctuation of reaction rate in each process. Simulations run with four different intensities of DNA damage, i.e. Low-damage, Medium-damage, High-damage, and Excess-damage, realized cell cycle arrest in all cases. Low-damage, Medium-damage, High-damage, and Excess-damage corresponded to the DNA damage caused by 100, 200, 400, and 800 J/m(2) doses of UV-irradiation, respectively, based on expression of p21, which plays a crucial role in cell cycle arrest. In simulations run with High-damage and Excess-damage, the length of the cell cycle arrest was shortened despite the severe DNA damage, and p53 began to oscillate. Cells initiated apoptosis and were killed at 400 and 800 J/m(2) doses of UV-irradiation, corresponding to High-damage and Excess-damage, respectively. Therefore, our model indicated that the oscillatory mode of p53 profoundly affects cell fate selection.

Sophisticated Framework between Cell Cycle Arrest and Apoptosis Induction Based on p53 Dynamics

The tumor suppressor, p53, regulates several gene expressions that are related to the DNA repair protein, cell cycle arrest and apoptosis induction, which activates the implementation of both cell cycle arrest and induction of apoptosis. However, it is not clear how p53 specifically regulates the implementation of these functions. By applying several well-known kinetic mathematical models, we constructed a novel model that described the influence that DNA damage has on the implementation of both the G2/M phase cell cycle arrest and the intrinsic apoptosis induction via its activation of the p53 synthesis process. The model, which consisted of 32 dependent variables and 115 kinetic parameters, was used to examine interference by DNA damage in the implementation of both G2/M phase cell cycle arrest and intrinsic apoptosis induction. A low DNA damage promoted slightly the synthesis of p53, which showed a sigmoidal behavior with time. In contrast, in the case of a high DNA damage, the p53 showed an oscillation behavior with time. Regardless of the DNA damage level, there were delays in the G2/M progression. The intrinsic apoptosis was only induced in situations where grave DNA damage produced an oscillation of p53. In addition, to wreck the equilibrium between Bcl-2 and Bax the induction of apoptosis required an extreme activation of p53 produced by the oscillation dynamics, and was only implemented after the release of the G2/M phase arrest. When the p53 oscillation is observed, there is possibility that the cell implements the apoptosis induction. Moreover, in contrast to the cell cycle arrest system, the apoptosis induction system is responsible for safeguarding the system that suppresses malignant transformations. The results of these experiments will be useful in the future for elucidating of the dominant factors that determine the cell fate such as normal cell cycles, cell cycle arrest and apoptosis.

AN INTEGRATED COMPREHENSIVE WORKBENCH FOR INFERRING GENETIC NETWORKS: VOYAGENE

We propose an integrated, comprehensive network-inferring system for genetic interactions, named VoyaGene, which can analyze experimentally observed expression profiles by using and combining the following five independent inferring models: Clustering, Threshold-Test, Bayesian, multi-level digraph and S-system models. Since VoyaGene also has effective tools for visualizing the inferred results, researchers may evaluate the combination of appropriate inferring models, and can construct a genetic network to an accuracy that is beyond the reach of a single inferring model. Through the use of VoyaGene, the present study demonstrates the effectiveness of combining different inferring models.

Stochasticity of intranuclear biochemical reaction processes controls the final decision of cell fate associated with DNA damage

A massive integrative mathematical model of DNA double-strand break (DSB) generation, DSB repair system, p53 signaling network, and apoptosis induction pathway was constructed to explore the dominant factors of unknown criteria of cell fate decision. In the proposed model, intranuclear reactions were modeled as stochastic processes and cytoplasmic reactions as deterministic processes, and both reaction sets were simulated simultaneously. The simulated results at the single-cell level showed that the model generated several sustained oscillations (pulses) of p53, Mdm2, ATM, and Wip1, and cell-to-cell variability in the number of p53 pulses depended on IR intensity. In cell populations, the model generated damped p53 oscillations, and IR intensity affected the amplitude of the first p53 oscillation. Cells were then subjected to the same IR dose exhibiting apoptosis induction variability. These simulated results are in quantitative agreement with major biological findings observed in human breast cancer epithelial MCF7, NIH3T3, and fibrosarcoma cells, demonstrating that the proposed model was concededly biologically appropriate. Statistical analysis of the simulated results shows that the generation of multiple p53 pulses is a prerequisite for apoptosis induction. Furthermore, cells exhibited considerable individual variability in p53 dynamics, which correlated with intrinsic apoptosis induction. The simulated results based on the proposed model demonstrated that the stochasticity of intranuclear biochemical reaction processes controls the final decision of cell fate associated with DNA damage. Applying stochastic simulation to an exploration of intranuclear biochemical reaction processes is indispensable in enhancing the understanding of the dynamic characteristics of biological multi-layered systems of higher organisms.

Design of virtual-labo-system for metabolic engineering : Development of biochemical engineering system analyzing tool-kit (BEST KIT)

Abstract BEST-KIT is an efficient and user-friendly “biochemical engineering system analyzing tool-kit” integrated the following key modules: 1) mathematical modeling and editing of reaction-scheme, 2) automatic derivation of differential equations, 3) numerical calculation, 4) nonlinear optimization, 5) visualization, 6) retrieve the information on reaction mechanism and kinetic parameters from data-base of metabolic pathways. The users of this simulator are assumed to be unfamiliar with computer technology and with computer programming. The integrated interface (UNIX version) is based on Xlib, XToolkit and OSF/Motif Widget.

Mathematical modeling of G2/M phase in the cell cycle with involving the p53/Mdm2 oscillation system

In the cell cycle, the disruption of a checkpoint control mechanism for G2/M phase which monitors DNA damages is one of the triggers for oncogenic transformation. The major event of this mechanism is the p53/Mdm2 signaling pathway-mediated repression of M-phase Promoting Factor (MPF) activation. With the occurring some DNA damages, the protein levels of the p53/Mdm2 shows the oscillation, and the temporal response of the MPF activation delays. However, the detailed interactions between the p53/Mdm2 oscillation and the MPF activation are still unclear biologically. In this study, we designed a mathematical model which can realize the qualitative temporal dynamics of G2/M phase involving the p53/Mdm2 signaling pathway. Moreover we performed some simulations and comprehensive system analysis in order to evaluate the robustness and to explore the dominant control factors of the model. A novel mathematical model (proposed model) was designed by integrating a model for the MPF activation with the p53/Mdm2 signaling pathway. The numerical solutions of the dynamics with employing the proposed model showed the qualitative correspondence with the p53/Mdm2 oscillation and the temporal delay of the MPF activation, which were observed experimentally. Without the assumption of DNA damage, the sensitivity of kinetic parameters of this model was low, and the model system showed high stability. In the case of some DNA damages, however, the sensitivity became to be higher, and the model system showed instability. Thus, we can evaluate that some DNA damages can easily affect the stability of the checkpoint control mechanism. A defective function of Wee1 phosphorylation which affects the dynamics of MPF inhibited the DNA damagemediated temporal delay of the MPF activation. Since a chronic decline of protein level for Wee1 was observed in tumor cells, we proposed that the phosphorylation is one of the dominant factors for the checkpoint control mechanism in G2/M phase.