Discovery of novel transcription control relationships with gene regulatory networks generated from multiple-disruption full genome expression libraries.

Gene regulatory networks elucidated from strategic, genome-wide experimental data can aid in the discovery of novel gene function information and expression regulation events from observation of transcriptional regulation among genes of known and unknown biological function. To create a reliable and comprehensive data set for the elucidation of transcription regulation networks, we conducted systematic genome-wide disruption expression experiments of yeast on 118 genes with known involvement in transcription regulation. We report several novel regulatory relationships between known transcription factors and other genes with previously unknown biological function discovered with this expression library. Here we report the downstream regulatory subnetworks for UME6 and MET28. The elucidated network topology among these genes demonstrates MET28's role as a nodal point between genes involved in cell division and those involved in DNA repair mechanisms.

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.

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.

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.

Novel biological activity of the region (106-126) on human prion sequence.

We report that the synthetic peptide Prp106-126 (KTNMKHMAGAAAAGAVVGGLG-COOH) and the reversed peptide Prp126-106 (GLGGVVAGAAAAGAMHKMNTK-COOH) of human prion (hPrp) can express the decarboxylase activity for oxaloacetate in the presence of trifluoroethanol, similar to that of Oxaldie 1 (LAKLLKALAKLLKK-CONH2) reported previously. The degree of the relative activity of Prp106-126 and Prp126-106 to Oxaldie 1 is 0.47 and 0.21, respectively. Based on this experimental result, we applied the informational system method (ISM) developed by Veljkovic et al. to the amino acid sequence of Prp106-126 and Prp126-106 to extract a common factor. The same spectra were obtained, indicating that the same periodicity may be conserved on their sequences, as a necessary factor for expressing the same biological activity, irrespective of the orientation of the primary sequence.