Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

Deregulation of ErbB signaling plays a key role in the progression of multiple human cancers. To help understand ErbB signaling quantitatively, in this work we combine traditional experiments with computational modeling, building a model that describes how stimulation of all four ErbB receptors with epidermal growth factor (EGF) and heregulin (HRG) leads to activation of two critical downstream proteins, extracellular-signal-regulated kinase (ERK) and Akt. Model analysis and experimental validation show that (i) ErbB2 overexpression, which occurs in approximately 25% of all breast cancers, transforms transient EGF-induced signaling into sustained signaling, (ii) HRGinduced ERK activity is much more robust to the ERK cascade inhibitor U0126 than EGF-induced ERK activity, and (iii) phosphoinositol-3 kinase is a major regulator of post-peak but not pre-peak EGF-induced ERK activity. Sensitivity analysis leads to the hypothesis that ERK activation is robust to parameter perturbation at high ligand doses, while Akt activation is not.

We propose a new method for inferring S-system models of large-scale genetic networks. The proposed method is based on the problem decomposition strategy and a cooperative coevolutionary algorithm. As the subproblems divided by the problem decomposition strategy are solved simultaneously using the cooperative coevolutionary algorithm, the proposed method can be used to infer any S-system model ready for computational simulation. To verify the effectiveness of the proposed method, we apply it to two artificial genetic network inference problems. Finally, the proposed method is used to analyze the actual DNA microarray data.

ErbB tyrosine kinase receptors mediate mitogenic signal cascade by binding a variety of ligands and recruiting the different cassettes of adaptor proteins. In the present study, we examined heregulin (HRG)-induced signal transduction of ErbB4 receptor and found that the phosphatidylinositol 3'-kinase (PI3K)-Akt pathway negatively regulated the extracellular signal-regulated kinase (ERK) cascade by phosphorylating Raf-1 on Ser(259). As the time-course kinetics of Akt and ERK activities seemed to be transient and complex, we constructed a mathematical simulation model for HRG-induced ErbB4 receptor signalling to explain the dynamics of the regulation mechanism in this signal transduction cascade. The model reflected well the experimental results observed in HRG-induced ErbB4 cells and in other modes of growth hormone-induced cell signalling that involve Raf-Akt cross-talk. The model suggested that HRG signalling is regulated by protein phosphatase 2A as well as Raf-Akt cross-talk, and protein phosphatase 2A modulates the kinase activity in both the PI3K-Akt and MAPK (mitogen-activated protein kinase) pathways.

The different kinetics displayed by extracellular signal-regulated kinase (ERK) 3 activation often results in distinct cellular phenotypes of mammalian cells. In PC12 cells, the epidermal growth factor (EGF)-stimulated transient activation of ERK induces cell proliferation, whereas a nerve growth factor-stimulated sustained activation of ERK induces differentiation (1, 2). Similarly, different growth factor ligands cause distinct kinetics of ERK activation in human breast cancer cells (3, 4). ERK and Akt/protein kinase B are deterministic kinases that control the activation of nuclear transcription factors (5-7); therefore, it is expected that the activation kinetics of these kinases might affect the following gene expression profiles. However, the question concerning gene expression dynamics induced by kinetically different kinase activities and its effect on cell determination mechanisms remains unsolved.In this study we focused on the dose-dependent time course analysis of early transcription induced by two ligands of the ErbB family receptor, EGF and heregulin (HRG), which induce distinct kinase activity patterns and phenotypes of MCF-7 cells. Although many studies attempted to delineate the biochemical characteristics of ErbB ligands and receptors, no systematic study has been reported concerning the analysis of ErbB receptor-mediated cell fate control.MCF-7 cells endogenously express all family members of the ErbB protein-tyrosine kinase receptors (EGFR/ErbB1, ErbB2, ErbB3, and ErbB4 receptors). EGF preferably binds to an EGFR, whereas HRG first binds to either the ErbB3 or ErbB4 receptor and then induces trans-activation of ErbB2 (8). ErbB receptors tend to form heterodimers in response to ligand binding when different ErbB receptors are co-expressed in the same cell. In particular, ErbB2 is the preferred heterodimerization partner among the receptor family (9), and it functions as an oncogenic unit through heterodimer formation with ErbB3 (10). EGFR activation induces selfdown-regulation of the receptor by recruitment of the Cbl ubiquitin ligase (11,12), and the activation of ErbB3 strongly evokes phosphatidylinositol 3Ј-kinase (PI3K) activation (13,14). Activation of ErbB receptor is often accompanied by activation of Shc-ERK and PI3K-Akt pathways. These two pathways often cross-talk or inhibit each other (15, 16) thereby resulting in distinct activity patterns pertaining to intracellular signaling that activate various types of transcription factors (17-19). In addition, many studies attempted to identify specific gene expression induced by different ErbB ligands that show signaling diversities and distinct biological outcomes (20, 21); however, earlier results using platelet-derived growth factor (PDGF)-␤ receptor mutants indicated that diverse signaling pathways induce broadly overlapping transcription (22).