Kaori Ide

Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm

MOTIVATION To resolve the high-dimensionality of the genetic network inference problem in the S-system model, a problem decomposition strategy has been proposed. While this strategy certainly shows promise, it cannot provide a model readily applicable to the computational simulation of the genetic network when the given time-series data contain measurement noise. This is a significant limitation of the problem decomposition, given that our analysis and understanding of the genetic network depend on the computational simulation. RESULTS 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.

Ligand-Specific c-Fos Expression Emerges from the Spatiotemporal Control of ErbB Network Dynamics

Activation of ErbB receptors by epidermal growth factor (EGF) or heregulin (HRG) determines distinct cell-fate decisions, although signals propagate through shared pathways. Using mathematical modeling and experimental approaches, we unravel how HRG and EGF generate distinct, all-or-none responses of the phosphorylated transcription factor c-Fos. In the cytosol, EGF induces transient and HRG induces sustained ERK activation. In the nucleus, however, ERK activity and c-fos mRNA expression are transient for both ligands. Knockdown of dual-specificity phosphatases extends HRG-stimulated nuclear ERK activation, but not c-fos mRNA expression, implying the existence of a HRG-induced repressor of c-fos transcription. Further experiments confirmed that this repressor is mainly induced by HRG, but not EGF, and requires new protein synthesis. We show how a spatially distributed, signaling-transcription cascade robustly discriminates between transient and sustained ERK activities at the c-Fos system level. The proposed control mechanisms are general and operate in different cell types, stimulated by various ligands.

Ligand-specific sequential regulation of transcription factors for differentiation of MCF-7 cells

BackgroundSharing a common ErbB/HER receptor signaling pathway, heregulin (HRG) induces differentiation of MCF-7 human breast cancer cells while epidermal growth factor (EGF) elicits proliferation. Although cell fates resulting from action of the aforementioned ligands completely different, the respective gene expression profiles in early transcription are qualitatively similar, suggesting that gene expression during late transcription, but not early transcription, may reflect ligand specificity. In this study, based on both the data from time-course quantitative real-time PCR on over 2,000 human transcription factors and microarray of all human genes, we identified a series of transcription factors which may control HRG-specific late transcription in MCF-7 cells.ResultsWe predicted that four transcription factors including EGR4, FRA-1, FHL2, and DIPA should have responsibility of regulation in MCF-7 cell differentiation. Validation analysis suggested that one member of the activator protein 1 (AP-1) family, FOSL-1 (FRA-1 gene), appeared immediately following c-FOS expression, might be responsible for expression of transcription factor FHL2 through activation of the AP-1 complex. Furthermore, RNAi gene silencing of FOSL-1 and FHL2 resulted in increase of extracellular signal-regulated kinase (ERK) phosphorylation of which duration was sustained by HRG stimulation.ConclusionOur analysis indicated that a time-dependent transcriptional regulatory network including c-FOS, FRA-1, and FHL2 is vital in controlling the ERK signaling pathway through a negative feedback loop for MCF-7 cell differentiation.

Mutation of epidermal growth factor receptor is associated with MIG6 expression

Controlled activation of epidermal growth factor receptor (EGFR) is systematically guaranteed at the molecular level; however, aberrant activation of EGFR is frequently found in cancer. Transcription induced by EGFR activation often involves the coordinated expression of genes that positively and negatively regulate the original signaling pathway; therefore, alterations in EGFR kinase activity may reflect changes in gene expression associated with the pathway. In the present study, we investigated transcriptional changes after EGF stimulation with or without the EGFR kinase inhibitor Iressa in H1299 human non‐small‐cell lung cancer cells [parental H1299, H1299 cells that overexpress wild‐type EGFR (EGFR‐WT) and mutant H1299 cells that overexpress EGFR where Leu858 is substituted with Arg (L858R)]. The results obtained clearly demonstrate differences in transcriptional activity in the absence or presence of EGFR kinase activity, with genes sharing the same molecular functions showing distinct expression dynamics. The results show the particular enrichment of EGFR/ErbB signaling‐related genes in a differentially expressed gene set, and significant protein expression of MIG6/RALT(ERRFI1), an EGFR negative regulator, was confirmed in L858R. High MIG6 protein expression was correlated with basal EGFR phosphorylation and inversely correlated with EGF‐induced extracellular signal‐regulated protein kinase phosphorylation levels. Investigation of the NCI‐60 cell lines showed that ERRFI1 expression was correlated with EGFR expression, regardless of tissue type. These results suggest that cells accumulate MIG6 as an inherent negative regulator to suppress excess EGFR activity when basal EGFR kinase activity is considerably high. Taking all the above together, an EGFR mutation can cause transcriptional changes to accommodate the activation potency of the original signaling pathway at the cellular level.

Integrative Genome-Wide Expression Analysis Bears Evidence of Estrogen Receptor-Independent Transcription in Heregulin-Stimulated MCF-7 Cells

Heregulin ß-1 (HRG) is an extracellular ligand that activates mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-OH kinase (PI3K)/Akt signaling pathways through ErbB receptors. MAPK and Akt have been shown to phosphorylate the estrogen receptor (ER) at Ser-118 and Ser-167, respectively, thereby mimicking the effects of estrogenic activity such as estrogen responsive element (ERE)-dependent transcription. In the current study, integrative analysis was performed using two tiling array platforms, comprising histone H3 lysine 9 (H3K9) acetylation and RNA mapping, together with array comparative genomic hybridization (CGH) analysis in an effort to identify HRG-regulated genes in ER-positive MCF-7 breast cancer cells. Through application of various threshold settings, 333 (326 up-regulated and 7 down-regulated) HRG-regulated genes were detected. Prediction of upstream transcription factors (TFs) and pathway analysis indicated that 21% of HRG-induced gene regulation may be controlled by the MAPK cascade, while only 0.6% of the gene expression is controlled by ERE. A comparison with previously reported estrogen (E2)-regulated gene expression data revealed that only 12 common genes were identified between the 333 HRG-regulated (3.6%) and 239 E2-regulated (5.0%) gene groups. However, with respect to enriched upstream TFs, 4 common TFs were identified in the 14 HRG-regulated (28.6%) and 13 E2-regulated (30.8%) gene groups. These results indicated that while E2 and HRG may induce common TFs, the regulatory mechanisms that govern HRG- and E2-induced gene expression differ.

Genome-wide comprehensive analysis of transcriptional regulation by ArgR in Thermus thermophilus

ArgR is known to serve as a repressor/activator of the metabolism of arginine. To elucidate the role of ArgR in the metabolism of Thermus thermophilus cells, comparative genome-wide comprehensive analysis was conducted for wild-type T. thermophilus and its mutant lacking the argR gene. Transcriptome analysis and chromatin affinity precipitation coupled with high-density tiling chip (ChAP-chip) analysis identified 34 genetic loci that are directly regulated by ArgR and indicated that ArgR decreases the expression of arginine biosynthesis and also regulates several other genes involved in amino acid metabolism, including lysine biosynthetic genes, as suggested by our previous study. Among genes whose expression was regulated by ArgR, the largest effect of argR knockout was observed in a putative operon, including genes TTHA0284, TTHA0283, and TTHA0282 involved in arginine biosynthesis. The promoter of this operon, argG, was repressed approximately 21-fold by ArgR. DNase I footprint analysis coupled with electrophoretic mobility shift assay suggested that high arginine-dependent repression was attributed to the fact that the promoter contains three operators for ArgR binding and ArgR is bound to the binding sites cooperatively, possibly forming a DNA loop, in the hexameric form stabilized by arginine binding.

In Silico Simulation of Epidermal Growth Factor Signaling in Prostate Cancer Cells

The epidermal growth factor receptor (EGFR) and its signaling pathways are closely involved in the development and progression of prostate cancer. To understand the EGF-stimulated signaling pathways in prostate cancer cells, we constructed a mathematical model of EGF receptor signaling in PCRV cells based on the experimental data. The model was described by twenty-seven ordinary differential equations, and all parameters were estimated by genetic algorithm. The validity of the model was confirmed with time-course western blot data, showing that the model could successfully reproduce all experimental results.

Genome-wide functional annotation environment for thermus thermophilus in OBIGrid

We developed OBITco (Open BioInfomatics Thermus thermophilus Cyber Outlet) for gene annotation of T. thermophilus HB8 strain. To provide system services for numbers of researchers in the project, we adopted Web based technology and high-level user authentication system with three functions which are rollback function, hierarch representative function and easy-and-systematic annotation. The robust and secure network connection protects the confidential information within the project, thus, researchers can easily access real-time information on DNA sequences, ORF annotations or homology search results. T. thermophilus HB8 possesses 2,195 ORFs, 1156 Intergenic regions, 47 putative tRNA regions, and 6 rRNA regions. BLAST against nr/nt database and InterProScan for all ORFs were used to get homology hit records. The system provides an ORF viewer to show basic information of ORFs and database homology hit records. Researchers can update annotation information of ORF by simple operation, and then new annotation is applied to central database in real-time. Latest information can be utilized for lab experiments such as functional analysis, network analysis and structural analysis. The system can be also utilized as data storage/exchange place for the researchers for everyday experiments.