A series of recent studies on large-scale networks of signaling and metabolic systems revealed that a certain network structure often called “bow-tie network” are observed. In signaling systems, bow-tie network takes a form with diverse and redundant inputs and outputs connected via a small numbers of core molecules. While arguments have been made that such network architecture enhances robustness and evolvability of biological systems, its functional role at a cellular level remains obscure. A hypothesis was proposed that such a network function as a stimuli-reaction classifier where dynamics of core molecules dictate downstream transcriptional activities, hence physiological responses against stimuli. In this study, we examined whether such hypothesis can be verified using experimental data from Alliance for Cellular Signaling (AfCS) that comprehensively measured GPCR related ligands response for B-cell and macrophage. In a GPCR signaling system, cAMP and Ca2+ act as core molecules. Stimuli-response for 32 ligands to B-Cells and 23 ligands to macrophages has been measured. We found that ligands with correlated changes of cAMP and Ca2+ tend to cluster closely together within the hyperspaces of both cell types and they induced genes involved in the same cellular processes. It was found that ligands inducing cAMP synthesis activate genes involved in cell growth and proliferation; cAMP and Ca2+ molecules that increased together form a feedback loop and induce immune cells to migrate and adhere together. In contrast, ligands without a core molecules response are scattered throughout the hyperspace and do not share clusters. G-protein coupling receptors together with immune response specific receptors were found in cAMP and Ca2+ activated clusters. Analyses have been done on the original software applicable for discovering ‘bow-tie’ network architectures within the complex network of intracellular signaling where ab initio clustering has been implemented as well. Groups of potential transcription factors for each specific group of genes were found to be partly conserved across B-Cell and macrophage. A series of findings support the hypothesis.
Alpha-arbutin (4-hydroxyphenyl alpha-glucopyranoside) is a known inhibitor of tyrosinase in keratinocytes; however, its effect on other genes and pathways in other skin cells has not been thoroughly investigated. In this study, we investigate the mechanism of alpha-arbutin activity in human dermal fibroblast cultures for 48 h. Results showed that the oxidative stress pathway was activated as alpha-arbutin reduced reactive oxygen species. In addition, we found a high possibility of wound healing and the upregulation of the insulin-like growth factor 1 receptor (IFG1R) pathway. We also investigated the role of the NRF2 gene in mediating the alpha-arbutin response. In silico comparative genomics analysis conducted using our original tool, SHOE, suggested transcription factors with a role in tumor suppression and toxicity response as candidates for regulating the alpha-arbutin–mediated pathway.
The identification of cis-elements (motifs) in the regulatory regions of higher eukaryotes is an important and challenging problem in computational biology. Eukaryotic transcriptional regulatory mechanisms pose several difficulties for promoter analysis: including a high variance in the motif locations, frequently large divergence from motif consensus patterns, and a large amount of repetitive elements (confusing to many motif finding procedures). One promising approach to this difficult problem involves cross-species comparison. In this work we analyzed the full-length regulatory regions of genes involved in the G-protein coupling MAP kinase pathway and compared the results with ribosomal genes using human, mouse and rat genomic data. We found 19 high likely transcription factors (TFs) candidates for MAPK and 12 TFs for the ribosomal dataset. In the case of the MAPK dataset, regulatory regions of genes functionally grouped as receptors and MAP-core genes were found mostly highly conserved across the three species.
Transcription factor-based reprogramming reverts adult cells to an embryonic state, yielding potential for generating different tissue types. However, recent reports indicated the substantial differences in pattern of gene expression between induced pluripotent stem (iPS) cells and embryonic stem cells (ESC). In this study, we compare gene expression signatures of different iPS and ES cell lines and relate expression profiles of differently expressed genes to their expression status in somatic cells. As a result, we discovered that genes resistant to reprogramming comprise two major clusters, which are reprogramming dependent “Induced Genes” and somatic origin “Inherited Genes,” both exhibiting preferences in methylation marks. Closer look into the Induced Genes by means of the transcription regulation analysis predicted several groups of genes with various roles in reprogramming and transcription factor DNA binding model. We believe that our results are a helpful source for biologists for further improvement of iPS cell technology.
The mammalian target of rapamycine (mTOR) pathway is a key regulator of cellular growth, development, and ageing, and unraveling its control is essential for understanding life and death of biological organisms. A motif-discovery workbench including nine tools was used to identify transcription factors involved in five basic (Insulin, MAPK, VEGF, Hypoxia, and mTOR core) activities of the mTOR pathway. Discovered transcription factors are classified as “process-specific” or “pathway-ubiquitous” with highlights toward their regulating/regulated activities within the mTOR pathway. Our transcription regulation results will facilitate further research on investigating the control mechanism in mTOR pathway.
Components of fish roe possess antioxidant and antiaging activities, making them potentially very beneficial natural resources. Here, we investigated chum salmon eggs (CSEs) as a source of active ingredients, including vitamins, unsaturated fatty acids, and proteins. We incubated human dermal fibroblast cultures for 48 hours with high and low concentrations of CSE extracts and analyzed changes in gene expression. Cells treated with CSE extract showed concentration-dependent upregulation of collagen type I genes and of multiple antioxidative genes, including OXR1, TXNRD1, and PRDX family genes. We further conducted in silico phylogenetic footprinting analysis of promoter regions. These results suggested that transcription factors such as acute myeloid leukemia-1a and cyclic adenosine monophosphate response element-binding protein may be involved in the observed upregulation of antioxidative genes. Our results support the idea that CSEs are strong candidate sources of antioxidant materials and cosmeceutically effective ingredients.
BackgroundMicroarray and DNA-sequencing based technologies continue to produce enormous amounts of data on gene expression. This data has great potential to illuminate our understanding of biology and medicine, but the data alone is of limited value without computational tools to allow human investigators to visualize and interpret it in the context of their problem of interest.ResultsWe created a web server called SHOE that provides an interactive, visual presentation of the available evidence of transcriptional regulation and gene co-expression to facilitate its exploration and interpretation. SHOE predicts the likely transcription factor binding sites in orthologous promoters of humans, mice, and rats using the combined information of 1) transcription factor binding preferences (position-specific scoring matrix (PSSM) libraries such as Transfac32, Jaspar, HOCOMOCO, ChIP-seq, SELEX, PBM, and iPS-reprogramming factor), 2) evolutionary conservation of putative binding sites in orthologous promoters, and 3) co-expression tendencies of gene pairs based on 1,714 normal human cells selected from the Gene Expression Omnibus Database.ConclusionSHOE enables users to explore potential interactions between transcription factors and target genes via multiple data views, discover transcription factor binding motifs on top of gene co-expression, and visualize genes as a network of gene and transcription factors on its native gadget GeneViz, the CellDesigner pathway analyzer, and the Reactome database to search the pathways involved. As we demonstrate here when using the CREB1 and Nf-κB datasets, SHOE can reliably identify experimentally verified interactions and predict plausible novel ones, yielding new biological insights into the gene regulatory mechanisms involved. SHOE comes with a manual describing how to run it on a local PC or via the Garuda platform (www.garuda-alliance.org), where it joins other popular gadgets such as the CellDesigner pathway analyzer and the Reactome database, as part of analysis workflows to meet the growing needs of molecular biologists and medical researchers. SHOE is available from the following URL http://ec2-54-150-223-65.ap-northeast-1.compute.amazonaws.comA video demonstration of SHOE can be found here: https://www.youtube.com/watch?v=qARinNb9NtEElectronic supplementary materialThe online version of this article (10.1186/s12864-018-5101-3) contains supplementary material, which is available to authorized users.
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