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Inflammatory Gene Regulatory Networks in Amnion Cells FollowingCytokine Stimulation: Translational Systems Approach to Modeling HumanParturition

机译:羊膜细胞中的炎性基因调控网络细胞因子刺激:建模人类的转化系统方法。分娩

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摘要

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammationgene expression signature. Binding motifs for nuclear factor-κB wereprominent in the gene interaction and regulatory networks for both datasets;however, we found little evidence to support the utilization ofpathogen-associated molecular pattern (PAMP) signaling. The tissue specimenswere also enriched for transcripts governed by hypoxia-inducible factor. Theapproach presented here provides an uncomplicated means to infer globalrelationships among gene clusters involved in cellular responses tolabor-associated signals.
机译:大多数研究人类劳动分子调控的研究都是使用单基因方法进行的。尽管产生多维数据集的技术很容易获得,但是对此类数据进行简便分析的手段仍然有限。这项研究的目的是开发一种系统方法来推断体外控制细胞因子攻击的细胞中全局基因表达的调控机制,并将这些方法应用于预测分娩期间子宫内组织中的基因调控网络(GRN)。为此,将微阵列分析应用于用白介素-1β刺激的人羊膜间充质细胞(AMC),并对差异表达的转录本进行分层聚类,时间表达谱分析和基序富集分析,从而构建了GRN。然后将这些方法应用于在不存在或存在自发足月劳动的情况下收集的胎膜标本。对AMC中细胞因子反应性基因的分析显示出无菌的免疫反应特征,其启动子富含一些与炎症相关的转录因子的反应元件。与胎膜数据集相比,共有34个基因通常被上调,其中许多是急性炎症的一部分基因表达签名。核因子-κB的结合基序为在这两个数据集的基因相互作用和调控网络中都很突出;但是,我们发现几乎没有证据支持利用病原体相关分子模式(PAMP)信号。组织标本还富集了由缺氧诱导因子控制的转录本。的这里介绍的方法提供了一种简单的方法来推断全局细胞应答中涉及的基因簇之间的关系劳动相关信号。

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