title: Inflammatory gene regulatory networks in amnion cells following cytokine stimulation: translational systems approach to modeling human parturition.
abstract: 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 inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals.
authors.affiliation: Division of Maternal-Fetal Medicine and Laboratory of Perinatal Research, Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio, United States of America.
authors.forename: Ruth
authors.initials: R
authors.lastname: Li
authors.forename: William E
authors.initials: WE
authors.lastname: Ackerman
authors.forename: Taryn L
authors.initials: TL
authors.lastname: Summerfield
authors.forename: Lianbo
authors.initials: L
authors.lastname: Yu
authors.forename: Parul
authors.initials: P
authors.lastname: Gulati
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
authors.forename: Kun
authors.initials: K
authors.lastname: Huang
authors.forename: Roberto
authors.initials: R
authors.lastname: Romero
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Kniss
mesh_terms: D000650:Amnion / Q000166:cytology / Q000378:metabolism*; D001665:Binding Sites / Q000235:genetics; D002478:Cells, Cultured; D016000:Cluster Analysis; D016207:Cytokines / Q000494:pharmacology*; D005260:Female; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks / Q000187:drug effects*; D006801:Humans; D007249:Inflammation / Q000235:genetics*; D053583:Interleukin-1beta / Q000494:pharmacology; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D036801:Parturition / Q000235:genetics; D011247:Pregnancy; D011248:Pregnancy Complications / Q000235:genetics; D020133:Reverse Transcriptase Polymerase Chain Reaction; D015398:Signal Transduction / Q000235:genetics; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D016207:Cytokines; D053583:Interleukin-1beta; D014157:Transcription Factors