Glucocorticoid-Driven Transcriptomes in Human Airway Epithelial Cells: Commonalities, Differences and Functional Insight from Cell Lines and Primary Cells

Abstract

RATIONALE Glucocorticoids are stress response hormones that act on the glucocorticoid receptor (GR) to execute effects, including repression of inflammatory gene expression. The molecular mechanisms for this process are still elusive, indeed controversial. This is, to a large extent, due the knowledge gap in understanding the functional impacts of the key glucocorticoid‐modulated genes in relevant tissues. Identification of such genes may be problematic because the effects of glucocorticoids on gene expression are context‐dependent and show variable effects between different cell types. This confounds the identification of key gene expression features within the glucocorticoid‐response. The current study addresses this by comparing the glucocorticoid‐driven transcriptomes in 3 variants of human airway epithelial cells, a critical player in airway inflammation and physiological responses to glucocorticoid. These include two airway epithelial cell lines, pulmonary type II A549 and bronchial epithelial BEAS‐2B cells, and primary human bronchial epithelial (HBE) cells. METHODS Gene expression profiling of RNA extracted from A549, BEAS‐2B and HBE cells following budesonide treatment for 6 h was performed using Affymetrix PrimeView microarrays. Genes showing significant induction (fold ≥ 2, P ≤ 0.05) or repression (fold ≤ 0.5, P ≤ 0.05) compared to untreated cells, in any of the cell types were used for further analyses. Representative genes were validated using qPCR. Gene ontology and Ingenuity Pathway Analysis (IPA) were performed using differentially regulated genes in each cell variant. RESULTS Using stringent (fold ≥ 2 or ≤ 0.5, P ≤ 0.05) cutoff criteria, only 17 and 8 of genes induced or repressed, respectively, by glucocorticoid were common to all 3 epithelial cell variants. While a major fraction of the significantly modulated genes was apparently unique to each cell variant, hierarchical clustering revealed greater commonality than was suggested by the stringent cut‐off. Applying less stringent cut‐offs (fold ≥ 1.25 or ≤ 0.8) within the pool of genes identified by stringent cut‐off revealed 93 induced and 82 repressed genes that were in common among all 3 cell variants. Validation of 52 budesonide‐induced genes using qPCR confirmed, for most of the genes, the grouping scheme determined by applying the less stringent cut‐off. Gene ontology (GO) analysis of the genes induced in common showed enrichment of transcriptional control, proliferation/apoptosis and signaling terms. Equally, the GO term growth factor activity was profoundly enriched with budesonide‐repressed genes across all variants. CONCLUSIONS The current comparative transcriptome analysis revealed a surprisingly large variance among 3 variants of airway epithelial cells in response to glucocorticoids. Despite this, the common gene expression features obtained by such analysis represent unbiased listing of potentially key molecular players in glucocorticoid response. While many of these genes, and the associated pathways, are consistent with anti‐infl...

Genomic determinants implicated in the glucocorticoid-mediated induction of KLF9 in pulmonary epithelial cells

“…Krüppel-Like Factor 9 (KLF9), along with 16 other genes, was significantly induced (≥2-fold, P ≤ 0.05) by glucocorticoids in 3 different variants of human pulmonary epithelial cells (8). Such "in common" regulation for KLF9 by glucocorticoids has also been reported in other cell types or tissues.…”

“…Upon ligand binding, GR translocates from the cytoplasm to the nucleus, where it is recruited to thousands of genomic loci and regulates the expression of hundreds of genes (5)(6)(7). Several studies show that the glucocorticoid-dependent recruitment of GR to genomic loci and subsequent regulation of gene expression varies between different tissues, cells types and cell lines, and is therefore highly contextdependent (8)(9)(10)(11)(12)(13).…”

“…Nevertheless, many glucocorticoid-induced genes respond to glucocorticoids in a similar fashion regardless of the cell line, type or tissue of origin (8,10,14). While presumably such genes possess genomic characteristics, or features, that are conserved, i.e.…”

“…Airway epithelial cells are not only critical in the pathogenesis of asthma, but also represent key effector cells in mediating therapeutic responses to glucocorticoids in dampening airway and lung inflammation (39,40). The current study therefore takes advantage of the established "in common" glucocorticoid regulation of KLF9 in primary human bronchial epithelial cells (HBE) and both alveolar type II (A549) and bronchial (BEAS-2B) epithelial cell lines (8,14). These cell lines represent well-studied human models, for which high-quality genomic data exists (5,19,20,24,26,27), and are here used to explore genomic features that may impact on the GR-mediated expression of KLF9 in therapeutically relevant cells.…”

scGCN: a Graph Convolutional Networks Algorithm for Knowledge Transfer in Single Cell Omics

“…The fast advance of single-cell technologies leads to the rapid growth of single cell omics data. As 42 more and more single-cell data becomes available, there is an urgent need to leverage existing data 43 with the newly generated data in a reliable and reproducible way, learning from the established 44 single-cell data with well-defined labels as reference, and transferring labels to new datasets to 45 assign cell-level annotations [10,11]. However, existing datasets and new datasets are often 46 collected from different tissues and species [14,15], under various experimental conditions, 47 generated by different platforms [16,17], and in the form of different omics types [18].…”