Received for publication April 2, 2004.
Revised July 22, 2004.
Accepted for publication July 22, 2004.

Transcriptional Response to Corticotropin-releasing Factor in AtT-20 Cells

Abstract

Corticotropin-releasing factor (CRF) plays a central role in regulation of the hypothalamic-pituitary-adrenal axis, mediating endocrine and behavioral responses to various stressors. Two high affinity receptors for CRF have been described. Although many of the intracellular signaling pathways activated by CRF have been extensively studied, our knowledge of transcriptional responses downstream of the CRF receptor 1 (CRFR1) is still limited. To elucidate gene networks regulated by CRF and CRFR1, we applied microarray technology to explore transcriptional response to CRF stimulation. Therefore mouse pituitary derived AtT-20 cells were continuously exposed to CRF either in the presence or absence of a specific CRFR1 antagonist R121919. Transcriptional responses to different treatments were studied in a time course ranging from 0.5 to 24 hours. Microarray data were analyzed using classical microarray data analysis tools such as correspondence factor analysis, cluster analysis and fold change filtering. Furthermore spectral map analysis was applied, a recently introduced unsupervised multivariate analysis method. A broad and transient transcriptional response to CRF was identified that could be blocked by the antagonist. This way several known CRF-induced target genes and novel CRF responsive genes were identified. These include transcription factors such as cAMP responsive element modulator (CREM, 7X increased), secreted peptides such as cholecystokinin (1.5X) and proteins involved in modulating intracellular signaling, for example regulator of G-protein signaling 2 (Rgs2, 11X). Upregulation of many of these genes can be explained as negative feedback, attenuating CRF activated pathways. Additionally, spectral map analysis proved to be a promising new tool for microarray data analysis.

Key words: Neuropeptides, CRF, CREB, Signaling network analyses, Regulation of gene expression, Anti-depressants, Neuropeptides, peptidases, Peptide hormones