1: J Biol Chem. 2003 May 30;278(22):19723-31. Epub 2003 Mar 18. 

Gene expression profiles and transcription factors involved in parathyroid
hormone signaling in osteoblasts revealed by microarray and bioinformatics.

Qin L, Qiu P, Wang L, Li X, Swarthout JT, Soteropoulos P, Tolias P, Partridge
NC.

Department of Physiology and Biophysics, University of Medicine and Dentistry of
New Jersey-Robert Wood Johnson Medical School, Piscataway 08854, USA.

Parathyroid hormone (PTH) binds to its receptor PTH1R (parathyroid hormone 1
receptor) in osteoblastic cells to regulate bone remodeling and calcium
homeostasis. While prolonged exposure to PTH causes increased bone resorption,
intermittent injections of PTH have an anabolic effect on bone. The molecular
mechanisms regulating these processes are still largely unknown. Here, we
present our results on gene expression profile changes in the PTH-treated
osteoblastic cell line, UMR 106-01, using DNA microarray analysis. A total of
125 known genes and 30 unknown expressed sequence tags (ESTs) were found to have
at least 2-fold expression changes after PTH treatment at 4, 12, and 24 h. 14
genes were previously known to be PTH-regulated but many were unknown to be
regulated by PTH prior to our experiments. Real-time reverse transcriptase-PCR
confirmed that 90 and 50% of the genes are regulated more than 2-fold by PTH in
UMR 106-01 and rat primary osteoblastic cells, respectively. Most genes belong
to the following protein families: hormones, growth factors, and receptors;
signal transduction pathway proteins; transcription factors; proteases;
metabolic enzymes; structural and matrix proteins; transporters; etc. These
results provide a comprehensive and deeper knowledge about PTH regulation of
osteoblastic gene expression. Next, we designed a computational method to
extract information about transcription factors likely involved in regulating
these genes. These factors include those previously known to be involved in PTH
signaling (AP-1 and the cAMP response element-binding protein), those that were
identified by microarray data (C/EBP), and some novel transcription factors
(AP-2, AP-4, SP1, FoxD3, etc.). Our results suggest that a reliable
bioinformatics approach can be easily applied for other systems.

PMID: 12644456 [PubMed - indexed for MEDLINE]


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