Localization and control of expression of VEGF-A and the VEGFR-2 receptor in fetal sheep intestines.

We studied expression of vascular endothelial growth factor A (VEGF-A) and its main receptor, VEGFR-2, in the small intestine from five groups of fetal sheep (each n = 5): 1) preterm controls, 2) term controls, 3) preterm animals where the fetus was infused with cortisol, or 4) saline, and 5) term animals where adrenalectomy had been performed preterm. The main transcript expressed in fetal small intestine was VEGF-A165. Comparing term with preterm animals, there were significantly higher levels of expression of VEGF-A protein (p = 0.005). Levels of VEGF-A protein expression were lower in term adrenalectomized animals (p = 0.01) and were higher in preterm animals infused with cortisol (p = 0.01), compared with their respective control groups. Immunohistochemistry demonstrated strongest expression of VEGF-A protein in the epithelial cells and lamina propria of the villi. Intestinal expression of mRNA encoding the VEGFR-2 receptor did not significantly vary with gestational age. In situ hybridization localized VEGFR-2 to the lamina propria of the villous core and receptor autoradiography using 125I VEGF-A demonstrated binding in the same site. These data show that intestinal VEGF-A is up-regulated with advancing gestation in a glucocorticoid-dependent manner--novel findings consistent with a role for VEGF-A stimulated angiogenesis in preparing the fetal gut for birth.

Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles.

We propose a computational strategy for discovering gene networks affected by a chemical compound. Two kinds of DNA microarray data are assumed to be used: One dataset is short time-course data that measure responses of genes following an experimental treatment. The other dataset is obtained by several hundred single gene knock-downs. These two datasets provide three kinds of information; (i) A gene network is estimated from time-course data by the dynamic Bayesian network model, (ii) Relationships between the knocked-down genes and their regulatees are estimated directly from knock-down microarrays and (iii) A gene network can be estimated by gene knock-down data alone using the Bayesian network model. We propose a method that combines these three kinds of information to provide an accurate gene network that most strongly relates to the mode-of-action of the chemical compound in cells. This information plays an essential role in pharmacogenomics. We illustrate this method with an actual example where human endothelial cell gene networks were generated from a novel time course of gene expression following treatment with the drug fenofibrate, and from 270 novel gene knock-downs. Finally, we succeeded in inferring the gene network related to PPAR-alpha, which is a known target of fenofibrate.

Endothelial cells preparing to die by apoptosis initiate a program of transcriptome and glycome regulation.

The protein-based changes that underlie the cell biology of apoptosis have been extensively studied. In contrast, mRNA- and polysaccharide-based changes have received relatively little attention. We have combined transcriptome and glycome analyses to show that apoptotic endothelial cell cultures undergo programmed changes to RNA transcript abundance and cell surface polysaccharide profiles. Although a few of the transcriptome changes were protective, most appeared to prepare cells for apoptosis by decreasing the reception and transduction of pro-survival signals, increasing pro-death signals, increasing abundance of apoptotic machinery, inhibiting cellular proliferation, recruiting phagocytes to regions of cell death, and promoting phagocytosis. Additional transcriptomal changes appeared to alter the synthesis and modification of cell surface glycosaminoglycans. The resultant reduced abundance of sulphated cell surface glycosaminoglycans may further promote cell death by inhibiting the presentation of extracellular matrix-tethered survival factors to their receptors on dying cells. We propose that the transcriptome and glycome regulation presented here synergize with previously described protein-based changes to guide the apoptotic program.