Chemokine and chemokine receptor gene expression in the mesenteric adipose tissue of KKAy mice.

OBJECTIVE: To investigate chemokines and their receptors gene expression in the intra-abdominal adipose tissue of diabetic/obese mice. METHODS: KKAy mice were fed either by a high-fat diet (HFD) or a low-fat diet (LFD) and obese characteristics were analyzed. Various adipose tissues were isolated from HFD-fed obese KKAy mice and from obese controls. We carried out RT-PCR, GeneChip microarray, and real-time PCR analyses on samples derived from the adipose tissues. RESULTS: The HFD-feded obese KKAy mice had the physiological characteristics of obese animal and had increased levels of the transcripts of several chemokine and chemokine receptor genes, such as CCL5, CCL19, CCL25, CXCL10, CXCL13, CCR6, and CCR7, in their intra-abdominal adipose tissue. The strong expression of CCR6 and CCR7 was verified by microarray and quantitative real-time PCR analysis. The HFD increased CCR6 and CCR7 expression only in mesenteric (ME) adipose tissue, not in subcutaneous (SC) adipose tissue. DISCUSSION: Since the enhanced expression of such molecules is likely to contribute to the inflammation in chronic inflammatory disease, our data suggest that the increased levels of CCR6 and CCR7 are involved in the inflammation response in the intra-abdominal adipose tissue of the obese/diabetic mice.

Expression, purification, crystallization, and preliminary X-Ray analysis of the human UDP-glucose dehydrogenase.

UDP-glucose dehydrogenase (UGDH) catalyzes the synthesis of UDP-glucuronic acid from UDP-glucose resulting in the formation of proteoglycans that are involved in promoting normal cellular growth and migration. Overproduction of proteoglycans has been implicated in the progression of certain epithelial cancers. Here, human UGDH (hUGDH) was purified and crystallized from a solution of 0.2 M ammonium sulfate, 0.1 M Na cacodylate, pH 6.5, and 21% PEG 8000. Diffraction data were collected to a resolution of 2.8 A. The crystal belongs to the orthorhombic space group P2(1)2(1)2(1) with unit-cell parameters a = 173.25, b = 191.16, c = 225.94 A, and alpha = beta = gamma = 90.0 degrees. Based on preliminary analysis of the diffraction data, we propose that the biological unit of hUGDH is a tetramer.

A novel hypothesis for the binding mode of HERG channel blockers.

We present a new docking model for HERG channel blockade. Our new model suggests three key interactions such that (1) a protonated nitrogen of the channel blocker forms a hydrogen bond with the carbonyl oxygen of HERG residue T623; (2) an aromatic moiety of the channel blocker makes a pi-pi interaction with the aromatic ring of HERG residue Y652; and (3) a hydrophobic group of the channel blocker forms a hydrophobic interaction with the benzene ring of HERG residue F656. The previous model assumes two interactions such that (1) a protonated nitrogen of the channel blocker forms a cation-pi interaction with the aromatic ring of HERG residue Y652; and (2) a hydrophobic group of the channel blocker forms a hydrophobic interaction with the benzene ring of HERG residue F656. To test these models, we classified 69 known HERG channel blockers into eight binding types based on their plausible binding modes, and further categorized them into two groups based on the number of interactions our model would predict with the HERG channel (two or three). We then compared the pIC(50) value distributions between these two groups. If the old hypothesis is correct, the distributions should not differ between the two groups (i.e., both groups show only two binding interactions). If our novel hypothesis is correct, the distributions should differ between Groups 1 and 2. Consistent with our hypothesis, the two groups differed with regard to pIC(50), and the group having more predicted interactions with the HERG channel had a higher mean pIC(50) value. Although additional work will be required to further validate our hypothesis, this improved understanding of the HERG channel blocker binding mode may help promote the development of in silico predictions methods for identifying potential HERG channel blockers.