Inhibition of cell death in human mammary epithelial cells by the cooked meat-derived carcinogen 2-amino-1-methyl-6-phenylimidazo[4, 5-b]pyridine

2-Amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) is a mammary gland carcinogen present in the human diet in cooked meat. To examine if PhIP and its reactive metabolite N-hydroxy-PhIP inhibit apoptosis in human mammary epithelial MCF-10A cells, confluent cultures deprived of serum and growth factors were incubated for 24 h with either compound. The percentages of dead cells (mean +/- SEM, n = 3) as measured by trypan blue exclusion were 5.7 +/- 0.6, 3.4 +/- 0.3, 2.7 +/- 0.3, and 0.2 +/- 0.003%, in control, 1 microM N-hydroxy-PhIP-, 5 microM N-hydroxy-PhIP-, and 100 microM PhIP-treated dishes, respectively. The expression of Bcl-2 and Bcl-x(L) as quantitated by Western blotting was 1.2- to 1.9-fold higher in the treated groups. PhIP-DNA adducts induced by N-hydroxy-PhIP in MCF-10A cells measured by the (32)P-postlabeling assay were low (<1 x 10(7), relative adduct labeling). No adducts were detected after incubation with PhIP. Western blot analysis indicated that PhIP increased ERK2 phosphorylation concomitant with Bcl-2. The results suggest that the inhibition of cell death in mammary epithelial cells by PhIP occurs independently of PhIP-DNA adducts and may involve enhanced signaling through the MAP kinase pathways.     

Variants in the interleukin-1 alpha and beta genes,and the risk for periodontal disease in dogs

Elevated levels of interleukin-1 (IL-1) have been shown to amplify the inflammatory response against periodontopathogenic bacteria. In humans, polymorphisms in the IL1A and IL1B genes are the most well-studied genetic polymorphisms associated with periodontal disease (PD). In contrast to human, there is a lack of knowledge on the genetic basis of canine PD. A case–control study was conducted in which a molecular analysis of dog IL1A and IL1B genes was performed. Of the eight genetic variants identified, seven in IL1A gene and one in IL1B gene, IL1A/1_g.388A >C and IL1A/1_g.521T >A showed statistically significant differences between groups (adjusted OR (95% CI): 0.15 (0.03–0.76), P= 0.022; 5.76 (1.03–32.1), P= 0.046, respectively). It suggests that in the studied population the IL1A/1_g.388C allele is associated with a decreased PD risk, whereas the IL1A/1_g.521A allele can confer an increased risk. Additionally, the IL1A/2_g.515G >T variation resulted in a change of amino acid, i.e. glycine to valine. In silico analysis suggests that this change can alter protein structure and function, predicting it to be deleterious or damaging. This work suggests that IL1 genetic variants may be important in PD susceptibility in canines.     

Characterization of MHC-I in the blue tit (Cyanistes caeruleus) reveals low levels of genetic diversity and trans-population evolution across European populations

The major histcompatibility complex (MHC) is a vital component of the adaptive immune system in all vertebrates. This study is the first to characterize MHC class I (MHC-I) in blue tits (Cyanistes caeruleus), and we use MHC-I exon 3 sequence data from individuals originating from three locations across Europe: Spain, the Netherlands to Sweden. Our phylogeny of the 17 blue tit MHC-I alleles contains one allele cluster with low nucleotide diversity compared to the remaining more diverse alleles. We found a significant evidence for balancing selection in the peptide-binding region in the diverse allele group only. No separation according to geographic location was found in the phylogeny of alleles. Although the number of MHC-I loci of the blue tit is comparable to that of other passerine species, the nucleotide diversity of MHC-I appears to be much lower than that of other passerine species, including the closely related great tit (Parus major) and the severely inbred Seychelles warbler (Acrocephalus sechellensis). We believe that this initial MHC-I characterization in blue tits provides an important step towards understanding the mechanisms shaping MHC-I diversity in natural populations.     

The promoter of filamentation (POF1) protein from <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis> is an ATPase involved in the protein quality control process

Background

The gene YCL047C, which has been renamed promoter of filamentation gene (POF1), has recently been described as a cell component involved in yeast filamentous growth. The objective of this work is to understand the molecular and biological function of this gene.

Results

Here, we report that the protein encoded by the POF1 gene, Pof1p, is an ATPase that may be part of the Saccharomyces cerevisiae protein quality control pathway. According to the results, Δpof1 cells showed increased sensitivity to hydrogen peroxide, tert-butyl hydroperoxide, heat shock and protein unfolding agents, such as dithiothreitol and tunicamycin. Besides, the overexpression of POF1 suppressed the sensitivity of Δpct1, a strain that lacks a gene that encodes a phosphocholine cytidylyltransferase, to heat shock. In vitro analysis showed, however, that the purified Pof1p enzyme had no cytidylyltransferase activity but does have ATPase activity, with catalytic efficiency comparable to other ATPases involved in endoplasmic reticulum-associated degradation of proteins (ERAD). Supporting these findings, co-immunoprecipitation experiments showed a physical interaction between Pof1p and Ubc7p (an ubiquitin conjugating enzyme) in vivo.

Conclusions

Taken together, the results strongly suggest that the biological function of Pof1p is related to the regulation of protein degradation.

     

Prediction of indirect interactions in proteins

Background  

Both direct and indirect interactions determine molecular recognition of ligands by proteins. Indirect interactions can be defined as effects on recognition controlled from distant sites in the proteins, e.g. by changes in protein conformation and mobility, whereas direct interactions occur in close proximity of the protein's amino acids and the ligand. Molecular recognition is traditionally studied using three-dimensional methods, but with such techniques it is difficult to predict the effects caused by mutational changes of amino acids located far away from the ligand-binding site. We recently developed an approach, proteochemometrics, to the study of molecular recognition that models the chemical effects involved in the recognition of ligands by proteins using statistical sampling and mathematical modelling.