Polyunsaturated fatty acids and signalling via phospholipase C-β and A2 in myocardium

Dietary n-6 and n-3 polyunsaturated fatty acids (PUFAs) have potent biological effects on the blood(cells), the vasculature and the myocardium. In the epidemiological studies in which the benefit from the regular ingestion of n-3 PUFAs was reported, the responsible mechanisms remain obscure. A great deal of the PUFA-effect can be explained by the known interference with the eicosanoid metabolism. Many processes, believed to be involved in atherogenesis such as adhesion and infiltration of bloodcells (in)to the vasculature, platelet aggregation, secretion of endothelium-derived factors and mitogenic responses of vascular smooth muscle cells are partially mediated by receptor-activated phospholipases C- and A₂. As PUFAs take part at many steps of the signalling pathways, the latter could represent important action sites to beneficially interfere with atherogenesis. In this brief review, we have discussed the results of studies on the influence of alteration of PUFA composition of the membrane phospholipids or of exogenously administered non-esterified PUFAs on phospholipid signalling. For convenience, we have mainly focused our discussion on those studies available on the myocardium. By changing the PUFA composition of the phospholipids, the endogenous substrates for the membrane-associated phospholipase C- and A₂ are changed. This is accompanied by changes in their hydrolytic action on these substrates resulting in altered products (the molecular species of 1,2-diacylglycerols and the non-esterified PUFAs) which on their turn evoke changes in events downstream of the signalling cascades: activation of distinct protein kinase C isoenzymes, formation of distinct eicosanoids and non-esterified PUFA effects on Ca ²⁺ channels. It has also become more clear that the membrane physicochemical properties, in terms of fluidity and cholesterol content of the bilayer, might undergo changes due to altered PUFA incorporation into the membrane phospholipids. The latter effects could have consequences for the receptor functioning, receptor-GTP-binding protein coupling, GTP-binding protein-phospholipase C- or A₂ coupling as well. It should be noted that most of these studies have been carried out with cardiomyocytes isolated from hearts of animals on PUFA diet or incubation of cultured cardiomyocytes with non-esterified PUFAs in the presence of albumin. Studies need to be performed to prove that the PUFA-diet induced modulations of the phospholipid signalling reactions do occur in vivo and that these effects are involved in the mechanism of beneficial effects of dietary PUFAs on the process of atherosclerosis.     

An Inhibitor-Based Method To Measure Initial Decomposition of Naturally Occurring Polysaccharides in Sediments

A method that can be used to measure the initial decomposition rates of polysaccharides in sediment samples was developed. It uses toluene to specifically inhibit microbial uptake of carbohydrates without affecting extracellular hydrolysis of polysaccharides. Accumulating carbohydrates were determined by high-performance liquid chromatography. Field-sampled litter from the common reed (Phragmites australis), which contains cellulose and arabinoxylan as its main polysaccharides, was used as a model system. Toluene concentrations of between 1 and 10% resulted in the accumulation of similar amounts of monomeric carbohydrates, which was linear over time for most neutral sugars. Toluene (3%) did not have an effect on extracellular enzyme activities, and microbial sugar uptake was completely inhibited, as demonstrated with (sup14)C-labelled xylose and glucose. Experiments with enhancement cultures and fixed reed litter suggested that enzymatic hydrolysis of polysaccharides in reed litter was the main source of glucose, xylose, arabinose, and galactose accumulation. In contrast, the accumulation of high amounts of the alditols mannitol and glucitol was probably caused by lysis of the microbial population in toluene-treated reed litter. Glucose accumulated at rates of 1.3 and 0.10 (mu)mol (middot) g of dry matter content(sup-1) (middot) h(sup-1) under aerobic and anaerobic conditions, respectively, whereas xylose accumulation rates were only 10% of the glucose accumulation rates.     

Maize endosperm ADP-glucose pyrophosphorylase SHRUNKEN2 and BRITTLE2 subunit interactions

ADP-glucose pyrophosphorylase (AGP) represents a key regulatory step in polysaccharide synthesis in organisms ranging from bacteria to plants. Higher plant AGPs are complex in nature and are heterotetramers consisting of two similar but distinct subunits. How the subunits are assembled into enzymatically active polymers is not yet understood. Here, we address this issue by using naturally occurring null mutants of the Shrunken2 (Sh2) and Brittle2 (Bt2) loci of maize as well as the yeast two-hybrid expression system. In the absence of the maize endosperm large AGP subunit (SH2), the BT2 subunit remains as a monomer in the developing endosperm. In contrast, the SH2 protein, in the absence of BT2, is found in a complex of 100 kD. A direct interaction between SH2 and BT2 was proven when they were both expressed in yeast. Several motifs are essential for SH2:BT2 interaction because truncations removing the N or C terminus of either subunit eliminate SH2:BT2 interactions. Analysis of subunit interaction mutants (sim) also identified motifs essential for protein interactions.     

Modulation of the Maladaptive Stress Response to Manage Diseases of Protein Folding

Diseases of protein folding arise because of the inability of an altered peptide sequence to properly engage protein homeostasis components that direct protein folding and function. To identify global principles of misfolding disease pathology we examined the impact of the local folding environment in alpha-1-antitrypsin deficiency (AATD), Niemann-Pick type C1 disease (NPC1), Alzheimer''s disease (AD), and cystic fibrosis (CF). Using distinct models, including patient-derived cell lines and primary epithelium, mouse brain tissue, and Caenorhabditis elegans, we found that chronic expression of misfolded proteins not only triggers the sustained activation of the heat shock response (HSR) pathway, but that this sustained activation is maladaptive. In diseased cells, maladaptation alters protein structure–function relationships, impacts protein folding in the cytosol, and further exacerbates the disease state. We show that down-regulation of this maladaptive stress response (MSR), through silencing of HSF1, the master regulator of the HSR, restores cellular protein folding and improves the disease phenotype. We propose that restoration of a more physiological proteostatic environment will strongly impact the management and progression of loss-of-function and gain-of-toxic-function phenotypes common in human disease.     

Antagonistic sensory cues generate gustatory plasticity in Caenorhabditis elegans

Caenorhabditis elegans shows chemoattraction to 0.1-200 mM NaCl, avoidance of higher NaCl concentrations, and avoidance of otherwise attractive NaCl concentrations after prolonged exposure to NaCl (gustatory plasticity). Previous studies have shown that the ASE and ASH sensory neurons primarily mediate attraction and avoidance of NaCl, respectively. Here we show that balances between at least four sensory cell types, ASE, ASI, ASH, ADF and perhaps ADL, modulate the response to NaCl. Our results suggest that two NaCl-attraction signalling pathways exist, one of which uses Ca(2+)/cGMP signalling. In addition, we provide evidence that attraction to NaCl is antagonised by G-protein signalling in the ASH neurons, which is desensitised by the G-protein-coupled receptor kinase GRK-2. Finally, the response to NaCl is modulated by G-protein signalling in the ASI and ADF neurons, a second G-protein pathway in ASH and cGMP signalling in neurons exposed to the body fluid.     

Comparison of methods for analysis of selective genotyping survival data

Survival traits and selective genotyping datasets are typically not normally distributed, thus common models used to identify QTL may not be statistically appropriate for their analysis. The objective of the present study was to compare models for identification of QTL associated with survival traits, in particular when combined with selective genotyping. Data were simulated to model the survival distribution of a population of chickens challenged with Marek disease virus. Cox proportional hazards (CPH), linear regression (LR), and Weibull models were compared for their appropriateness to analyze the data, ability to identify associations of marker alleles with survival, and estimation of effects when all individuals were genotyped (full genotyping) and when selective genotyping was used. Little difference in power was found between the CPH and the LR model for low censoring cases for both full and selective genotyping. The simulated data were not transformed to follow a Weibull distribution and, as a result, the Weibull model generally resulted in less power than the other two models and overestimated effects. Effect estimates from LR and CPH were unbiased when all individuals were genotyped, but overestimated when selective genotyping was used. Thus, LR is preferred for analyzing survival data when the amount of censoring is low because of ease of implementation and interpretation. Including phenotypic data of non-genotyped individuals in selective genotyping analysis increased power, but resulted in LR having an inflated false positive rate, and therefore the CPH model is preferred for this scenario, although transformation of the data may also make the Weibull model appropriate for this case. The results from the research presented herein are directly applicable to interval mapping analyses.     

Genomic Selection Using Low-Density Marker Panels

Genomic selection (GS) using high-density single-nucleotide polymorphisms (SNPs) is promising to improve response to selection in populations that are under artificial selection. High-density SNP genotyping of all selection candidates each generation, however, may not be cost effective. Smaller panels with SNPs that show strong associations with phenotype can be used, but this may require separate SNPs for each trait and each population. As an alternative, we propose to use a panel of evenly spaced low-density SNPs across the genome to estimate genome-assisted breeding values of selection candidates in pedigreed populations. The principle of this approach is to utilize cosegregation information from low-density SNPs to track effects of high-density SNP alleles within families. Simulations were used to analyze the loss of accuracy of estimated breeding values from using evenly spaced and selected SNP panels compared to using all high-density SNPs in a Bayesian analysis. Forward stepwise selection and a Bayesian approach were used to select SNPs. Loss of accuracy was nearly independent of the number of simulated quantitative trait loci (QTL) with evenly spaced SNPs, but increased with number of QTL for the selected SNP panels. Loss of accuracy with evenly spaced SNPs increased steadily over generations but was constant when the smaller number individuals that are selected for breeding each generation were also genotyped using the high-density SNP panel. With equal numbers of low-density SNPs, panels with SNPs selected on the basis of the Bayesian approach had the smallest loss in accuracy for a single trait, but a panel with evenly spaced SNPs at 10 cM was only slightly worse, whereas a panel with SNPs selected by forward stepwise selection was inferior. Panels with evenly spaced SNPs can, however, be used across traits and populations and their performance is independent of the number of QTL affecting the trait and of the methods used to estimate effects in the training data and are, therefore, preferred for broad applications in pedigreed populations under artificial selection.     

A gene frequency model for QTL mapping using Bayesian inference

Background

Information for mapping of quantitative trait loci (QTL) comes from two sources: linkage disequilibrium (non-random association of allele states) and cosegregation (non-random association of allele origin). Information from LD can be captured by modeling conditional means and variances at the QTL given marker information. Similarly, information from cosegregation can be captured by modeling conditional covariances. Here, we consider a Bayesian model based on gene frequency (BGF) where both conditional means and variances are modeled as a function of the conditional gene frequencies at the QTL. The parameters in this model include these gene frequencies, additive effect of the QTL, its location, and the residual variance. Bayesian methodology was used to estimate these parameters. The priors used were: logit-normal for gene frequencies, normal for the additive effect, uniform for location, and inverse chi-square for the residual variance. Computer simulation was used to compare the power to detect and accuracy to map QTL by this method with those from least squares analysis using a regression model (LSR).

Results

To simplify the analysis, data from unrelated individuals in a purebred population were simulated, where only LD information contributes to map the QTL. LD was simulated in a chromosomal segment of 1 cM with one QTL by random mating in a population of size 500 for 1000 generations and in a population of size 100 for 50 generations. The comparison was studied under a range of conditions, which included SNP density of 0.1, 0.05 or 0.02 cM, sample size of 500 or 1000, and phenotypic variance explained by QTL of 2 or 5%. Both 1 and 2-SNP models were considered. Power to detect the QTL for the BGF, ranged from 0.4 to 0.99, and close or equal to the power of the regression using least squares (LSR). Precision to map QTL position of BGF, quantified by the mean absolute error, ranged from 0.11 to 0.21 cM for BGF, and was better than the precision of LSR, which ranged from 0.12 to 0.25 cM.

Conclusions

In conclusion given a high SNP density, the gene frequency model can be used to map QTL with considerable accuracy even within a 1 cM region.