Effect of dietary cis and trans fatty acids on serum lipoprotein[a] levels in humans.

Serum lipoprotein[a] (Lp[a]) is a strong risk factor for coronary heart disease. We therefore examined the effect of dietary fatty acid composition on serum Lp[a] levels in three strictly controlled experiments with healthy normocholesterolemic men and women. In Expt. I, 58 subjects consumed a control diet high in saturated fatty acids for 17 days. For the next 36 days, 6.5% of total energy intake from saturated fatty acids was replaced by monounsaturates plus polyunsaturates (monounsaturated fatty acid diet; n = 29) or by polyunsaturates alone (polyunsaturated fatty acid diet; n = 29). Both diets caused a slight, nonsignificant, increase in median Lp[a] levels, with no difference between diets. In Expt. II, 10% of energy from the cholesterol-raising saturated fatty acids (lauric, myristic, and palmitic acid) was replaced by oleic acid or by trans-monounsaturated fatty acids. Each of the 59 participants received each diet for 3 weeks in random order. The median level of Lp[a] was 26 mg/l on the saturated fatty acid diet; it increased to 32 mg/l (P less than 0.020) on the oleic acid diet and to 45 mg/l (P less than 0.001) on the trans-fatty acid diet. The difference in Lp[a] between the trans-fatty acid and the oleic acid diets was also highly significant (P less than 0.001). Expt. III involved 56 subjects; all received 8% of energy from stearic acid, from linoleic acid, or from trans-monounsaturates, for 3 weeks each. All other nutrients were equal.(ABSTRACT TRUNCATED AT 250 WORDS)     

Specificity of RepC protein in plasmid pT181 DNA replication

The plasmid pT181 of Staphylococcus aureus consists of 4437 base pairs and encodes resistance to tetracycline. Initiation of pT181 DNA replication specifically requires the plasmid-encoded initiator protein, RepC. The initiator protein binds specifically to a 32-base pair sequence within the pT181 origin of replication. RepC protein also has a nicking-closing activity that is specific for the pT181 origin. Replication of pT181 initiates by covalent extension of the nick and proceeds by a rolling circle mechanism. Two other small, multicopy plasmids pC221 and pS194 belong to the pT181 family and have common structural organization and replication properties. The replication proteins and replication origins of these plasmids have extensive sequence homologies, although they belong to different incompatibility groups. In spite of this homology, the replication proteins and replication origins of these three plasmids do not show any cross-reactivity in vivo. We have carried out a series of in vitro experiments to determine the specificity of pT181-encoded initiator protein, RepC. DNA binding experiments showed that although the binding of RepC to the pT181 origin was very efficient, little or no binding was seen with pC221 and pS194 origins. The nicking-closing activity of RepC was found to be equally efficient with the pC221 and pS194 plasmids. The plasmids pC221 and pS194 replicated efficiently in a RepC-dependent in vitro system. However, replication of these plasmids was greatly reduced in the presence of a competing pT181 origin. The results presented here suggest that nicking-closing by RepC at the origin is not sufficient for maximal replication and that tight binding of RepC to the origin plays an important role in the initiation of DNA replication.     

Effect of consumption of phenols from olives and extra virgin olive oil on LDL oxidizability in healthy humans

A high intake of olive oil has been proposed as an explanation for the low incidence of coronary heart disease in Mediterranean countries, but it is unclear whether olive oil offers specific benefits beyond a low content of saturated fat. Some types of extra virgin olive oil are rich in non-polar phenols, which might be taken up by plasma LDL particles and protect these from becoming atherogenic by oxidative modification. In a pilot study we found that consumption of 47 g fortified olive oil containing 31 mg phenols significantly increased the lag time of LDL oxidation from 112 ± 5 min before to 130 ± 7 min 2h after the meal. However, this study was not controlled, and in the current study we therefore investigated whether olive oil phenols increase the lag time of LDL oxidation in postprandial samples when compared with a control group.

Twelve healthy men and women consumed four different olive oil supplements with a meal on four separate occasions: one similar to the supplement in the pilot study (positive control); one containing mainly non-polar olive oil phenols; one containing mainly polar olive oil phenols; and one without phenols (placebo). Lag time significantly increased 2 h after the meals with the positive control (8 ± 2 min), the polar phenols (8 ± 2 min), and the placebo (8 ± 2 min), but not after the non-polar phenols (-0.4 ± 3 min). Increases were not statistically different between supplements.

These results indicate that the lag time of LDL-oxidation is increased after consumption of a meal. This increase is probably due to non-specific meal or time effects and not to phenols from olives or olive oil. Furthermore, these findings stress the need for adequate controlled studies to avoid misinterpretations of the data.     

Coupling of M3 Acetylcholine Receptor to Gq16 Activates a Natriuretic Peptide Receptor Guanylyl Cyclase

Muscarinic activation of tracheal smooth muscle (TSM) involves a M₃AChR/heterotrimeric-G protein/NPR-GC coupling mechanism. G protein activators Mastoparan (MAS) and Mastoparan-7 stimulated 4- and 10-fold the NPR-GC respectively, being insensitive to PTX and antibodies against Gα_i/o subfamily. Muscarinic and MAS stimulation of NPR-GC was blocked by antibodies against C-terminal of Gα_q16, whose expression was confirmed by RT-PCR. However, synthetic peptides from C-terminal of Gα_q15/16 stimulated the NPR-GC. Coupling of α_q16 to M₃AChR is supported by MAS decreased [³H]QNB binding, being abolished after M₃AChR-4-DAMP-alkylation. Anti-i₃M₃AChR antibodies blocked the muscarinic activation of NPR-GC, and synthetic peptide from i₃M₃AChR (M₃P) was more potent than MAS increasing GTPγ [³⁵S] and decreasing the [³H]QNB activities. Coupling between NPR-GC and Gα_q16 was evaluated by using trypsin-solubilized-fraction from TSM membranes, which displayed a MAS-sensitive-NPR-GC activity, being immunoprecipitated with anti-Gα_q16, also showing an immunoreactive heterotrimeric-G-β -subunit. These data support the existence of a novel transducing cascade, involving Gα_q16β γ coupling M₃AChR to NPR-GC.     

A holistic high-throughput screening framework for biofuel feedstock assessment that characterises variations in soluble sugars and cell wall composition in <Emphasis Type="Italic">Sorghum bicolor</Emphasis>

Background

A major hindrance to the development of high yielding biofuel feedstocks is the ability to rapidly assess large populations for fermentable sugar yields. Whilst recent advances have outlined methods for the rapid assessment of biomass saccharification efficiency, none take into account the total biomass, or the soluble sugar fraction of the plant. Here we present a holistic high-throughput methodology for assessing sweet Sorghum bicolor feedstocks at 10 days post-anthesis for total fermentable sugar yields including stalk biomass, soluble sugar concentrations, and cell wall saccharification efficiency.

Results

A mathematical method for assessing whole S. bicolor stalks using the fourth internode from the base of the plant proved to be an effective high-throughput strategy for assessing stalk biomass, soluble sugar concentrations, and cell wall composition and allowed calculation of total stalk fermentable sugars. A high-throughput method for measuring soluble sucrose, glucose, and fructose using partial least squares (PLS) modelling of juice Fourier transform infrared (FTIR) spectra was developed. The PLS prediction was shown to be highly accurate with each sugar attaining a coefficient of determination (R ² ) of 0.99 with a root mean squared error of prediction (RMSEP) of 11.93, 5.52, and 3.23 mM for sucrose, glucose, and fructose, respectively, which constitutes an error of <4% in each case. The sugar PLS model correlated well with gas chromatography–mass spectrometry (GC-MS) and brix measures. Similarly, a high-throughput method for predicting enzymatic cell wall digestibility using PLS modelling of FTIR spectra obtained from S. bicolor bagasse was developed. The PLS prediction was shown to be accurate with an R ² of 0.94 and RMSEP of 0.64 μg.mgDW^-1.h^-1.

Conclusions

This methodology has been demonstrated as an efficient and effective way to screen large biofuel feedstock populations for biomass, soluble sugar concentrations, and cell wall digestibility simultaneously allowing a total fermentable yield calculation. It unifies and simplifies previous screening methodologies to produce a holistic assessment of biofuel feedstock potential.

     

Prospective identification, isolation by flow cytometry, and in vivo self-renewal of multipotent mammalian neural crest stem cells

Multipotent and self-renewing neural stem cells have been isolated in culture, but equivalent cells have not yet been prospectively identified in neural tissue. Using cell surface markers and flow cytometry, we have isolated neural crest stem cells (NCSCs) from mammalian fetal peripheral nerve. These cells are phenotypically and functionally indistinguishable from NCSCs previously isolated by culturing embryonic neural tube explants. Moreover, in vivo BrdU labeling indicates that these stem cells self-renew in vivo. NCSCs freshly isolated from nerve tissue can be directly transplanted in vivo, where they generate both neurons and glia. These data indicate that neural stem cells persist in peripheral nerve into late gestation by undergoing self-renewal. Such persistence may explain the origins of some PNS tumors in humans.     

Impact of QTL properties on the accuracy of multi-breed genomic prediction

Background

Although simulation studies show that combining multiple breeds in one reference population increases accuracy of genomic prediction, this is not always confirmed in empirical studies. This discrepancy might be due to the assumptions on quantitative trait loci (QTL) properties applied in simulation studies, including number of QTL, spectrum of QTL allele frequencies across breeds, and distribution of allele substitution effects. We investigated the effects of QTL properties and of including a random across- and within-breed animal effect in a genomic best linear unbiased prediction (GBLUP) model on accuracy of multi-breed genomic prediction using genotypes of Holstein-Friesian and Jersey cows.

Methods

Genotypes of three classes of variants obtained from whole-genome sequence data, with moderately low, very low or extremely low average minor allele frequencies (MAF), were imputed in 3000 Holstein-Friesian and 3000 Jersey cows that had real high-density genotypes. Phenotypes of traits controlled by QTL with different properties were simulated by sampling 100 or 1000 QTL from one class of variants and their allele substitution effects either randomly from a gamma distribution, or computed such that each QTL explained the same variance, i.e. rare alleles had a large effect. Genomic breeding values for 1000 selection candidates per breed were estimated using GBLUP modelsincluding a random across- and a within-breed animal effect.

Results

For all three classes of QTL allele frequency spectra, accuracies of genomic prediction were not affected by the addition of 2000 individuals of the other breed to a reference population of the same breed as the selection candidates. Accuracies of both single- and multi-breed genomic prediction decreased as MAF of QTL decreased, especially when rare alleles had a large effect. Accuracies of genomic prediction were similar for the models with and without a random within-breed animal effect, probably because of insufficient power to separate across- and within-breed animal effects.

Conclusions

Accuracy of both single- and multi-breed genomic prediction depends on the properties of the QTL that underlie the trait. As QTL MAF decreased, accuracy decreased, especially when rare alleles had a large effect. This demonstrates that QTL properties are key parameters that determine the accuracy of genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0124-6) contains supplementary material, which is available to authorized users.     

Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance

The objective of this simulation study was to compare the effect of the number of QTL and distribution of QTL variance on the accuracy of breeding values estimated with genomewide markers (MEBV). Three distinct methods were used to calculate MEBV: a Bayesian Method (BM), Least Angle Regression (LARS) and Partial Least Square Regression (PLSR). The accuracy of MEBV calculated with BM and LARS decreased when the number of simulated QTL increased. The accuracy decreased more when QTL had different variance values than when all QTL had an equal variance. The accuracy of MEBV calculated with PLSR was affected neither by the number of QTL nor by the distribution of QTL variance. Additional simulations and analyses showed that these conclusions were not affected by the number of individuals in the training population, by the number of markers and by the heritability of the trait. Results of this study show that the effect of the number of QTL and distribution of QTL variance on the accuracy of MEBV depends on the method that is used to calculate MEBV.