Pyrophosphate-stimulated uptake of calcium into the germlings of Phytophthora infestans.

The uptake of 1 micrometer calcium into 6-h-old germination tubes of the fungus Phytophthora infestans follows Michaelis-Menten kinetics with a Km of 33 +/- 4 micrometer and a V of 0.3 nmol.min-1.(5 x 10(4) cells)-1.Uptake is inhibited by ruthenium red and lanthanum (both at 1 micrometer) and by the proton conductors 2,4-dinitrophenol (1 mM) and carbonylcyanide m-chlorophenylhydrazone and carbonylcyanide p-trifluoromethoxyphenylhydrazone (1--10 micrometer) and also by sodium azide. These data suggest that calcium uptake is dependent on energy and on a carrier. Calcium uptake is stimulated by pyrophosphate but not by ATP, orthophosphate, or polyphosphate. This stimulation is prevented by proton conductors or by incubation at 0 degrees C.     

A cryptic invasion within an invasion and widespread introgression in the European water frog complex: consequences of uncontrolled commercial trade and weak international legislation

In Western Europe, many pond owners introduce amphibians for ornamental purposes. Although indigenous amphibians are legally protected in most European countries, retailers are circumventing national and international legislation by selling exotic nonprotected sibling species. We investigated to what extent non‐native species of the European water frog complex (genus Pelophylax) have become established in Belgium, using morphological, mitochondrial and nuclear genetic markers. A survey of 87 sampling sites showed the presence of non‐native water frogs at 47 locations, mostly Marsh frogs (Pelophylax ridibundus). Surprisingly, at least 19% of all these locations also harboured individuals with mitochondrial haplotypes characteristic of Anatolian water frogs (Pelophylax cf. bedriagae). Nuclear genotyping indicated widespread hybridization and introgression between P. ridibundus and P. cf. bedriagae. In addition, water frogs of Turkish origin obtained through a licensed retailer, also contained P. ridibundus and P. cf. bedriagae, with identical haplotypes to the wild Belgian populations. Although P. ridibundus might have invaded Belgium by natural range expansion from neighbouring countries, our results suggest that its invasion was at least partly enhanced by commercial trade, with origins as far as the Middle East. Also the invasion and rapid spread of Anatolian lineages, masked by their high morphological similarity to P. ridibundus, is likely the result of unregulated commercial trade. We expect that Anatolian frogs will further invade the exotic as well as the native range of P. ridibundus and other Pelophylax species elsewhere in Western and Central Europe, with risks of large‐scale hybridization and introgression.     

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.

     

Intestinal endotoxin in induction of type 1 diabetes

We studied serum level of intestinal flora endotoxin (LPS) in 45 children and adolescents aged 3-17 years old with diabetes mellitus type 1. Levels of endotoxin, were significantly elevated in type 1 diabetic patients (2.89 +/- 0.33 Eu/ml) compared with control (0.4 +/- 0.03 Eu/ml). There was significant difference in serum LPS levels in patients with type 1 diabetes onset (3.93 +/- 0.79 Eu/ml) compared with children and adolescent with old time diabetes (2.37 +/- 0.27 Eu/ml). These results have a major implication on our understanding of the role of gut flora endotoxin in pathogenesis of type 1 diabetes.     

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.