Platelet aggregation. II. Adenyl cyclase, prostaglandin E1, and calcium

In exploration of the proposal that prostaglandin E1 (PGE1) inhibits platelet aggregation via stimulation of adenyl cyclase, the temporal relationship of adenosine cyclic 3',5' monophosphate (cyclic AMP) synthesis and inhibition of ADP-induced aggregation in response to PGE1 was studied. The requirement for calcium in aggregation led to the investigation of the effects of calcium ions on platelet adenyl cyclase activity. PGE1 stimulated the synthesis of cyclic AMP from adenosine-5'-triphosphate-8-14-C by platelet membrane fractions and also increased cyclic AMP synthesis in intact platelets previously incubated for 2 hours with adenosine-14-C. The accumulation of cyclic AMP increased signficiantly at low concentrations of PGE1 and reached a maximum at about 1 mug. Regardless of the inducing agent, calcium ions are an absolute requirement for the aggregation of platelets.     

The location of redox centers in biological membranes determined by resonance x-ray diffraction. I. Observation of the resonance effect

We have developed resonance X-ray diffraction methods to locate for the first time intrinsic metal atoms associated with redox centers within biological membrane systems. The study of membranes containing dilute concentrations of resonant scatterers has been made possible by the development of synchrotron radiation sources of X-rays. The technique permits altering the scattering power of a particular atom relative to others by varying the incident X-ray energy. Thus, this method may be used to locate a metal atom within a complex integral protein without chemical modification of the membrane. We present resonance diffraction data taken with synchroton radiation for two different membrane systems: cytochrome oxidase incorporated into lipid vesicles and a photosynthetic reaction center-cytochrome c complex also reincorporated into lipid vesicles.     

Genetic and Environmental Effects on the Expression of Peptidases and Larval Viability in Drosophila Melanogaster

The peptidase system in Drosophila melanogaster, consisting of dipeptidase-A, dipeptidase-B, dipeptidase-C and the leucine aminopeptidases, was used as a model to study the adaptive significance of enzyme activity variation. The involvement of the peptidases in osmoregulation has been suggested from the ubiquitous distribution of peptidase activities in nearly all tissues and the high concentration of amino acids and oligopeptides in the hemolymph. Under this hypothesis, larvae counteract increases in environmental osmotic stress by hydrolyzing peptides into amino acids both intra- and extracellularly to increase physiological osmotic concentration. The expression of the peptidases was studied by assaying for peptidase activities in third instar larvae of isogenic lines, which were reared under increasing levels of environmental osmotic stress using either D-mannitol or NaCl. Second and third chromosome substitution isogenic lines were used to assess the relative contribution of regulatory and structural genes in enzyme activity variation. Results indicate that: (1) genetic variation exists for peptidase activities, (2) the effect of osmotic stress is highly variable among peptidases, (3) changes in peptidase activities in response to osmotic stress depend on both genetic background and osmotic effector and (4) peptidase activities are correlated with each other, but these phenotypic correlations depend on genetic background, osmotic effector, and level of osmotic stress. Osmotic concentration in the larval hemolymph is correlated with leucine aminopeptidase activity, but changes in hemolymph osmotic concentration in response to environmental osmotic stress depend on the osmotic effector in the environment. Although these findings suggest that genetic and environmental factors contribute significantly toward the expression of enzymes with similar functions, a relative larval viability study of genotypes that differed significantly in dipeptidase-B (DIP-B) activity revealed that low DIP-B activity did not confer any measurable reduction in larval viability under increasing levels of environmental osmotic stress. These negative results suggest that, either DIP-B does not play a major role in osmoregulation or differential osmoregulation is not related to egg to adult viability in these tests.     

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.

     

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.     

Planktonic and sediment-associated aerobic methanotrophs in two seep systems along the North American margin

Methane vents are of significant geochemical and ecological importance. Notable progress has been made toward understanding anaerobic methane oxidation in marine sediments; however, the diversity and distribution of aerobic methanotrophs in the water column are poorly characterized. Both environments play an essential role in regulating methane release from the oceans to the atmosphere. In this study, the diversity of particulate methane monooxygenase (pmoA) and 16S rRNA genes from two methane vent environments along the California continental margin was characterized. The pmoA phylotypes recovered from methane-rich sediments and the overlying water column differed. Sediments harbored the greatest number of unique pmoA phylotypes broadly affiliated with the Methylococcaceae family, whereas planktonic pmoA phylotypes formed three clades that were distinct from the sediment-hosted methanotrophs and distantly related to established methanotrophic clades. Water column-associated phylotypes were highly similar between field sites, suggesting that planktonic methanotroph diversity is controlled primarily by environmental factors rather than geographical proximity. Analysis of 16S rRNA genes from methane-rich waters did not readily recover known methanotrophic lineages, with only a few phylotypes demonstrating distant relatedness to Methylococcus. The development of new pmo primers increased the recovery of monooxygenase genes from the water column and led to the discovery of a highly diverged monooxygenase sequence which is phylogenetically intermediate to Amo and pMMO. This sequence potentiates insight into the amo/pmo superfamily. Together, these findings lend perspective into the diversity and segregation of aerobic methanotrophs within different methane-rich habitats in the marine environment.