Direct activation of human resting T cells by IL 2: the role of an IL 2 receptor distinct from the Tac protein

High concentrations of interleukin 2 (IL 2) were shown to produce a delayed but pronounced proliferation of purified resting T cells in the apparent absence of other activation signals. Because these stimulatory effects of IL 2 occurred in the absence of detectable Tac+ cells, the possibility that IL 2 might be initially interacting with an IL 2 binding protein distinct from the Tac protein was studied. Chemical cross-linking studies with 125I-IL 2 revealed the presence of an IL 2 binding protein distinct from the Tac protein on the surface of these unstimulated T cells. This second IL 2 receptor has an estimated molecular size of 70,000 daltons, lacks reactivity with the anti-Tac antibody, and appears to be identical to the p70 protein recently proposed as a component of the high affinity IL 2 receptor. Scatchard analysis of IL 2 binding assays performed with the unactivated T cells revealed approximately 600 to 700 p70 sites per cell and an apparent Kd of 340 pM. These data indicate that the p70 protein present on resting T cells binds IL 2 with an intermediate affinity compared with the previously recognized high and low affinity forms of the receptor and may account for the high concentration of IL 2 needed to induce resting T cell proliferation. To investigate the early biologic consequences of IL 2 binding to the p70 protein, potential changes in the expression of genes involved in T cell activation were examined. Northern blotting revealed the rapid induction of c-myc, c-myb, and Tac mRNA after stimulation of resting T cells with a high concentration of IL 2. The anti-Tac antibody did not inhibit IL 2 induced expression of these genes, suggesting that the p70 protein rather than the Tac antigen or the high affinity IL 2 receptor complex mediated this signal. However, in contrast to these early activation events, the anti-Tac antibody significantly inhibited IL 2 induced T cell proliferation. This finding implicates the high affinity form of the IL 2 receptor in the proliferative response of the IL 2 activated T cells. Thus these data support a two step model for the induction of resting T cell proliferation by high doses of IL 2 involving the initial generation of an activation or "competence" signal through the p70 protein and a subsequent proliferation or "progression" signal through the high affinity form of the receptor.     

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.     

Hepatic beta-oxidation and carnitine palmitoyltransferase I in neonatal pigs after dietary treatments of clofibric acid, isoproterenol, and medium-chain triglycerides

A suckling piglet model was used to study nutritional and pharmacologic means of stimulating hepatic fatty acid beta-oxidation. Newborn pigs were fed milk diets containing either long- or medium-chain triglycerides (LCT or MCT). The long-chain control diet was supplemented further with clofibric acid (0.5%) or isoproterenol (40 ppm), and growth was monitored for 10-12 days. Clofibrate increased rates of hepatic peroxisomal and mitochondrial beta-oxidation of [1-(14)C]-palmitate by 60 and 186%, respectively. Furthermore, malonyl-CoA sensitive carnitine palmitoyltransferase (CPT I) activity increased 64% (P < 0.05) in pigs receiving clofibrate. Increased CPT I activity was not congruent with changes in message, as elevated abundance of CPT I mRNA was not detected (P = 0.16) when assessed by qRT-PCR. Neither rates of beta-oxidation nor CPT activities were affected by dietary MCT or by isoproterenol treatment (P > 0.1). Collectively, these findings indicate that clofibrate effectively induced hepatic CPT activity concomitant with increased fatty acid beta-oxidation.     

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.     

Production of Diamino propionic acid ammonia lyase by a new strain of Salmonella typhimurium PU011

Background  

Seeds of the legume plant Lathyrus sativus, which is grown in arid and semi arid tropical regions, contain Diamino Propionic acid (DAP). DAP is a neurotoxin, which, when consumed, causes a disease called Lathyrism. Lathryrism may manifest as Neurolathyrism or Osteolathyrism, in which the nervous system, and bone formation respectively, are affected. DAP ammonia lyase is produced by a few microorganisms such as Salmonella typhi, Salmonella typhimurium and Pseudomonas, and is capable of detoxifying DAP.