Reaction of derivatives of methyl 2,3-O-benzylidene-6-deoxy-α-L-mannopyranoside with butyllithium: Synthesis of methyl 2, 6-dideoxy-4-O-methyl-α-L-erytho-hexopyranosid-3-ulose

Methyl 2,3-O-benzylidene-6-deoxy-α-L-mannopyranoside (2) reacted with butyllithium to give a mixture of 1,5-anhydro-3-C-butyl-1,2,6-trideoxy-L-ribo-hex-1-enitol (3) and its L-arabino analogue (4), together with methyl 2,3,6-trideoxy-α-L-erythro-hex-2-enopyranoside (5). In contrast, the 4-O-methyl analogue (8) of 2 was converted by butyllithium into methyl 2,6-dideoxy-4-O-methyl-α-L-erythro-hexo-pyranosid-3-ulose (9), which was further characterized as its oxime 10. The 4-O-benzyl analogue of 8, obtained as two separate diastereoisomers (6 and 7) differing in configuration at C-2 of the dioxolane ring, gave a complex mixture of products on treatment with butyllithium.     

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.

     

The spatial organization of centromeric heterochromatin during normal human lymphopoiesis: evidence for ontogenically determined spatial patterns

It is believed that pericentromeric heterochromatin may play a major role in the epigenetic regulation of gene expression. We have previously shown that centromeres in human peripheral blood cells aggregate into distinct "myeloid" and "lymphoid" spatial patterns, suggesting that the three-dimensional organization of centromeric heterochromatin in interphase may be ontogenically determined during hematopoietic differentiation. To investigate this possibility, the spatial patterns of association of different centromeres were analyzed in hematopoietic progenitors and compared with those in early-B and early-T cells, mature B and T lymphocytes, and, additionally, mature granulocytes and monocytes. We show that those patterns change during lymphoid differentiation, with major spatial arrangements taking place at different stages during T and B cell differentiation. Heritable patterns of centromere association are observed, which can occur either at the level of the common lymphoid progenitor, or in early-T or early-B committed cells. A correlation of the observed patterns of centromere association with the gene content of the respective chromosomes further suggests that the variation in the composition of these heterochromatic structures may contribute to the dynamic relocation of genes in different nuclear compartments during cell differentiation, which might have functional implications for cell-stage-specific gene expression.     

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.     

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.     

Proteaceae from phosphorus‐impoverished habitats preferentially allocate phosphorus to photosynthetic cells: An adaptation improving phosphorus‐use efficiency

Plants allocate nutrients to specific leaf cell types; eudicots are thought to predominantly allocate phosphorus (P) to epidermal/bundle sheath cells. However, three Proteaceae species have been shown to preferentially allocate P to mesophyll cells instead. These Proteaceae species are highly adapted to P‐impoverished habitats, with exceptionally high photosynthetic P‐use efficiencies (PPUE). We hypothesized that preferential allocation of P to photosynthetic mesophyll cells is an important trait in species adapted to extremely P‐impoverished habitats, contributing to their high PPUE. We used elemental X‐ray mapping to determine leaf cell‐specific nutrient concentrations for 12 Proteaceae species, from habitats of strongly contrasting soil P concentrations, in Australia, Brazil, and Chile. We found that only species from extremely P‐impoverished habitats preferentially allocated P to photosynthetic mesophyll cells, suggesting it has evolved as an adaptation to their extremely P‐impoverished habitat and that it is not a family‐wide trait. Our results highlight the possible role of soil P in driving the evolution of ecologically relevant nutrient allocation patterns and that these patterns cannot be generalized across families. Furthermore, preferential allocation of P to photosynthetic cells may provide new and exciting strategies to improve PPUE in crop species.