Reversal of alpha,alpha'-Dipyridyl-induced Porphyrin Synthesis in Etiolated and Greening Red Kidney Bean Leaves

The chemical induction of porphyrin synthesis has been investigated in etiolated and greening leaves of Phaseolus vulgaris L. var. Red Kidney. When these leaves are incubated in darkness with solutions of transition metal ion chelators such as α,α′-dipyridyl, 1,10-phenanthroline, pyridine-2-aldoxime, or other related aromatic heterocyclic nitrogenous bases, they synthesize large amounts of protochlorophyllide and Mg protoporphyrins. Greening leaves produce more porphyrin than do etiolated leaves under such conditions. If the leaves are then transferred to 1 millimolar solutions of various transition metal salts such as Fe²⁺, Zn²⁺, or Co²⁺ (but not Mn²⁺ or Mg²⁺), Mg protoporphyrin (monomethyl ester) synthesis immediately ceases and the pigment(s) rapidly disappear(s); protochlorophyllide synthesis gradually diminishes during 4 to 8 hours of treatment. The loss in Mg protoporphyrin(s) can be accounted for by a simultaneous increase in protochlorophyllide in partially greened leaves but not in etiolated leaves. In the latter, the decline in Mg protoporphyrin(s) initiated by the application of Zn²⁺ is retarded by low temperature and anaerobiosis but not by respiratory inhibitors. Cycloheximide inhibits the loss of Mg protoporphyrin(s) but does not affect their conversion to protochlorophyllide.     

The effects of levulinic Acid and 4,6-dioxoheptanoic Acid on the metabolism of etiolated and greening barley leaves

Application of levulinic acid (LA), a competitive inhibitor of δ-aminolevulinic acid (ALA) dehydratase, to greening plant tissues causes ALA to accumulate at the expense of chlorophyll. 4,6-Dioxoheptanoic acid (DA), which has been reported to be an effective inhibitor of this enzyme in animal systems, has a similar but more powerful effect on ALA and chlorophyll metabolism in greening leaves of Hordeum vulgare L. var. Larker. Both LA and DA also inhibit the uptake of [¹⁴C]amino acids into etiolated and greening barley leaves and reduce their incorporation into protein. Treatment of etiolated and greening leaves with these compounds results in the inhibition of ¹⁴CO₂ evolution from labeled precursors, including amino and organic acids. Inhibition of ¹⁴CO₂ evolution by these compounds is more effective in greening leaves than in etiolated leaves when [4-¹⁴C]ALA or [1-¹⁴C]glutamate are employed as precursors. Both LA and DA also inhibit the uptake and increase the incorporation of ³²Pi into organophosphorus by etiolated barley leaves. These results indicate that LA and DA have more far-reaching effects upon plant metabolism than was previously believed.     

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.

     

Complement Activation in Patients with Focal Segmental Glomerulosclerosis

Background

Recent pre-clinical studies have shown that complement activation contributes to glomerular and tubular injury in experimental FSGS. Although complement proteins are detected in the glomeruli of some patients with FSGS, it is not known whether this is due to complement activation or whether the proteins are simply trapped in sclerotic glomeruli. We measured complement activation fragments in the plasma and urine of patients with primary FSGS to determine whether complement activation is part of the disease process.

Study Design

Plasma and urine samples from patients with biopsy-proven FSGS who participated in the FSGS Clinical Trial were analyzed.

Setting and Participants

We identified 19 patients for whom samples were available from weeks 0, 26, 52 and 78. The results for these FSGS patients were compared to results in samples from 10 healthy controls, 10 patients with chronic kidney disease (CKD), 20 patients with vasculitis, and 23 patients with lupus nephritis.

Outcomes

Longitudinal control of proteinuria and estimated glomerular filtration rate (eGFR).

Measurements

Levels of the complement fragments Ba, Bb, C4a, and sC5b-9 in plasma and urine.

Results

Plasma and urine Ba, C4a, sC5b-9 were significantly higher in FSGS patients at the time of diagnosis than in the control groups. Plasma Ba levels inversely correlated with the eGFR at the time of diagnosis and at the end of the study. Plasma and urine Ba levels at the end of the study positively correlated with the level of proteinuria, the primary outcome of the study.

Limitations

Limited number of patients with samples from all time-points.

Conclusions

The complement system is activated in patients with primary FSGS, and elevated levels of plasma Ba correlate with more severe disease. Measurement of complement fragments may identify a subset of patients in whom the complement system is activated. Further investigations are needed to confirm our findings and to determine the prognostic significance of complement activation in patients with FSGS.     

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.     

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,^5,12,20) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization.Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods^{3,4,9,10,13-15,17-19,22,23,25}. In this application, we demonstrate a program which follows Rabotyagov et al.''s approach and integrates a modern and commonly used SWAT water quality model⁷ with a multiobjective evolutionary algorithm SPEA2²⁶, and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.     

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.