HlyC, the internal protein acyltransferase that activates hemolysin toxin: the role of conserved tyrosine and arginine residues in enzymatic activity as probed by chemical modification and site-directed mutagenesis.

Internal fatty acylation of proteins is a recognized means of modifying biological behavior. Escherichia coli hemolysin A (HlyA), a toxic protein, is transcribed as a nontoxic protein and made toxic by internal acylation of two lysine residue epsilon-amino groups; HlyC catalyzes the acyl transfer from acyl-acyl carrier protein (ACP), the obligate acyl donor. Conserved residues among the respective homologous C proteins that activate 13 different RTX (repeats in toxin) toxins of which HlyA is the prototype likely include some residues that are important in catalysis. Possible roles of two conserved tyrosines and two conserved arginines were investigated by noting the effects of chemical modifiers and site-directed mutagenesis. TNM modification of HlyC at pH 8.0 led to extensive inhibition that was prevented by the presence of the substrate myristoyl-ACP but not by the product, ACPSH. NAI had no effect. Y70G and Y150G greatly diminished enzyme activity, whereas mutations Y70F and Y150F exhibited wild-type activity. Modification of arginine residues with PG markedly lowered acyltransferase activity with moderate protection by both myristoyl-ACP and ACPSH. Under optimum conditions, four separate mutations of the two conserved arginine residues (R24A, R24K, R87A, and R87K) had little effect on acyltransferase activity.     

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.

     

Identification of nucleotide sequences for the specific and rapid detection of Yersinia pestis

Suppression subtractive hybridization, a cost-effective approach for targeting unique DNA, was used to identify a 41.7-kb Yersinia pestis-specific region. One primer pair designed from this region amplified PCR products from natural isolates of Y. pestis and produced no false positives for near neighbors, an important criterion for unambiguous bacterial identification.     

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.     

Genetic Variability of Yersinia pestis Isolates as Predicted by PCR-Based IS100 Genotyping and Analysis of Structural Genes Encoding Glycerol-3-Phosphate Dehydrogenase (glpD)

A PCR-based genotyping system that detects divergence of IS100 locations within the Yersinia pestis genome was used to characterize a large collection of isolates of different biovars and geographical origins. Using sequences derived from the glycerol-negative biovar orientalis strain CO92, a set of 27 locus-specific primers was designed to amplify fragments between the end of IS100 and its neighboring gene. Geographically diverse members of the orientalis biovar formed a homogeneous group with identical genotype with the exception of strains isolated in Indochina. In contrast, strains belonging to the glycerol-positive biovar antiqua showed a variety of fingerprinting profiles. Moreover, strains of the biovar medievalis (also glycerol positive) clustered together with the antiqua isolates originated from Southeast Asia, suggesting their close phylogenetic relationships. Interestingly, a Manchurian biovar antiqua strain Nicholisk 51 displayed a genotyping pattern typical of biovar orientalis isolates. Analysis of the glycerol pathway in Y. pestis suggested that a 93-bp deletion within the glpD gene encoding aerobic glycerol-3-phosphate dehydrogenase might account for the glycerol-negative phenotype of the orientalis biovar. The glpD gene of strain Nicholisk 51 did not possess this deletion, although it contained two nucleotide substitutions characteristic of the glpD version found exclusively in biovar orientalis strains. To account for this close relationship between biovar orientalis strains and the antiqua Nicholisk 51 isolate, we postulate that the latter represents a variant of this biovar with restored ability to ferment glycerol. The fact that such a genetic lesion might be repaired as part of the natural evolutionary process suggests the existence of genetic exchange between different Yersinia strains in nature. The relevance of this observation on the emergence of epidemic Y. pestis strains is discussed.     

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.