Thermostable and alkaline lipolytic and proteolytic enzymes produced by a thermophilic mold

The morphological, cultural and physiological characteristics of a thermophilic eumycete isolated from soil, showing strong lipase and protease activities, are described. The lipolytic and proteolytic crude enzyme preparations, recovered from submerged culture liquids, show considerable thermostability and optimum of activity at alkaline pH.     

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.

     

Multilocus Hybridization Typing in Pediococcus acidilactici Strains

In previous a study we demonstrated the presence of several genomic subpopulations within a collection of Pediococcus acidilactici strains isolated from different environments, through a multilocus typing analysis taking into consideration housekeeping conserved loci and protein coding genes of the primary metabolism. In this study, representative strains of five genomic subpopulations previously described (I, II, III, V, VII) were analyzed by restriction analysis of chromosomal DNA and subsequent hybridization assays using as probes amplified fragments obtained from five housekeeping genes (16S rDNA, rpoC, ldhD, ldhL, and metS). A computer similarity and clustering analysis of hybridization data showed the subdivision of P. acidilactici strains in five distinct genotypes according to the grouping previously obtained confirming that pediocin AcH/PA-1 producer strains represent one genomic lineage within the species P. acidilactici. Received: 30 January 2001 / Accepted: 16 May 2001     

Lactobacillus helveticus heterogeneity in natural cheese starters: the diversity in phenotypic characteristics

The study of wild strains from natural habitats is a useful means of understanding better the heterogeneity within a species of biotechnological importance, and of obtaining atypical isolates with unknown capabilities. In the present research carried out on different Lactobacillus helveticus strains isolated from natural cheese starters, it was observed that several biotechnologically important characteristics can differ greatly between strains. Biotypes were found which differ in terms of fructose, maltose and trehalose fermentation, acidifying activity, proteolytic and peptidase activity, and antibiotic and lysozyme resistance. The possibility of choosing Lact. heleveticus strains with specific biotechnological profiles will influence the quality and the variety of dairy products.     

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.     

Genetic relationship among Bacillus licheniformis rolling-circle-replicating plasmids and complete nucleotide sequence of pBL63.1, an atypical replicon

The degree of biodiversity among Bacillus licheniformis plasmids and their relation to other Bacillus subtilis group plasmids has been evaluated. To attain this goal we surveyed the diversity and linkage of replication modules in a collection of 21 naturally occurring plasmids of B. licheniformis strains, isolated from different geographical areas. On the basis of rep gene sequence analysis it was possible to group the B. licheniformis plasmids rep genes in two main cluster. Comparison with known rep genes from Bacillus rolling-circle-replicating (RCR) plasmids revealed the presence in B. licheniformis plasmids of replication genes with a DNA sequence peculiar to B. licheniformis species together with rep genes with a very high sequence similarity to B. subtilis plasmids. Furthermore, the molecular organization of an atypical replicon, pBL63.1, was shown. This plasmid did not display any significant similarity with known Bacillus RCR plasmids. The complete nucleotide sequence evidenced a replication module with an unexpected similarity with Rep proteins from RCR plasmids of bacterial species phylogenetically distantly related to Bacillus. pBL63.1 represents an exception to the low-level diversity hypothesis among Bacillus RC replicons.