IDENTIFICATION OF COENZYME Q10 FROM PORPHYRIDIUM PURPUREUM (RHODOPHYTA) BY MATRIX‐ASSISTED LASER DESORPTION IONIZATION CURVED FIELD REFLECTRON MASS SPECTROMETRY1

Antioxidant agents from natural sources are currently the focus of scientific interest and are part of several natural product screenings. Coenzymes Q (CoQ, ubiquinones) are integral parts of the electron transport chain of the inner mitochondrial membrane. As antioxidants they protect phospholipids against peroxidation and are also involved in various processes of tissue protection. Their natural occurrence was validated for Saccharomyces cerevisiae as CoQ₆, for Escherichia coli as CoQ₈, and for humans as CoQ₁₀. After carrying out a preparative reversed‐phase (RP)–HPLC separation of extracts isolated from unicellular red alga Porphyridium purpureum (Bory) K. M. Drew et R. Ross, it was possible to identify a 2,3‐dimethoxy‐5‐methyl‐6‐decaprenyl‐1,4‐benzoquinone (CoQ₁₀) within these extracts using a matrix‐assisted laser desorption ionization (MALDI) curved field reflectron (CFR) mass spectrometer. Detected mass fragments showed a high significance and could be structurally interpreted for both commercialized standard and CoQ₁₀ isolated from P. purpureum.     

Microbial-induced immunomodulation by targeting the NF-κB system

Virtually all eukaryotes have developed defense mechanisms to efficiently counter potential threats from prokaryotic microorganisms; an example is the conserved nuclear factor-kappaB (NF-κB) signaling system. However, bacterial pathogens and commensals have in turn evolved highly effective counter mechanisms to modulate this immune regulatory circuit. Modifications in ubiquitin, ubiquitin-like (Ubl) proteins such as neural precursor cell expressed, developmentally down-regulated 8 (NEDD8) and other post-translational modifications (PTMs) in the NF-κB system represent attractive targets for microbial manipulation. In this review, we describe recent advances in understanding the different strategies that bacteria have evolved to interfere with PTMs in NF-κB signal transmission.     

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

Background

Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction.

Methods

Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values.

Results

Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied.

Conclusions

These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.     

Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model

Background

Genomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with different methods using pedigree or high-density SNP genotypes were evaluated and compared in a commercial layer chicken breeding line.

Methods

The following traits were analyzed: egg production, egg weight, egg color, shell strength, age at sexual maturity, body weight, albumen height, and yolk weight. Predictions appropriate for early or late selection were compared. A total of 2,708 birds were genotyped for 23,356 segregating SNP, including 1,563 females with records. Phenotypes on relatives without genotypes were incorporated in the analysis (in total 13,049 production records).The data were analyzed with a Reduced Animal Model using a relationship matrix based on pedigree data or on marker genotypes and with a Bayesian method using model averaging. Using a validation set that consisted of individuals from the generation following training, these methods were compared by correlating EBV with phenotypes corrected for fixed effects, selecting the top 30 individuals based on EBV and evaluating their mean phenotype, and by regressing phenotypes on EBV.

Results

Using high-density SNP genotypes increased accuracies of EBV up to two-fold for selection at an early age and by up to 88% for selection at a later age. Accuracy increases at an early age can be mostly attributed to improved estimates of parental EBV for shell quality and egg production, while for other egg quality traits it is mostly due to improved estimates of Mendelian sampling effects. A relatively small number of markers was sufficient to explain most of the genetic variation for egg weight and body weight.     

Root growth dynamics of Nicotiana attenuata seedlings are affected by simulated herbivore attack

Many studies demonstrate resource-based trade-offs between growth and defence on a large timescale. Yet, the short-term dynamics of this growth reaction are still completely unclear, making it difficult to explain growth-defence trade-offs mechanistically. In this study, image-based non-destructive methods were used to quantify root growth reactions happening within hours following simulated herbivore attack. The induction of wound reactions in Nicotiana attenuata in the seedling stage led to transiently decreased root growth rates. Application of the oral secretion of the specialist herbivore Manduca sexta to the leaves led to a transient decrease in root growth that was more pronounced than if a mere mechanical wounding was imposed. Root growth reduction was more pronounced than leaf growth reduction. When fatty acid-amino acid conjugates (FACs) were applied to wounds, root growth reduction occurred in the same intensity as when oral secretion was applied. Timing of the transient growth reduction coincided with endogenous bursts of jasmonate (JA) and ethylene emissions reported in literature. Simulation of a wound response by applying methyl jasmonate (MeJA) led to more prolonged negative effects on root growth. Increased nicotine concentrations, trichome lengths and densities were observed within 72 h in seedlings that were treated with MeJA or that were mechanically wounded. Overall, these reactions indicate that even in a very early developmental stage, the diversion of plant metabolism from primary (growth-sustaining) to secondary (defence-related) metabolism can cause profound alterations of plant growth performance.     

Multiscale dynamic modeling and simulation of a biorefinery

A biorefinery comprises a variety of process steps to synthesize products from sustainable natural resources. Dynamic plant-wide simulation enhances the process understanding, leads to improved cost efficiency and enables model-based operation and control. It is thereby important for an increased competitiveness to conventional processes. To this end, we developed a Modelica library with replaceable building blocks that allow dynamic modeling of an entire biorefinery. For the microbial conversion step, we built on the dynamic flux balance analysis (DFBA) approach to formulate process models for the simulation of cellular metabolism under changing environmental conditions. The resulting system of differential-algebraic equations with embedded optimization criteria (DAEO) is solved by a tailor-made toolbox. In summary, our modeling framework comprises three major pillars: A Modelica library of dynamic unit operations, an easy-to-use interface to formulate DFBA process models and a DAEO toolbox that allows simulation with standard environments based on the Modelica modeling language. A biorefinery model for dynamic simulation of the OrganoCat pretreatment process and microbial conversion of the resulting feedstock by Corynebacterium glutamicum serves as case study to demonstrate its practical relevance.     

Evaluation of coagulation activation after Rhinovirus infection in patients with asthma and healthy control subjects: an observational study

Background

Asthma exacerbations are frequently triggered by rhinovirus infections. Both asthma and respiratory tract infection can activate haemostasis. Therefore we hypothesized that experimental rhinovirus-16 infection and asthmatic airway inflammation act in synergy on the haemostatic balance.

Methods

28 patients (14 patients with mild allergic asthma and 14 healthy non-allergic controls) were infected with low-dose rhinovirus type 16. Venous plasma and bronchoalveolar lavage fluid (BAL fluid) were obtained before and 6 days after infection to evaluate markers of coagulation activation, thrombin-antithrombin complexes, von Willebrand factor, plasmin-antiplasmin complexes, plasminogen activator inhibitor type-1, endogenous thrombin potential and tissue factor-exposing microparticles by fibrin generation test, in plasma and/or BAL fluid. Data were analysed by nonparametric tests (Wilcoxon, Mann Whitney and Spearman correlation).

Results

13 patients with mild asthma (6 females, 19-29 y) and 11 healthy controls (10 females, 19-31 y) had a documented Rhinovirus-16 infection. Rhinovirus-16 challenge resulted in a shortening of the fibrin generation test in BAL fluid of asthma patients (t = -1: 706 s vs. t = 6: 498 s; p = 0.02), but not of controls (t = -1: 693 s vs. t = 6: 636 s; p = 0.65). The fold change in tissue factor-exposing microparticles in BAL fluid inversely correlated with the fold changes in eosinophil cationic protein and myeloperoxidase in BAL fluid after virus infection (r = -0.517 and -0.528 resp., both p = 0.01).Rhinovirus-16 challenge led to increased plasminogen activator inhibitor type-1 levels in plasma in patients with asthma (26.0 ng/mL vs. 11.5 ng/mL in healthy controls, p = 0.04). Rhinovirus-16 load in BAL showed a linear correlation with the fold change in endogenous thrombin potential, plasmin-antiplasmin complexes and plasminogen activator inhibitor type-1.

Conclusions

Experimental rhinovirus infection induces procoagulant changes in the airways of patients with asthma through increased activity of tissue factor-exposing microparticles. These microparticle-associated procoagulant changes are associated with both neutrophilic and eosinophilic inflammation. Systemic activation of haemostasis increases with Rhinoviral load.

Trial registration

This trial was registered at the Dutch trial registry (http://www.trialregister.nl): NTR1677.