Pro-and anti-inflammatory effects of glucocorticoid Fluticasone on ovarian and immune functions in commercial-aged laying hens.

Ovarian chronic inflammation has been created and extended in the laying hen mainly via increasing laying frequency and microbial infection, especially during the late stage of production period. This study was aimed to evaluate glucocorticoid (GC) Fluticasone as an anti-inflammatory agent on the gene expression of the ovarian pro-and anti-inflammatory mediators (follicular cyclooxygenases COX 1, 2, and cytokines), inflammatory responses of the immune system, ovarian functions (ovulation rate and follicular growths), and hormones in the commercial-aged laying hens. White Leghorn hens aged 92-weeks were used for four weeks to be supplemented by 2 ppm Fluticasone as an optimum dose obtained in a pre-trial base on ovulation rate. As compared to control, Fluticasone resulted in a significant decrease in the mRNA expression of COX-1 and pro-and anti-inflammatory cytokines, and increase in COX-2 mRNA expression and heterophil to lymphocyte ratio (P < 0.001). A significant reduction was observed in the ovulation rate, follicular size (P < 0.001), ovarian hormones, immunoglobulins, body weight, and food consummation (P ≤ 0.05) by administering GC Fluticasone. Although a relative anti-inflammatory improvement was created by Fluticasone in the ovarian condition, the administration of this glucocorticoid resulted in a considerable reduction in ovarian hormones and functions of commercial aged laying hens.

The stimulation and inhibition of beta-2 adrenergic receptor on the inflammatory responses of ovary and immune system in the aged laying hens.

BACKGROUND: Ovarian chronic inflammation has been known to incidence in the laying hen mainly via increasing laying frequency and microbial infection, especially during late stage of production period. This study was aimed to evaluate beta-2 adrenergic agonist (Beta-2 Adrenergic Agonist, BAA) Salmeterol and beta blocker (Beta Blocker, BB) Propranolol on the gene expression of the ovarian pro- and anti-inflammatory mediators, inflammatory responses of immune system, ovarian functions and, hormones in the laying hens on the late stage of production period. Forty-eight White Leghorn hens aged 92 weeks were used for 4 weeks to be supplemented by Salmeterol and Propranolol. Ovulation rate and follicular growth were determined based on laying frequency and ovarian visual evaluation, respectively; the mRNA expressions of follicular beta-2 adrenergic receptor (Beta-2 Adrenergic Receptor, ß2ADR), cyclooxygenases (Cyclooxygenases, COX) 1 and 2, and cytokines were measured by real-time PCR. The plasma concentration of ovarian hormones, cellular, and humoral immune responses were measured via ELISA, heterophil to lymphocyte ratio (Heterophil to Lymphocyte ratio, H:L), and sheep red blood cell (Sheep Red Blood Cell, SRBC) test, respectively. RESULTS: As compared to control, both of BAA Salmeterol and BB Propranolol resulted in a significant decrease in the mRNA expression of ß2ADR, cyclooxygenases, and pro- and anti-inflammatory cytokines (P < 0.01). A significant elevation was observed in the ovulation rate (P < 0.05), plasma estradiol content on both treated groups (P < 0.05), and the content of progesterone and was just significantly (P < 0.05) increased in Salmeterol group. H:L was reduced in BAA group (P < 0.05), and immunoglobulin (Ig) M was elevated in both treated hens, when compared to control. The results indicated that Salmeterol significantly increases body weight (P < 0.05). CONCLUSION: The stimulation and inhibition of beta-2 adrenergic signaling could reduce ovarian inflammatory condition in addition to enhancing laying efficiency in the aged laying hens.

Meta-analysis suggests evidence of novel stress-related pathway components in Orsay virus - Caenorhabditis elegans viral model.

The genetic model organism, Caenorhabditis elegans (C. elegans), shares many genes with humans and is the best-annotated of the eukaryotic genome. Therefore, the identification of new genes and pathways is unlikely. Nevertheless, host-pathogen interaction studies from viruses, recently discovered in the environment, has created new opportunity to discover these pathways. For example, the exogenous RNAi response in C. elegans by the Orsay virus as seen in plants and other eukaryotes is not systemic and transgenerational, suggesting different RNAi pathways between these organisms. Using a bioinformatics meta-analysis approach, we show that the top 17 genes differentially-expressed during C. elegans infection by Orsay virus are functionally uncharacterized genes. Furthermore, functional annotation using similarity search and comparative modeling, was able to predict folds correctly, but could not assign easily function to the majority. However, we could identify gene expression studies that showed a similar pattern of gene expression related to toxicity, stress and immune response. Those results were strengthened using protein-protein interaction network analysis. This study shows that novel molecular pathway components, of viral innate immune response, can be identified and provides models that can be further used as a framework for experimental studies. Whether these features are reminiscent of an ancient mechanism evolutionarily conserved, or part of a novel pathway, remain to be established. These results reaffirm the tremendous value of this approach to broaden our understanding of viral immunity in C. elegans.

Bioinformatics analysis identify novel OB fold protein coding genes in C. elegans.

BACKGROUND: The C. elegans genome has been extensively annotated by the WormBase consortium that uses state of the art bioinformatics pipelines, functional genomics and manual curation approaches. As a result, the identification of novel genes in silico in this model organism is becoming more challenging requiring new approaches. The Oligonucleotide-oligosaccharide binding (OB) fold is a highly divergent protein family, in which protein sequences, in spite of having the same fold, share very little sequence identity (5-25%). Therefore, evidence from sequence-based annotation may not be sufficient to identify all the members of this family. In C. elegans, the number of OB-fold proteins reported is remarkably low (n=46) compared to other evolutionary-related eukaryotes, such as yeast S. cerevisiae (n=344) or fruit fly D. melanogaster (n=84). Gene loss during evolution or differences in the level of annotation for this protein family, may explain these discrepancies. METHODOLOGY/PRINCIPAL FINDINGS: This study examines the possibility that novel OB-fold coding genes exist in the worm. We developed a bioinformatics approach that uses the most sensitive sequence-sequence, sequence-profile and profile-profile similarity search methods followed by 3D-structure prediction as a filtering step to eliminate false positive candidate sequences. We have predicted 18 coding genes containing the OB-fold that have remarkably partially been characterized in C. elegans. CONCLUSIONS/SIGNIFICANCE: This study raises the possibility that the annotation of highly divergent protein fold families can be improved in C. elegans. Similar strategies could be implemented for large scale analysis by the WormBase consortium when novel versions of the genome sequence of C. elegans, or other evolutionary related species are being released. This approach is of general interest to the scientific community since it can be used to annotate any genome.

Guanine-rich RNAs and DNAs that bind heme robustly catalyze oxygen transfer reactions.

Diverse guanine-rich RNAs and DNAs that fold to form guanine quadruplexes are known to form tight complexes with Fe(III) heme. We show here that a wide variety of such complexes robustly catalyze two-electron oxidations, transferring oxygen from hydrogen peroxide to thioanisole, indole, and styrene substrates. Use of (18)O-labeled hydrogen peroxide reveals the source of the oxygen transferred to form thioanisole sulfoxide and styrene oxide to be the activated ferryl moiety within these systems. Hammett analysis of the kinetics of thioanisole sulfoxide formation is unable to distinguish between a one-step, direct oxygen transfer and a two-step, oxygen rebound mechanism for this catalysis. Oxygen transfer to indole produces a range of products, including indigo and related dyes. Docking of heme onto a high-resolution structure of the G-quadruplex fold of Bcl-2 promoter DNA, which both binds heme and transfers oxygen, suggests a relatively open active site for this class of ribozymes and deoxyribozymes. That heme-dependent catalysis of oxygen transfer is a property of many RNAs and DNAs has ramifications for primordial evolution, enzyme design, cellular oxidative disease, and anticancer therapeutics.

Predicting protein complexes by data integration of different types of interactions.

The explosion of high throughput interaction data from proteomics studies gives us the opportunity to integrate Protein-Protein Interactions (PPI) from different type of interactions. These methods rely on the assumption that proteins within a complex have more interactions across the different data sets which translate into the identification of dense subgraphs. However, the relative importance of the types of interaction are not equivalent in their reliability and accuracy consequently they should be analysed separately. Here we propose a method that use graph theory and mathematical modelling to solve this problem. Our approach has four steps that: i) score independently each type of interaction; ii) build an interaction specific networks for each type; iii) weight the specific networks; and iv) combine and normalise the scores. Using this approach to the BRCA1 Associated genome Surveillance Complex (BASC), we correctly identified the known core components of the complex and subcomplexes that have solved structures as well as predicted new interactions and core complexes. The method presented in this study is of general use. It is flexible enough to allow the development of any scoring system and can be applied to any protein complex to provide the latest knowledge in its interactions and structure.

RPA nucleic acid-binding properties of IFI16-HIN200.

InterFeron-gamma Inducible protein 16 (IFI16) belongs to the interferon inducible HIN200 protein family that contains transcriptional regulators linked to cell cycle regulation and differentiation. All family members contain at most two domains of 200 amino acids, called HIN200, each containing two Oligonucleotide/Oligosaccharide Binding (OB) folds. IFI16 is involved in transcriptional repression and is a component of the DNA repair multi-protein complex known as BASC, which forms after UV-induced DNA damage. In this study, we used fold recognition and biophysical approaches as a tool to infer and validate functions to the HIN200 domain. Since the best template to model IFI16-HIN200 is Replication Protein A (RPA) in complex with single-stranded nucleic acids, we tested six RPA nucleic acid-binding characteristics for IFI16-HIN200. Our results indicate that IFI16-HIN200 is an RPA-like, OB-fold, nucleic acid-binding protein that binds to ssDNA with higher affinity than to dsDNA, recognizes ssDNA in the same orientation as RPA, oligomerizes upon ssDNA binding, wraps and stretches ssDNA, but does not destabilize dsDNA. We finally propose a framework model explaining how the HIN200 domain could prevent ssDNA from re-annealing.

Characterization of Aedes Dredd: a novel initiator caspase from the yellow fever mosquito, Aedes aegypti.

Caspases play an essential role during programmed cell death in all metazoans. These enzymes are cysteine proteases and comprise a multi-gene family with more than a dozen mammalian family members. Although caspases have been characterized in many animals, including Drosophila melanogaster, little is known about the caspases that exist in mosquitoes. Here we describe the identification and characterization of Aedes Dredd (AeDredd), a novel caspase in the yellow fever mosquito, Aedes aegypti. AeDredd contains two N-terminal death effector domains and the well conserved caspase catalytic domain. Multiple sequence alignments and functional substrate assays of recombinant protein suggest that AeDredd is an orthologue of Drosophila Dredd and human caspase-8, both central effectors of the death receptor-mediated apoptotic pathway. AeDredd exhibits substrate specificity most similar to human caspase-8. AeDredd transcripts were found in all developmental stages with highest expression in early pupae. Within adults, AeDredd was found in all the tissues examined, with the highest transcript levels detected in fat body tissues. This is the first functional characterization of a death domain-containing caspase in an insect vector of human disease, and will initiate studies on the role of apoptosis in the innate immune response of vectors towards intracellular parasites such as viruses.

Thermodynamics and stability of the PAAD/DAPIN/PYRIN domain of IFI-16.

The PAAD domain is a conserved domain recently identified in more than 35 human proteins that are involved in apoptosis and inflammatory signaling pathways. Structural studies have confirmed that this domain belongs to the death domain superfamily which includes PAAD/CARD/DED/DD families. Recently, the 3D structures determined by NMR of NALP1 and ASC PAAD domain, members of the PAAD family, have shown that it is composed of a 6 helix bundle as with other death domain family members. However, helix-3 in the solved structures is unordered in solution. In this study we compare the thermodynamic, folding and stability properties of different members of the PAAD and CARD families and investigate structural conformational changes induced by the helix inducers trifluoroethanol and SDS on the PAAD domain of IFI16 and on the CARD domain of RAIDD. We show that inside the PAAD and CARD families, members have similar thermodynamic properties, however, the DeltaG of folding for PAAD and CARD members are, respectively, -1.4 and -5.5 kcal mol(-1). This difference is attributed to less alpha helical content for PAAD due to the unfolding of helix-3 that lowers bonded energy and increases disorder when compared to CARD members. Despite identical fold between PAAD and CARD families but limited sequence identity, there are striking differences in the thermodynamics of both families.

Target selection of soluble protein complexes for structural proteomics studies.

BACKGROUND: Protein expression in E. coli is the most commonly used system to produce protein for structural studies, because it is fast and inexpensive and can produce large quantity of proteins. However, when proteins from other species such as mammalian are produced in this system, problems of protein expression and solubility arise 1. Structural genomics project are currently investigating proteomics pipelines that would produce sufficient quantities of recombinant proteins for structural studies of protein complexes. To investigate how the E. coli protein expression system could be used for this purpose, we purified apoptotic binary protein complexes formed between members of the Caspase Associated Recruitment Domain (CARD) family. RESULTS: A combinatorial approach to the generation of protein complexes was performed between members of the CARD domain protein family that have the ability to form hetero-dimers between each other. In our method, each gene coding for a specific protein partner is cloned in pET-28b (Novagen) and PGEX2T (Amersham) expression vectors. All combinations of protein complexes are then obtained by reconstituting complexes from purified components in native conditions, after denaturation-renaturation or co-expression. Our study applied to 14 soluble CARD domain proteins revealed that co-expression studies perform better than native and denaturation-renaturation methods. In this study, we confirm existing interactions obtained in vivoin mammalian cells and also predict new interactions. CONCLUSION: The simplicity of this screening method could be easily scaled up to identify soluble protein complexes for structural genomic projects. This study reports informative statistics on the solubility of human protein complexes expressed in E.coli belonging to the human CARD protein family.

Interdomain and membrane interactions of CTP:phosphocholine cytidylyltransferase revealed via limited proteolysis and mass spectrometry.

CTP:phosphocholine cytidylyltransferase (CCT) is a multi-domain enzyme that regulates phosphatidylcholine synthesis. It converts to an active form upon binding cell membranes, and interdomain dissociations have been hypothesized to accompany this process. To identify these interdomain and membrane interactions, the tertiary structures of three forms of CCTalpha were probed by monitoring accessibility to proteases. Time-limited digestion with chymotrypsin or arginine C of soluble CCTalpha (CCT(sol)), phospholipid vesicle-bound CCT (CCT(mem)), and a soluble constitutively active CCT truncated at amino acid 236 generated complex mixtures of peptides that were resolved and identified by gel electrophoresis/immunoblotting and by matrix-assisted laser desorption/ionization-mass spectrometry, with or without coupling to capillary liquid chromatography. Identification of cleavage sites enabled assembly of peptide bond accessibility maps for each CCT form. Our results reveal a approximately 80-residue core within the catalytic domain (domain C) as the most inaccessible region in all three forms and the C-terminal phosphorylation domain as the most accessible. Membrane binding has little effect on the protease accessibility of these domains. To map the protease sites onto the catalytic domain, its three-dimensional structure was modeled from the atomic coordinates of glycerol-phosphate cytidylyltransferase (Protein Data Bank code 1COZ). The protease inaccessibility of most sites in domain C could be explained by burial or location within secondary structural elements. The accessibility of the N-terminal domain (domain N) was enhanced upon membrane binding. Residues Phe(234)-Leu(303) were inaccessible in CCT(mem), suggesting burial in the membrane. Surprisingly, residues Leu(274)-Leu(303) of this domain were also inaccessible in CCT(sol). We propose that this region is buried by interdomain contacts with domain N in CCT(sol). Membrane binding and burial of domain M in the lipid bilayer may disrupt this interaction, leading to increased exposure of sites in domain N.

Interaction profile-based protein classification of death domain.

BACKGROUND: The increasing number of protein sequences and 3D structure obtained from genomic initiatives is leading many of us to focus on proteomics, and to dedicate our experimental and computational efforts on the creation and analysis of information derived from 3D structure. In particular, the high-throughput generation of protein-protein interaction data from a few organisms makes such an approach very important towards understanding the molecular recognition that make-up the entire protein-protein interaction network. Since the generation of sequences, and experimental protein-protein interactions increases faster than the 3D structure determination of protein complexes, there is tremendous interest in developing in silico methods that generate such structure for prediction and classification purposes. In this study we focused on classifying protein family members based on their protein-protein interaction distinctiveness. Structure-based classification of protein-protein interfaces has been described initially by Ponstingl et al. 1 and more recently by Valdar et al. 2 and Mintseris et al. 3, from complex structures that have been solved experimentally. However, little has been done on protein classification based on the prediction of protein-protein complexes obtained from homology modeling and docking simulation. RESULTS: We have developed an in silico classification system entitled HODOCO (Homology modeling, Docking and Classification Oracle), in which protein Residue Potential Interaction Profiles (RPIPS) are used to summarize protein-protein interaction characteristics. This system applied to a dataset of 64 proteins of the death domain superfamily was used to classify each member into its proper subfamily. Two classification methods were attempted, heuristic and support vector machine learning. Both methods were tested with a 5-fold cross-validation. The heuristic approach yielded a 61% average accuracy, while the machine learning approach yielded an 89% average accuracy. CONCLUSION: We have confirmed the reliability and potential value of classifying proteins via their predicted interactions. Our results are in the same range of accuracy as other studies that classify protein-protein interactions from 3D complex structure obtained experimentally. While our classification scheme does not take directly into account sequence information our results are in agreement with functional and sequence based classification of death domain family members.