Moult cycle specific differential gene expression profiling of the crab Portunus pelagicus

Background: Crustacean moulting is a complex process involving many regulatory pathways. A holistic approach to examine differential gene expression profiles of transcripts relevant to the moulting process, across all moult cycle stages, was used in this study. Custom cDNA microarrays were constructed for Portunus pelagicus. The printed arrays contained 5000 transcripts derived from both the whole organism, and from individual organs such as the brain, eyestalk, mandibular organ and Y-organ from all moult cycle stages.Results: A total of 556 clones were sequenced from the cDNA libraries used to construct the arrays. These cDNAs represented 175 singletons and 62 contigs, resulting in 237 unique putative genes. The gene sequences were classified into the following biological functions: cuticular proteins associated with arthropod exoskeletons, farnesoic acid O-methyltransferase (FaMeT), proteins belonging to the hemocyanin gene family, lectins, proteins relevant to lipid metabolism, mitochondrial proteins, muscle related proteins, phenoloxidase activators and ribosomal proteins. Moult cycle-related differential expression patterns were observed for many transcripts. Of particular interest were those relating to the formation and hardening of the exoskeleton, and genes associated with cell respiration and energy metabolism.Conclusions: The expression data presented here provide a chronological depiction of the molecular events associated with the biological changes that occur during the crustacean moult cycle. Tracing the temporal expression patterns of a large variety of transcripts involved in the moult cycle of P. pelagicus can provide a greater understanding of gene function, interaction, and regulation of both known and new genes with respect to the moulting process

Structure of the St. Louis encephalitis virus postfusion envelope trimer

St. Louis encephalitis virus (SLEV) is a mosquito-borne flavivirus responsible for several human encephalitis outbreaks over the last 80 years. Mature flavivirus virions are coated with dimeric envelope (E) proteins that mediate attachment and fusion with host cells. E is a class II fusion protein, the hallmark of which is a distinct dimer-to-trimer rearrangement that occurs upon endosomal acidification and insertion of hydrophobic fusion peptides into the endosomal membrane. Herein, we report the crystal structure of SLEV E in the posfusion trimer conformation. The structure revealed specific features that differentiate SLEV E from trimers of related flavi- and alphaviruses. SLEV E fusion loops have distinct intermediate spacing such that they are positioned further apart than previously observed in flaviviruses but closer together than Semliki Forest virus, an alphavirus. Domains II and III (DII and DIII) of SLEV E also adopt different angles relative to DI, which suggests that the DI-DII joint may accommodate spheroidal motions. However, trimer interfaces are well conserved among flaviviruses, so it is likely the differences observed represent structural features specific to SLEV function. Analysis of surface potentials revealed a basic platform underneath flavivirus fusion loops that may interact with the anionic lipid head groups found in membranes. Taken together, these results highlight variations in E structure and assembly that may direct virus-specific interactions with host determinants to influence pathogenesis

Computational Prediction of Heme-Binding Residues by Exploiting Residue Interaction Network

Computational identification of heme-binding residues is beneficial for predicting and designing novel heme proteins. Here we proposed a novel method for heme-binding residue prediction by exploiting topological properties of these residues in the residue interaction networks derived from three-dimensional structures. Comprehensive analysis showed that key residues located in heme-binding regions are generally associated with the nodes with higher degree, closeness and betweenness, but lower clustering coefficient in the network. HemeNet, a support vector machine (SVM) based predictor, was developed to identify heme-binding residues by combining topological features with existing sequence and structural features. The results showed that incorporation of network-based features significantly improved the prediction performance. We also compared the residue interaction networks of heme proteins before and after heme binding and found that the topological features can well characterize the heme-binding sites of apo structures as well as those of holo structures, which led to reliable performance improvement as we applied HemeNet to predicting the binding residues of proteins in the heme-free state. HemeNet web server is freely accessible at http://mleg.cse.sc.edu/hemeNet/

HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information

<p>Abstract</p> <p>Background</p> <p>Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues.</p> <p>Results</p> <p>Here we introduced an efficient algorithm HemeBIND for predicting heme binding residues by integrating structural and sequence information. We systematically investigated the characteristics of binding interfaces based on a non-redundant dataset of heme-protein complexes. It was found that several sequence and structural attributes such as evolutionary conservation, solvent accessibility, depth and protrusion clearly illustrate the differences between heme binding and non-binding residues. These features can then be separately used or combined to build the structure-based classifiers using support vector machine (SVM). The results showed that the information contained in these features is largely complementary and their combination achieved the best performance. To further improve the performance, an attempt has been made to develop a post-processing procedure to reduce the number of false positives. In addition, we built a sequence-based classifier based on SVM and sequence profile as an alternative when only sequence information can be used. Finally, we employed a voting method to combine the outputs of structure-based and sequence-based classifiers, which demonstrated remarkably better performance than the individual classifier alone.</p> <p>Conclusions</p> <p>HemeBIND is the first specialized algorithm used to predict binding residues in protein structures for heme ligands. Extensive experiments indicated that both the structure-based and sequence-based methods have effectively identified heme binding residues while the complementary relationship between them can result in a significant improvement in prediction performance. The value of our method is highlighted through the development of HemeBIND web server that is freely accessible at <url>http://mleg.cse.sc.edu/hemeBIND/</url>.</p

Genetic polymorphisms of the RAS-cytokine pathway and chronic kidney disease

Chronic kidney disease (CKD) in children is irreversible. It is associated with renal failure progression and atherosclerotic cardiovascular (CV) abnormalities. Nearly 60% of children with CKD are affected since birth with congenital or inherited kidney disorders. Preliminary evidence primarily from adult CKD studies indicates common genetic risk factors for CKD and atherosclerotic CV disease. Although multiple physiologic pathways share common genes for CKD and CV disease, substantial evidence supports our attention to the renin angiotensin system (RAS) and the interlinked inflammatory cascade because they modulate the progressions of renal and CV disease. Gene polymorphisms in the RAS-cytokine pathway, through altered gene expression of inflammatory cytokines, are potential factors that modulate the rate of CKD progression and CV abnormalities in patients with CKD. For studying such hypotheses, the cooperative efforts among scientific groups and the availability of robust and affordable technologies to genotype thousands of single nucleotide polymorphisms (SNPs) across the genome make genome-wide association studies an attractive paradigm for studying polygenic diseases such as CKD. Although attractive, such studies should be interpreted carefully, with a fundamental understanding of their potential weaknesses. Nevertheless, whole-genome association studies for diabetic nephropathy and future studies pertaining to other types of CKD will offer further insight for the development of targeted interventions to treat CKD and associated atherosclerotic CV abnormalities in the pediatric CKD population

Comparative genomic analysis of innate immunity reveals novel and conserved components in crustacean food crop species

Abstract Background Growing global demands for crustacean food crop species have driven large investments in aquaculture research worldwide. However, large-scale production is susceptible to pathogen-mediated destruction particularly in developing economies. Thus, a thorough understanding of the immune system components of food crop species is imperative for research to combat pathogens. Results Through a comparative genomics approach utilising extant data from 55 species, we describe the innate immune system of the class Malacostraca, which includes all food crop species. We identify 7407 malacostracan genes from 39 gene families implicated in different aspects of host defence and demonstrate dynamic evolution of innate immunity components within this group. Malacostracans have achieved flexibility in recognising infectious agents through divergent evolution and expansion of pathogen recognition receptors genes. Antiviral RNAi, Toll and JAK-STAT signal transduction pathways have remained conserved within Malacostraca, although the Imd pathway appears to lack several key components. Immune effectors such as the antimicrobial peptides (AMPs) have unique evolutionary profiles, with many malacostracan AMPs not found in other arthropods. Lastly, we describe four putative novel immune gene families, potentially representing important evolutionary novelties of the malacostracan immune system. Conclusion Our analyses across the broader Malacostraca have allowed us to not only draw analogies with other arthropods but also to identify evolutionary novelties in immune modulation components and form strong hypotheses as to when key pathways have evolved or diverged. This will serve as a key resource for future immunology research in crustacean food crops

THE RED FOOT OF A LEPIDOPLEURID CHITON - EVIDENCE FOR TISSUE HEMOGLOBINS

Volume: 30Start Page: 244End Page: 24