Synaptogyrin-3 mediates presynaptic dysfunction induced by Tau

Synaptic dysfunction is an early pathological feature of neurodegenerative diseases associated with Tau, including Alzheimer's disease. Interfering with early synaptic dysfunction may be therapeutically beneficial to prevent cognitive decline and disease progression, but the mechanisms underlying synaptic defects associated with Tau are unclear. In disease conditions, Tau mislocalizes into pre- and postsynaptic compartments; here we show that, under pathological conditions, Tau binds to presynaptic vesicles in Alzheimer's disease patient brain. We define that the binding of Tau to synaptic vesicles is mediated by the transmembrane vesicle protein Synaptogyrin-3. In fly and mouse models of Tauopathy, reduction of Synaptogyrin-3 prevents the association of presynaptic Tau with vesicles, alleviates Tau-induced defects in vesicle mobility, and restores neurotransmitter release. This work therefore identifies Synaptogyrin-3 as the binding partner of Tau on synaptic vesicles, revealing a new presynapse-specific Tau interactor, which may contribute to early synaptic dysfunction in neurodegenerative diseases associated with Tau

Testing the additional predictive value of high-dimensional molecular data

While high-dimensional molecular data such as microarray gene expression data have been used for disease outcome prediction or diagnosis purposes for about ten years in biomedical research, the question of the additional predictive value of such data given that classical predictors are already available has long been under-considered in the bioinformatics literature. We suggest an intuitive permutation-based testing procedure for assessing the additional predictive value of high-dimensional molecular data. Our method combines two well-known statistical tools: logistic regression and boosting regression. We give clear advice for the choice of the only method parameter (the number of boosting iterations). In simulations, our novel approach is found to have very good power in different settings, e.g. few strong predictors or many weak predictors. For illustrative purpose, it is applied to two publicly available cancer data sets. Our simple and computationally efficient approach can be used to globally assess the additional predictive power of a large number of candidate predictors given that a few clinical covariates or a known prognostic index are already available

Nogo-B regulates migration and contraction of airway smooth muscle cells by decreasing ARPC 2/3 and increasing MYL-9 expression

<p>Abstract</p> <p>Background</p> <p>Abnormal proliferation, apoptosis, migration and contraction of airway smooth muscle (ASM) cells in airway remodeling in asthma are basically excessive repair responses to a network of inflammatory mediators such as PDGF, but the mechanisms of such responses remain unclear. Nogo-B, a member of the reticulum family 4(RTN4), is known to play a key role in arteriogenesis and tissue repair. Further studies are needed to elucidate the role of Nogo-B in airway smooth muscle abnormalities.</p> <p>Methods</p> <p>A mouse model of chronic asthma was established by repeated OVA inhalation and subjected to Nogo-B expression analysis using immunohistochemistry and Western Blotting. Then, primary human bronchial smooth muscle cells (HBSMCs) were cultured <it>in vitro </it>and a siRNA interference was performed to knockdown the expression of Nogo-B in the cells. The effects of Nogo-B inhibition on PDGF-induced HBSMCs proliferation, migration and contraction were evaluated. Finally, a proteomic analysis was conducted to unveil the underlying mechanisms responsible for the function of Nogo-B.</p> <p>Results</p> <p>Total Nogo-B expression was approximately 3.08-fold lower in chronic asthmatic mice compared to naïve mice, which was obvious in the smooth muscle layer of the airways. Interference of Nogo-B expression by siRNA resulted nearly 96% reduction in mRNA in cultured HBSMCs. In addition, knockdown of Nogo-B using specific siRNA significantly decreased PDGF-induced migration of HBSMCs by 2.3-fold, and increased the cellular contraction by 16% compared to negative controls, but had limited effects on PDGF-induced proliferation. Furthermore, using proteomic analysis, we demonstrate that the expression of actin related protein 2/3 complex subunit 5 (ARPC 2/3) decreased and, myosin regulatory light chain 9 isoform a (MYL-9) increased after Nogo-B knockdown.</p> <p>Conclusions</p> <p>These data define a novel role for Nogo-B in airway remodeling in chronic asthma. Endogenous Nogo-B, which may exert its effects through ARPC 2/3 and MYL-9, is necessary for the migration and contraction of airway smooth muscle cells.</p

PepShell : visualization of conformational proteomics data

Proteins are dynamic molecules; they undergo crucial conformational changes induced by post-translational modifications and by binding of cofactors or other molecules. The characterization of these conformational changes and their relation to protein function is a central goal of structural biology. Unfortunately, most conventional methods to obtain structural information do not provide information on protein dynamics. Therefore, mass spectrometry-based approaches, such as limited proteolysis, hydrogen-deuterium exchange, and stable-isotope labeling, are frequently used to characterize protein conformation and dynamics, yet the interpretation of these data can be cumbersome and time consuming. Here, we present PepShell, a tool that allows interactive data analysis of mass spectrometry-based conformational proteomics studies by visualization of the identified peptides both at the sequence and structure levels. Moreover, PepShell allows the comparison of experiments under different conditions, including different proteolysis times or binding of the protein to different substrates or inhibitors

Expression of eicosanoid receptors subtypes and eosinophilic inflammation: implication on chronic rhinosinusitis

BACKGROUND: Eicosanoid receptors are G-protein-coupled receptors playing an important immunomodulatory role in airway diseases. However, there is little information on the expression of these receptors and their link with eosinophilic inflammation in paranasal sinus diseases. We aimed with this study to investigate the tissue expression of leukotrienes and prostaglandin E2 receptors in chronic rhinosinusitis patients and the link of this regulation with eosinophilic inflammation. METHODS: Samples were prepared from nasal tissue of patients with chronic rhinosinusitis without nasal polyps (CRS, n = 11), with nasal polyps (CRS-NP, n = 13) and healthy subjects (Controls, n = 6). mRNA expression of CysLT(1), CysLT(2), BLT(1), BLT(2), E-prostanoid receptors (EP(1), EP(2), EP(3), EP(4)) and sol-IL-5Rα was determined by real-time PCR. Concentrations of PGE2, LTC4/D4/E4, LTB4 and sol-IL-5Rα were determined by ELISA and of ECP by ImmunoCap. Protein expression and tissue localization of eicosanoid receptors and activated eosinophils were evaluated by immunohistochemistry. RESULTS: CysLT(1 )mRNA expression was significantly increased in CRS-NP compared to CRS and controls, and CRS compared to controls, whereas CysLT(2 )mRNA was enhanced in both CRS groups without differences between them. Levels of both receptors correlated to the number of activated eosinophils, sol-IL-5Rα, ECP and LTC(4)/D(4)/E(4 )concentrations in the disease groups. PGE(2 )protein concentrations and prostanoid receptors EP(1 )and EP(3 )were down-regulated in the CRS-NP tissue vs. CRS and controls, whereas EP(2 )and EP(4 )expression was enhanced in CRS and CRS-NP patients vs. controls. No differences in BLT receptors were observed between patients and controls. CONCLUSION: CyLTs receptors are up-regulated in nasal polyp tissue and their expression correlate with eosinophilic inflammation supporting previous results. Eicosanoid receptors mRNA pattern observed suggests that down-regulation of EP(1 )and EP(3 )in CRS-NP and up-regulation EP(2 )and EP(4 )in CRS and CRS-NP groups may have some role in the development of the diseases and their regulation may not be directly linked to eosinophil activation but involve post-transcriptional events mainly related to other inflammatory cell sources

A voting approach to identify a small number of highly predictive genes using multiple classifiers

<p>Abstract</p> <p>Background</p> <p>Microarray gene expression profiling has provided extensive datasets that can describe characteristics of cancer patients. An important challenge for this type of data is the discovery of gene sets which can be used as the basis of developing a clinical predictor for cancer. It is desirable that such gene sets be compact, give accurate predictions across many classifiers, be biologically relevant and have good biological process coverage.</p> <p>Results</p> <p>By using a new type of multiple classifier voting approach, we have identified gene sets that can predict breast cancer prognosis accurately, for a range of classification algorithms. Unlike a wrapper approach, our method is not specialised towards a single classification technique. Experimental analysis demonstrates higher prediction accuracies for our sets of genes compared to previous work in the area. Moreover, our sets of genes are generally more compact than those previously proposed. Taking a biological viewpoint, from the literature, most of the genes in our sets are known to be strongly related to cancer.</p> <p>Conclusion</p> <p>We show that it is possible to obtain superior classification accuracy with our approach and obtain a compact gene set that is also biologically relevant and has good coverage of different biological processes.</p

Large-scale comparative genomic ranking of taxonomically restricted genes (TRGs) in bacterial and archaeal genomes

BACKGROUND: Lineage-specific, or taxonomically restricted genes (TRGs), especially those that are species and strain-specific, are of special interest because they are expected to play a role in defining exclusive ecological adaptations to particular niches. Despite this, they are relatively poorly studied and little understood, in large part because many are still orphans or only have homologues in very closely related isolates. This lack of homology confounds attempts to establish the likelihood that a hypothetical gene is expressed and, if so, to determine the putative function of the protein. METHODOLOGY/PRINCIPAL FINDINGS: We have developed "QIPP" ("Quality Index for Predicted Proteins"), an index that scores the "quality" of a protein based on non-homology-based criteria. QIPP can be used to assign a value between zero and one to any protein based on comparing its features to other proteins in a given genome. We have used QIPP to rank the predicted proteins in the proteomes of Bacteria and Archaea. This ranking reveals that there is a large amount of variation in QIPP scores, and identifies many high-scoring orphans as potentially "authentic" (expressed) orphans. There are significant differences in the distributions of QIPP scores between orphan and non-orphan genes for many genomes and a trend for less well-conserved genes to have lower QIPP scores. CONCLUSIONS: The implication of this work is that QIPP scores can be used to further annotate predicted proteins with information that is independent of homology. Such information can be used to prioritize candidates for further analysis. Data generated for this study can be found in the OrphanMine at http://www.genomics.ceh.ac.uk/orphan_mine