An emerging cyberinfrastructure for biodefense pathogen and pathogen–host data

The NIAID-funded Biodefense Proteomics Resource Center (RC) provides storage, dissemination, visualization and analysis capabilities for the experimental data deposited by seven Proteomics Research Centers (PRCs). The data and its publication is to support researchers working to discover candidates for the next generation of vaccines, therapeutics and diagnostics against NIAID's Category A, B and C priority pathogens. The data includes transcriptional profiles, protein profiles, protein structural data and host–pathogen protein interactions, in the context of the pathogen life cycle in vivo and in vitro. The database has stored and supported host or pathogen data derived from Bacillus, Brucella, Cryptosporidium, Salmonella, SARS, Toxoplasma, Vibrio and Yersinia, human tissue libraries, and mouse macrophages. These publicly available data cover diverse data types such as mass spectrometry, yeast two-hybrid (Y2H), gene expression profiles, X-ray and NMR determined protein structures and protein expression clones. The growing database covers over 23 000 unique genes/proteins from different experiments and organisms. All of the genes/proteins are annotated and integrated across experiments using UniProt Knowledgebase (UniProtKB) accession numbers. The web-interface for the database enables searching, querying and downloading at the level of experiment, group and individual gene(s)/protein(s) via UniProtKB accession numbers or protein function keywords. The system is accessible at http://www.proteomicsresource.org/

A Structure-Based Approach for Detection of Thiol Oxidoreductases and Their Catalytic Redox-Active Cysteine Residues

Cysteine (Cys) residues often play critical roles in proteins, for example, in the formation of structural disulfide bonds, metal binding, targeting proteins to the membranes, and various catalytic functions. However, the structural determinants for various Cys functions are not clear. Thiol oxidoreductases, which are enzymes containing catalytic redox-active Cys residues, have been extensively studied, but even for these proteins there is little understanding of what distinguishes their catalytic redox Cys from other Cys functions. Herein, we characterized thiol oxidoreductases at a structural level and developed an algorithm that can recognize these enzymes by (i) analyzing amino acid and secondary structure composition of the active site and its similarity to known active sites containing redox Cys and (ii) calculating accessibility, active site location, and reactivity of Cys. For proteins with known or modeled structures, this method can identify proteins with catalytic Cys residues and distinguish thiol oxidoreductases from the enzymes containing other catalytic Cys types. Furthermore, by applying this procedure to Saccharomyces cerevisiae proteins containing conserved Cys, we could identify the majority of known yeast thiol oxidoreductases. This study provides insights into the structural properties of catalytic redox-active Cys and should further help to recognize thiol oxidoreductases in protein sequence and structure databases

Searching the protein structure database for ligand-binding site similarities using CPASS v.2

<p>Abstract</p> <p>Background</p> <p>A recent analysis of protein sequences deposited in the NCBI RefSeq database indicates that ~8.5 million protein sequences are encoded in prokaryotic and eukaryotic genomes, where ~30% are explicitly annotated as "hypothetical" or "uncharacterized" protein. Our Comparison of Protein Active-Site Structures (CPASS v.2) database and software compares the sequence and structural characteristics of experimentally determined ligand binding sites to infer a functional relationship in the absence of global sequence or structure similarity. CPASS is an important component of our Functional Annotation Screening Technology by NMR (FAST-NMR) protocol and has been successfully applied to aid the annotation of a number of proteins of unknown function.</p> <p>Findings</p> <p>We report a major upgrade to our CPASS software and database that significantly improves its broad utility. CPASS v.2 is designed with a layered architecture to increase flexibility and portability that also enables job distribution over the Open Science Grid (OSG) to increase speed. Similarly, the CPASS interface was enhanced to provide more user flexibility in submitting a CPASS query. CPASS v.2 now allows for both automatic and manual definition of ligand-binding sites and permits pair-wise, one versus all, one versus list, or list versus list comparisons. Solvent accessible surface area, ligand root-mean square difference, and Cβ distances have been incorporated into the CPASS similarity function to improve the quality of the results. The CPASS database has also been updated.</p> <p>Conclusions</p> <p>CPASS v.2 is more than an order of magnitude faster than the original implementation, and allows for multiple simultaneous job submissions. Similarly, the CPASS database of ligand-defined binding sites has increased in size by ~ 38%, dramatically increasing the likelihood of a positive search result. The modification to the CPASS similarity function is effective in reducing CPASS similarity scores for false positives by ~30%, while leaving true positives unaffected. Importantly, receiver operating characteristics (ROC) curves demonstrate the high correlation between CPASS similarity scores and an accurate functional assignment. As indicated by distribution curves, scores ≥ 30% infer a functional similarity. Software URL: <url>http://cpass.unl.edu</url>.</p

Radiation induced CNS toxicity – molecular and cellular mechanisms

Radiotherapy of tumours proximal to normal CNS structures is limited by the sensitivity of the normal tissue. Prior to the development of prophylactic strategies or treatment protocols a detailed understanding of the mechanisms of radiation induced CNS toxicity is mandatory. Histological analysis of irradiated CNS specimens defines possible target structures prior to a delineation of cellular and molecular mechanisms. Several lesions can be distinguished: Demyelination, proliferative and degenerative glial reactions, endothelial cell loss and capillary occlusion. All changes are likely to result from complex alterations within several functional CNS compartments. Thus, a single mechanism responsible cannot be separated. At least four factors contribute to the development of CNS toxicity: (1) damage to vessel structures; (2) deletion of oligodendrocyte-2 astrocyte progenitors (O-2A) and mature oligodendrocytes; (3) deletion of neural stem cell populations in the hippocampus, cerebellum and cortex; (4) generalized alterations of cytokine expression. Several underlying cellular and molecular mechanisms involved in radiation induced CNS toxicity have been identified. The article reviews the currently available data on the cellular and molecular basis of radiation induced CNS side effects.   http://www.bjcancer.com © 2001 Cancer Research Campaig

The Chemotactic Defect in Wiskott-Aldrich Syndrome Macrophages Is Due to the Reduced Persistence of Directional Protrusions

Wiskott-Aldrich syndrome protein (WASp) is an actin nucleation promoting factor that is required for macrophages to directionally migrate towards various chemoattractants. The chemotaxis defect of WASp-deficient cells and its activation by Cdc42 in vivo suggest that WASp plays a role in directional sensing, however, its precise role in macrophage chemotaxis is still unclear. Using shRNA-mediated downregulation of WASp in the murine monocyte/macrophage cell line RAW/LR5 (shWASp), we found that WASp was responsible for the initial wave of actin polymerization in response to global stimulation with CSF-1, which in Dictyostelium discoideum amoebae and carcinoma cells has been correlated with the ability to migrate towards chemoattractants. Real-time monitoring of shWASp cells, as well as WASp−/− bone marrow-derived macrophages (BMMs), in response to a CSF-1 gradient revealed that the protrusions from WASp-deficient cells were directional, showing intact directional sensing. However, the protrusions from WASp-deficient cells demonstrated reduced persistence compared to their respective control shRNA and wild-type cells. Further examination showed that tyrosine phosphorylation of WASp was required for both the first wave of actin polymerization following global CSF-1 stimulation and proper directional responses towards CSF-1. Importantly, the PI3K, Rac1 and WAVE2 proteins were incorporated normally in CSF-1 – elicited protrusions in the absence of WASp, suggesting that membrane protrusion driven by the WAVE2 complex signaling is intact. Collectively, these results suggest that WASp and its phosphorylation play critical roles in coordinating the actin cytoskeleton rearrangements necessary for the persistence of protrusions required for directional migration of macrophages towards CSF-1

S100B as a potential biomarker and therapeutic target in multiple sclerosis

Multiple sclerosis (MS) pathology is characterized by neuroinflammation and demyelination. Recently, the inflammatory molecule S100B was identified in cerebrospinal fluid (CSF) and serum of MS patients. Although seen as an astrogliosis marker, lower/physiological levels of S100B are involved in oligodendrocyte differentiation/maturation. Nevertheless, increased S100B levels released upon injury may induce glial reactivity and oligodendrocyte demise, exacerbating tissue damage during an MS episode or delaying the following remyelination. Here, we aimed to unravel the functional role of S100B in the pathogenesis of MS. Elevated S100B levels were detected in the CSF of relapsing-remitting MS patients at diagnosis. Active demyelinating MS lesions showed increased expression of S100B and its receptor, the receptor for advanced glycation end products (RAGE), in the lesion area, while chronic active lesions displayed increased S100B in demyelinated areas with lower expression of RAGE in the rim. Interestingly, reactive astrocytes were identified as the predominant cellular source of S100B, whereas RAGE was expressed by activated microglia/macrophages. Using an ex vivo demyelinating model, cerebral organotypic slice cultures treated with lysophosphatidylcholine (LPC), we observed a marked elevation of S100B upon demyelination, which co-localized mostly with astrocytes. Inhibition of S100B action using a directed antibody reduced LPC-induced demyelination, prevented astrocyte reactivity and abrogated the expression of inflammatory and inflammasome-related molecules. Overall, high S100B expression in MS patient samples suggests its usefulness as a diagnostic biomarker for MS, while the beneficial outcome of its inhibition in our demyelinating model indicates S100B as an emerging therapeutic target in MS.This work was supported by Medal of Honor L’Oréal for Women in Science (FCT, UNESCO, L’Óreal) and innovation grant (Ordem dos Farmacêuticos) to AF, a post-doctoral grant from Fundação para a Ciência e Tecnologia (FCT-SFRH/BPD/96794/2013) and a DuPré Grant from the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) to AB, and by FCT-Pest- OE/SAU/UI4013 to iMed.ULisboa.info:eu-repo/semantics/publishedVersio

Prediction of acute multiple sclerosis relapses by transcription levels of peripheral blood cells

<p>Abstract</p> <p>Background</p> <p>The ability to predict the spatial frequency of relapses in multiple sclerosis (MS) would enable physicians to decide when to intervene more aggressively and to plan clinical trials more accurately.</p> <p>Methods</p> <p>In the current study our objective was to determine if subsets of genes can predict the time to the next acute relapse in patients with MS. Data-mining and predictive modeling tools were utilized to analyze a gene-expression dataset of 94 non-treated patients; 62 patients with definite MS and 32 patients with clinically isolated syndrome (CIS). The dataset included the expression levels of 10,594 genes and annotated sequences corresponding to 22,215 gene-transcripts that appear in the microarray.</p> <p>Results</p> <p>We designed a two stage predictor. The first stage predictor was based on the expression level of 10 genes, and predicted the time to next relapse with a resolution of 500 days (error rate 0.079, p < 0.001). If the predicted relapse was to occur in less than 500 days, a second stage predictor based on an additional different set of 9 genes was used to give a more accurate estimation of the time till the next relapse (in resolution of 50 days). The error rate of the second stage predictor was 2.3 fold lower than the error rate of random predictions (error rate = 0.35, p < 0.001). The predictors were further evaluated and found effective both for untreated MS patients and for MS patients that subsequently received immunomodulatory treatments after the initial testing (the error rate of the first level predictor was < 0.18 with p < 0.001 for all the patient groups).</p> <p>Conclusion</p> <p>We conclude that gene expression analysis is a valuable tool that can be used in clinical practice to predict future MS disease activity. Similar approach can be also useful for dealing with other autoimmune diseases that characterized by relapsing-remitting nature.</p