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Author Fan, Y.; Wang, S.; Hernandez, J.; Yenigun, V.B.; Hertlein, G.; Fogarty, C.E.; Lindblad, J.L.; Bergmann, A.
Title Genetic models of apoptosis-induced proliferation decipher activation of JNK and identify a requirement of EGFR signaling for tissue regenerative responses in Drosophila Type Journal Article
Year 2014 Publication PLoS Genetics Abbreviated Journal PLoS Genet
Volume 10 Issue 1 Pages (down) e1004131
Keywords
Abstract Recent work in several model organisms has revealed that apoptotic cells are able to stimulate neighboring surviving cells to undergo additional proliferation, a phenomenon termed apoptosis-induced proliferation. This process depends critically on apoptotic caspases such as Dronc, the Caspase-9 ortholog in Drosophila, and may have important implications for tumorigenesis. While it is known that Dronc can induce the activity of Jun N-terminal kinase (JNK) for apoptosis-induced proliferation, the mechanistic details of this activation are largely unknown. It is also controversial if JNK activity occurs in dying or in surviving cells. Signaling molecules of the Wnt and BMP families have been implicated in apoptosis-induced proliferation, but it is unclear if they are the only ones. To address these questions, we have developed an efficient assay for screening and identification of genes that regulate or mediate apoptosis-induced proliferation. We have identified a subset of genes acting upstream of JNK activity including Rho1. We also demonstrate that JNK activation occurs both in apoptotic cells as well as in neighboring surviving cells. In a genetic screen, we identified signaling by the EGFR pathway as important for apoptosis-induced proliferation acting downstream of JNK signaling. These data underscore the importance of genetic screening and promise an improved understanding of the mechanisms of apoptosis-induced proliferation.
Address University of Massachusetts Medical School, Department of Cancer Biology, Worcester, Massachusetts, United States of America ; Graduate Program in Developmental Biology, Baylor College of Medicine, Houston, Texas, United States of America ; MD Anderson Cancer Center, Department of Biochemistry & Molecular Biology, Houston, Texas, United States of America
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1553-7390 ISBN Medium
Area Expedition Conference
Notes PMID:24497843 Approved no
Call Number refbase @ admin @ Serial 35558
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Author Davies, M.R.; Broadbent, S.E.; Harris, S.R.; Thomson, N.R.; van der Woude, M.W.
Title Horizontally acquired glycosyltransferase operons drive salmonellae lipopolysaccharide diversity Type Journal Article
Year 2013 Publication PLoS Genetics Abbreviated Journal PLoS Genet
Volume 9 Issue 6 Pages (down) e1003568
Keywords Antigens, Bacterial/*genetics/metabolism; Gene Transfer, Horizontal/*genetics; Genetic Variation; Genome, Bacterial; Glycosyltransferases/*genetics; Gram-Negative Bacteria/genetics; Host-Pathogen Interactions/genetics/*immunology; Humans; Lipopolysaccharides/genetics; Salmonella enterica/genetics/*pathogenicity
Abstract The immunodominant lipopolysaccharide is a key antigenic factor for Gram-negative pathogens such as salmonellae where it plays key roles in host adaptation, virulence, immune evasion, and persistence. Variation in the lipopolysaccharide is also the major differentiating factor that is used to classify Salmonella into over 2600 serovars as part of the Kaufmann-White scheme. While lipopolysaccharide diversity is generally associated with sequence variation in the lipopolysaccharide biosynthesis operon, extraneous genetic factors such as those encoded by the glucosyltransferase (gtr) operons provide further structural heterogeneity by adding additional sugars onto the O-antigen component of the lipopolysaccharide. Here we identify and examine the O-antigen modifying glucosyltransferase genes from the genomes of Salmonella enterica and Salmonella bongori serovars. We show that Salmonella generally carries between 1 and 4 gtr operons that we have classified into 10 families on the basis of gtrC sequence with apparent O-antigen modification detected for five of these families. The gtr operons localize to bacteriophage-associated genomic regions and exhibit a dynamic evolutionary history driven by recombination and gene shuffling events leading to new gene combinations. Furthermore, evidence of Dam- and OxyR-dependent phase variation of gtr gene expression was identified within eight gtr families. Thus, as O-antigen modification generates significant intra- and inter-strain phenotypic diversity, gtr-mediated modification is fundamental in assessing Salmonella strain variability. This will inform appropriate vaccine and diagnostic approaches, in addition to contributing to our understanding of host-pathogen interactions.
Address Centre for Immunology and Infection, Hull York Medical School and the Department of Biology, University of York, York, UK
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1553-7390 ISBN Medium
Area Expedition Conference
Notes PMID:23818865 Approved no
Call Number refbase @ user @ Serial 24684
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Author Bendl, J.; Stourac, J.; Salanda, O.; Pavelka, A.; Wieben, E.D.; Zendulka, J.; Brezovsky, J.; Damborsky, J.
Title PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations Type Journal Article
Year 2014 Publication PLoS Computational Biology Abbreviated Journal PLoS Comput Biol
Volume 10 Issue 1 Pages (down) e1003440
Keywords
Abstract Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp.
Address Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic ; Center of Biomolecular and Cellular Engineering, International Centre for Clinical Research, St. Anne's University Hospital Brno, Brno, Czech Republic
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1553-734X ISBN Medium
Area Expedition Conference
Notes PMID:24453961 Approved no
Call Number refbase @ user @ Serial 53539
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Author Wallach, T.; Schellenberg, K.; Maier, B.; Kalathur, R.K.R.; Porras, P.; Wanker, E.E.; Futschik, M.E.; Kramer, A.
Title Dynamic circadian protein-protein interaction networks predict temporal organization of cellular functions Type Journal Article
Year 2013 Publication PLoS Genetics Abbreviated Journal PLoS Genet
Volume 9 Issue 3 Pages (down) e1003398
Keywords ARNTL Transcription Factors/genetics/metabolism; *CLOCK Proteins/genetics/metabolism; Cell Cycle/genetics/physiology; Circadian Clocks/*genetics; Circadian Rhythm/*genetics; HEK293 Cells; Humans; Protein Interaction Maps/*genetics; Protein Phosphatase 1/genetics/metabolism; Receptor, Epidermal Growth Factor/metabolism; Signal Transduction
Abstract Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner.
Address Laboratory of Chronobiology, Charite-Universitatsmedizin, Berlin, Germany
Corporate Author Thesis
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1553-7390 ISBN Medium
Area Expedition Conference
Notes PMID:23555304 Approved no
Call Number refbase @ admin @ Serial 35130
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Author Cui, J.; Stahl, E.A.; Saevarsdottir, S.; Miceli, C.; Diogo, D.; Trynka, G.; Raj, T.; Mirkov, M.U.; Canhao, H.; Ikari, K.; Terao, C.; Okada, Y.; Wedren, S.; Askling, J.; Yamanaka, H.; Momohara, S.; Taniguchi, A.; Ohmura, K.; Matsuda, F.; Mimori, T.; Gupta, N.; Kuchroo, M.; Morgan, A.W.; Isaacs, J.D.; Wilson, A.G.; Hyrich, K.L.; Herenius, M.; Doorenspleet, M.E.; Tak, P.-P.; Crusius, J.B.A.; van der Horst-Bruinsma, I.E.; Wolbink, G.J.; van Riel, P.L.C.M.; van de Laar, M.; Guchelaar, H.-J.; Shadick, N.A.; Allaart, C.F.; Huizinga, T.W.J.; Toes, R.E.M.; Kimberly, R.P.; Bridges, S.L.J.; Criswell, L.A.; Moreland, L.W.; Fonseca, J.E.; de Vries, N.; Stranger, B.E.; De Jager, P.L.; Raychaudhuri, S.; Weinblatt, M.E.; Gregersen, P.K.; Mariette, X.; Barton, A.; Padyukov, L.; Coenen, M.J.H.; Karlson, E.W.; Plenge, R.M.
Title Genome-wide association study and gene expression analysis identifies CD84 as a predictor of response to etanercept therapy in rheumatoid arthritis Type Journal Article
Year 2013 Publication PLoS Genetics Abbreviated Journal PLoS Genet
Volume 9 Issue 3 Pages (down) e1003394
Keywords Adult; Aged; Alleles; *Antigens, CD/genetics/metabolism; Antirheumatic Agents/administration & dosage; *Arthritis, Rheumatoid/drug therapy/physiopathology; Asian Continental Ancestry Group/genetics; *Biomarkers, Pharmacological/metabolism; European Continental Ancestry Group/genetics; Female; Gene Expression Regulation; *Genome-Wide Association Study; Humans; Immunoglobulin G/administration & dosage; Male; Middle Aged; Polymorphism, Single Nucleotide; Receptors, Tumor Necrosis Factor/administration & dosage; Tumor Necrosis Factor-alpha
Abstract Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (DeltaDAS) in the etanercept subset of patients (P = 8 x 10(-8)), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3' UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1 x 10(-11) in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better DeltaDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry.
Address Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1553-7390 ISBN Medium
Area Expedition Conference
Notes PMID:23555300 Approved no
Call Number ref @ user @ Serial 74245
Permanent link to this record