DOCSLIB.ORG

CX3CR1 Is Dysregulated in Blood and Brain from Schizophrenia Patients

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
CX3CR1 Is Dysregulated in Blood and Brain from Schizophrenia Patients CX3CR1 is dysregulated in blood and brain from schizophrenia patients Aurélie Bergona,b, Raoul Belzeauxc,d,e, Magali Comtef, Florence Pelletierc,d, Mylène Hervéc,d, Erin J Gardinerg-j, Natalie J Beveridgeg-j, Bing Liug,h,k, Vaughan Carrj,l,m, Rodney J Scottg-j, Brian Kellyg,h,i, Murray J Cairnsg-j, Nishantha Kumarasingheg-j,n, Ulrich Schallg-j, Olivier Blino, José Boucrautc,d, Paul A Tooneyg-j, Eric Fakraf,p, and El Chérif Ibrahimc,d, * aINSERM, TAGC UMR_S 1090, 13288 Marseille Cedex 09, France bAix Marseille Université, TAGC UMR_S 1090, 13288 Marseille Cedex 09, France cAix Marseille Université, CNRS, CRN2M UMR 7286, 13344 Marseille Cedex 15, France dFondaMental, Fondation de Recherche et de Soins en Santé Mentale, 94000 Créteil, France eAP-HM, Hôpital Sainte Marguerite, Pôle de Psychiatrie Universitaire Solaris, 13009 Marseille, France fAix-Marseille Université, CNRS, Institut de Neurosciences de la Timone UMR 7289, 13005 Marseille, France gSchool of Biomedical Sciences and Pharmacy and School of Medicine and Public Health, Faculty of Health, The University of Newcastle, University Drive, Callaghan, NSW 2308 Australia hCentre for Translational Neuroscience and Mental Health, The University of Newcastle, Callaghan, NSW 2308 Australia iHunter Medical Research Institute, New Lambton Heights, NSW 2305Australia CX3CR1 mRNA in schizophrenia jSchizophrenia Research Institute, Darlinghurst, NSW 2010 Australia kKids Cancer Alliance, Cancer Institute NSW, Sydney, Australia lSchool of Psychiatry, University of New South Wales, Randwick, NSW 2301 Australia mDepartment of Psychiatry, Monash University, Clayton, VIC 3168 Australia nUniversity of Sri Jayewardenepura, Nugegoda, and National Institute of Mental Health, Angoda, Sri Lanka oCIC-UPCET et Pharmacologie Clinique, Hôpital de la Timone, 13005 Marseille, France pCHU de Saint-Etienne, Pôle de Psychiatrie, 42100 Saint-Etienne, France * Corresponding author at: Aix Marseille Université, CNRS, CRN2M UMR 728651, Bd Pierre Dramard, 13344 Marseille Cedex 15, France. Tel: +33 (0)4 91 69 89 56; fax: +33 (0)4 91 69 89 20. Email address: [email protected] (E. C. Ibrahim) 2 CX3CR1 mRNA in schizophrenia Abstract The molecular mechanisms underlying schizophrenia remain largely unknown. Although schizophrenia is a mental disorder, increasing evidence indicates that inflammatory processes driven by diverse adverse environmental factors play a significant role. Since gene expression studies have been conducted on both brain and blood samples, it is possible to investigate convergent signatures that may reveal players of the interaction between the immune and nervous systems in schizophrenia pathophysiology. We conducted 2 meta-analyses of microarray gene expression data concerning schizophrenia (N=474) and healthy (N=485) control-matched samples from brain and blood tissues. Then, we assessed whether significantly dysregulated genes in schizophrenia could be shared between blood and brain. To validate our findings, we tested the expression of one top gene candidate by RT-qPCR on a cohort of schizophrenia subjects stabilized by atypical antipsychotic monotherapy (N=29) and matched healthy controls (N=31). Brain and blood meta-analyses converged to indicate that inflammation was the major biological process associated with schizophrenia and that the chemokine receptor CX3CR1 was significantly underexpressed in schizophrenia patients both in blood and brain. We confirmed such differential expression, in schizophrenia patients compared to healthy controls, in our own validation cohort. The dysregulated expression of a chemokine receptor could be the hallmark of specific subsets of immune cells participating in schizophrenia pathophysiology. Current knowledge on CX3CR1 gain or lack of function is discussed for speculation on a role in psychiatric disorders. Keywords CX3CR1 schizophrenia mRNA inflammation transcriptomics meta-analysis 3 CX3CR1 mRNA in schizophrenia 1. Introduction Schizophrenia (SCZ) is a complex and devastating brain disorder with an elusive etiology. Although heritability estimates for SCZ is close to 70 % (Lichtenstein et al., 2009; Sullivan et al., 2003), intense investigations over the past 2 decades to define conserved genetic variations among thousands of SCZ samples did not provide, consensual replications or validations (Gratten et al., 2014). As an alternative strategy to identify the possible causes of the disease, gene expression profiling has been proposed to fill the gap between genetic variation and environmental players that overlay an epigenetic layer of susceptibility factors (Mitchell and Mirnics, 2012). Therefore the transcriptional landscape can be considered as an intermediate phenotype between genomic sequence variability and complex traits that may help in revealing the biological pathways whose perturbations underlie the progressive sliding from normality to a psychiatric pathology. In fact, the high throughput transcriptome profiling experiments conducted with DNA microarrays identified several molecular processes in SCZ such as myelination, synaptic transmission, metabolism, ubiquitination and immune function (Kumarasinghe et al., 2012; Mistry et al., 2013b). Initially, as for all investigated psychiatric diseases, postmortem brain samples have been considered as a gold standard material to profile SCZ (Arion et al., 2007; Barnes et al., 2011; Chen et al., 2013; Hagihara et al., 2014; Mistry et al., 2013a, b; Perez-Santiago et al., 2012; Saetre et al., 2007; Schmitt et al., 2011; Torkamani et al., 2010). However, such tissue presents many limitations for sample size collection and access, tissue preparation and conservation, and antemortem diagnosis. Therefore, with the aim of developing biomarkers, blood collection has been considered. It is easily obtained and allows the longitudinal follow-up of many genes whose expression is also correlated in the brain tissue (Mamdani et al., 2013; Woelk et al., 2011). 4 CX3CR1 mRNA in schizophrenia Many transcriptomic microarray studies in SCZ were made available in public domains such as the Gene Expression Omnibus (GEO) from NCBI (Barrett et al., 2013), ArrayExpress from EBI (Rustici et al., 2013), and the Stanley Medical Research Institute (SMRI) online genomics database (Higgs et al., 2006). One can thus easily retrieve raw data from both postmortem and blood SCZ studies, and combine data as a meta-analysis to increase both sample size and sensitivity for the identification of differentially expressed genes and biological processes. Of course, in order to keep the benefit of increasing the number of the analyzed samples, it is important to apply normalization procedures that will balance the effects that may arise from the heterogeneity in tissue region, microarray platform, sample quality that could collectively deteriorate the meta-analysis. Indeed, different methods have been proposed and discussed to conduct meta-analysis (Chang et al., 2013; Chen et al., 2011; Conlon et al., 2007; Lopez et al., 2008; Phan et al., 2012; Schurmann et al., 2012; Seita et al., 2012; Stevens and Doerge, 2005; Tian and Suarez-Farinas, 2013; Warnat et al., 2005). In the present study, we conducted a meta-analysis to explore by whether a common paradigm could exist in various brain regions and be shared with blood to distinguish SCZ from healthy individuals. To achieve this goal, we used samples from publicly available microarray data involving SCZ and matched control cohorts, as well as data made available from the Gardiner et al. (2013), and Kumarasinghe et al. (2013) publications (Gardiner et al., 2013; Kumarasinghe et al., 2013). To validate our procedure, we tested the expression of a gene candidate on a cohort of stabilized SCZ patients and healthy controls by RT-qPCR. Altogether, our work allows us to pinpoint a biological process and potential specific cell populations for future experiments investigating SCZ physiopathology. 5 CX3CR1 mRNA in schizophrenia 2. Materials and methods 2.1 Microarray Datasets Microarray datasets were selected on the basis of use of either brain or blood tissue (i.e. cell lines were excluded), availability of raw data and information on covariates such as age and sex for blood as well as pH and postmortem interval (PMI) for brain tissues. The treatment and the acute or remitted status of patients were not taken into account for the selection of datasets. Each dataset comprises cohorts of neuropathologically normal subjects and SCZ subjects, as diagnosed and reported in their respective studies (Table 1). Sources for data include GEO (http://www.ncbi.nlm.nih.gov/geo), ArrayExpress (http://www.ebi.ac.uk/arrayexpress/), and the Stanley database (https://www.stanleygenomics.org/). GEO and ArrayExpress studies were identified by extensive manual and combinatorial keyword searches (schizophrenia, psychosis, control, human, brain, blood, microarray) until November 1st 2014. Although additional datasets were retrievable (including some microarrays with custom design and not pangenomic), many represent repeated runs of the samples from the same subjects, so we selected datasets that do not allow overlap between samples and/or individuals. Two additional studies of whole blood were obtained from the investigators (Gardiner et al., 2013; Kumarasinghe et al., 2013). Altogether, ten datasets relied on different postmortem brain areas (prefrontal, frontal and temporal cortex, cerebellum, hippocampus, striatum and thalamus) and five on blood tissue (whole blood and PBMCs) (see Table 1 for details
Load more

Recommended publications
  • Mediator of DNA Damage Checkpoint 1 (MDC1) Is a Novel Estrogen Receptor Co-Regulator in Invasive 6 Lobular Carcinoma of the Breast 7 8 Evelyn K
    bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 1 Running Title: MDC1 co-regulates ER in ILC 2 3 Research article 4 5 Mediator of DNA damage checkpoint 1 (MDC1) is a novel estrogen receptor co-regulator in invasive 6 lobular carcinoma of the breast 7 8 Evelyn K. Bordeaux1+, Joseph L. Sottnik1+, Sanjana Mehrotra1, Sarah E. Ferrara2, Andrew E. Goodspeed2,3, James 9 C. Costello2,3, Matthew J. Sikora1 10 11 +EKB and JLS contributed equally to this project. 12 13 Affiliations 14 1Dept. of Pathology, University of Colorado Anschutz Medical Campus 15 2Biostatistics and Bioinformatics Shared Resource, University of Colorado Comprehensive Cancer Center 16 3Dept. of Pharmacology, University of Colorado Anschutz Medical Campus 17 18 Corresponding author 19 Matthew J. Sikora, PhD.; Mail Stop 8104, Research Complex 1 South, Room 5117, 12801 E. 17th Ave.; Aurora, 20 CO 80045. Tel: (303)724-4301; Fax: (303)724-3712; email: [email protected]. Twitter: 21 @mjsikora 22 23 Authors' contributions 24 MJS conceived of the project. MJS, EKB, and JLS designed and performed experiments. JLS developed models 25 for the project. EKB, JLS, SM, and AEG contributed to data analysis and interpretation. SEF, AEG, and JCC 26 developed and performed informatics analyses. MJS wrote the draft manuscript; all authors read and revised the 27 manuscript and have read and approved of this version of the manuscript.
    [Show full text]
  • Proteasome System of Protein Degradation and Processing
    ISSN 0006-2979, Biochemistry (Moscow), 2009, Vol. 74, No. 13, pp. 1411-1442. © Pleiades Publishing, Ltd., 2009. Original Russian Text © A. V. Sorokin, E. R. Kim, L. P. Ovchinnikov, 2009, published in Uspekhi Biologicheskoi Khimii, 2009, Vol. 49, pp. 3-76. REVIEW Proteasome System of Protein Degradation and Processing A. V. Sorokin*, E. R. Kim, and L. P. Ovchinnikov Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; E-mail: [email protected]; [email protected] Received February 5, 2009 Abstract—In eukaryotic cells, degradation of most intracellular proteins is realized by proteasomes. The substrates for pro- teolysis are selected by the fact that the gate to the proteolytic chamber of the proteasome is usually closed, and only pro- teins carrying a special “label” can get into it. A polyubiquitin chain plays the role of the “label”: degradation affects pro- teins conjugated with a ubiquitin (Ub) chain that consists at minimum of four molecules. Upon entering the proteasome channel, the polypeptide chain of the protein unfolds and stretches along it, being hydrolyzed to short peptides. Ubiquitin per se does not get into the proteasome, but, after destruction of the “labeled” molecule, it is released and labels another molecule. This process has been named “Ub-dependent protein degradation”. In this review we systematize current data on the Ub–proteasome system, describe in detail proteasome structure, the ubiquitination system, and the classical ATP/Ub- dependent mechanism of protein degradation, as well as try to focus readers’ attention on the existence of alternative mech- anisms of proteasomal degradation and processing of proteins.
    [Show full text]
  • PSMD10 Antibody Cat
    PSMD10 Antibody Cat. No.: 57-836 PSMD10 Antibody Western blot analysis of PSMD10 using rabbit polyclonal PSMD10 Antibody using 293 cell lysates (2 ug/lane) either nontransfected (Lane 1) or transiently transfected (Lane 2) with the PSMD10 gene. Specifications HOST SPECIES: Rabbit SPECIES REACTIVITY: Human HOMOLOGY: Predicted species reactivity based on immunogen sequence: Mouse, Rat This PSMD10 antibody is generated from rabbits immunized with a KLH conjugated IMMUNOGEN: synthetic peptide between 184-213 amino acids from the C-terminal region of human PSMD10. TESTED APPLICATIONS: WB APPLICATIONS: For WB starting dilution is: 1:1000 PREDICTED MOLECULAR 24 kDa WEIGHT: September 29, 2021 1 https://www.prosci-inc.com/psmd10-antibody-57-836.html Properties This antibody is purified through a protein A column, followed by peptide affinity PURIFICATION: purification. CLONALITY: Polyclonal ISOTYPE: Rabbit Ig CONJUGATE: Unconjugated PHYSICAL STATE: Liquid BUFFER: Supplied in PBS with 0.09% (W/V) sodium azide. CONCENTRATION: batch dependent Store at 4˚C for three months and -20˚C, stable for up to one year. As with all antibodies STORAGE CONDITIONS: care should be taken to avoid repeated freeze thaw cycles. Antibodies should not be exposed to prolonged high temperatures. Additional Info OFFICIAL SYMBOL: PSMD10 26S proteasome non-ATPase regulatory subunit 10, 26S proteasome regulatory subunit ALTERNATE NAMES: p28, Gankyrin, p28(GANK), PSMD10 ACCESSION NO.: O75832 GENE ID: 5716 USER NOTE: Optimal dilutions for each application to be determined by the researcher. Background and References The 26S proteasome is a multicatalytic proteinase complex with a highly ordered structure composed of 2 complexes, a 20S core and a 19S regulator.
    [Show full text]
  • Anti-Inflammatory Role of Curcumin in LPS Treated A549 Cells at Global Proteome Level and on Mycobacterial Infection
    Anti-inflammatory Role of Curcumin in LPS Treated A549 cells at Global Proteome level and on Mycobacterial infection. Suchita Singh1,+, Rakesh Arya2,3,+, Rhishikesh R Bargaje1, Mrinal Kumar Das2,4, Subia Akram2, Hossain Md. Faruquee2,5, Rajendra Kumar Behera3, Ranjan Kumar Nanda2,*, Anurag Agrawal1 1Center of Excellence for Translational Research in Asthma and Lung Disease, CSIR- Institute of Genomics and Integrative Biology, New Delhi, 110025, India. 2Translational Health Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, 110067, India. 3School of Life Sciences, Sambalpur University, Jyoti Vihar, Sambalpur, Orissa, 768019, India. 4Department of Respiratory Sciences, #211, Maurice Shock Building, University of Leicester, LE1 9HN 5Department of Biotechnology and Genetic Engineering, Islamic University, Kushtia- 7003, Bangladesh. +Contributed equally for this work. S-1 70 G1 S 60 G2/M 50 40 30 % of cells 20 10 0 CURI LPSI LPSCUR Figure S1: Effect of curcumin and/or LPS treatment on A549 cell viability A549 cells were treated with curcumin (10 µM) and/or LPS or 1 µg/ml for the indicated times and after fixation were stained with propidium iodide and Annexin V-FITC. The DNA contents were determined by flow cytometry to calculate percentage of cells present in each phase of the cell cycle (G1, S and G2/M) using Flowing analysis software. S-2 Figure S2: Total proteins identified in all the three experiments and their distribution betwee curcumin and/or LPS treated conditions. The proteins showing differential expressions (log2 fold change≥2) in these experiments were presented in the venn diagram and certain number of proteins are common in all three experiments.
    [Show full text]
  • Association Weight Matrix for the Genetic Dissection of Puberty in Beef Cattle
    Association weight matrix for the genetic dissection of puberty in beef cattle Marina R. S. Fortesa,b,c, Antonio Revertera,b, Yuandan Zhanga,d, Eliza Collisa,b, Shivashankar H. Nagarajb,NickN.Jonssona,c,e, Kishore C. Prayagaa,b,1, Wes Barrisa,b, and Rachel J. Hawkena,b,2 aCooperative Research Centre for Beef Genetic Technologies; bCommonwealth Scientific and Industrial Research Organization, division of Livestock Industries, Queensland Bioscience Precinct, Brisbane QLD 4067, Australia; cThe University of Queensland, School of Veterinary Science, Gatton QLD 4343, Australia; dAnimal Genetics and Breeding Unit, University of New England, Armidale NSW 2351, Australia; and eFaculty of Veterinary Medicine, University of Glasgow, Glasgow G61 1QH, United Kingdom Edited by George Seidel, Colorado State University, Fort Collins, CO, and approved June 21, 2010 (received for review February 23, 2010) We describe a systems biology approach for the genetic dissection tional data on traits related to puberty are available. For example, of complex traits based on applying gene network theory to the re- weight and condition score are often measured on occasions sults from genome-wide associations. The associations of single- throughout an animal’s development. Hence, understanding ge- nucleotide polymorphisms (SNP) that were individually associated netics of cattle puberty and its biology serves two purposes: as with a primary phenotype of interest, age at puberty in our study, a strategy to develop efficient livestock resources and as a model were explored across 22 related traits. Genomic regions were sur- for human biology. veyed for genes harboring the selected SNP. As a result, an asso- The focus of this work is to demonstrate a unique systems ap- ciation weight matrix (AWM) was constructed with as many rows proach, which we call an association weight matrix (AWM), ap- as genes and as many columns as traits.
    [Show full text]
  • Produktinformation
    Produktinformation Diagnostik & molekulare Diagnostik Laborgeräte & Service Zellkultur & Verbrauchsmaterial Forschungsprodukte & Biochemikalien Weitere Information auf den folgenden Seiten! See the following pages for more information! Lieferung & Zahlungsart Lieferung: frei Haus Bestellung auf Rechnung SZABO-SCANDIC Lieferung: € 10,- HandelsgmbH & Co KG Erstbestellung Vorauskassa Quellenstraße 110, A-1100 Wien T. +43(0)1 489 3961-0 Zuschläge F. +43(0)1 489 3961-7 [email protected] • Mindermengenzuschlag www.szabo-scandic.com • Trockeneiszuschlag • Gefahrgutzuschlag linkedin.com/company/szaboscandic • Expressversand facebook.com/szaboscandic PSMD10 Antibody, Biotin conjugated Product Code CSB-PA018899LD01HU Abbreviation 26S proteasome non-ATPase regulatory subunit 10 Storage Upon receipt, store at -20°C or -80°C. Avoid repeated freeze. Uniprot No. O75832 Immunogen Recombinant Human 26S proteasome non-ATPase regulatory subunit 10 protein (1-226AA) Raised In Rabbit Species Reactivity Human Tested Applications ELISA Relevance Acts as a chaperone during the assembly of the 26S proteasome, specifically of the PA700/19S regulatory complex (RC). In the initial step of the base subcomplex assembly is part of an intermediate PSMD10:PSMC4:PSMC5:PAAF1 module which probably assembles with a PSMD5:PSMC2:PSMC1:PSMD2 module. Independently of the proteasome, regulates EGF-induced AKT activation through inhibition of the RHOA/ROCK/PTEN pahway, leading to prolonged AKT activation. Plays an important role in RAS-induced tumorigenesis. Acts as an proto-oncoprotein by being involved in negative regulation of tumor suppressors RB1 and p53/TP53. Overexpression is leading to phosphorylation of RB1 and proteasomal degradation of RB1. Regulates CDK4-mediated phosphorylation of RB1 by competing with CDKN2A for binding with CDK4. Facilitates binding of MDM2 to p53/TP53 and the mono- and polyubiquitination of p53/TP53 by MDM2 suggesting a function in targeting the TP53:MDM2 complex to the 26S proteasome.
    [Show full text]
  • PSMD10 Antibody (Center) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AW5126
    10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 PSMD10 Antibody (Center) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AW5126 Specification PSMD10 Antibody (Center) - Product Information Application IF, WB, IHC-P,E Primary Accession O75832 Other Accession Q9Z2X2 Reactivity Human Predicted Mouse Host Rabbit Clonality Polyclonal Calculated MW H=24,16;M=25;Ra t=25 KDa Isotype Rabbit Ig Antigen Source HUMAN PSMD10 Antibody (Center) - Additional Information Gene ID 5716 Fluorescent image of Hela cells stained with PSMD10 Antibody (Center)(Cat#AW5126). Antigen Region AW5126 was diluted at 1:25 dilution. An 43-76 Alexa Fluor 488-conjugated goat anti-rabbit lgG at 1:400 dilution was used as the Other Names secondary antibody (green). Cytoplasmic 26S proteasome non-ATPase regulatory subunit 10, 26S proteasome regulatory actin was counterstained with Alexa Fluor® subunit p28, Gankyrin, p28(GANK), PSMD10 555 conjugated with Phalloidin (red). Dilution IF~~1:25 WB~~ 1:1000 IHC-P~~1:25 Target/Specificity This PSMD10 antibody is generated from a rabbit immunized with a KLH conjugated synthetic peptide between 43-76 amino acids from the Central region of human PSMD10. Format Purified polyclonal antibody supplied in PBS with 0.09% (W/V) sodium azide. This antibody is purified through a protein A column, followed by peptide affinity purification. Western blot analysis of lysates from MCF-7, PC-3, K562 cell line (from left to right), using Storage PSMD10 Antibody (Center)(Cat. #AW5126). Page 1/3 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 Maintain refrigerated at 2-8°C for up to 2 AW5126 was diluted at 1:1000 at each lane.
    [Show full text]
  • Identification of Differential Modules in Ankylosing Spondylitis Using Systemic Module Inference and the Attract Method
    EXPERIMENTAL AND THERAPEUTIC MEDICINE 16: 149-154, 2018 Identification of differential modules in ankylosing spondylitis using systemic module inference and the attract method FANG-CHANG YUAN1, BO LI2 and LI-JUN ZHANG3 1Department of Orthopedics, People's Hospital of Rizhao, Rizhao, Shandong 276826; 2Department of Joint Surgery, Hospital of Xinjiang Production and Construction Corps, Urumchi, Xinjiang Uygur Autonomous Region 830002; 3Department of Orthopedics, The Fifth People's Hospital of Jinan, Jinan, Shandong 250022, P.R. China Received July 15, 2016; Accepted April 28, 2017 DOI: 10.3892/etm.2018.6134 Abstract. The objective of the present study was to identify spondyloarthropathies, which also includes reactive arthritis, differential modules in ankylosing spondylitis (AS) by inte- psoriatic arthritis and enteropathic arthritis (1). Several grating network analysis, module inference and the attract features, such as synovitis, chondroid metaplasia, cartilage method. To achieve this objective, four steps were conducted. destruction and subchondral bone marrow changes, are The first step was disease objective network (DON) for AS, commonly observed in the joints of patients with AS (2). Due and healthy objective network (HON) inference dependent on to the complex progression of the joint remodeling process, gene expression data, protein-protein interaction networks and clinical research has not systematically evaluated histopatho- Spearman's correlation coefficient. In the second step, module logical changes (3), and no clear sequence of the pathological detection was performed by utilizing a clique-merging algo- mechanism has been obtained for this disease. rithm, which comprised of exploring maximal cliques by clique With the development of high throughput technology and algorithm and refining or merging maximal cliques with a high gene data analysis over the past decade, rapid progress has been overlap.
    [Show full text]
  • Discovery of Candidate DNA Methylation Cancer Driver Genes
    Published OnlineFirst May 10, 2021; DOI: 10.1158/2159-8290.CD-20-1334 RESEARCH ARTICLE Discovery of Candidate DNA Methylation Cancer Driver Genes Heng Pan1,2,3, Loïc Renaud4,5,6,7, Ronan Chaligne4,5,6, Johannes Bloehdorn8, Eugen Tausch8, Daniel Mertens9, Anna Maria Fink10, Kirsten Fischer10, Chao Zhang3,6, Doron Betel3,6, Andreas Gnirke11, Marcin Imielinski1,3,4,5,12, Jérôme Moreaux13,14,15,16, Michael Hallek10, Alexander Meissner11,17, Stephan Stilgenbauer8, Catherine J. Wu11,18, Olivier Elemento1,2,3,5, and Dan A. Landau3,4,5,6 Downloaded from cancerdiscovery.aacrjournals.org on September 28, 2021. © 2021 American Association for Cancer Research. Published OnlineFirst May 10, 2021; DOI: 10.1158/2159-8290.CD-20-1334 ABSTRACT Epigenetic alterations, such as promoter hypermethylation, may drive cancer through tumor suppressor gene inactivation. However, we have limited ability to differentiate driver DNA methylation (DNAme) changes from passenger events. We developed DNAme driver inference–MethSig–accounting for the varying stochastic hypermethylation rate across the genome and between samples. We applied MethSig to bisulfite sequencing data of chronic lymphocytic leukemia (CLL), multiple myeloma, ductal carcinoma in situ, glioblastoma, and to methylation array data across 18 tumor types in TCGA. MethSig resulted in well-calibrated quantile–quantile plots and reproducible inference of likely DNAme drivers with increased sensitivity/specificity compared with benchmarked methods. CRISPR/Cas9 knockout of selected candidate CLL DNAme drivers provided a fitness advantage with and without therapeutic intervention. Notably, DNAme driver risk score was closely associated with adverse outcome in independent CLL cohorts. Collectively, MethSig represents a novel inference framework for DNAme driver discovery to chart the role of aberrant DNAme in cancer.
    [Show full text]
  • Genetically Incorporated Crosslinkers Reveal Nlee Attenuates Host
    RESEARCH ARTICLE Genetically incorporated crosslinkers reveal NleE attenuates host autophagy dependent on PSMD10 Jingxiang Li1, Shupan Guo1, Fangni Chai1, Qi Sun1, Pan Li1, Li Gao2, Lunzhi Dai2, Xiaoxiao Ouyang1, Zhihui Zhou1, Li Zhou1, Wei Cheng1, Shiqian Qi1, Kefeng Lu1, Haiyan Ren1* 1Division of Respiratory and Critical Care Medicine, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China; 2Department of General Practice and National Clinical Research Center for Geriatrics, State Key Laboratory of Biotherapy, West China Hospital, and Sichuan University, Chengdu, China Abstract Autophagy acts as a pivotal innate immune response against infection. Some virulence effectors subvert the host autophagic machinery to escape the surveillance of autophagy. The mechanism by which pathogens interact with host autophagy remains mostly unclear. However, traditional strategies often have difficulty identifying host proteins that interact with effectors due to the weak, dynamic, and transient nature of these interactions. Here, we found that Enteropathogenic Escherichia coli (EPEC) regulates autophagosome formation in host cells dependent on effector NleE. The 26S Proteasome Regulatory Subunit 10 (PSMD10) was identified as a direct interaction partner of NleE in living cells by employing genetically incorporated crosslinkers. Pairwise chemical crosslinking revealed that NleE interacts with the N-terminus of PSMD10. We demonstrated that PSMD10 homodimerization is necessary for its interaction with ATG7 and promotion of autophagy, but not necessary for PSMD10 interaction with ATG12. Therefore, NleE-mediated PSMD10 in monomeric state attenuates host autophagosome formation. *For correspondence: Our study reveals the mechanism through which EPEC attenuates host autophagy activity. [email protected] Competing interests: The authors declare that no competing interests exist.
    [Show full text]
  • TLR4 Signaling SASH1 Is a Scaffold Molecule in Endothelial
    SASH1 Is a Scaffold Molecule in Endothelial TLR4 Signaling Shauna M. Dauphinee, Ashley Clayton, Angela Hussainkhel, Cindy Yang, Yoo-Jin Park, Megan E. Fuller, Josip Blonder, This information is current as Timothy D. Veenstra and Aly Karsan of September 27, 2021. J Immunol 2013; 191:892-901; Prepublished online 17 June 2013; doi: 10.4049/jimmunol.1200583 http://www.jimmunol.org/content/191/2/892 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2013/06/17/jimmunol.120058 Material 3.DC1 http://www.jimmunol.org/ References This article cites 46 articles, 14 of which you can access for free at: http://www.jimmunol.org/content/191/2/892.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision by guest on September 27, 2021 • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology SASH1 Is a Scaffold Molecule in Endothelial TLR4 Signaling Shauna M. Dauphinee,*,† Ashley Clayton,*,† Angela Hussainkhel,*,‡ Cindy Yang,x Yoo-Jin Park,x Megan E.
    [Show full text]
  • Proteasome Biology: Chemistry and Bioengineering Insights
    polymers Review Proteasome Biology: Chemistry and Bioengineering Insights Lucia Raˇcková * and Erika Csekes Centre of Experimental Medicine, Institute of Experimental Pharmacology and Toxicology, Slovak Academy of Sciences, Dúbravská cesta 9, 841 04 Bratislava, Slovakia; [email protected] * Correspondence: [email protected] or [email protected] Received: 28 September 2020; Accepted: 23 November 2020; Published: 4 December 2020 Abstract: Proteasomal degradation provides the crucial machinery for maintaining cellular proteostasis. The biological origins of modulation or impairment of the function of proteasomal complexes may include changes in gene expression of their subunits, ubiquitin mutation, or indirect mechanisms arising from the overall impairment of proteostasis. However, changes in the physico-chemical characteristics of the cellular environment might also meaningfully contribute to altered performance. This review summarizes the effects of physicochemical factors in the cell, such as pH, temperature fluctuations, and reactions with the products of oxidative metabolism, on the function of the proteasome. Furthermore, evidence of the direct interaction of proteasomal complexes with protein aggregates is compared against the knowledge obtained from immobilization biotechnologies. In this regard, factors such as the structures of the natural polymeric scaffolds in the cells, their content of reactive groups or the sequestration of metal ions, and processes at the interface, are discussed here with regard to their
    [Show full text]