Rabbit Anti-IKK Gamma/FITC Conjugated Antibody-SL2898R-FITC
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Laboratory Mouse Models for the Human Genome-Wide Associations
Laboratory Mouse Models for the Human Genome-Wide Associations The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Kitsios, Georgios D., Navdeep Tangri, Peter J. Castaldi, and John P. A. Ioannidis. 2010. Laboratory mouse models for the human genome-wide associations. PLoS ONE 5(11): e13782. Published Version doi:10.1371/journal.pone.0013782 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:8592157 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Laboratory Mouse Models for the Human Genome-Wide Associations Georgios D. Kitsios1,4, Navdeep Tangri1,6, Peter J. Castaldi1,2,4,5, John P. A. Ioannidis1,2,3,4,5,7,8* 1 Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts, United States of America, 2 Tufts University School of Medicine, Boston, Massachusetts, United States of America, 3 Department of Hygiene and Epidemiology, University of Ioannina School of Medicine and Biomedical Research Institute, Foundation for Research and Technology-Hellas, Ioannina, Greece, 4 Tufts Clinical and Translational Science Institute, Tufts Medical Center, Boston, Massachusetts, United States of America, 5 Department of Medicine, Center for Genetic Epidemiology and Modeling, Tufts Medical Center, Tufts University -
Profiling Data
Compound Name DiscoveRx Gene Symbol Entrez Gene Percent Compound Symbol Control Concentration (nM) JNK-IN-8 AAK1 AAK1 69 1000 JNK-IN-8 ABL1(E255K)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317I)-nonphosphorylated ABL1 87 1000 JNK-IN-8 ABL1(F317I)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317L)-nonphosphorylated ABL1 65 1000 JNK-IN-8 ABL1(F317L)-phosphorylated ABL1 61 1000 JNK-IN-8 ABL1(H396P)-nonphosphorylated ABL1 42 1000 JNK-IN-8 ABL1(H396P)-phosphorylated ABL1 60 1000 JNK-IN-8 ABL1(M351T)-phosphorylated ABL1 81 1000 JNK-IN-8 ABL1(Q252H)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(Q252H)-phosphorylated ABL1 56 1000 JNK-IN-8 ABL1(T315I)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(T315I)-phosphorylated ABL1 92 1000 JNK-IN-8 ABL1(Y253F)-phosphorylated ABL1 71 1000 JNK-IN-8 ABL1-nonphosphorylated ABL1 97 1000 JNK-IN-8 ABL1-phosphorylated ABL1 100 1000 JNK-IN-8 ABL2 ABL2 97 1000 JNK-IN-8 ACVR1 ACVR1 100 1000 JNK-IN-8 ACVR1B ACVR1B 88 1000 JNK-IN-8 ACVR2A ACVR2A 100 1000 JNK-IN-8 ACVR2B ACVR2B 100 1000 JNK-IN-8 ACVRL1 ACVRL1 96 1000 JNK-IN-8 ADCK3 CABC1 100 1000 JNK-IN-8 ADCK4 ADCK4 93 1000 JNK-IN-8 AKT1 AKT1 100 1000 JNK-IN-8 AKT2 AKT2 100 1000 JNK-IN-8 AKT3 AKT3 100 1000 JNK-IN-8 ALK ALK 85 1000 JNK-IN-8 AMPK-alpha1 PRKAA1 100 1000 JNK-IN-8 AMPK-alpha2 PRKAA2 84 1000 JNK-IN-8 ANKK1 ANKK1 75 1000 JNK-IN-8 ARK5 NUAK1 100 1000 JNK-IN-8 ASK1 MAP3K5 100 1000 JNK-IN-8 ASK2 MAP3K6 93 1000 JNK-IN-8 AURKA AURKA 100 1000 JNK-IN-8 AURKA AURKA 84 1000 JNK-IN-8 AURKB AURKB 83 1000 JNK-IN-8 AURKB AURKB 96 1000 JNK-IN-8 AURKC AURKC 95 1000 JNK-IN-8 -
Supplementary Table 7. Characterization of Human Proteins Involved in the Prostate Cancer Pathway
Supplementary Table 7. Characterization of human proteins involved in the prostate cancer pathway f Protein UniProt Protein PONDR-FIT MobiDB Location (length) Location (length) Nint ID length (%)b consensus of long disordered of AIBSse a c d (NAIBS) (%) regions BAD, Bcl2-associated Q92934 168 100.00 84.54 1-105 (105) 1-53 (53) 66 agonist of cell death (4/70.8) 122-147 (27) 57-80 (24) 158-168 (11) 100-129 (30) 146-157 (12) CREB5; cyclic AMP- Q02930 508 85.24 75.39 46-59 (14) 66-86 (21) 65 responsive element (7/67.9) 86-393 (308) 99-183 (85) binding protein 5 447-470 (24) 188-358 (171) 479-508 (31) 362-370 (9) 378-406 (29) 421-444 (24) 503-508 (6) CREB1, cyclic AMP- P16220 341 79.47 40.47 1-32 (32) 32-44 (13) 169 responsive element- (7/29.3) 40-50 (11) 89-104 (16) binding protein 1 102-132 (33) 128-145 (18) 138-171 (34) 166-191 (26) 271-285 (15) 265-270 (6) 307-314 (8) 329-341 (13) FOXO1, Forkhead box Q12778 655 78.63 72.82 1-69 (69) 1-32 (32) 68 protein O1 (19/56.9) 74-101 (28) 54-82 (29) 105-160 (56) 88-118 (31) 199-210 (12) 160-172 (13) 229-336 (107) 182-196 (15) 385-450 (66) 216-226 (11) 463-488 (26) 258-280 (23) 498-569 (72) 289-297 (9) 644-655 (12) 306-314 (9) 323-365 (43) 371-388 (18) 301-409 (8) 447-469 (23) 483-517 (35) 528-545 (18) 550-565 (16) 570-592 (23) 605-612 (8) TCF7L1, transcription Q9HCS4 588 77.04 61.90 1-104 (104) 1-46 (46) 4 factor 7 like 1 (16/54.5) 161-183 (23) 53-74 (22) 192-238 (47) 94-135 (42) 316-344 (29) 146-159 (14) 406-512 (107) 191-201 (11) 524-546 (21) 234-252 (19) 274-288 (15) 349-371 (23) 373-383 (11) -
Molecular Classification of Patients with Unexplained Hamartomatous and Hyperplastic Polyposis
ORIGINAL CONTRIBUTION Molecular Classification of Patients With Unexplained Hamartomatous and Hyperplastic Polyposis Kevin Sweet, MS, CGC Context Significant proportions of patients with hamartomatous polyposis or with Joseph Willis, MD hyperplastic/mixed polyposis remain without specific clinical and molecular diagnosis Xiao-Ping Zhou, MD, PhD or present atypically. Assigning a syndromic diagnosis is important because it guides management, especially surveillance and prophylactic surgery. Carol Gallione, PhD Objective To systematically classify patients with unexplained hamartomatous or hy- Takeshi Sawada, MD, PhD perplastic/mixed polyposis by extensive molecular analysis in the context of central Pia Alhopuro, MD rereview of histopathology results. Sok Kean Khoo, PhD Design, Setting, and Patients Prospective, referral-based study of 49 unrelated patients from outside institutions (n=28) and at a comprehensive cancer center (n=21), Attila Patocs, MD, PhD conducted from May 2, 2002, until December 15, 2004. Germline analysis of PTEN, Cossette Martin, PhD BMPR1A, STK11 (sequence, deletion), SMAD4, and ENG (sequence), specific exon screen- Scott Bridgeman, BSc ing of BRAF, MYH, and BHD, and rereview of polyp histology results were performed. John Heinz, PhD Main Outcome Measures Molecular, clinical, and histopathological findings in pa- tients with unexplained polyposis. Robert Pilarski, MS, CGC Results Of the 49 patients, 11 (22%) had germline mutations. Of 14 patients with Rainer Lehtonen, BSc juvenile polyposis, 2 with early-onset disease had mutations in ENG, encoding endo- Thomas W. Prior, PhD glin, previously only associated with hereditary hemorrhagic telangiectasia; 1 had hemi- zygous deletion encompassing PTEN and BMPR1A; and 1 had an SMAD4 mutation. Thierry Frebourg, MD, PhD One individual previously classified with Peutz-Jeghers syndrome had a PTEN dele- Bin Tean Teh, MD, PhD tion. -
The UBE2L3 Ubiquitin Conjugating Enzyme: Interplay with Inflammasome Signalling and Bacterial Ubiquitin Ligases
The UBE2L3 ubiquitin conjugating enzyme: interplay with inflammasome signalling and bacterial ubiquitin ligases Matthew James George Eldridge 2018 Imperial College London Department of Medicine Submitted to Imperial College London for the degree of Doctor of Philosophy 1 Abstract Inflammasome-controlled immune responses such as IL-1β release and pyroptosis play key roles in antimicrobial immunity and are heavily implicated in multiple hereditary autoimmune diseases. Despite extensive knowledge of the mechanisms regulating inflammasome activation, many downstream responses remain poorly understood or uncharacterised. The cysteine protease caspase-1 is the executor of inflammasome responses, therefore identifying and characterising its substrates is vital for better understanding of inflammasome-mediated effector mechanisms. Using unbiased proteomics, the Shenoy grouped identified the ubiquitin conjugating enzyme UBE2L3 as a target of caspase-1. In this work, I have confirmed UBE2L3 as an indirect target of caspase-1 and characterised its role in inflammasomes-mediated immune responses. I show that UBE2L3 functions in the negative regulation of cellular pro-IL-1 via the ubiquitin- proteasome system. Following inflammatory stimuli, UBE2L3 assists in the ubiquitylation and degradation of newly produced pro-IL-1. However, in response to caspase-1 activation, UBE2L3 is itself targeted for degradation by the proteasome in a caspase-1-dependent manner, thereby liberating an additional pool of IL-1 which may be processed and released. UBE2L3 therefore acts a molecular rheostat, conferring caspase-1 an additional level of control over this potent cytokine, ensuring that it is efficiently secreted only in appropriate circumstances. These findings on UBE2L3 have implications for IL-1- driven pathology in hereditary fever syndromes, and autoinflammatory conditions associated with UBE2L3 polymorphisms. -
Efficient Analysis of Mouse Genome Sequences Reveal Many Nonsense Variants
Efficient analysis of mouse genome sequences reveal many nonsense variants Sophie Steelanda,b,1, Steven Timmermansa,b,1, Sara Van Ryckeghema,b, Paco Hulpiaua,b, Yvan Saeysa,c, Marc Van Montagud,e,f,2, Roosmarijn E. Vandenbrouckea,b,3, and Claude Liberta,b,2,3 aInflammation Research Center, Flanders Institute for Biotechnology (VIB), 9052 Ghent, Belgium; bDepartment of Biomedical Molecular Biology, Ghent University, 9052 Ghent, Belgium; cDepartment of Internal Medicine, Ghent University, 9052 Ghent, Belgium; dDepartment of Plant Systems Biology, VIB, 9052 Ghent, Belgium; eDepartment of Plant Biotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium; and fInternational Plant Biotechnology Outreach, VIB, Ghent, Belgium Contributed by Marc Van Montagu, March 30, 2016 (sent for review December 31, 2015; reviewed by Bruce Beutler, Stefano Bruscoli, Stefan Rose-John, and Klaus Schulze-Osthoff) Genetic polymorphisms in coding genes play an important role alive, archiving them, and distributing mutant strains to in- when using mouse inbred strains as research models. They have terested users (4). been shown to influence research results, explain phenotypical Since Clarence Little showed in the early 20th century that the differences between inbred strains, and increase the amount of principle of inbreeding also applies to mice, several hundred interesting gene variants present in the many available inbred inbred mouse strains have been generated (5). Some of these lines. SPRET/Ei is an inbred strain derived from Mus spretus that strains display specific phenotypes that are the result of a mutant has ∼1% sequence difference with the C57BL/6J reference ge- gene, and in several cases have formed the basis for identifying nome. -
Inhibition of Mitochondrial Complex II in Neuronal Cells Triggers Unique
www.nature.com/scientificreports OPEN Inhibition of mitochondrial complex II in neuronal cells triggers unique pathways culminating in autophagy with implications for neurodegeneration Sathyanarayanan Ranganayaki1, Neema Jamshidi2, Mohamad Aiyaz3, Santhosh‑Kumar Rashmi4, Narayanappa Gayathri4, Pulleri Kandi Harsha5, Balasundaram Padmanabhan6 & Muchukunte Mukunda Srinivas Bharath7* Mitochondrial dysfunction and neurodegeneration underlie movement disorders such as Parkinson’s disease, Huntington’s disease and Manganism among others. As a corollary, inhibition of mitochondrial complex I (CI) and complex II (CII) by toxins 1‑methyl‑4‑phenylpyridinium (MPP+) and 3‑nitropropionic acid (3‑NPA) respectively, induced degenerative changes noted in such neurodegenerative diseases. We aimed to unravel the down‑stream pathways associated with CII inhibition and compared with CI inhibition and the Manganese (Mn) neurotoxicity. Genome‑wide transcriptomics of N27 neuronal cells exposed to 3‑NPA, compared with MPP+ and Mn revealed varied transcriptomic profle. Along with mitochondrial and synaptic pathways, Autophagy was the predominant pathway diferentially regulated in the 3‑NPA model with implications for neuronal survival. This pathway was unique to 3‑NPA, as substantiated by in silico modelling of the three toxins. Morphological and biochemical validation of autophagy markers in the cell model of 3‑NPA revealed incomplete autophagy mediated by mechanistic Target of Rapamycin Complex 2 (mTORC2) pathway. Interestingly, Brain Derived Neurotrophic Factor -
Targeting Lymphomas Through MALT1 Inhibition
www.impactjournals.com/oncotarget/ Oncotarget, December, Vol.3, No 12 Targeting Lymphomas Through MALT1 Inhibition Lorena Fontan and Ari Melnick Diffuse large B-cell lymphoma (DLBCL), the most contain mutations in TLR and BCR signaling components common form of non-Hodgkin Lymphoma, comprises [4, 5]. These data revealed that MALT1 is a bona fide a heterogeneous group of diseases that can be classified therapeutic target, inhibition of which may disrupt into at least three different entities with distinct gene oncogenic signaling induced by somatic mutations in expression signatures. Among these, the activated B ABC-DLBCLs. However Z-VRPR-FMK is not suitable cell-like (ABC)-DLBCLs are the most resistant to as a therapeutic agent due its unfavorable pharmacological current standard immune-chemotherapy regimens [1]. properties. Development of novel targeted therapies with activity Fortunately, two recent studies identified small in this DLBCL subtype is required to improve clinical molecule inhibitors of the MALT1 protease activity outcome for these patients. with potent activity against ABC-DLBCL cells both Efforts to identify recurrent somatic mutations in in vitro and in vivo [6, 7]. One of the studies identified ABC-DLBCLs have revealed common biological themes phenothiazine compounds as mediating reversible MALT1 despite their considerable genetic heterogeneity. Most cleavage inhibition [7]; whereas the other identified a notably frequent activating somatic mutation in B-cell novel compound termed “MALT1 inhibitor-2” (MI- receptor (BCR) and Toll like receptor (TLR) signaling 2), that irreversibly binds the active site of MALT1 and pathways, leading to constitutive NF-κB activity [2]. potently suppresses its enzymatic activity at nanomolar Along these lines the MALT1 paracaspase has emerged as concentrations [6]. -
Ufmylation Inhibits the Proinflammatory Capacity of Interferon-Γ–Activated Macrophages
UFMylation inhibits the proinflammatory capacity of interferon-γ–activated macrophages Dale R. Balcea,1,2, Ya-Ting Wanga,b, Michael R. McAllasterb,1, Bria F. Dunlapa, Anthony Orvedahlc, Barry L. Hykes Jra, Lindsay Droita, Scott A. Handleya, Craig B. Wilend,e, John G. Doenchf, Robert C. Orchardg, Christina L. Stallingsb, and Herbert W. Virgina,1,2 aDepartment of Pathology and Immunology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110; bDepartment of Molecular Microbiology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110; cDepartment of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110; dDepartment of Laboratory Medicine, Yale School of Medicine, New Haven, CT 06510; eDepartment of Immunobiology, Yale School of Medicine, New Haven, CT 06510; fBroad Institute of MIT and Harvard, Cambridge, MA 02142; and gDepartment of Immunology and Microbiology, University of Texas Southwestern Medical Center, Dallas, TX 75390 Contributed by Herbert W. Virgin, November 19, 2020 (sent for review June 15, 2020; reviewed by Masaaki Komatsu and Hong Zhang) Macrophages activated with interferon-γ (IFN-γ) in combination in regulating this aspect of cellular immunity. Thus, understanding with other proinflammatory stimuli, such as lipopolysaccharide pathways that positively and negatively regulate IFN-γ–dependent or tumor necrosis factor-α (TNF-α), respond with transcriptional macrophage activation is an important priority. and cellular changes that enhance clearance of intracellular path- Here we performed a genome-wide CRISPR screen to identify ogens at the risk of damaging tissues. IFN-γ effects must therefore proteins that negatively regulate IFN-γ responses in macrophages. -
(12) United States Patent (10) Patent No.: US 7,863,289 B2 Spevak Et Al
US00786.3289B2 (12) United States Patent (10) Patent No.: US 7,863,289 B2 Spevak et al. (45) Date of Patent: *Jan. 4, 2011 (54) COMPOUNDS AND METHODS FOR KINASE 5,658,775 A 8, 1997 Gilboa MODULATION, AND INDICATIONS 5,681,959 A 10/1997 Bishop et al. THEREFOR 5,700,637 A 12/1997 Southern (75) Inventors: Wayne Spevak, Berkeley, CA (US); 5,700.809 A 12/1997 Leeson et al. Hanna Cho, Oakland, CA (US); Prabha 5,712,285 A 1/1998 Curtis et al. N. Ibrahim, Mountain View, CA (US); 5,721,118 A 2, 1998 Scheffler Shenghua Shi, San Diego, CA (US); 5,744,305 A 4/1998 Fodor et al. Shumeye Mamo, Oakland, CA (US); 5,747,276 A 5/1998 Hoch et al. Samuel J. Gillette, Oakland, CA (US); 5,763,198 A 6/1998 Hirth et al. Hongyao Zhu, Berkeley, CA (US) 5,770.456 A 6/1998 Holmes (73) Assignee: Plexxikon, Inc., Berkeley, CA (US) 5,800,992 A 9, 1998 Fodor et al. 5,807,522 A 9, 1998 Brown et al. (*) Notice: Subject to any disclaimer, the term of this 5,830,645 A 11/1998 Pinkel et al. patent is extended or adjusted under 35 5,840,485 A 11/1998 Leblet al. U.S.C. 154(b) by 356 days. 5,856,174 A 1/1999 Lipshutz et al. 5,877,007 A 3/1999 Housey This patent is Subject to a terminal dis claimer. 5,959,098 A 9/1999 Goldberg et al. 5,965,452 A 10, 1999 Kovacs (21) Appl. -
Association of TNFAIP3 Polymorphism with Rheumatic Heart Disease in Chinese Han Population
Immunogenetics (2009) 61:739–744 DOI 10.1007/s00251-009-0405-8 ORIGINAL PAPER Association of TNFAIP3 polymorphism with rheumatic heart disease in Chinese Han population Rong Hua & Ji-bin Xu & Jiu-cun Wang & Li Zhu & bing Li & Yang Liu & Sheng-dong Huang & Li Jin & Zhi-yun Xu & Xiao-feng Wang Received: 6 September 2009 /Accepted: 13 October 2009 /Published online: 10 November 2009 # Springer-Verlag 2009 Abstract In a pair-matched case–control study (239 versus (p=0.000). Under a dominant model, CC/CT carriers had 478) conducted in Chinese Han population, we investigated a 0.54-fold reduced risk of RHD (95% confidence interval the association between tumor necrosis factor-α-induced 0.38–0.75, p=0.000) than TT carriers. Therefore, we report protein 3 (TNFAIP3) gene, tumor necrosis factor receptor- a new genetic variant (rs582757) in the TNFAIP3 gene that associated factor 1 (TRAF1) gene, complement component associated with the prevalence of RHD in Chinese Han 5 (C5) gene, and rheumatic heart disease (RHD). We population. Further genetic and functional studies are observed no association with RHD for the five tagging required to identify the etiological variants in linkage single nucleotide polymorphisms (tSNP) in the C5 gene, disequilibrium with this polymorphism. the three tSNPs in the TNFAIP3 gene, or the two tSNPs in the TRAF1 gene. However, we determined that the tSNP, Keywords Rheumatic heart disease . Polymorphism . rs582757, located at intron_5 of the TNFAIP3 gene, Genetics . Association associated with RHD in Chinese Han population. Both the distribution of genotype and allele frequencies differed significantly between case and control subjects (p=0.001 Introduction and p=0.0004, respectively). -
The Human Gene Connectome As a Map of Short Cuts for Morbid Allele Discovery
The human gene connectome as a map of short cuts for morbid allele discovery Yuval Itana,1, Shen-Ying Zhanga,b, Guillaume Vogta,b, Avinash Abhyankara, Melina Hermana, Patrick Nitschkec, Dror Friedd, Lluis Quintana-Murcie, Laurent Abela,b, and Jean-Laurent Casanovaa,b,f aSt. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065; bLaboratory of Human Genetics of Infectious Diseases, Necker Branch, Paris Descartes University, Institut National de la Santé et de la Recherche Médicale U980, Necker Medical School, 75015 Paris, France; cPlateforme Bioinformatique, Université Paris Descartes, 75116 Paris, France; dDepartment of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; eUnit of Human Evolutionary Genetics, Centre National de la Recherche Scientifique, Unité de Recherche Associée 3012, Institut Pasteur, F-75015 Paris, France; and fPediatric Immunology-Hematology Unit, Necker Hospital for Sick Children, 75015 Paris, France Edited* by Bruce Beutler, University of Texas Southwestern Medical Center, Dallas, TX, and approved February 15, 2013 (received for review October 19, 2012) High-throughput genomic data reveal thousands of gene variants to detect a single mutated gene, with the other polymorphic genes per patient, and it is often difficult to determine which of these being of less interest. This goes some way to explaining why, variants underlies disease in a given individual. However, at the despite the abundance of NGS data, the discovery of disease- population level, there may be some degree of phenotypic homo- causing alleles from such data remains somewhat limited. geneity, with alterations of specific physiological pathways under- We developed the human gene connectome (HGC) to over- come this problem.