Rabbit Anti-Beta Arrestin 2/FITC Conjugated Antibody
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Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. -
Beta-Arrestin-Mediated Signaling in the Heart
SPECIAL ARTICLE Circ J 2008; 72: 1725–1729 Beta-Arrestin-Mediated Signaling in the Heart Priyesh A. Patel, BS; Douglas G. Tilley, PhD*; Howard A. Rockman, MD*,** Beta-arrestin is a multifunctional adapter protein well known for its role in G-protein-coupled receptor (GPCR) desensitization. Exciting new evidence indicates thatβ-arrestin is also a signaling molecule capable of initiating its own G-protein-independent signaling at GPCRs. One of the best-studiedβ-arrestin signaling pathways is the one involvingβ-arrestin-dependent activation of a mitogen-activated protein kinase cascade, the extracellular regulated kinase (ERK). ERK signaling, which is classically activated by agonist stimulation of the epidermal growth factor receptor (EGFR), can be activated by a number of GPCRs in aβ-arrestin-dependent manner. Recent work in animal models of heart failure suggests thatβ-arrestin-dependent activation of EGFR/ERK signaling by theβ-1-adrenergic receptor, and possibly the angiotensin II Type 1A receptor, are cardioprotective. Hence, a new model of signaling at cardiac GPCRs has emerged and implicates classical G-protein-mediated signaling with promoting harmful remodeling in heart failure, while concurrently linkingβ-arrestin-dependent, G-protein-inde- pendent signaling with cardioprotective effects. Based on this paradigm, a new class of drugs could be identified, termed “biased ligands”, which simultaneously block harmful G-protein signaling, while also promoting cardio- protectiveβ-arrestin-dependent signaling, leading to a potential breakthrough -
BMC Evolutionary Biology Biomed Central
BMC Evolutionary Biology BioMed Central Research article Open Access On the origins of arrestin and rhodopsin Carlos E Alvarez1,2,3 Address: 1Center for Molecular and Human Genetics, The Research Institute at Nationwide Children's Hospital, Columbus, OH, 43205, USA, 2Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, 43210, USA and 3Novartis Institutes of BioMedical Research, CH-4002 Basel, Switzerland Email: Carlos E Alvarez - [email protected] Published: 29 July 2008 Received: 11 January 2008 Accepted: 29 July 2008 BMC Evolutionary Biology 2008, 8:222 doi:10.1186/1471-2148-8-222 This article is available from: http://www.biomedcentral.com/1471-2148/8/222 © 2008 Alvarez; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: G protein coupled receptors (GPCRs) are the most numerous proteins in mammalian genomes, and the most common targets of clinical drugs. However, their evolution remains enigmatic. GPCRs are intimately associated with trimeric G proteins, G protein receptor kinases, and arrestins. We conducted phylogenetic studies to reconstruct the history of arrestins. Those findings, in turn, led us to investigate the origin of the photosensory GPCR rhodopsin. Results: We found that the arrestin clan is comprised of the Spo0M protein family in archaea and bacteria, and the arrestin and Vps26 families in eukaryotes. The previously known animal arrestins are members of the visual/beta subfamily, which branched from the founding "alpha" arrestins relatively recently. -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
140503 IPF Signatures Supplement Withfigs Thorax
Supplementary material for Heterogeneous gene expression signatures correspond to distinct lung pathologies and biomarkers of disease severity in idiopathic pulmonary fibrosis Daryle J. DePianto1*, Sanjay Chandriani1⌘*, Alexander R. Abbas1, Guiquan Jia1, Elsa N. N’Diaye1, Patrick Caplazi1, Steven E. Kauder1, Sabyasachi Biswas1, Satyajit K. Karnik1#, Connie Ha1, Zora Modrusan1, Michael A. Matthay2, Jasleen Kukreja3, Harold R. Collard2, Jackson G. Egen1, Paul J. Wolters2§, and Joseph R. Arron1§ 1Genentech Research and Early Development, South San Francisco, CA 2Department of Medicine, University of California, San Francisco, CA 3Department of Surgery, University of California, San Francisco, CA ⌘Current address: Novartis Institutes for Biomedical Research, Emeryville, CA. #Current address: Gilead Sciences, Foster City, CA. *DJD and SC contributed equally to this manuscript §PJW and JRA co-directed this project Address correspondence to Paul J. Wolters, MD University of California, San Francisco Department of Medicine Box 0111 San Francisco, CA 94143-0111 [email protected] or Joseph R. Arron, MD, PhD Genentech, Inc. MS 231C 1 DNA Way South San Francisco, CA 94080 [email protected] 1 METHODS Human lung tissue samples Tissues were obtained at UCSF from clinical samples from IPF patients at the time of biopsy or lung transplantation. All patients were seen at UCSF and the diagnosis of IPF was established through multidisciplinary review of clinical, radiological, and pathological data according to criteria established by the consensus classification of the American Thoracic Society (ATS) and European Respiratory Society (ERS), Japanese Respiratory Society (JRS), and the Latin American Thoracic Association (ALAT) (ref. 5 in main text). Non-diseased normal lung tissues were procured from lungs not used by the Northern California Transplant Donor Network. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Disease-Related Cellular Protein Networks Differentially Affected
www.nature.com/scientificreports OPEN Disease‑related cellular protein networks diferentially afected under diferent EGFR mutations in lung adenocarcinoma Toshihide Nishimura1,8*, Haruhiko Nakamura1,2,8, Ayako Yachie3,8, Takeshi Hase3,8, Kiyonaga Fujii1,8, Hirotaka Koizumi4, Saeko Naruki4, Masayuki Takagi4, Yukiko Matsuoka3, Naoki Furuya5, Harubumi Kato6,7 & Hisashi Saji2 It is unclear how epidermal growth factor receptor EGFR major driver mutations (L858R or Ex19del) afect downstream molecular networks and pathways. This study aimed to provide information on the infuences of these mutations. The study assessed 36 protein expression profles of lung adenocarcinoma (Ex19del, nine; L858R, nine; no Ex19del/L858R, 18). Weighted gene co-expression network analysis together with analysis of variance-based screening identifed 13 co-expressed modules and their eigen proteins. Pathway enrichment analysis for the Ex19del mutation demonstrated involvement of SUMOylation, epithelial and mesenchymal transition, ERK/mitogen- activated protein kinase signalling via phosphorylation and Hippo signalling. Additionally, analysis for the L858R mutation identifed various pathways related to cancer cell survival and death. With regard to the Ex19del mutation, ROCK, RPS6KA1, ARF1, IL2RA and several ErbB pathways were upregulated, whereas AURK and GSKIP were downregulated. With regard to the L858R mutation, RB1, TSC22D3 and DOCK1 were downregulated, whereas various networks, including VEGFA, were moderately upregulated. In all mutation types, CD80/CD86 (B7), MHC, CIITA and IFGN were activated, whereas CD37 and SAFB were inhibited. Costimulatory immune-checkpoint pathways by B7/CD28 were mainly activated, whereas those by PD-1/PD-L1 were inhibited. Our fndings may help identify potential therapeutic targets and develop therapeutic strategies to improve patient outcomes. -
Table S4. Trophoblast Differentiation-Associated Genes
Table S4. Trophoblast differentiation-associated genes Gene Stem Chromosomal Affymetrix ID Gene Title Symbol Ave Dif Ave GenBank Location dif/ stem t-test 1390511_at LOC308394 Cgm4 10 1863 BI285801 1 193.51 0.006 1378534_at similar to brain carcinoembryonic antigen LOC308394 10 1746 NM_001025679 1q21 183.10 0.001 1388433_at keratin complex 1, acidic, gene 19 Krt1-19 53 7958 NM_199498 10q32.1 149.07 0.022 1369029_at phospholipid scramblase 1 Plscr1 20 2050 NM_057194 8q31 101.12 0.028 1389856_at carcinoembryonic antigen gene family 4 Cgm4 57 5073 NM_012525 1q21 89.73 0.001 carcinoembryonic antigen-related cell 1368996_at adhesion molecule 3 Ceacam3 202 17879 NM_012702 1q21 88.71 0.001 1392832_at similar to angiopoietin-like 1 LOC684489 17 1398 XM_001068284 --- 83.66 0.001 1377666_at choline dehydrogenase Chdh 26 1571 NM_198731 16p16 60.59 0.003 cytochrome P450, family 11, subfamily a, 1368468_at polypeptide 1 Cyp11a1 196 9216 NM_017286 8q24 47.11 0.000 1376934_x_at similar to brain carcinoembryonic antigen Cgm4 53 2146 BI285801 1 40.22 0.000 stimulated by retinoic acid gene 6 homolog 1390525_a_at (mouse) Stra6 28 1037 NM_001029924 8q24 37.44 0.001 1382690_at carcinoembryonic antigen gene family 4 Cgm4 81 2729 NM_012525 1q21 33.86 0.001 1367809_at prolactin family 4, subfamily a, member 1 Prl4a1 683 22573 NM_017036 17p11 33.05 0.004 calcium channel, voltage-dependent, L type, 1383458_at alpha 1D subunit Cacna1d 26 802 BF403759 16 30.89 0.001 1370852_at spleen protein 1 precursor LOC171573 692 20968 NM_138537 8q21 30.29 0.003 1376036_at transporter -
AP2B1 Monoclonal Antibody (M01), Clone 2D5
AP2B1 monoclonal antibody (M01), clone 2D5 Catalog # : H00000163-M01 規格 : [ 50 ug ] List All Specification Application Image Product Mouse monoclonal antibody raised against a partial recombinant Western Blot (Recombinant protein) Description: AP2B1. Immunohistochemistry Immunogen: AP2B1 (NP_001273.1, 585 a.a. ~ 651 a.a) partial recombinant protein (Formalin/PFA-fixed paraffin- with GST tag. MW of the GST tag alone is 26 KDa. embedded sections) Sequence: SHGIHRKHLPIHHGSTDAGDSPVGTTTATNLEQPQVIPSQGDLLGDLLNL DLGPPVNVPQVSSMQMG Host: Mouse Reactivity: Human enlarge Isotype: IgG1 Kappa Sandwich ELISA (Recombinant protein) Quality Control Antibody Reactive Against Recombinant Protein. Testing: enlarge ELISA Western Blot detection against Immunogen (33.11 KDa) . Storage Buffer: In 1x PBS, pH 7.4 Storage Store at -20°C or lower. Aliquot to avoid repeated freezing and thawing. Instruction: MSDS: Download Interspecies Rat (100%) Antigen Sequence: Datasheet: Download Applications Western Blot (Recombinant protein) Protocol Download Immunohistochemistry (Formalin/PFA-fixed paraffin-embedded sections) Page 1 of 3 2021/1/21 enlarge this image Immunoperoxidase of monoclonal antibody to AP2B1 on formalin-fixed paraffin-embedded human placenta. [antibody concentration 3 ug/ml] Protocol Download Sandwich ELISA (Recombinant protein) Detection limit for recombinant GST tagged AP2B1 is 0.1 ng/ml as a capture antibody. Protocol Download ELISA Gene Information Entrez GeneID: 163 GeneBank NM_001282 Accession#: Protein NP_001273.1 Accession#: Gene Name: AP2B1 Gene Alias: ADTB2,AP105B,AP2-BETA,CLAPB1,DKFZp781K0743 Gene adaptor-related protein complex 2, beta 1 subunit Description: Omim ID: 601025 Gene Ontology: Hyperlink Gene Summary: The protein encoded by this gene is one of two large chain components of the assembly protein complex 2, which serves to link clathrin to receptors in coated vesicles. -
Integrating Protein Copy Numbers with Interaction Networks to Quantify Stoichiometry in Mammalian Endocytosis
bioRxiv preprint doi: https://doi.org/10.1101/2020.10.29.361196; this version posted October 29, 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-ND 4.0 International license. Integrating protein copy numbers with interaction networks to quantify stoichiometry in mammalian endocytosis Daisy Duan1, Meretta Hanson1, David O. Holland2, Margaret E Johnson1* 1TC Jenkins Department of Biophysics, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218. 2NIH, Bethesda, MD, 20892. *Corresponding Author: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.10.29.361196; this version posted October 29, 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-ND 4.0 International license. Abstract Proteins that drive processes like clathrin-mediated endocytosis (CME) are expressed at various copy numbers within a cell, from hundreds (e.g. auxilin) to millions (e.g. clathrin). Between cell types with identical genomes, copy numbers further vary significantly both in absolute and relative abundance. These variations contain essential information about each protein’s function, but how significant are these variations and how can they be quantified to infer useful functional behavior? Here, we address this by quantifying the stoichiometry of proteins involved in the CME network. We find robust trends across three cell types in proteins that are sub- vs super-stoichiometric in terms of protein function, network topology (e.g. -
An Integrated Approach to Comprehensively Map the Molecular Context of Proteins
bioRxiv preprint doi: https://doi.org/10.1101/264788; this version posted February 13, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Liu et al. An integrated approach to comprehensively map the molecular context of proteins Xiaonan Liu1,2, Kari Salokas1,2, Fitsum Tamene1,2,3 and Markku Varjosalo1,2,3* 1Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland 2Helsinki Institute of Life Science, University of Helsinki, Helsinki 00014, Finland 3Proteomics Unit, University of Helsinki, Helsinki 00014, Finland *Corresponding author Abstract: Protein-protein interactions underlie almost all cellular functions. The comprehensive mapping of these complex cellular networks of stable and transient associations has been made available by affi nity purifi cation mass spectrometry (AP-MS) and more recently by proximity based labelling methods such as BioID. Due the advancements in both methods and MS instrumentation, an in-depth analysis of the whole human proteome is at grasps. In order to facilitate this, we designed and optimized an integrated approach utilizing MAC-tag combining both AP-MS and BioID in a single construct. We systematically applied this approach to 18 subcellular localization markers and generated a molecular context database, which can be used to defi ne molecular locations for any protein of interest. In addition, we show that by combining the AP-MS and BioID results we can also obtain interaction distances within a complex. Taken together, our combined strategy off ers comprehensive approach for mapping physical and functional protein interactions. Introduction: Majority of proteins do not function in isolation geting the endogenous bait protein, allowing and their interactions with other proteins defi ne purifi cation of the bait protein together with the their cellular functions. -
Supp Table 6.Pdf
Supplementary Table 6. Processes associated to the 2037 SCL candidate target genes ID Symbol Entrez Gene Name Process NM_178114 AMIGO2 adhesion molecule with Ig-like domain 2 adhesion NM_033474 ARVCF armadillo repeat gene deletes in velocardiofacial syndrome adhesion NM_027060 BTBD9 BTB (POZ) domain containing 9 adhesion NM_001039149 CD226 CD226 molecule adhesion NM_010581 CD47 CD47 molecule adhesion NM_023370 CDH23 cadherin-like 23 adhesion NM_207298 CERCAM cerebral endothelial cell adhesion molecule adhesion NM_021719 CLDN15 claudin 15 adhesion NM_009902 CLDN3 claudin 3 adhesion NM_008779 CNTN3 contactin 3 (plasmacytoma associated) adhesion NM_015734 COL5A1 collagen, type V, alpha 1 adhesion NM_007803 CTTN cortactin adhesion NM_009142 CX3CL1 chemokine (C-X3-C motif) ligand 1 adhesion NM_031174 DSCAM Down syndrome cell adhesion molecule adhesion NM_145158 EMILIN2 elastin microfibril interfacer 2 adhesion NM_001081286 FAT1 FAT tumor suppressor homolog 1 (Drosophila) adhesion NM_001080814 FAT3 FAT tumor suppressor homolog 3 (Drosophila) adhesion NM_153795 FERMT3 fermitin family homolog 3 (Drosophila) adhesion NM_010494 ICAM2 intercellular adhesion molecule 2 adhesion NM_023892 ICAM4 (includes EG:3386) intercellular adhesion molecule 4 (Landsteiner-Wiener blood group)adhesion NM_001001979 MEGF10 multiple EGF-like-domains 10 adhesion NM_172522 MEGF11 multiple EGF-like-domains 11 adhesion NM_010739 MUC13 mucin 13, cell surface associated adhesion NM_013610 NINJ1 ninjurin 1 adhesion NM_016718 NINJ2 ninjurin 2 adhesion NM_172932 NLGN3 neuroligin