Beta COP (COPB1) (NM 001144062) Human Tagged ORF Clone Product Data

OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RC227862L4 beta COP (COPB1) (NM_001144062) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: beta COP (COPB1) (NM_001144062) Human Tagged ORF Clone Tag: mGFP Symbol: COPB1 Synonyms: BARMACS; COPB Vector: pLenti-C-mGFP-P2A-Puro (PS100093) E. coli Selection: Chloramphenicol (34 ug/mL) Cell Selection: Puromycin ORF Nucleotide The ORF insert of this clone is exactly the same as(RC227862). Sequence: Restriction Sites: SgfI-MluI Cloning Scheme: ACCN: NM_001144062 ORF Size: 2859 bp This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 beta COP (COPB1) (NM_001144062) Human Tagged ORF Clone – RC227862L4 OTI Disclaimer: The molecular sequence of this clone aligns with the gene accession number as a point of reference only. However, individual transcript sequences of the same gene can differ through naturally occurring variations (e.g. polymorphisms), each with its own valid existence. This clone is substantially in agreement with the reference, but a complete review of all prevailing variants is recommended prior to use. More info OTI Annotation: This clone was engineered to express the complete ORF with an expression tag. Expression varies depending on the nature of the gene. RefSeq: NM_001144062.1, NP_001137534.1 RefSeq Size: 3368 bp RefSeq ORF: 2862 bp Locus ID: 1315 UniProt ID: P53618 MW: 107.1 kDa Gene Summary: This gene encodes a protein subunit of the coatomer complex associated with non-clathrin coated vesicles. The coatomer complex, also known as the coat protein complex 1, forms in the cytoplasm and is recruited to the Golgi by activated guanosine triphosphatases. Once at the Golgi membrane, the coatomer complex may assist in the movement of protein and lipid components back to the endoplasmic reticulum. Alternatively spliced transcript variants have been described. [provided by RefSeq, Jan 2009] This product is to be used for laboratory only. Not for diagnostic or therapeutic use. ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 2 / 2.

Copy Link

Recommended publications

View of HER2: Human Epidermal Growth Factor Receptor 2; TNBC: Triple-Negative Breast Resistance to Systemic Therapy in Patients with Breast Cancer
Wen et al. Cancer Cell Int (2018) 18:128 https://doi.org/10.1186/s12935-018-0625-9 Cancer Cell International PRIMARY RESEARCH Open Access Sulbactam‑enhanced cytotoxicity of doxorubicin in breast cancer cells Shao‑hsuan Wen1†, Shey‑chiang Su2†, Bo‑huang Liou3, Cheng‑hao Lin1 and Kuan‑rong Lee1* Abstract Background: Multidrug resistance (MDR) is a major obstacle in breast cancer treatment. The predominant mecha‑ nism underlying MDR is an increase in the activity of adenosine triphosphate (ATP)-dependent drug efux trans‑ porters. Sulbactam, a β-lactamase inhibitor, is generally combined with β-lactam antibiotics for treating bacterial infections. However, sulbactam alone can be used to treat Acinetobacter baumannii infections because it inhibits the expression of ATP-binding cassette (ABC) transporter proteins. This is the frst study to report the efects of sulbactam on mammalian cells. Methods: We used the breast cancer cell lines as a model system to determine whether sulbactam afects cancer cells. The cell viabilities in the present of doxorubicin with or without sulbactam were measured by MTT assay. Protein identities and the changes in protein expression levels in the cells after sulbactam and doxorubicin treatment were determined using LC–MS/MS. Real-time reverse transcription polymerase chain reaction (real-time RT-PCR) was used to analyze the change in mRNA expression levels of ABC transporters after treatment of doxorubicin with or without sulbactam. The efux of doxorubicin was measures by the doxorubicin efux assay. Results: MTT assay revealed that sulbactam enhanced the cytotoxicity of doxorubicin in breast cancer cells. The results of proteomics showed that ABC transporter proteins and proteins associated with the process of transcription and initiation of translation were reduced.
[Show full text]
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway.
[Show full text]
Transcriptomic Analysis of the Aquaporin (AQP) Gene Family
Pancreatology 19 (2019) 436e442 Contents lists available at ScienceDirect Pancreatology journal homepage: www.elsevier.com/locate/pan Transcriptomic analysis of the Aquaporin (AQP) gene family interactome identiﬁes a molecular panel of four prognostic markers in patients with pancreatic ductal adenocarcinoma Dimitrios E. Magouliotis a, b, Vasiliki S. Tasiopoulou c, Konstantinos Dimas d, * Nikos Sakellaridis d, Konstantina A. Svokos e, Alexis A. Svokos f, Dimitris Zacharoulis b, a Division of Surgery and Interventional Science, Faculty of Medical Sciences, UCL, London, UK b Department of Surgery, University of Thessaly, Biopolis, Larissa, Greece c Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, Larissa, Greece d Department of Pharmacology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, Larissa, Greece e The Warren Alpert Medical School of Brown University, Providence, RI, USA f Riverside Regional Medical Center, Newport News, VA, USA article info abstract Article history: Background: This study aimed to assess the differential gene expression of aquaporin (AQP) gene family Received 14 October 2018 interactome in pancreatic ductal adenocarcinoma (PDAC) using data mining techniques to identify novel Received in revised form candidate genes intervening in the pathogenicity of PDAC. 29 January 2019 Method: Transcriptome data mining techniques were used in order to construct the interactome of the Accepted 9 February 2019 AQP gene family and to determine which genes members are differentially expressed in PDAC as Available online 11 February 2019 compared to controls. The same techniques were used in order to evaluate the potential prognostic role of the differentially expressed genes. Keywords: PDAC Results: Transcriptome microarray data of four GEO datasets were incorporated, including 142 primary Aquaporin tumor samples and 104 normal pancreatic tissue samples.
[Show full text]
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
[Show full text]
Supplementary Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No.
[Show full text]
Formation of COPI-Coated Vesicles at a Glance Eric C
© 2018. Published by The Company of Biologists Ltd | Journal of Cell Science (2018) 131, jcs209890. doi:10.1242/jcs.209890 CELL SCIENCE AT A GLANCE Formation of COPI-coated vesicles at a glance Eric C. Arakel1 and Blanche Schwappach1,2,* ABSTRACT unresolved, this review attempts to refocus the perspectives of The coat protein complex I (COPI) allows the precise sorting of lipids the field. and proteins between Golgi cisternae and retrieval from the Golgi KEY WORDS: Arf1, ArfGAP, COPI, Coatomer, Golgi, Endoplasmic to the ER. This essential role maintains the identity of the early reticulum, Vesicle coat secretory pathway and impinges on key cellular processes, such as protein quality control. In this Cell Science at a Glance and accompanying poster, we illustrate the different stages of COPI- Introduction coated vesicle formation and revisit decades of research in the Vesicle coat proteins, such as the archetypal clathrin and the coat context of recent advances in the elucidation of COPI coat structure. protein complexes II and I (COPII and COPI, respectively) are By calling attention to an array of questions that have remained molecular machines with two central roles: enabling vesicle formation, and selecting protein and lipid cargo to be packaged within them. Thus, coat proteins fulfil a central role in the 1Department of Molecular Biology, Universitätsmedizin Göttingen, Humboldtallee homeostasis of the cell’s endomembrane system and are the basis 23, 37073 Göttingen, Germany. 2Max-Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany. of functionally segregated compartments. COPI operates in retrieval from the Golgi to the endoplasmic reticulum (ER) and in intra-Golgi *Author for correspondence ([email protected]) transport (Beck et al., 2009; Duden, 2003; Lee et al., 2004a; Spang, E.C.A., 0000-0001-7716-7149; B.S., 0000-0003-0225-6432 2009), and maintains ER- and Golgi-resident chaperones and enzymes where they belong.
[Show full text]
Supplementary Figures 1-14 and Supplementary References
SUPPORTING INFORMATION Spatial Cross-Talk Between Oxidative Stress and DNA Replication in Human Fibroblasts Marko Radulovic,1,2 Noor O Baqader,1 Kai Stoeber,3† and Jasminka Godovac-Zimmermann1* 1Division of Medicine, University College London, Center for Nephrology, Royal Free Campus, Rowland Hill Street, London, NW3 2PF, UK. 2Insitute of Oncology and Radiology, Pasterova 14, 11000 Belgrade, Serbia 3Research Department of Pathology and UCL Cancer Institute, Rockefeller Building, University College London, University Street, London WC1E 6JJ, UK †Present Address: Shionogi Europe, 33 Kingsway, Holborn, London WC2B 6UF, UK TABLE OF CONTENTS 1. Supplementary Figures 1-14 and Supplementary References. Figure S-1. Network and joint spatial razor plot for 18 enzymes of glycolysis and the pentose phosphate shunt. Figure S-2. Correlation of SILAC ratios between OXS and OAC for proteins assigned to the SAME class. Figure S-3. Overlap matrix (r = 1) for groups of CORUM complexes containing 19 proteins of the 49-set. Figure S-4. Joint spatial razor plots for the Nop56p complex and FIB-associated complex involved in ribosome biogenesis. Figure S-5. Analysis of the response of emerin nuclear envelope complexes to OXS and OAC. Figure S-6. Joint spatial razor plots for the CCT protein folding complex, ATP synthase and V-Type ATPase. Figure S-7. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated by GO to nucleocytoplasmic transport (GO:0006913). Figure S-8. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated to endocytosis (GO:0006897). Figure S-9. Joint spatial razor plots for 401-set proteins annotated by GO to small GTPase mediated signal transduction (GO:0007264) and/or GTPase activity (GO:0003924).
[Show full text]
The Role of ARF Family Proteins and Their Regulators and Effectors in Cancer Progression: a Therapeutic Perspective
fcell-08-00217 April 17, 2020 Time: 19:19 # 1 REVIEW published: 21 April 2020 doi: 10.3389/fcell.2020.00217 The Role of ARF Family Proteins and Their Regulators and Effectors in Cancer Progression: A Therapeutic Perspective Cristina Casalou†, Andreia Ferreira† and Duarte C. Barral* CEDOC, NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Lisbon, Portugal The Adenosine diphosphate-Ribosylation Factor (ARF) family belongs to the RAS superfamily of small GTPases and is involved in a wide variety of physiological processes, such as cell proliferation, motility and differentiation by regulating membrane Edited by: trafﬁc and associating with the cytoskeleton. Like other members of the RAS Sunil Kumar Verma, superfamily, ARF family proteins are activated by Guanine nucleotide Exchange Factors Centre for Cellular & Molecular (GEFs) and inactivated by GTPase-Activating Proteins (GAPs). When active, they bind Biology (CCMB), India effectors, which mediate downstream functions. Several studies have reported that Reviewed by: Wei-Hsiung Yang, cancer cells are able to subvert membrane trafﬁc regulators to enhance migration and Mercer University, United States invasion. Indeed, members of the ARF family, including ARF-Like (ARL) proteins have Ira Daar, National Cancer Institute (NCI), been implicated in tumorigenesis and progression of several types of cancer. Here, we United States review the role of ARF family members, their GEFs/GAPs and effectors in tumorigenesis *Correspondence: and cancer progression, highlighting the ones that can have a pro-oncogenic behavior Duarte C. Barral or function as tumor suppressors. Moreover, we propose possible mechanisms and [email protected] approaches to target these proteins, toward the development of novel therapeutic †These authors have contributed equally to this work strategies to impair tumor progression.
[Show full text]
Ykt6 Membrane-To-Cytosol Cycling Regulates Exosomal Wnt Secretion
bioRxiv preprint doi: https://doi.org/10.1101/485565; this version posted December 3, 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. Ykt6 membrane-to-cytosol cycling regulates exosomal Wnt secretion Karen Linnemannstöns1,2, Pradhipa Karuna1,2, Leonie Witte1,2, Jeanette Kittel1,2, Adi Danieli1,2, Denise Müller1,2, Lena Nitsch1,2, Mona Honemann-Capito1,2, Ferdinand Grawe3,4, Andreas Wodarz3,4 and Julia Christina Gross1,2* Affiliations: 1Hematology and Oncology, University Medical Center Goettingen, Goettingen, Germany. 2Developmental Biochemistry, University Medical Center Goettingen, Goettingen, Germany. 3Molecular Cell Biology, Institute I for Anatomy, University of Cologne Medical School, Cologne, Germany 4Cluster of Excellence-Cellular Stress Response in Aging-Associated Diseases (CECAD), Cologne, Germany *Correspondence: Dr. Julia Christina Gross, Hematology and Oncology/Developmental Biochemistry, University Medical Center Goettingen, Justus-von-Liebig Weg 11, 37077 Goettingen Germany Abstract Protein trafficking in the secretory pathway, for example the secretion of Wnt proteins, requires tight regulation. These ligands activate Wnt signaling pathways and are crucially involved in development and disease. Wnt is transported to the plasma membrane by its cargo receptor Evi, where Wnt/Evi complexes are endocytosed and sorted onto exosomes for long-range secretion. However, the trafficking steps within the endosomal compartment are not fully understood. The promiscuous SNARE Ykt6 folds into an auto-inhibiting conformation in the cytosol, but a portion associates with membranes by its farnesylated and palmitoylated C-terminus. Here, we demonstrate that membrane detachment of Ykt6 is essential for exosomal Wnt secretion.
[Show full text]
Host Cell Factors Necessary for Influenza a Infection: Meta-Analysis of Genome Wide Studies
Host Cell Factors Necessary for Influenza A Infection: Meta-Analysis of Genome Wide Studies Juliana S. Capitanio and Richard W. Wozniak Department of Cell Biology, Faculty of Medicine and Dentistry, University of Alberta Abstract: The Influenza A virus belongs to the Orthomyxoviridae family. Influenza virus infection occurs yearly in all countries of the world. It usually kills between 250,000 and 500,000 people and causes severe illness in millions more. Over the last century alone we have seen 3 global influenza pandemics. The great human and financial cost of this disease has made it the second most studied virus today, behind HIV. Recently, several genome-wide RNA interference studies have focused on identifying host molecules that participate in Influen- za infection. We used nine of these studies for this meta-analysis. Even though the overlap among genes identified in multiple screens was small, network analysis indicates that similar protein complexes and biological functions of the host were present. As a result, several host gene complexes important for the Influenza virus life cycle were identified. The biological function and the relevance of each identified protein complex in the Influenza virus life cycle is further detailed in this paper. Background and PA bound to the viral genome via nucleoprotein (NP). The viral core is enveloped by a lipid membrane derived from Influenza virus the host cell. The viral protein M1 underlies the membrane and anchors NEP/NS2. Hemagglutinin (HA), neuraminidase Viruses are the simplest life form on earth. They parasite host (NA), and M2 proteins are inserted into the envelope, facing organisms and subvert the host cellular machinery for differ- the viral exterior.
[Show full text]
WRN-Mutated Colorectal Cancer Is Characterized by a Distinct Genetic Phenotype
Article WRN-Mutated Colorectal Cancer Is Characterized by a Distinct Genetic Phenotype Kai Zimmer, Alberto Puccini, Joanne Xiu, Yasmine Baca, Gilbert Spizzo, Heinz-Josef Lenz, Francesca Battaglin, Richard M. Goldberg, Axel Grothey, Anthony F. Shields, Mohamed E. Salem, John L. Marshall, W. Michael Korn, Dominik Wolf, Florian Kocher and Andreas Seeber Supplementary Material Table S1. Mutations in the WRN gene. Protein Change N (%) Effect of Mutation S1128fs 26 (30.9) Frameshift R369X 6 (7.1) Nonsense Frameshift* 4 (4.7) L6fs 4 (4.7) Frameshift D163fs 2 (2.38) Frameshift R389fs 2 (2.38) Frameshift R889X 2 (2.38) NA S952X 2 (2.38) Nonsense A136fs 1 (1.19) Frameshift c.1269+2T>C 1 (1.19) NA c.1898+2T>G 1 (1.19) NA c.209+2T>A 1 (1.19) Splicing c.210-1G>A 1 (1.19) Splicing c.3383+2T>C 1 (1.19) NA c.355+1G>T 1 (1.19) Splicing c.3687+2T>G 1 (1.19) Splicing c.3983-1G>T 1 (1.19) Splicing E1068X 1 (1.19) Nonsense E1217X 1 (1.19) Nonsense E244X 1 (1.19) Nonsense E371X 1 (1.19) NA E399X 1 (1.19) Nonsense E488X 1 (1.19) Nonsense E48X 1 (1.19) Nonsense E513X 1 (1.19) Frameshift F1037fs 1 (1.19) Frameshift G1377fs 1 (1.19) Frameshift I1183fs 1 (1.19) Frameshift K135fs 1 (1.19) Nonsense K167X 1 (1.19) Frameshift K5fs 1 (1.19) Frameshift K901fs 1 (1.19) Frameshift L967fs 1 (1.19) Frameshift M497fs 1 (1.19) Frameshift Cancers 2020, 12, x; doi: www.mdpi.com/journal/cancers Cancers 2020, 12 S2 of 13 N166fs 1 (1.19) Frameshift Q11fs 1 (1.19) Frameshift R1305X 1 (1.19) Nonsense R279fs 1 (1.19) Frameshift R565X 1 (1.19) Nonsene R741X 1 (1.19) Nonsense R987X 1 (1.19) NA T1011fs 1 (1.19) Frameshift W1014X 1 (1.19) Nonsense Y57X 1 (1.19) Nonsense Grand Total 84 *4 Frameshift mutations could not be described more precisely.
[Show full text]
Research Article Complex and Multidimensional Lipid Raft Alterations in a Murine Model of Alzheimer’S Disease
SAGE-Hindawi Access to Research International Journal of Alzheimer’s Disease Volume 2010, Article ID 604792, 56 pages doi:10.4061/2010/604792 Research Article Complex and Multidimensional Lipid Raft Alterations in a Murine Model of Alzheimer’s Disease Wayne Chadwick, 1 Randall Brenneman,1, 2 Bronwen Martin,3 and Stuart Maudsley1 1 Receptor Pharmacology Unit, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Suite 100, Baltimore, MD 21224, USA 2 Miller School of Medicine, University of Miami, Miami, FL 33124, USA 3 Metabolism Unit, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Suite 100, Baltimore, MD 21224, USA Correspondence should be addressed to Stuart Maudsley, [email protected] Received 17 May 2010; Accepted 27 July 2010 Academic Editor: Gemma Casadesus Copyright © 2010 Wayne Chadwick et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Various animal models of Alzheimer’s disease (AD) have been created to assist our appreciation of AD pathophysiology, as well as aid development of novel therapeutic strategies. Despite the discovery of mutated proteins that predict the development of AD, there are likely to be many other proteins also involved in this disorder. Complex physiological processes are mediated by coherent interactions of clusters of functionally related proteins. Synaptic dysfunction is one of the hallmarks of AD. Synaptic proteins are organized into multiprotein complexes in high-density membrane structures, known as lipid rafts. These microdomains enable coherent clustering of synergistic signaling proteins.
[Show full text]