Fast Transport of RNA Granules by Direct Interactions with KIF5A/KLC1 Motors Prevents Axon 2 Degeneration 3 4 Yusuke Fukuda1,2, Maria F
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Hares, K. M., Miners, S., Scolding, N
Hares, K. M. , Miners, S., Scolding, N., Love, S., & Wilkins, A. (2019). KIF5A and KLC1 expression in Alzheimer’s disease: relationship and genetic influences. AMRC Open Research, 1, [1]. https://doi.org/10.12688/amrcopenres.12861.1 Publisher's PDF, also known as Version of record License (if available): CC BY Link to published version (if available): 10.12688/amrcopenres.12861.1 Link to publication record in Explore Bristol Research PDF-document This is the final published version of the article (version of record). It first appeared online via F1000 Research at https://amrcopenresearch.org/articles/1-1/v1 . Please refer to any applicable terms of use of the publisher. University of Bristol - Explore Bristol Research General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/red/research-policy/pure/user-guides/ebr-terms/ AMRC Open Research AMRC Open Research 2019, 1:1 Last updated: 11 APR 2019 RESEARCH ARTICLE KIF5A and KLC1 expression in Alzheimer’s disease: relationship and genetic influences [version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved] Kelly Hares 1, Scott Miners2, Neil Scolding1, Seth Love2, Alastair Wilkins1 1Bristol Medical School: Translational Health Sciences, MS and Stem Cell Group, University of Bristol, Bristol, BS10 5NB, UK 2Bristol Medical School: Translational Health Sciences, Dementia Research Group, University of Bristol, Bristol, BS10 5NB, UK First published: 19 Feb 2019, 1:1 (https://doi.org/10.12688/amrcopenres.12861.1 Open Peer Review v1 ) Latest published: 19 Feb 2019, 1:1 ( https://doi.org/10.12688/amrcopenres.12861.1) Referee Status: Abstract Invited Referees Background: Early disturbances in axonal transport, before the onset of gross 1 2 3 neuropathology, occur in a spectrum of neurodegenerative diseases including Alzheimer’s disease. -
A Comparative Analysis of Transcribed Genes in the Mouse Hypothalamus and Neocortex Reveals Chromosomal Clustering
A comparative analysis of transcribed genes in the mouse hypothalamus and neocortex reveals chromosomal clustering Wee-Ming Boon*, Tim Beissbarth†, Lavinia Hyde†, Gordon Smyth†, Jenny Gunnersen*, Derek A. Denton*‡, Hamish Scott†, and Seong-Seng Tan* *Howard Florey Institute, University of Melbourne, Parkville 3052, Australia; and †Genetics and Bioinfomatics Division, Walter and Eliza Hall Institute of Medical Research, Royal Parade, Parkville 3050, Australia Contributed by Derek A. Denton, August 26, 2004 The hypothalamus and neocortex are subdivisions of the mamma- representing all of the genes that are expressed (qualitative and lian forebrain, and yet, they have vastly different evolutionary quantitative) in the hypothalamus and neocortex under standard histories, cytoarchitecture, and biological functions. In an attempt conditions. to define these attributes in terms of their genetic activity, we have In the current study, we describe the use of the Serial Analysis compared their genetic repertoires by using the Serial Analysis of of Gene Expression (SAGE) database, which allows simulta- Gene Expression database. From a comparison of 78,784 hypothal- neous detection of the expression levels of the entire genome amus tags with 125,296 neocortical tags, we demonstrate that each without a priori knowledge of gene sequences (13). SAGE takes structure possesses a different transcriptional profile in terms of advantage of the fact that a small sequence tag taken from a gene ontological characteristics and expression levels. Despite its defined position within the transcript is sufficient to identify the more recent evolutionary history, the neocortex has a more com- gene (from known cDNA or EST sequences), and up to 40 tags plex pattern of gene activity. -
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. -
Drp1 Overexpression Induces Desmin Disassembling and Drives Kinesin-1 Activation Promoting Mitochondrial Trafficking in Skeletal Muscle
Cell Death & Differentiation (2020) 27:2383–2401 https://doi.org/10.1038/s41418-020-0510-7 ARTICLE Drp1 overexpression induces desmin disassembling and drives kinesin-1 activation promoting mitochondrial trafficking in skeletal muscle 1 1 2 2 2 3 Matteo Giovarelli ● Silvia Zecchini ● Emanuele Martini ● Massimiliano Garrè ● Sara Barozzi ● Michela Ripolone ● 3 1 4 1 5 Laura Napoli ● Marco Coazzoli ● Chiara Vantaggiato ● Paulina Roux-Biejat ● Davide Cervia ● 1 1 2 1,4 6 Claudia Moscheni ● Cristiana Perrotta ● Dario Parazzoli ● Emilio Clementi ● Clara De Palma Received: 1 August 2019 / Revised: 13 December 2019 / Accepted: 23 January 2020 / Published online: 10 February 2020 © The Author(s) 2020. This article is published with open access Abstract Mitochondria change distribution across cells following a variety of pathophysiological stimuli. The mechanisms presiding over this redistribution are yet undefined. In a murine model overexpressing Drp1 specifically in skeletal muscle, we find marked mitochondria repositioning in muscle fibres and we demonstrate that Drp1 is involved in this process. Drp1 binds KLC1 and enhances microtubule-dependent transport of mitochondria. Drp1-KLC1 coupling triggers the displacement of KIF5B from 1234567890();,: 1234567890();,: kinesin-1 complex increasing its binding to microtubule tracks and mitochondrial transport. High levels of Drp1 exacerbate this mechanism leading to the repositioning of mitochondria closer to nuclei. The reduction of Drp1 levels decreases kinesin-1 activation and induces the partial recovery of mitochondrial distribution. Drp1 overexpression is also associated with higher cyclin-dependent kinase-1 (Cdk-1) activation that promotes the persistent phosphorylation of desmin at Ser-31 and its disassembling. Fission inhibition has a positive effect on desmin Ser-31 phosphorylation, regardless of Cdk-1 activation, suggesting that induction of both fission and Cdk-1 are required for desmin collapse. -
Understanding the Role of the Chromosome 15Q25.1 in COPD Through Epigenetics and Transcriptomics
European Journal of Human Genetics (2018) 26:709–722 https://doi.org/10.1038/s41431-017-0089-8 ARTICLE Understanding the role of the chromosome 15q25.1 in COPD through epigenetics and transcriptomics 1 1,2 1,3,4 5,6 5,6 Ivana Nedeljkovic ● Elena Carnero-Montoro ● Lies Lahousse ● Diana A. van der Plaat ● Kim de Jong ● 5,6 5,7 6 8 9 10 Judith M. Vonk ● Cleo C. van Diemen ● Alen Faiz ● Maarten van den Berge ● Ma’en Obeidat ● Yohan Bossé ● 11 1,12 12 1 David C. Nickle ● BIOS Consortium ● Andre G. Uitterlinden ● Joyce J. B. van Meurs ● Bruno C. H. Stricker ● 1,4,13 6,8 5,6 1 1 Guy G. Brusselle ● Dirkje S. Postma ● H. Marike Boezen ● Cornelia M. van Duijn ● Najaf Amin Received: 14 March 2017 / Revised: 6 November 2017 / Accepted: 19 December 2017 / Published online: 8 February 2018 © The Author(s) 2018. This article is published with open access Abstract Chronic obstructive pulmonary disease (COPD) is a major health burden in adults and cigarette smoking is considered the most important environmental risk factor of COPD. Chromosome 15q25.1 locus is associated with both COPD and smoking. Our study aims at understanding the mechanism underlying the association of chromosome 15q25.1 with COPD through epigenetic and transcriptional variation in a population-based setting. To assess if COPD-associated variants in 1234567890();,: 15q25.1 are methylation quantitative trait loci, epigenome-wide association analysis of four genetic variants, previously associated with COPD (P < 5 × 10−8) in the 15q25.1 locus (rs12914385:C>T-CHRNA3, rs8034191:T>C-HYKK, rs13180: C>T-IREB2 and rs8042238:C>T-IREB2), was performed in the Rotterdam study (n = 1489). -
Proteomic Analysis Uncovers Measles Virus Protein C Interaction with P65
bioRxiv preprint doi: https://doi.org/10.1101/2020.05.08.084418; this version posted May 9, 2020. 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. Proteomic Analysis Uncovers Measles Virus Protein C Interaction with p65/iASPP/p53 Protein Complex Alice Meignié1,2*, Chantal Combredet1*, Marc Santolini 3,4, István A. Kovács4,5,6, Thibaut Douché7, Quentin Giai Gianetto 7,8, Hyeju Eun9, Mariette Matondo7, Yves Jacob10, Regis Grailhe9, Frédéric Tangy1**, and Anastassia V. Komarova1, 10** 1 Viral Genomics and Vaccination Unit, Department of Virology, Institut Pasteur, CNRS UMR-3569, 75015 Paris, France 2 Université Paris Diderot, Sorbonne Paris Cité, Paris, France 3 Center for Research and Interdisciplinarity (CRI), Université de Paris, INSERM U1284 4 Network Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA 5 Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208-3109, USA 6 Department of Network and Data Science, Central European University, Budapest, H-1051, Hungary 7 Proteomics platform, Mass Spectrometry for Biology Unit (MSBio), Institut Pasteur, CNRS USR 2000, Paris, France. 8 Bioinformatics and Biostatistics Hub, Computational Biology Department, Institut Pasteur, CNRS USR3756, Paris, France 9 Technology Development Platform, Institut Pasteur Korea, Seongnam-si, Republic of Korea 10 Laboratory of Molecular Genetics of RNA Viruses, Institut Pasteur, CNRS UMR-3569, -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
Profilin-1 Is Required for Survival of Adult Hematopoietic Stem Cells
Extended methods Immunohistochemistry HepG-2, SMMC-7721, and 293T cells were obtained from Cell Resource Center of Shanghai Institute for Biological Science, Chinese Academy Science, Shanghai, China. HUVEC cells were kindly provided by Prof. Ping-Jin Gao at Institute of Health Sciences (Shanghai, China). All these cell lines were cultured in DMEM with 10% FBS. MDA- MB-231 cell line was kindly provided by Prof. Ming-Yao Liu (East China Normal University, Shanghai, China) and was cultured in Leibovitz L-15 medium with 10% FBS. All these cell lines were originally purchased from ATCC. MDA-MB-231, SMMC-7721 or HepG2 cells were grown on coverslips in 24-well plates and fixed in either 4% paraformaldehyde or pre-chilled methanol (-20°C) for 10 min. In some cases, WT or VPS33B-null Lin-Sca-1+c-Kit+Flk2-CD34- LT-HSCs were collected by flow cytometry and fixed for immunofluorescence staining. Cells were then blocked with 3% BSA in PBS for 60 min followed by incubation with primary antibodies overnight. The antibodies used were anti-HA (Sigma), anti-Flag (Sigma), anti-VPS33B (Sigma), anti- VPS16B (Abcam), anti-GDI2 (Proteintech), anti-LAMP1 (Proteintech), anti-FLOT1 (Abways), anti-CD63 (Proteintech), anti-ANGPTL2 (R&D system), anti-ANGPTL3 (R&D system), anti-TPO (Abways), anti-GLUT1 (Proteintech), anti-LDHA (Proteintech), anti-PKM2 (CST), anti-RAB11A (Abways), anti-RAB27A (Abways) and anti-V5 (Biodragon). Fluorescent-conjugated secondary antibodies (Alexa Fluor® 488 or Alexa Fluor® 555) against mouse, rabbit, or goat were obtained from the Thermo Scientific Inc. The details for all the antibodies are listed in Table S3. -
RET Gene Fusions in Malignancies of the Thyroid and Other Tissues
G C A T T A C G G C A T genes Review RET Gene Fusions in Malignancies of the Thyroid and Other Tissues Massimo Santoro 1,*, Marialuisa Moccia 1, Giorgia Federico 1 and Francesca Carlomagno 1,2 1 Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, 80131 Naples, Italy; [email protected] (M.M.); [email protected] (G.F.); [email protected] (F.C.) 2 Institute of Endocrinology and Experimental Oncology of the CNR, 80131 Naples, Italy * Correspondence: [email protected] Received: 10 March 2020; Accepted: 12 April 2020; Published: 15 April 2020 Abstract: Following the identification of the BCR-ABL1 (Breakpoint Cluster Region-ABelson murine Leukemia) fusion in chronic myelogenous leukemia, gene fusions generating chimeric oncoproteins have been recognized as common genomic structural variations in human malignancies. This is, in particular, a frequent mechanism in the oncogenic conversion of protein kinases. Gene fusion was the first mechanism identified for the oncogenic activation of the receptor tyrosine kinase RET (REarranged during Transfection), initially discovered in papillary thyroid carcinoma (PTC). More recently, the advent of highly sensitive massive parallel (next generation sequencing, NGS) sequencing of tumor DNA or cell-free (cfDNA) circulating tumor DNA, allowed for the detection of RET fusions in many other solid and hematopoietic malignancies. This review summarizes the role of RET fusions in the pathogenesis of human cancer. Keywords: kinase; tyrosine kinase inhibitor; targeted therapy; thyroid cancer 1. The RET Receptor RET (REarranged during Transfection) was initially isolated as a rearranged oncoprotein upon the transfection of a human lymphoma DNA [1]. -
Actin Nucleator Spire 1 Is a Regulator of Ectoplasmic Specialization in the Testis Qing Wen1,Nanli1,Xiangxiao 1,2,Wing-Yeelui3, Darren S
Wen et al. Cell Death and Disease (2018) 9:208 DOI 10.1038/s41419-017-0201-6 Cell Death & Disease ARTICLE Open Access Actin nucleator Spire 1 is a regulator of ectoplasmic specialization in the testis Qing Wen1,NanLi1,XiangXiao 1,2,Wing-yeeLui3, Darren S. Chu1, Chris K. C. Wong4, Qingquan Lian5,RenshanGe5, Will M. Lee3, Bruno Silvestrini6 and C. Yan Cheng 1 Abstract Germ cell differentiation during the epithelial cycle of spermatogenesis is accompanied by extensive remodeling at the Sertoli cell–cell and Sertoli cell–spermatid interface to accommodate the transport of preleptotene spermatocytes and developing spermatids across the blood–testis barrier (BTB) and the adluminal compartment of the seminiferous epithelium, respectively. The unique cell junction in the testis is the actin-rich ectoplasmic specialization (ES) designated basal ES at the Sertoli cell–cell interface, and the apical ES at the Sertoli–spermatid interface. Since ES dynamics (i.e., disassembly, reassembly and stabilization) are supported by actin microfilaments, which rapidly converts between their bundled and unbundled/branched configuration to confer plasticity to the ES, it is logical to speculate that actin nucleation proteins play a crucial role to ES dynamics. Herein, we reported findings that Spire 1, an actin nucleator known to polymerize actins into long stretches of linear microfilaments in cells, is an important regulator of ES dynamics. Its knockdown by RNAi in Sertoli cells cultured in vitro was found to impede the Sertoli cell tight junction (TJ)-permeability barrier through changes in the organization of F-actin across Sertoli cell cytosol. Unexpectedly, Spire 1 knockdown also perturbed microtubule (MT) organization in Sertoli cells cultured in vitro. -
RET Aberrations in Diverse Cancers: Next-Generation Sequencing of 4,871 Patients Shumei Kato1, Vivek Subbiah2, Erica Marchlik3, Sheryl K
Published OnlineFirst September 28, 2016; DOI: 10.1158/1078-0432.CCR-16-1679 Personalized Medicine and Imaging Clinical Cancer Research RET Aberrations in Diverse Cancers: Next-Generation Sequencing of 4,871 Patients Shumei Kato1, Vivek Subbiah2, Erica Marchlik3, Sheryl K. Elkin3, Jennifer L. Carter3, and Razelle Kurzrock1 Abstract Purpose: Aberrations in genetic sequences encoding the tyrosine (52/88)], cell cycle–associated genes [39.8% (35/88)], the PI3K kinase receptor RET lead to oncogenic signaling that is targetable signaling pathway [30.7% (27/88)], MAPK effectors [22.7% with anti-RET multikinase inhibitors. Understanding the compre- (20/88)], or other tyrosine kinase families [21.6% (19/88)]. hensive genomic landscape of RET aberrations across multiple RET fusions were mutually exclusive with MAPK signaling cancers may facilitate clinical trial development targeting RET. pathway alterations. All 72 patients harboring coaberrations Experimental Design: We interrogated the molecular portfolio had distinct genomic portfolios, and most [98.6% (71/72)] of 4,871 patients with diverse malignancies for the presence of had potentially targetable coaberrations with either an FDA- RET aberrations using Clinical Laboratory Improvement Amend- approved or an investigational agent. Two cases with lung ments–certified targeted next-generation sequencing of 182 or (KIF5B-RET) and medullary thyroid carcinoma (RET M918T) 236 gene panels. thatrespondedtoavandetanib(multikinase RET inhibitor)- Results: Among diverse cancers, RET aberrations were iden- containing regimen are shown. tified in 88 cases [1.8% (88/4, 871)], with mutations being Conclusions: RET aberrations were seen in 1.8% of diverse the most common alteration [38.6% (34/88)], followed cancers, with most cases harboring actionable, albeit dis- by fusions [30.7% (27/88), including a novel SQSTM1-RET] tinct, coexisting alterations. -
Applying Expression Profile Similarity for Discovery of Patient-Specific
bioRxiv preprint doi: https://doi.org/10.1101/172015; this version posted September 17, 2017. 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 4.0 International license. Applying expression profile similarity for discovery of patient-specific functional mutations Guofeng Meng Partner Institute of Computational Biology, Yueyang 333, Shanghai, China email: [email protected] Abstract The progress of cancer genome sequencing projects yields unprecedented information of mutations for numerous patients. However, the complexity of mutation profiles of patients hinders the further understanding of mechanisms of oncogenesis. One basic question is how to uncover mutations with functional impacts. In this work, we introduce a computational method to predict functional somatic mutations for each of patient by integrating mutation recurrence with similarity of expression profiles of patients. With this method, the functional mutations are determined by checking the mutation enrichment among a group of patients with similar expression profiles. We applied this method to three cancer types and identified the functional mutations. Comparison of the predictions for three cancer types suggested that most of the functional mutations were cancer-type-specific with one exception to p53. By checking prediction results, we found that our method effectively filtered non-functional mutations resulting from large protein sizes. In addition, this methods can also perform functional annotation to each patient to describe their association with signalling pathways or biological processes. In breast cancer, we predicted "cell adhesion" and other mutated gene associated terms to be significantly enriched among patients.