Identification of Novel Compounds That Inhibit HIV-1 Gene Expression by Targeting Viral RNA Processing

Total Page:16

File Type:pdf, Size:1020Kb

Identification of Novel Compounds That Inhibit HIV-1 Gene Expression by Targeting Viral RNA Processing Identification of Novel Compounds That Inhibit HIV-1 Gene Expression by Targeting Viral RNA Processing by Ahalya Balachandran A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Molecular Genetics University of Toronto © Copyright by Ahalya Balachandran 2015 Identification of Novel Compounds That Inhibit HIV-1 Gene Expression by Targeting Viral RNA Processing Ahalya Balachandran Master of Science Department of Molecular Genetics University of Toronto 2015 Abstract Novel strategies targeting different stages of the HIV lifecycle are vital for continued success in combating viral infection. Since HIV gene expression is dependent upon controlled splicing of the viral transcript, small molecule modulators of RNA processing hold tremendous promise as novel drugs. To this end, we screened splicing modulators for their effect on HIV-1 gene expression. We identified four compounds, 191, 791, 833 and 892, that strongly suppressed accumulation of HIV-1 incompletely spliced RNA and expression of viral structural/regulatory proteins. Furthermore, compound treatment had limited effects on alternative splicing of host RNA splicing events. Subsequent studies confirmed anti-HIV activity of two compounds in the context of peripheral blood mononuclear cells. The distinct effects of these compounds from previously characterized HIV-1 RNA processing inhibitors validate targeting this stage of the virus lifecycle. Elucidating the mechanism by which these compounds alter HIV-1 gene expression holds key insights for novel therapeutic strategies. ii Acknowledgments I would like to thank my supervisor, Dr. Alan Cochrane, for the opportunity to work on this project in his laboratory over the past few years. I would also like to thank my committee members, Dr. Lori Frappier, Dr. Craig Smibert, and Dr. Peter Roy, for their continued guidance and support. It has been a pleasure working with all members of the Cochrane Lab over the past few years. I’d like to thank all the students and post docs for their help and support along the way. Special thanks go to Raymond Wong for taking me under his wing when I was an undergraduate student and for sharing his knowledge and experience about the drug screening projects in our lab. I’d also like to thank Dr. Alex Chen for training me in preparation for working with replicative HIV in the BSL3 facility and the Scott Gray-Owen Lab for source of PBMCs. Last but not least, I’d like to thank our collaborators Dr. Peter Stoilov at West Virginia and Dr. Sandy Pan from the Blencowe Lab for examining the effect of the compounds on cellular alternative splicing. The work presented here would not be possible without funding provided by CIHR grants, as well as the Ontario Graduate Scholarship Award. iii Table of Contents Acknowledgments.......................................................................................................................... iii Table of Contents ........................................................................................................................... iv List of Tables ............................................................................................................................... viii List of Figures ................................................................................................................................ ix List of Appendices ......................................................................................................................... xi Abbreviations ................................................................................................................................ xii 1 Introduction .................................................................................................................................1 1.1 mRNA processing ................................................................................................................1 1.1.1 mRNA capping ........................................................................................................1 1.1.2 Constitutive splicing and the spliceosome ...............................................................2 1.1.3 Alternative splicing ..................................................................................................2 1.1.4 Polyadenylation........................................................................................................4 1.1.5 RNA export ..............................................................................................................4 1.1.6 Translational initiation .............................................................................................6 1.1.7 Interdependence of events in mRNA processing .....................................................6 1.2 Regulation of mRNA splicing .............................................................................................7 1.2.1 Role of cis elements in splicing ...............................................................................7 1.2.2 Role of trans factors in splicing .............................................................................10 1.2.2.1 SR-protein family of splicing factors ......................................................10 1.2.2.2 Heterogeneous nuclear ribonucleoproteins (hnRNPs) ............................10 1.2.3 Regulation of splicing factors ................................................................................11 1.2.4 Splicing factors and signaling pathways ................................................................12 1.3 Perturbation of alternative splicing in disease ...................................................................14 1.4 HIV-1 utilizes host alternative splicing machinery for viral gene expression ...................15 iv 1.4.1 Overview of the HIV-1 lifecycle ...........................................................................15 1.4.2 Current treatment strategies for HIV-1 ..................................................................16 1.4.3 Limitations of current HIV-1 therapies ..................................................................18 1.4.4 HIV-1 RNA processing..........................................................................................19 1.4.5 Regulation of HIV-1 RNA splicing .......................................................................19 1.4.6 HIV-1 gene expression and Rev-dependent export ...............................................24 1.5 Modulation of RNA splicing as a therapeutic strategy ......................................................27 1.5.1 Modulation of AS using small molecules ..............................................................27 1.5.1.1 Spliceosome inhibitors ............................................................................29 1.5.1.2 Histone deacetylase (HDAC) inhibitors ..................................................29 1.5.1.3 Topoisomerase (Topo I) inhibitors ..........................................................30 1.5.1.4 Kinase and phosphatase inhibitors ..........................................................30 1.6 Effect of splicing modulators on HIV-1 gene expression ..................................................31 1.7 Research objective and rationale .......................................................................................33 2 Materials and Methods ..............................................................................................................34 2.1 HIV-1 provirus doxycycline-inducible cell lines ...............................................................34 2.2 Assess activity of compounds on HIV-1 gene expression .................................................34 2.2.1 Preparation of compounds .....................................................................................34 2.2.2 Compound treatment assay ....................................................................................34 2.3 HIV-1 p24 antigen ELISA .................................................................................................36 2.4 XTT cytotoxicity assay ......................................................................................................36 2.5 Analysis of HIV-1 protein expression ...............................................................................37 2.6 Analysis of HIV-1 RNA expression and localization ........................................................38 2.6.1 RNA extraction and reverse transcription ..............................................................38 2.6.2 Quantification of HIV-1 mRNA expression by qPCR ..........................................38 2.6.3 Analysis of splice site selection within the HIV-1 MS RNA ................................39 v 2.6.4 Analysis of HIV-1 US RNA subcellular localization ............................................40 2.7 Monitoring protein synthesis by SUnSET .........................................................................42 2.8 Viral protein degradation assay .........................................................................................44 2.9 Proteasomal degradation protection assay .........................................................................44 2.10 Analysis of cellular alternative splicing events by RT-PCR .............................................45 2.11 Analysis of cellular alternative splicing by RNA sequencing ...........................................45 2.11.1 Sample preparation for RNA sequencing (RNAseq) .............................................45
Recommended publications
  • Transcriptional Regulation of RKIP in Prostate Cancer Progression
    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Sciences Transcriptional Regulation of RKIP in Prostate Cancer Progression Submitted by: Sandra Marie Beach In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Sciences Examination Committee Major Advisor: Kam Yeung, Ph.D. Academic William Maltese, Ph.D. Advisory Committee: Sonia Najjar, Ph.D. Han-Fei Ding, M.D., Ph.D. Manohar Ratnam, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: May 16, 2007 Transcriptional Regulation of RKIP in Prostate Cancer Progression Sandra Beach University of Toledo ACKNOWLDEGMENTS I thank my major advisor, Dr. Kam Yeung, for the opportunity to pursue my degree in his laboratory. I am also indebted to my advisory committee members past and present, Drs. Sonia Najjar, Han-Fei Ding, Manohar Ratnam, James Trempe, and Douglas Pittman for generously and judiciously guiding my studies and sharing reagents and equipment. I owe extended thanks to Dr. William Maltese as a committee member and chairman of my department for supporting my degree progress. The entire Department of Biochemistry and Cancer Biology has been most kind and helpful to me. Drs. Roy Collaco and Hong-Juan Cui have shared their excellent technical and practical advice with me throughout my studies. I thank members of the Yeung laboratory, Dr. Sungdae Park, Hui Hui Tang, Miranda Yeung for their support and collegiality. The data mining studies herein would not have been possible without the helpful advice of Dr. Robert Trumbly. I am also grateful for the exceptional assistance and shared microarray data of Dr.
    [Show full text]
  • Nuclear Organization and the Epigenetic Landscape of the Mus Musculus X-Chromosome Alicia Liu University of Connecticut - Storrs, [email protected]
    University of Connecticut OpenCommons@UConn Doctoral Dissertations University of Connecticut Graduate School 8-9-2019 Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome Alicia Liu University of Connecticut - Storrs, [email protected] Follow this and additional works at: https://opencommons.uconn.edu/dissertations Recommended Citation Liu, Alicia, "Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome" (2019). Doctoral Dissertations. 2273. https://opencommons.uconn.edu/dissertations/2273 Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome Alicia J. Liu, Ph.D. University of Connecticut, 2019 ABSTRACT X-linked imprinted genes have been hypothesized to contribute parent-of-origin influences on social cognition. A cluster of imprinted genes Xlr3b, Xlr4b, and Xlr4c, implicated in cognitive defects, are maternally expressed and paternally silent in the murine brain. These genes defy classic mechanisms of autosomal imprinting, suggesting a novel method of imprinted gene regulation. Using Xlr3b and Xlr4c as bait, this study uses 4C-Seq on neonatal whole brain of a 39,XO mouse model, to provide the first in-depth analysis of chromatin dynamics surrounding an imprinted locus on the X-chromosome. Significant differences in long-range contacts exist be- tween XM and XP monosomic samples. In addition, XM interaction profiles contact a greater number of genes linked to cognitive impairment, abnormality of the nervous system, and abnormality of higher mental function. This is not a pattern that is unique to the imprinted Xlr3/4 locus. Additional Alicia J. Liu - University of Connecticut - 2019 4C-Seq experiments show that other genes on the X-chromosome, implicated in intellectual disability and/or ASD, also produce more maternal contacts to other X-linked genes linked to cognitive impairment.
    [Show full text]
  • Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement.
    [Show full text]
  • Supplementary Materials
    Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine
    [Show full text]
  • Moving Towards Predictive Toxicology -A Systems Biology Approach
    Moving Towards Predictive Toxicology -A Systems Biology Approach by Philipp Antczak A thesis submitted to The University of Birmingham for the degree of Doctor of Philosophy (Sc,PhD) College of Life and Environmental Sciences School of Biosciences The University of Birmingham September 2011 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. Abstract Human health and the environment are at risk of being exposed to a large number of hazardous chemicals each day. Unfortunately, many of these chemicals have no or little recorded toxicity information. Predictive toxicology aims to provide tools and methodologies to address this is- sue. In combination with systems biology approaches these can provide a powerful toolbox for understanding the impact of chemicals on biological species. The work presented within this thesis demonstrates the effectiveness of such approaches in the context of industrial and environmentally relevant species. More specifically we focus on char- acterization of a general toxicity mechanism in Rattus norvegius and Daphnia magna as well as for the first time demonstrate that the transcriptional response of D. magna is predictive not only of chemical class but also of measured toxicity.
    [Show full text]
  • Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis
    Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis Ugo Ala1., Rosario Michael Piro1., Elena Grassi1, Christian Damasco1, Lorenzo Silengo1, Martin Oti2, Paolo Provero1*, Ferdinando Di Cunto1* 1 Molecular Biotechnology Center, Department of Genetics, Biology and Biochemistry, University of Turin, Turin, Italy, 2 Department of Human Genetics and Centre for Molecular and Biomolecular Informatics, University Medical Centre Nijmegen, Nijmegen, The Netherlands Abstract Background: Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings: We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion: Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. Citation: Ala U, Piro RM, Grassi E, Damasco C, Silengo L, et al.
    [Show full text]
  • Accurate Prediction of Kinase-Substrate Networks Using
    bioRxiv preprint doi: https://doi.org/10.1101/865055; this version posted December 4, 2019. 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. Accurate Prediction of Kinase-Substrate Networks Using Knowledge Graphs V´ıtNov´aˇcek1∗+, Gavin McGauran3, David Matallanas3, Adri´anVallejo Blanco3,4, Piero Conca2, Emir Mu~noz1,2, Luca Costabello2, Kamalesh Kanakaraj1, Zeeshan Nawaz1, Sameh K. Mohamed1, Pierre-Yves Vandenbussche2, Colm Ryan3, Walter Kolch3,5,6, Dirk Fey3,6∗ 1Data Science Institute, National University of Ireland Galway, Ireland 2Fujitsu Ireland Ltd., Co. Dublin, Ireland 3Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland 4Department of Oncology, Universidad de Navarra, Pamplona, Spain 5Conway Institute of Biomolecular & Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland 6School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland ∗ Corresponding authors ([email protected], [email protected]). + Lead author. 1 bioRxiv preprint doi: https://doi.org/10.1101/865055; this version posted December 4, 2019. 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. Abstract Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular pro- cesses. However, discovering specific kinase-substrate relationships is time-consuming and often rather serendipitous.
    [Show full text]
  • Dynamic Erasure of Random X-Chromosome Inactivation During Ipsc Reprogramming
    bioRxiv preprint doi: https://doi.org/10.1101/545558; this version posted February 9, 2019. 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. Dynamic Erasure of Random X-Chromosome Inactivation during iPSC Reprogramming Adrian Janiszewski1,*, Irene Talon1,*, Juan Song1, Natalie De Geest1, San Kit To1, Greet Bervoets2,3, Jean-Christophe Marine2,3, Florian Rambow2,3, Vincent Pasque1,✉. 1 KU Leuven - University of Leuven, Department of Development and Regeneration, Herestraat 49, B-3000 Leuven, Belgium. 2 Laboratory for Molecular Cancer Biology, VIB Center for Cancer Biology 3 Department of Oncology, KU Leuven, Belgium ✉ Correspondence to: [email protected] (V.P.) * These authors contributed equally Format: Research paper ABSTRACT Background: Induction and reversal of chromatin silencing is critical for successful development, tissue homeostasis and the derivation of induced pluripotent stem cells (iPSCs). X-chromosome inactivation (XCI) and reactivation (XCR) in female cells represent chromosome-wide transitions between active and inactive chromatin states. While XCI has long been studied and provided important insights into gene regulation, the dynamics and mechanisms underlying the reversal of stable chromatin silencing of X-linked genes are much less understood. Here, we use allele- specific transcriptomic approaches to study XCR during mouse iPSC reprogramming in order to elucidate the timing and mechanisms of chromosome-wide reversal of gene silencing. Results: We show that XCR is hierarchical, with subsets of genes reactivating early, late and very late.
    [Show full text]
  • The X-Ray Crystal Structure of the N-Terminal Domain of Ssr4, a Schizosaccharomyces Pombe Chromatin-Remodelling Protein ISSN 2053-230X
    research communications The X-ray crystal structure of the N-terminal domain of Ssr4, a Schizosaccharomyces pombe chromatin-remodelling protein ISSN 2053-230X Janet Newman, Tom Nebl, Huy Van‡ and Thomas S. Peat* Biomedical Program, CSIRO, 343 Royal Parade, Parkville, VIC 3052, Australia. *Correspondence e-mail: Received 13 October 2020 [email protected] Accepted 15 November 2020 Edited by M. J. van Raaij, Centro Nacional de Ssr4 is a yeast protein from Schizosaccharomyces pombe and is an essential part Biotecnologı´a – CSIC, Spain of the chromatin-remodelling [SWI/SNF and RSC (remodelling the structure of chromatin)] complexes found in S. pombe. These complexes (or their homo- ‡ Current address: Burnet Institute, logues) regulate gene expression in eukaryotic organisms, affecting a large 85 Commercial Road, Melbourne, VIC 3004, number of genes both positively and negatively. The downstream effects are Australia. seen in development, and in humans have implications for disease such as cancer. The chromatin structure is altered by modifying the DNA–histone Keywords: chromatin remodelling; SAD phasing; novel structure; Schizosaccharomyces contacts, thus opening up or closing down sections of DNA to specific pombe. transcription factors that regulate the transcription of genes. The Ssr4 sequence has little homology to other sequences in the Protein Data Bank, so the PDB references: N-terminal domain of Ssr4, structure was solved using an iodine derivative with SAD phasing. The structure native, 7k7w; iodine derivative, 7k7v; sulfur of the N-terminal domain is an antiparallel -sheet of seven strands with SAD data, 7k82 -helices on one side and random coil on the other. The structure is significantly different to deposited structures and was used as a target in the most recent Supporting information: this article has supporting information at journals.iucr.org/f Critical Assessment of Techniques for Protein Structure Prediction (CASP; https://predictioncenter.org/) competition.
    [Show full text]
  • Anti-SSR4 Antibody [26G5] (ARG57030)
    Product datasheet [email protected] ARG57030 Package: 50 μl anti-SSR4 antibody [26G5] Store at: -20°C Summary Product Description Mouse Monoclonal antibody [26G5] recognizes SSR4 Tested Reactivity Hu Tested Application WB Host Mouse Clonality Monoclonal Clone 26G5 Isotype IgG1, kappa Target Name SSR4 Antigen Species Human Immunogen Recombinant fragment around aa. 24-144 of Human SSR4. Conjugation Un-conjugated Alternate Names SSR-delta; Translocon-associated protein subunit delta; CDG1Y; Signal sequence receptor subunit delta; TRAPD; TRAP-delta Application Instructions Application table Application Dilution WB 1:1000 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 19 kDa Properties Form Liquid Purification Purification with Protein A. Buffer PBS (pH 7.4), 0.02% Sodium azide and 10% Glycerol. Preservative 0.02% Sodium azide Stabilizer 10% Glycerol Concentration 1 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. Note For laboratory research only, not for drug, diagnostic or other use. www.arigobio.com 1/2 Bioinformation Database links GeneID: 6748 Human Swiss-port # P51571 Human Gene Symbol SSR4 Gene Full Name signal sequence receptor, delta Background This gene encodes the delta subunit of the translocon-associated protein complex which is involved in translocating proteins across the endoplasmic reticulum membrane.
    [Show full text]
  • A Network Inference Approach to Understanding Musculoskeletal
    A NETWORK INFERENCE APPROACH TO UNDERSTANDING MUSCULOSKELETAL DISORDERS by NIL TURAN A thesis submitted to The University of Birmingham for the degree of Doctor of Philosophy College of Life and Environmental Sciences School of Biosciences The University of Birmingham June 2013 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Musculoskeletal disorders are among the most important health problem affecting the quality of life and contributing to a high burden on healthcare systems worldwide. Understanding the molecular mechanisms underlying these disorders is crucial for the development of efficient treatments. In this thesis, musculoskeletal disorders including muscle wasting, bone loss and cartilage deformation have been studied using systems biology approaches. Muscle wasting occurring as a systemic effect in COPD patients has been investigated with an integrative network inference approach. This work has lead to a model describing the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. This model has shown for the first time that oxygen dependent changes in the expression of epigenetic modifiers and not chronic inflammation may be causally linked to muscle dysfunction.
    [Show full text]
  • RNA Splicing in the Transition from B Cells to Antibody-Secreting Cells
    RNA Splicing in the Transition from B Cells to Antibody-Secreting Cells: The Influences of ELL2, Small Nuclear RNA, and Endoplasmic Reticulum Stress This information is current as of September 29, 2021. Ashley M. Nelson, Nolan T. Carew, Sage M. Smith and Christine Milcarek J Immunol published online 8 October 2018 http://www.jimmunol.org/content/early/2018/10/05/jimmun ol.1800557 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2018/10/05/jimmunol.180055 Material 7.DCSupplemental http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 29, 2021 *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 Copyright © 2018 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published October 8, 2018, doi:10.4049/jimmunol.1800557 The Journal of Immunology RNA Splicing in the Transition from B Cells to Antibody-Secreting Cells: The Influences of ELL2, Small Nuclear RNA, and Endoplasmic Reticulum Stress Ashley M. Nelson, Nolan T. Carew, Sage M. Smith, and Christine Milcarek In the transition from B cells to Ab-secreting cells (ASCs) many genes are induced, such as ELL2, Irf4, Prdm1, Xbp1, whereas other mRNAs do not change in abundance.
    [Show full text]