Global Analysis of LARP1 Translation Targets Reveals Tunable and Dynamic Features of 5′ TOP Motifs
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University of California, San Diego
UNIVERSITY OF CALIFORNIA, SAN DIEGO The post-terminal differentiation fate of RNAs revealed by next-generation sequencing A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Biomedical Sciences by Gloria Kuo Lefkowitz Committee in Charge: Professor Benjamin D. Yu, Chair Professor Richard Gallo Professor Bruce A. Hamilton Professor Miles F. Wilkinson Professor Eugene Yeo 2012 Copyright Gloria Kuo Lefkowitz, 2012 All rights reserved. The Dissertation of Gloria Kuo Lefkowitz is approved, and it is acceptable in quality and form for publication on microfilm and electronically: __________________________________________________________________ __________________________________________________________________ __________________________________________________________________ __________________________________________________________________ __________________________________________________________________ Chair University of California, San Diego 2012 iii DEDICATION Ma and Ba, for your early indulgence and support. Matt and James, for choosing more practical callings. Roy, my love, for patiently sharing the ups and downs of this journey. iv EPIGRAPH It is foolish to tear one's hair in grief, as though sorrow would be made less by baldness. ~Cicero v TABLE OF CONTENTS Signature Page .............................................................................................................. iii Dedication .................................................................................................................... -
Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids
Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10. -
L-Leucine Increases Translation of RPS14 and LARP1 in Erythroblasts
LETTERS TO THE EDITOR Table 1. Top 20 differentially translated known 5’TOP mRNAs in L-leucine increases translation of RPS14 and LARP1 L-leucine treated erythroblasts from del(5q) myelodysplastic syn- in erythroblasts from del(5q) myelodysplastic drome patients. syndrome patients Genes LogFC of TE in patients z score patients Deletion of the long arm of chromosome 5 [del(5q)] is RPS15 3.55 2.46 the most common cytogenetic abnormality found in the RPS27A 3.48 2.40 1 myelodysplastic syndromes (MDS). Patients with the 5q- RPS25 3.47 2.39 syndrome have macrocytic anemia and the del(5q) as the RPS20 3.43 2.35 sole karyotypic abnormality.1 Haploinsufficiency of the ribosomal protein gene RPS14, mapping to the common- RPL12 3.35 2.29 ly deleted region (CDR) on chromosome 5q,2 underlies PABPC4 3.01 2.01 3 the erythroid defect found in the 5q- syndrome, and is RPS24 2.97 1.98 associated with p53 activation,4-6 a block in the process- ing of pre-ribosomal RNA,3 and deregulation of riboso- RPS3 2.95 1.96 mal- and translation-related genes.7 Defective mRNA EEF2 2.83 1.86 translation represents a potential therapeutic target in the RPS18 2.76 1.80 5q- syndrome and other ribosomopathies, such as RPS26 2.75 1.79 Diamond-Blackfan anemia (DBA).8 Evidence suggests that the translation enhancer L- RPS5 2.69 1.74 leucine may have some efficacy in the treatment of the RPS21 2.64 1.70 8 5q- syndrome and DBA. A DBA patient treated with L- RPS9 2.54 1.62 leucine showed a marked improvement in anemia and 8 EIF3E 2.53 1.61 achieved transfusion independence. -
EEF1D Mouse Monoclonal Antibody [Clone ID: OTI4B9] 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 CF811676 EEF1D Mouse Monoclonal Antibody [Clone ID: OTI4B9] Product data: Product Type: Primary Antibodies Clone Name: OTI4B9 Applications: IHC, WB Recommended Dilution: WB 1:500~2000, IHC 1:2000 Reactivity: Human, Mouse, Rat Host: Mouse Isotype: IgG1 Clonality: Monoclonal Immunogen: Full length human recombinant protein of human EEF1D (NP_115754) produced in E.coli. Formulation: Lyophilized powder (original buffer 1X PBS, pH 7.3, 8% trehalose) Reconstitution Method: For reconstitution, we recommend adding 100uL distilled water to a final antibody concentration of about 1 mg/mL. To use this carrier-free antibody for conjugation experiment, we strongly recommend performing another round of desalting process. (OriGene recommends Zeba Spin Desalting Columns, 7KMWCO from Thermo Scientific) Purification: Purified from mouse ascites fluids or tissue culture supernatant by affinity chromatography (protein A/G) Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Gene Name: Homo sapiens eukaryotic translation elongation factor 1 delta (EEF1D), transcript variant 1, mRNA. Database Link: NP_115754 Entrez Gene 1936 Human P29692 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 / 3 EEF1D Mouse Monoclonal Antibody [Clone ID: OTI4B9] – CF811676 Background: This gene encodes a subunit of the elongation factor-1 complex, which is responsible for the enzymatic delivery of aminoacyl tRNAs to the ribosome. -
Evolution of Translation EF-Tu: Trna
University of Illinois at Urbana-Champaign Luthey-Schulten Group NIH Resource for Macromolecular Modeling and Bioinformatics Computational Biophysics Workshop Evolution of Translation EF-Tu: tRNA VMD Developer: John Stone MultiSeq Developers Tutorial Authors Elijah Roberts Ke Chen John Eargle John Eargle Dan Wright Zhaleh Ghaemi Jonathan Lai Zan Luthey-Schulten August 2014 A current version of this tutorial is available at http://www.scs.illinois.edu/~schulten/tutorials/ef-tu CONTENTS 2 Contents 1 Introduction 3 1.1 The Elongation Factor Tu . 3 1.2 Getting Started . 4 1.2.1 Requirements . 4 1.2.2 Copying the tutorial files . 4 1.2.3 Working directory . 4 1.2.4 Preferences . 4 1.3 Configuring BLAST for MultiSeq . 5 2 Comparative Analysis of EF-Tu 5 2.1 Finding archaeal EF1A sequences . 6 2.2 Aligning archaeal sequences and removing redundancy . 8 2.3 Finding bacteria EF-Tu sequences . 11 2.4 Performing ClustalW Multiple Sequence and Profile-Profile Align- ments . 12 2.5 Creating Multiple Sequence with MAFFT . 16 2.6 Conservation of EF-Tu among the Bacteria . 16 2.7 Finding conserved residues across the bacterial and archaeal do- mains . 20 2.8 EF-Tu Interface with the Ribosome . 21 3 Computing a Maximum Likelihood Phylogenetic Tree with RAxML 23 3.1 Load the Phylogenetic Tree into MultiSeq . 25 3.2 Reroot and Manipulate the Phylogenetic Tree . 25 4 MultiSeq TCL Scripting: Genomic Context 27 5 Appendix A 30 5.1 Building a BLAST Database . 30 6 Appendix B 31 6.1 Saving QR subset of alignments in PHYLIP and FASTA format 31 6.2 Calculating Maximum Likelihood Trees with RAxML . -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Effects of Stressors on Differential Gene Expression And
EFFECTS OF STRESSORS ON DIFFERENTIAL GENE EXPRESSION AND SECONDARY METABOLITES BY AXINELLA CORRUGATA by Jennifer Grima A Thesis Submitted to the Faculty of Charles E. Schmidt College of Science in Partial Fulfillment of the Requirements for the Degree of Master of Science Florida Atlantic University Boca Raton, Florida May 2013 ACKNOWLEDGEMENTS This thesis was made possible by the help and support of my mentors and friends. Without their guidance and expertise, I would not have been able to accomplish all that I have. Their belief and encouragement in my efforts have motivated and inspired me along through this journey and into a new era in my life. First and foremost, I am grateful to Dr. Shirley Pomponi for taking on the role as my advisor and giving me the opportunity to experience life as a researcher. Not only has she guided me in my scientific studies, she has become a wonderful, lifelong friend. Dr. Pomponi and Dr. Amy Wright have also provided financial support that enabled me to conduct the research and complete this thesis. I would also like to acknowledge Dr. Amy Wright for her willingness to tender advice on all things chemistry related as well as providing me with the space, equipment, and supplies to conduct the chemical analyses. I am grateful to Dr. Esther Guzman who not only served as a committee member, but has also been readily available to help me in any endeavor, whether it be research or personal related. She is truly one of kind with her breadth of knowledge in research and her loyal and caring character. -
Structural Characterization of the Human Eukaryotic Initiation Factor 3 Protein Complex by Mass Spectrometry*□S
Supplemental Material can be found at: http://www.mcponline.org/cgi/content/full/M600399-MCP200 /DC1 Research Structural Characterization of the Human Eukaryotic Initiation Factor 3 Protein Complex by Mass Spectrometry*□S Eugen Damoc‡, Christopher S. Fraser§, Min Zhou¶, Hortense Videler¶, Greg L. Mayeurʈ, John W. B. Hersheyʈ, Jennifer A. Doudna§, Carol V. Robinson¶**, and Julie A. Leary‡ ‡‡ Protein synthesis in mammalian cells requires initiation The initiation phase of eukaryotic protein synthesis involves factor eIF3, an ϳ800-kDa protein complex that plays a formation of an 80 S ribosomal complex containing the initi- Downloaded from central role in binding of initiator methionyl-tRNA and ator methionyl-tRNAi bound to the initiation codon in the mRNA to the 40 S ribosomal subunit to form the 48 S mRNA. This is a multistep process promoted by proteins initiation complex. The eIF3 complex also prevents pre- called eukaryotic initiation factors (eIFs).1 Currently at least 12 mature association of the 40 and 60 S ribosomal subunits eIFs, composed of at least 29 distinct subunits, have been and interacts with other initiation factors involved in start identified (1). Mammalian eIF3, the largest initiation factor, is a codon selection. The molecular mechanisms by which multisubunit complex with an apparent molecular mass of www.mcponline.org eIF3 exerts these functions are poorly understood. Since ϳ800 kDa. This protein complex plays an essential role in its initial characterization in the 1970s, the exact size, translation by binding directly to the 40 S ribosomal subunit composition, and post-translational modifications of and promoting formation of the 43 S preinitiation complex ⅐ ⅐ mammalian eIF3 have not been rigorously determined. -
DNA·RNA Triple Helix Formation Can Function As a Cis-Acting Regulatory
DNA·RNA triple helix formation can function as a cis-acting regulatory mechanism at the human β-globin locus Zhuo Zhoua, Keith E. Gilesa,b,c, and Gary Felsenfelda,1 aLaboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892; bUniversity of Alabama at Birmingham Stem Cell Institute, University of Alabama at Birmingham, Birmingham, AL 35294; and cDepartment of Biochemistry and Molecular Genetics, University of Alabama at Birmingham, Birmingham, AL 35294 Contributed by Gary Felsenfeld, February 4, 2019 (sent for review January 4, 2019; reviewed by James Douglas Engel and Sergei M. Mirkin) We have identified regulatory mechanisms in which an RNA tran- of the criteria necessary to establish the presence of a triplex script forms a DNA duplex·RNA triple helix with a gene or one of its structure, we first describe and characterize triplex formation at regulatory elements, suggesting potential auto-regulatory mecha- the FAU gene in human erythroid K562 cells. FAU encodes a nisms in vivo. We describe an interaction at the human β-globin protein that is a fusion containing fubi, a ubiquitin-like protein, locus, in which an RNA segment embedded in the second intron of and ribosomal protein S30. Although fubi function is unknown, the β-globin gene forms a DNA·RNA triplex with the HS2 sequence posttranslational processing produces S30, a component of the within the β-globin locus control region, a major regulator of glo- 40S ribosome. We used this system to refine methods necessary bin expression. We show in human K562 cells that the triplex is to detect triplex formation and to distinguish it from R-loop stable in vivo. -
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. -
A Chemical-Genetic Screen for Identifying Substrates of the Er Kinase Perk
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2014 A Chemical-Genetic Screen for Identifying Substrates of the Er Kinase Perk Nancy L. Maas University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Biology Commons, Cell Biology Commons, and the Molecular Biology Commons Recommended Citation Maas, Nancy L., "A Chemical-Genetic Screen for Identifying Substrates of the Er Kinase Perk" (2014). Publicly Accessible Penn Dissertations. 1354. https://repository.upenn.edu/edissertations/1354 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1354 For more information, please contact [email protected]. A Chemical-Genetic Screen for Identifying Substrates of the Er Kinase Perk Abstract Cells constantly encounter changing environments that challenge the ability to adapt and survive. Signal transduction networks enable cells to appropriately sense and respond to these changes, and are often mediated through the activity of protein kinases. Protein kinases are a class of enzyme responsible for regulating a broad spectrum of cellular functions by transferring phosphate groups from ATP to substrate proteins, thereby altering substrate activity and function. PERK is a resident kinase of the endoplasmic reticulum, and is responsible for sensing perturbations in the protein folding capacity of the ER. When the influx of unfolded, nascent proteins exceeds the folding capacity of the ER, PERK initiates a cascade of signaling events that enable cell adaptation and ER stress resolution. These signaling pathways are not only essential for the survival of normal cells undergoing ER stress, but are also co-opted by tumor cells in order to survive the oxygen and nutrient-restricted conditions of the tumor microenvironment. -
Proteomics Provides Insights Into the Inhibition of Chinese Hamster V79
www.nature.com/scientificreports OPEN Proteomics provides insights into the inhibition of Chinese hamster V79 cell proliferation in the deep underground environment Jifeng Liu1,2, Tengfei Ma1,2, Mingzhong Gao3, Yilin Liu4, Jun Liu1, Shichao Wang2, Yike Xie2, Ling Wang2, Juan Cheng2, Shixi Liu1*, Jian Zou1,2*, Jiang Wu2, Weimin Li2 & Heping Xie2,3,5 As resources in the shallow depths of the earth exhausted, people will spend extended periods of time in the deep underground space. However, little is known about the deep underground environment afecting the health of organisms. Hence, we established both deep underground laboratory (DUGL) and above ground laboratory (AGL) to investigate the efect of environmental factors on organisms. Six environmental parameters were monitored in the DUGL and AGL. Growth curves were recorded and tandem mass tag (TMT) proteomics analysis were performed to explore the proliferative ability and diferentially abundant proteins (DAPs) in V79 cells (a cell line widely used in biological study in DUGLs) cultured in the DUGL and AGL. Parallel Reaction Monitoring was conducted to verify the TMT results. γ ray dose rate showed the most detectable diference between the two laboratories, whereby γ ray dose rate was signifcantly lower in the DUGL compared to the AGL. V79 cell proliferation was slower in the DUGL. Quantitative proteomics detected 980 DAPs (absolute fold change ≥ 1.2, p < 0.05) between V79 cells cultured in the DUGL and AGL. Of these, 576 proteins were up-regulated and 404 proteins were down-regulated in V79 cells cultured in the DUGL. KEGG pathway analysis revealed that seven pathways (e.g.