Cross-Talk Between Dnmt2-Dependent Trna
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(12) United States Patent (10) Patent No.: US 6,822,071 B1 Stephens Et Al
USOO6822071B1 (12) United States Patent (10) Patent No.: US 6,822,071 B1 Stephens et al. (45) Date of Patent: Nov. 23, 2004 (54) POLYPEPTIDES FROM CHLAMYDIA (56) References Cited PNEUMONIAE AND THEIR USE IN THE DIAGNOSIS, PREVENTION AND FOREIGN PATENT DOCUMENTS TREATMENT OF DISEASE WO 99/27105 * 6/1999 (75) Inventors: Richard S. Stephens, Orinda, CA (US); OTHER PUBLICATIONS Wayne Mitchell, San Francsico, CA Gerhold et al-BioEssays 18(12):973-981, 1996.* (US); Sue S. Kalman, Saratoga, CA Wells et al Journal of Leukocyte Biology 61(5):545-550, (US); Ronald Davis, Palo Alto, CA 1997.* (US) Russell et al Journal of Molecular Biology 244:33-350, 1994.* (73) Assignee: The Regents of the University of Rudinger et al., in “Peptide Hormones' Parsons, TA ets, California, Oakland, CA (US) University Park Press pp. 1–6, 1976.* Burgess et al, The Journal of Cell Biology, 111:2129-2138, Notice: Subject to any disclaimer, the term of this 1990.* patent is extended or adjusted under 35 Lazar et al, Molecular and Cellular Biology U.S.C. 154(b) by 0 days. 8(3):1247–1252, 1988.* Jobling et al, Mol-Microbiol. 5(7): 1755–67, 1991.* (21) Appl. No.: 09/438,185 Pir-68 Database Accession No. E72002 Kalmar et al. Apr. (22) Filed: Nov. 11, 1999 23, 1999.* (Under 37 CFR 1.47) * cited by examiner Primary Examiner Patricia A. Duffy Related U.S. Application Data (74) Attorney, Agent, or Firm Townsend and Townsend (60) Provisional application No. 60/128,606, filed on Apr. 8, and Crew 1999, and provisional application No. -
Prolonging Healthy Aging: Longevity Vitamins and Proteins PERSPECTIVE Bruce N
PERSPECTIVE Prolonging healthy aging: Longevity vitamins and proteins PERSPECTIVE Bruce N. Amesa,1 Edited by Cynthia Kenyon, Calico Labs, San Francisco, CA, and approved September 13, 2018 (received for review May 30, 2018) It is proposed that proteins/enzymes be classified into two classes according to their essentiality for immediate survival/reproduction and their function in long-term health: that is, survival proteins versus longevity proteins. As proposed by the triage theory, a modest deficiency of one of the nutrients/cofactors triggers a built-in rationing mechanism that favors the proteins needed for immediate survival and reproduction (survival proteins) while sacrificing those needed to protect against future damage (longevity proteins). Impairment of the function of longevity proteins results in an insidious acceleration of the risk of diseases associated with aging. I also propose that nutrients required for the function of longevity proteins constitute a class of vitamins that are here named “longevity vitamins.” I suggest that many such nutrients play a dual role for both survival and longevity. The evidence for classifying taurine as a conditional vitamin, and the following 10 compounds as putative longevity vitamins, is reviewed: the fungal antioxidant ergo- thioneine; the bacterial metabolites pyrroloquinoline quinone (PQQ) and queuine; and the plant antioxidant carotenoids lutein, zeaxanthin, lycopene, α-andβ-carotene, β-cryptoxanthin, and the marine carotenoid astaxanthin. Because nutrient deficiencies are highly prevalent in the United States (and elsewhere), appro- priate supplementation and/or an improved diet could reduce much of the consequent risk of chronic disease and premature aging. vitamins | essential minerals | aging | nutrition I propose that an optimal level of many of the known adverse health effects. -
Preferential Import of Queuosine-Modified Trnas Into
Published online 9 July 2021 Nucleic Acids Research, 2021, Vol. 49, No. 14 8247–8260 https://doi.org/10.1093/nar/gkab567 Preferential import of queuosine-modified tRNAs into Trypanosoma brucei mitochondrion is critical for organellar protein synthesis Sneha Kulkarni1,2, Mary Anne T. Rubio1,3,EvaHegedusov˝ a´ 1, Robert L. Ross4, Patrick A. Limbach 5, Juan D. Alfonzo3 and Zdenekˇ Paris 1,2,* 1Institute of Parasitology, Biology Centre, Czech Academy of Sciences, Ceskˇ eBud´ ejovice,ˇ Czech Republic, 2Faculty 3 of Science, University of South Bohemia, Ceskˇ eBud´ ejovice,ˇ Czech Republic, Department of Microbiology and The Downloaded from https://academic.oup.com/nar/article/49/14/8247/6318497 by guest on 01 October 2021 Center for RNA Biology, The Ohio State University, Columbus, OH, USA, 4Metabolomics Mass Spectrometry Core, Department of Cancer Biology, University of Cincinnati, Cincinnati, OH, USA and 5Rieveschl Laboratories for Mass Spectrometry, Department of Chemistry, University of Cincinnati, Cincinnati, OH, USA Received November 30, 2020; Revised May 28, 2021; Editorial Decision June 13, 2021; Accepted June 21, 2021 ABSTRACT sine (Q), a hypermodified 7-deaza-guanosine, is one of the most chemically intricate modifications described to date. Transfer RNAs (tRNAs) are key players in protein syn- Q is found at the wobble position 34 of tRNAs that contain thesis. To be fully active, tRNAs undergo extensive a5-GUN-3 anticodon sequence, where N represents any post-transcriptional modifications, including queuo- of the canonical nucleotides, which includes tRNAHisGUG, sine (Q), a hypermodified 7-deaza-guanosine present tRNAAspGUC, tRNAAsnGUU, tRNATyr GUA (3). Q is in the anticodon of several tRNAs in bacteria and eu- found in both bacteria and eukarya, and catalyzed by tRNA karya. -
Dissertation
Dissertation submitted to the Combined Faculty of Natural Sciences and Mathematics of the Ruperto-Carola University of Heidelberg, Germany for the degree of Doctor of Natural Sciences Presented by M.Sc. Matilde Bertolini born in Parma, Italy Oral examination: 02/03/2021 Profiling interactions of proximal nascent chains reveals a general co-translational mechanism of protein complex assembly Referees: Prof. Dr. Bernd Bukau Prof. Dr. Caludio Joazeiro Preface Contributions The experiments and analyses presented in this Thesis were conducted by myself unless otherwise indicated, under the supervision of Dr. Günter Kramer and Prof. Dr. Bernd Bukau. The Disome Selective Profiling (DiSP) technology was developed in collaboration with my colleague Kai Fenzl, with whom I also generated initial datasets of human HEK293-T and U2OS cells. Dr. Ilia Kats developed important bioinformatics tools for the analysis of DiSP data, including RiboSeqTools and the sigmoid fitting algorithm. He also offered great input on statistical analyses. Dr. Frank Tippmann performed analysis of crystal structures. Table of Contents TABLE OF CONTENTS List of Figures ......................................................................................................V List of Tables ...................................................................................................... VII List of Equations .............................................................................................. VIII Abbreviations .................................................................................................... -
Discovery of Novel Bacterial Queuine Salvage Enzymes and Pathways in Human Pathogens
Discovery of novel bacterial queuine salvage enzymes and pathways in human pathogens a,1 b,1 c,1 b d a Yifeng Yuan , Rémi Zallot , Tyler L. Grove , Daniel J. Payan , Isabelle Martin-Verstraete , Sara Sepic´ , Seetharamsingh Balamkundue, Ramesh Neelakandane, Vinod K. Gadie, Chuan-Fa Liue, Manal A. Swairjof,g, Peter C. Dedone,h,i, Steven C. Almoc, John A. Gerltb,j,k, and Valérie de Crécy-Lagarda,l,2 aDepartment of Microbiology and Cell Science, University of Florida, Gainesville, FL 32611; bInstitute for Genomic Biology, University of Illinois at Urbana–Champaign, Urbana, IL 61801; cDepartment of Biochemistry, Albert Einstein College of Medicine, Bronx, NY 10461; dLaboratoire de Pathogénèse des Bactéries Anaérobies, Institut Pasteur et Université de Paris, F-75015 Paris, France; eSingapore-MIT Alliance for Research and Technology, Infectious Disease Interdisciplinary Research Group, 138602 Singapore, Singapore; fDepartment of Chemistry and Biochemistry, San Diego State University, San Diego, CA 92182; gThe Viral Information Institute, San Diego State University, San Diego, CA 92182; hDepartment of Biological Engineering and Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139; iCenter for Environmental Health Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139; jDepartment of Biochemistry, University of Illinois at Urbana–Champaign, Urbana, IL 61801; kDepartment of Chemistry, University of Illinois at Urbana–Champaign, Urbana, IL 61801; and lUniversity of Florida Genetics Institute, Gainesville, FL 32610 Edited by Tina M. Henkin, The Ohio State University, Columbus, OH, and approved August 1, 2019 (received for review June 16, 2019) Queuosine (Q) is a complex tRNA modification widespread in 1A. The TGT enzyme, which is responsible for the base ex- eukaryotes and bacteria that contributes to the efficiency and accuracy change, is the signature enzyme in the Q biosynthesis pathway. -
Phylogeny Recapitulates Learning: Self-Optimization of Genetic Code
bioRxiv preprint doi: https://doi.org/10.1101/260877; this version posted February 6, 2018. 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. Phylogeny Recapitulates Learning: Self-Optimization of Genetic Code Oliver Attie1, Brian Sulkow1, Chong Di1, and Wei-Gang Qiu1,2,3,* 1Department of Biological Sciences, Hunter College & 2Graduate Center, City University of New York; 3Department of Physiology and Biophysics & Institute for Computational Biomedicine, Weil Cornell Medical College, New York, New York, USA Emails: Oliver Attie [email protected]; Brian Sulkow [email protected]; Chong Di [email protected]; *Correspondence: [email protected] Abstract Learning algorithms have been proposed as a non-selective mechanism capable of creating complex adaptive systems in life. Evolutionary learning however has not been demonstrated to be a plausible cause for the origin of a specific molecular system. Here we show that genetic codes as optimal as the Standard Genetic Code (SGC) emerge readily by following a molecular analog of the Hebb’s rule (“neurons fire together, wire together”). Specifically, error-minimizing genetic codes are obtained by maximizing the number of physio-chemically similar amino acids assigned to evolutionarily similar codons. Formulating genetic code as a Traveling Salesman Problem (TSP) with amino acids as “cities” and codons as “tour positions” and implemented with a Hopfield neural network, the unsupervised learning algorithm efficiently finds an abundance of genetic codes that are more error- minimizing than SGC. -
Effect of Correlated TRAN Abundances on Translation Errors and Evolution of Codon Usage Bias
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Faculty Publications and Other Works -- Ecology and Evolutionary Biology Ecology and Evolutionary Biology 9-2010 Effect of Correlated TRAN Abundances on Translation Errors and Evolution of Codon Usage Bias Premal Shah University of Tennessee - Knoxville Michael A. Gilchrist Follow this and additional works at: https://trace.tennessee.edu/utk_ecolpubs Part of the Ecology and Evolutionary Biology Commons Recommended Citation Shah, Premal and Gilchrist, Michael A., "Effect of Correlated TRAN Abundances on Translation Errors and Evolution of Codon Usage Bias" (2010). Faculty Publications and Other Works -- Ecology and Evolutionary Biology. https://trace.tennessee.edu/utk_ecolpubs/37 This Article is brought to you for free and open access by the Ecology and Evolutionary Biology at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Faculty Publications and Other Works -- Ecology and Evolutionary Biology by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Effect of Correlated tRNA Abundances on Translation Errors and Evolution of Codon Usage Bias Premal Shah1,2*, Michael A. Gilchrist1,2 1 Department of Ecology & Evolutionary Biology, University of Tennessee, Knoxville, Tennessee, United States of America, 2 National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America Abstract Despite the fact that tRNA abundances are thought to play a major role in determining translation error rates, their distribution across the genetic code and the resulting implications have received little attention. In general, studies of codon usage bias (CUB) assume that codons with higher tRNA abundance have lower missense error rates. -
The RNA Code and Protein Synthesis
Downloaded from symposium.cshlp.org on January 18, 2014 - Published by Cold Spring Harbor Laboratory Press The RNA Code and Protein Synthesis M. Nirenberg, T. Caskey, R. Marshall, et al. Cold Spring Harb Symp Quant Biol 1966 31: 11-24 Access the most recent version at doi:10.1101/SQB.1966.031.01.008 References This article cites 37 articles, 24 of which can be accessed free at: http://symposium.cshlp.org/content/31/11.refs.html Article cited in: http://symposium.cshlp.org/content/31/11#related-urls Email alerting Receive free email alerts when new articles cite this article - sign up in service the box at the top right corner of the article or click here To subscribe to Cold Spring Harbor Symposia on Quantitative Biology go to: http://symposium.cshlp.org/subscriptions Copyright © 1966 Cold Spring Harbor Laboratory Press Downloaded from symposium.cshlp.org on January 18, 2014 - Published by Cold Spring Harbor Laboratory Press The RNA Code and Protein Synthesis M. NIRENBERG, T. CASKEY, R. MARSHALL, R. BRIMACOMBE, D. KELLOGG, B. DOCTOIr D. HATFIELD, J. LEVIN, F. ROTTMAN, S. PESTKA, M. WILCOX, AND F. ANDERSON Laboratory of Biochemical Genetics, National Heart Institute, National Institutes of Health, Bethesda, Maryland and t Division of Biochemistry, Walter Reed Army Institute of Research, Walter Reed Army Medical Center, Washington, D.C. Many properties of the RNA code which were TABLE 1. CHARACTERISTICS OF AA-sRI~A BINDING TO RIBOSOMES discussed at the 1963 Cold Spring Harbor meeting were based on information obtained with randomly C14-Phe-sRNA bound to ribo- ordered synthetic polynucleotides. -
Synthesis of Tritium Labeled Queuine, Preq1 and Related Azide Probes Toward Examining the Prevalence of Queuine
Synthesis of Tritium Labeled Queuine, PreQ1 and Related Azide Probes Toward Examining the Prevalence of Queuine by Allen F. Brooks A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Medicinal Chemistry) in the University of Michigan 2012 Doctoral Committee: Research Professor Hollis D. Showalter, Co-Chair Associate Professor George A. Garcia, Co-Chair Professor Hashim M. Al-Hashimi Assistant Professor Garry D. Dotson Assistant Professor Matthew B. Soellner © Allen F. Brooks 2012 In memory of Edward and Lillian Pederson ii Acknowledgements With my remaining time short, it is appropriate to look back and thank those that supported me in my dissertation work either professionally or as a friend. First and foremost, I have to acknowledge my best friend from the program, Adam Lee. If it was not for the trip to the ACS meeting in Chicago, Adam and I likely would have never got to know each other. Luckily, fate arranged such an occurrence. If not for Adam’s friendship and the support of some others, I likely would have left the program in my second year. I also have to thank Jason Witek, an undergraduate who worked in the Showalter lab. We actually met during the Organic Mechanisms course, as he was in an academic program of his own design. The time we worked together in the lab was a productive one, and interestingly an amusing time as well. I also have to thank several other associates for their help in progressing my research as well as making time here more pleasant, those individuals being: Dr. -
Queuine, a Bacterial Derived Hypermodified Nucleobase, Shows Protection in in Vitro Models of Neurodegeneration
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.20.427538; this version posted January 22, 2021. 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. Queuine, a bacterial derived hypermodified nucleobase, shows protection in in vitro models of neurodegeneration Patricia Richard1*, Xavier Manière2*, Lucie Kozlowski2, Hélène Guillorit2,3, Patrice Garnier2, Antoine Danchin4, Nicole C. McKnight1** 1 Stellate Therapeutics Inc., 101 Avenue of the Americas, JLABS @ NYC, New York, NY 10013 2 Stellate Therapeutics SAS, 47 rue de Montmorency, 75003, Paris, France 3 Institut de Génomique Fonctionnelle, 141 rue de la Cardonille, 34094, Montpellier, France 4 Kodikos Labs, Institut Cochin, 24 rue du Faubourg Saint-Jacques, 75014, Paris, France ** corresponding author Email: [email protected] * These authors contributed equally to this work 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.01.20.427538; this version posted January 22, 2021. 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. Abstract Growing evidence suggests that human gut bacteria, comprising the microbiome that communicates with the brain through the so-called ‘gut-brain-axis’, are linked to neurodegener- ative disorders. Imbalances in the microbiome of Parkinson’s disease (PD) and Alzheimer’s dis- ease (AD) patients have been detected in several studies. Queuine is a hypermodified nucleobase enriched in the brain and exclusively produced by bacteria and salvaged by humans through their gut epithelium. Queuine replaces guanine at the wobble position of tRNAs with GUN anticodons and promotes efficient cytoplasmic and mitochondrial mRNA translation. -
A Numerical Representation and Classification of Codons To
bioRxiv preprint doi: https://doi.org/10.1101/2020.03.02.971036; this version posted March 3, 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. A Numerical Representation and Classication of Codons to Investigate Codon Alternation Patterns during Genetic Mutations on Disease Pathogenesis Antara Senguptaa, Pabitra Pal Choudhuryd, Subhadip Chakrabortyb,e, Swarup Royc,∗∗, Jayanta Kumar Dasd,∗, Ditipriya Mallicke, Siddhartha S Janae aDepartment of Master of Computer Applications, MCKV Institute of Engineering, Liluah, India bDepartment of Botany, Nabadwip Vidyasagar College, Nabadwip, India cDepartment of Computer Applications,Sikkim University, Gangtok, Sikkim, India dApplied Statistical Unit, Indian Statistical Institute, Kolkata, India eSchool of Biological Sciences, Indian Association for the Cultivation of Science, Kolkata, India 1. Introduction Genes are the functional units of heredity [4]. It is mainly responsible for the structural and functional changes and for the variation in organisms which could be good or bad. DNA (Deoxyribose Nucleic Acid) sequences build the genes of organisms which in turn encode for particular protein us- ing codon. Any uctuation in this sequence (codons), for example, mishaps during DNA transcription, might lead to a change in the genetic code which alter the protein synthesis. This change is called mutation. Mutation diers from Single Nucleotide Polymorphism(SNP) in many ways [23]. For instance, occurrence of mutation in a population should be less than 1% whereas SNP occurs with greater than 1%. Mutation always occurs in diseased group whereas SNP is occurs in both diseased and control population. Mutation is responsible for some disease phenotype but SNP may or may not be as- sociated with disease phenotype. -
Genetic Code Degeneracy Is Established by the Decoding Center
bioRxiv preprint doi: https://doi.org/10.1101/2021.05.16.444340; this version posted May 17, 2021. 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. 1 Genetic code degeneracy is established by the decoding center of the ribosome 2 3 Shixin Ye and Jean Lehmann* 4 5 INSERM U1195 unit, University of Paris-Saclay, 94276, Le Kremlin Bicêtre, France 6 Institute for InteGrative BioloGy of tHe Cell (I2BC), CEA, CNRS, University of Paris-Saclay, 7 91198 Gif-sur-Yvette, France 8 9 *Corresponding author 10 Emails: [email protected]; [email protected] 11 12 SUMMARY 13 The degeneracy of the genetic code confers a wide array of properties to coding sequences. Yet, 14 its origin is still unclear. A structural analysis has shown that the stability of the Watson-Crick 15 base pair at the second position of the anticodon-codon interaction is a critical parameter 16 controlling the extent of non-specific pairings accepted at the third position by the ribosome, a 17 flexibility at the root of degeneracy. Based on recent cryo-EM analyses, the present work shows 18 that residue A1493 of the decoding center provides a significant contribution to the stability of 19 this base pair, revealing that the ribosome is directly involved in the establishment of 20 degeneracy. Building on existing evolutionary models, we show the evidence that the early 21 appearance of A1493 and A1492 established the basis of degeneracy when an elementary 22 kinetic scheme of translation was prevailing.