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Patt E, Classen S, Hammel M, Schneidman-Duhovny D. Predicting RNA structure and dynamics with deep learning and solution scattering. Biophys J 2025; 124:549-564. [PMID: 39722452 PMCID: PMC11866959 DOI: 10.1016/j.bpj.2024.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Revised: 09/15/2024] [Accepted: 12/23/2024] [Indexed: 12/28/2024] Open
Abstract
Advanced deep learning and statistical methods can predict structural models for RNA molecules. However, RNAs are flexible, and it remains difficult to describe their macromolecular conformations in solutions where varying conditions can induce conformational changes. Small-angle x-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures. There are two main challenges in comparing SAXS profiles to RNA structures: the absence of cations essential for stability and charge neutralization in predicted structures and the inadequacy of a single structure to represent RNA's conformational plasticity. We introduce a solution conformation predictor for RNA (SCOPER) to address these challenges. This pipeline integrates kinematics-based conformational sampling with the innovative deep learning model, IonNet, designed for predicting Mg2+ ion binding sites. Validated through benchmarking against 14 experimental data sets, SCOPER significantly improved the quality of SAXS profile fits by including Mg2+ ions and sampling of conformational plasticity. We observe that an increased content of monovalent and bivalent ions leads to decreased RNA plasticity. Therefore, carefully adjusting the plasticity and ion density is crucial to avoid overfitting experimental SAXS data. SCOPER is an efficient tool for accurately validating the solution state of RNAs given an initial, sufficiently accurate structure and provides the corrected atomistic model, including ions.
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Affiliation(s)
- Edan Patt
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Scott Classen
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California
| | - Michal Hammel
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California.
| | - Dina Schneidman-Duhovny
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
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Bu F, Adam Y, Adamiak RW, Antczak M, de Aquino BRH, Badepally NG, Batey RT, Baulin EF, Boinski P, Boniecki MJ, Bujnicki JM, Carpenter KA, Chacon J, Chen SJ, Chiu W, Cordero P, Das NK, Das R, Dawson WK, DiMaio F, Ding F, Dock-Bregeon AC, Dokholyan NV, Dror RO, Dunin-Horkawicz S, Eismann S, Ennifar E, Esmaeeli R, Farsani MA, Ferré-D'Amaré AR, Geniesse C, Ghanim GE, Guzman HV, Hood IV, Huang L, Jain DS, Jaryani F, Jin L, Joshi A, Karelina M, Kieft JS, Kladwang W, Kmiecik S, Koirala D, Kollmann M, Kretsch RC, Kurciński M, Li J, Li S, Magnus M, Masquida B, Moafinejad SN, Mondal A, Mukherjee S, Nguyen THD, Nikolaev G, Nithin C, Nye G, Pandaranadar Jeyeram IPN, Perez A, Pham P, Piccirilli JA, Pilla SP, Pluta R, Poblete S, Ponce-Salvatierra A, Popenda M, Popenda L, Pucci F, Rangan R, Ray A, Ren A, Sarzynska J, Sha CM, Stefaniak F, Su Z, Suddala KC, Szachniuk M, Townshend R, Trachman RJ, Wang J, Wang W, Watkins A, Wirecki TK, Xiao Y, Xiong P, Xiong Y, Yang J, Yesselman JD, Zhang J, Zhang Y, Zhang Z, Zhou Y, Zok T, Zhang D, Zhang S, Żyła A, Westhof E, Miao Z. RNA-Puzzles Round V: blind predictions of 23 RNA structures. Nat Methods 2025; 22:399-411. [PMID: 39623050 PMCID: PMC11810798 DOI: 10.1038/s41592-024-02543-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 10/29/2024] [Indexed: 01/16/2025]
Abstract
RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson-Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.
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Grants
- T32 GM066706 NIGMS NIH HHS
- NSFC T2225007 National Natural Science Foundation of China (National Science Foundation of China)
- R35 GM134919 NIGMS NIH HHS
- R35GM145409 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R35 GM145409 NIGMS NIH HHS
- 32270707 National Natural Science Foundation of China (National Science Foundation of China)
- R35 GM122579 NIGMS NIH HHS
- R35 GM134864 NIGMS NIH HHS
- T32 grant GM066706 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- P20GM121342 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R21 CA219847 NCI NIH HHS
- 32171191 National Natural Science Foundation of China (National Science Foundation of China)
- P20 GM121342 NIGMS NIH HHS
- R35 GM152029 NIGMS NIH HHS
- R01 GM073850 NIGMS NIH HHS
- F32 GM112294 NIGMS NIH HHS
- ZIA DK075136 Intramural NIH HHS
- Z.M. is supported by Major Projects of Guangzhou National Laboratory, (Grant No. GZNL2023A01006, GZNL2024A01002, SRPG22-003, SRPG22-006, SRPG22-007, HWYQ23-003, YW-YFYJ0102), the National Key R&D Programs of China (2023YFF1204700, 2023YFF1204701, 2021YFF1200900, 2021YFF1200903). This work is part of the ITI 2021-2028 program and supported by IdEx Unistra (ANR-10-IDEX-0002 to E.W.), SFRI-STRAT’US project (ANR-20-SFRI-0012) and EUR IMCBio (IMCBio ANR-17-EURE-0023 to E.W.) under the framework of the French Investments for the Future Program.
- E.W. acknowledges also support from Wenzhou Institute, University of Chinese Academy of Sciences (WIUCASQD2024002).
- E.F.B. was additionally supported by European Molecular Biology Organization (EMBO) fellowship (ALTF 525-2022).
- Boniecki’s research was supported by the Polish National Science Center Poland (NCN) (grant 2016/23/B/ST6/03433 to Michal J. Boniecki). Predictions were performed using computational resources of the Interdisciplinary Centre for Mathematical and Computational Modelling of the University of Warsaw (ICM) (grant G66-9).
- J.M.B. is supported by the National Science Centre in Poland (NCN grants: 2017/26/A/NZ1/01083 to J.M.B., 2021/43/D/NZ1/03360 to S.M., 2020/39/B/NZ2/03127 to F.S., 2020/39/D/NZ2/02837 to T.K.W.). J.M.B. acknowledge Poland high-performance computing Infrastructure PLGrid (HPC Centers: ACK Cyfronet AGH, PCSS, CI TASK, WCSS) for providing computer facilities and support within the computational grant PLG/2023/016080.
- S.J.C. is supported by the National Institutes of Health under Grant R35-GM134919.
- R.D. is supported by Stanford Bio-X (to R.D., R.O.D., R.C.K., and S.E.); Stanford Gerald J. Lieberman Fellowship (to R.R.); the National Institutes of Health (R21 CA219847 and R35 GM122579 to R.D.), the Howard Hughes Medical Institute (HHMI, to R.D.); Consejo Nacional de Ciencia y Tecnología CONACyT Fellowship 312765 (P.C.); the Ruth L. Kirschstein National Research Service Award Postdoctoral Fellowships GM112294 (to J.D.Y.); National Science Foundation Graduate Research Fellowships (R.J.L.T. and R.R.); the National Library of Medicine T15 Training Grant (NLM T15007033 to K.A.C.); the U.S. Department of Energy, Office of Science Graduate Student Research program (R.J.L.T.).
- The National Institutes of Health grants 1R35 GM134864 and the Passan Foundation.
- R.O.D. is supported by the U.S. Department of Energy, Office of Science, Scientific Discovery through Advanced Computing (SciDAC) program (R.O.D.); Intel (R.O.D.).
- A.F.D. is supported, in part, by the intramural program of the National Heart, Lung and Blood Institute, National Institutes of Health, USA.
- Guangdong Science and Technology Department (2022A1515010328, 2023B1212060013, 2020B1212030004), Fundamental Research Funds for the Central Universities, Sun Yat-sen University (23ptpy41).
- D.K. is supported by the NSF CAREER award MCB-2236996, and start-up, SURFF, and START awards from the University of Maryland Baltimore County to D.K.
- BM is supported by the Interdisciplinary Thematic Institute IMCBio, as part of the ITI 2021-2028 program at the University of Strasbourg, CNRS and Inserm, by IdEx Unistra (ANR-10-IDEX-0002), and EUR (IMCBio ANR-17-EUR-0023), under the framework of the French Investments Program for the Future.
- T.H.D.N. is supported by UKRI-Medical Research Council grant MC_UP_1201/19.
- C.N. and M.K. acknowledge funding from the National Science Centre, Poland [OPUS 2019/33/B/NZ2/02100]; S.P.P. acknowledges funding from the National Science Centre, Poland [OPUS 2020/39/B/NZ2/01301]; S.K. acknowledges funding from the National Science Centre, Poland [Sheng 2021/40/Q/NZ2/00078]; C.N. acknowledge Polish high-performance computing infrastructure PLGrid (HPC Centers: PCSS, ACK Cyfronet AGH, CI TASK, WCSS) for providing computer facilities and support within the computational grants PLG/2022/016043, PLG/2022/015327 and PLG/2020/013424.
- AP is supported by an NSF-CAREER award CHE-2235785
- A.R. is supported by grants from the Natural Science Foundation of China (32325029, 32022039, 91940302, and 91640104), the National Key Research and Development Project of China (2021YFC2300300 and 2023YFC2604300).
- Marta Szachniuk are supported by the National Science Centre, Poland (2019/35/B/ST6/03074 to M.S.), the statutory funds of IBCH PAS and Poznan University of Technology.
- J.W. is supported by the Penn State College of Medicine’s Artificial Intelligence and Biomedical Informatics Program.
- J.Z. is supported by the Intramural Research Program of the NIH, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (ZIADK075136 to J.Z.), and an NIH Deputy Director for Intramural Research (DDIR) Challenge Award to J.Z.
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Affiliation(s)
- Fan Bu
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
- School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yagoub Adam
- Inter-institutional Graduate Program on Bioinformatics, Department of Computer Science and Mathematics, FFCLRP, University of São Paulo, Ribeirão Preto, Brazil
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria
| | - Ryszard W Adamiak
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Maciej Antczak
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Belisa Rebeca H de Aquino
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Nagendar Goud Badepally
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Robert T Batey
- Department of Biochemistry, University of Colorado at Boulder, Boulder, CO, USA
| | - Eugene F Baulin
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Pawel Boinski
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Michal J Boniecki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Janusz M Bujnicki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Kristy A Carpenter
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Jose Chacon
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Department of Cell and Developmental Biology, University of California San Diego, San Diego, CA, USA
| | - Shi-Jie Chen
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Wah Chiu
- Department of Bioengineering and James H. Clark Center, Stanford University, Stanford, CA, USA
| | - Pablo Cordero
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Stripe, South San Francisco, CA, USA
| | - Naba Krishna Das
- Department of Chemistry and Biochemistry, University of Maryland Baltimore County, Baltimore, MD, USA
| | - Rhiju Das
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
- Biophysics program, Stanford University, Stanford, CA, USA
| | - Wayne K Dawson
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Frank DiMaio
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Feng Ding
- Department of Physics and Astronomy, Clemson University, Clemson, SC, USA
| | - Anne-Catherine Dock-Bregeon
- Laboratory of Integrative Biology of Marine Models (LBI2M), Sorbonne University-CNRS UMR8227, Roscoff, France
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Ron O Dror
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Department of Structural Biology, Stanford University, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Stanisław Dunin-Horkawicz
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Stephan Eismann
- Department of Applied Physics, Stanford University, Stanford, CA, USA
- Atomic AI, South San Francisco, CA, USA
| | - Eric Ennifar
- Architecture et Réactivité de l'ARN, Institut de Biologie Moléculaire et Cellulaire du CNRS, Université de Strasbourg, Strasbourg, France
| | - Reza Esmaeeli
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Masoud Amiri Farsani
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Adrian R Ferré-D'Amaré
- Laboratory of Nucleic Acids, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Caleb Geniesse
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - George E Ghanim
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
| | - Horacio V Guzman
- Instituto de Ciencia de Materials de Barcelona, ICMAB-CSIC, Bellaterra E-08193, Spain & Departamento de Física Teórica de la Materia Condensada, Universidad Autónoma de Madrid, Madrid, Spain
| | - Iris V Hood
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Lin Huang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University Guangzhou, Guangdong, China
| | - Dharm Skandh Jain
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Farhang Jaryani
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Lei Jin
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Astha Joshi
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Masha Karelina
- Biophysics program, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Jeffrey S Kieft
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver School of Medicine, Aurora, CO, USA
- New York Structural Biology Center, New York, NY, USA
| | - Wipapat Kladwang
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Sebastian Kmiecik
- Laboratory of Computational Biology, Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Warsaw, Poland
| | - Deepak Koirala
- Department of Chemistry and Biochemistry, University of Maryland Baltimore County, Baltimore, MD, USA
| | - Markus Kollmann
- Department of Computer Science, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany
| | | | - Mateusz Kurciński
- Laboratory of Computational Biology, Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Warsaw, Poland
| | - Jun Li
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Shuang Li
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Marcin Magnus
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - BenoÎt Masquida
- UMR 7156, CNRS - Université de Strasbourg, IPCB, Strasbourg, France
| | - S Naeim Moafinejad
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Arup Mondal
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Sunandan Mukherjee
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | | | - Grigory Nikolaev
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Chandran Nithin
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
- Laboratory of Computational Biology, Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Warsaw, Poland
| | - Grace Nye
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Iswarya P N Pandaranadar Jeyeram
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Alberto Perez
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Phillip Pham
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Joseph A Piccirilli
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL, USA
- Department of Chemistry, The University of Chicago, Chicago, IL, USA
| | - Smita Priyadarshini Pilla
- Laboratory of Computational Biology, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland
| | - Radosław Pluta
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Simón Poblete
- Facultad de Ingeniería, Arquitectura y Diseño, Universidad San Sebastián, Santiago, Chile
- Centro BASAL Ciencia & Vida, Universidad San Sebastián, Santiago, Chile
| | - Almudena Ponce-Salvatierra
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Mariusz Popenda
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Lukasz Popenda
- NanoBioMedical Centre, Adam Mickiewicz University, Poznan, Poland
| | - Fabrizio Pucci
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
| | - Ramya Rangan
- Biophysics program, Stanford University, Stanford, CA, USA
- Atomic AI, South San Francisco, CA, USA
| | - Angana Ray
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Aiming Ren
- Life Sciences Institute, Zhejiang University, Hangzhou, China
| | - Joanna Sarzynska
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Congzhou Mike Sha
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Filip Stefaniak
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Zhaoming Su
- The State Key Laboratory of Biotherapy, West China Hospital, Chengdu, China
| | - Krishna C Suddala
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Marta Szachniuk
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Raphael Townshend
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Atomic AI, South San Francisco, CA, USA
| | - Robert J Trachman
- Laboratory of Nucleic Acids, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Jian Wang
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Wenkai Wang
- MOE Frontiers Science Center for Nonlinear Expectations, Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, China
| | - Andrew Watkins
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Prescient Design, Genentech Research and Early Development, South San Francisco, CA, USA
| | - Tomasz K Wirecki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Yi Xiao
- School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China
| | - Peng Xiong
- School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Department of Biomedical Engineering, Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China
| | - Yiduo Xiong
- School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China
| | - Jianyi Yang
- MOE Frontiers Science Center for Nonlinear Expectations, Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, China
| | - Joseph David Yesselman
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
- Department of Chemistry, University of Nebraska, Lincoln, NE, USA
| | - Jinwei Zhang
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Yi Zhang
- School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China
| | - Zhenzhen Zhang
- Department of Physics and Astronomy, Clemson University, Clemson, SC, USA
| | - Yuanzhe Zhou
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Tomasz Zok
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Dong Zhang
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Sicheng Zhang
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Adriana Żyła
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Eric Westhof
- Architecture et Réactivité de l'ARN, Institut de Biologie Moléculaire et Cellulaire du CNRS, Université de Strasbourg, Strasbourg, France.
- Engineering Research Center of Clinical Functional Materials and Diagnosis & Treatment Devices of Zhejiang Province, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, China.
| | - Zhichao Miao
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China.
- Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Clinical Research Center for Anesthesiology and Perioperative Medicine, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
- European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge, UK.
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3
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Feng S, Xiao W, Yu Y, Liu G, Zhang Y, Chen T, Lu C. Linker-Mediated Inactivation of the SAM-II Domain in the Tandem SAM-II/SAM-V Riboswitch. Int J Mol Sci 2024; 25:11288. [PMID: 39457069 PMCID: PMC11508383 DOI: 10.3390/ijms252011288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Revised: 10/16/2024] [Accepted: 10/18/2024] [Indexed: 10/28/2024] Open
Abstract
Tandem SAM-II/SAM-V riboswitch belongs to a class of riboswitches found in the marine bacterium 'Candidatus Pelagibacter ubique'. Previous studies have demonstrated that these riboswitches have the potential for digital modulation of gene expression at both the transcriptional and translational levels. In this study, we investigate the conformational changes in the tandem SAM-II/SAM-V riboswitch binding to S-adenosylmethionine (SAM) using selective 2'-hydroxyl acylation analyzed by the primer extension (SHAPE) assay, small-angle X-ray scattering (SAXS), and oligos depressing probing. Our findings reveal that the linker between SAM-II/SAM-V aptamers blocks the SAM response of the SAM-II domain. This result proposes a new mechanism for gene expression regulation, where the ligand-binding functions of tandem riboswitches can be selectively masked or released through a linker.
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Affiliation(s)
- Shanshan Feng
- College of Biological Science and Medical Engineering, Donghua University, Shanghai 201620, China; (S.F.); (W.X.); (Y.Y.); (Y.Z.); (T.C.)
| | - Wenwen Xiao
- College of Biological Science and Medical Engineering, Donghua University, Shanghai 201620, China; (S.F.); (W.X.); (Y.Y.); (Y.Z.); (T.C.)
| | - Yingying Yu
- College of Biological Science and Medical Engineering, Donghua University, Shanghai 201620, China; (S.F.); (W.X.); (Y.Y.); (Y.Z.); (T.C.)
| | - Guangfeng Liu
- National Center for Protein Science Shanghai, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201204, China;
| | - Yunlong Zhang
- College of Biological Science and Medical Engineering, Donghua University, Shanghai 201620, China; (S.F.); (W.X.); (Y.Y.); (Y.Z.); (T.C.)
| | - Ting Chen
- College of Biological Science and Medical Engineering, Donghua University, Shanghai 201620, China; (S.F.); (W.X.); (Y.Y.); (Y.Z.); (T.C.)
| | - Changrui Lu
- College of Biological Science and Medical Engineering, Donghua University, Shanghai 201620, China; (S.F.); (W.X.); (Y.Y.); (Y.Z.); (T.C.)
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4
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De Felice B, Gazzotti S, Ortenzi MA, Parolini M. Multi-level toxicity assessment of polylactic acid (PLA) microplastics on the cladoceran Daphnia magna. AQUATIC TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2024; 272:106966. [PMID: 38815345 DOI: 10.1016/j.aquatox.2024.106966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 05/12/2024] [Accepted: 05/19/2024] [Indexed: 06/01/2024]
Abstract
The accumulation of plastics waste in the environment has raised a worrisome concern, moving the society to seek out for sustainable solutions, such as the transition from the use of fossil-based, conventional plastics to bioplastics (BPs). However, once in the environment bioplastics have the same probability to accumulate and experience weathering processes than conventional plastics, leading to the formation of microplastics (MPs). However, to date the information on the potential toxicity of MPs originated from the weathering of bioplastics is limited. Thus, this study aimed at investigating the adverse effects induced by the exposure to MPs made of a bioplastic polymer, the polylactic acid (PLA), towards the freshwater cladoceran Daphnia magna. Organisms were exposed for 21 days to three concentrations (0.125 µg/mL, 1.25 µg/mL and 12.5 µg/mL) of PLA microplastics (hereafter PLA-MPs). A multi-level approach was performed to investigate the potential effects through the biological hierarchy, starting from the sub-individual up to the individual level. At the sub-individual level, changes in the oxidative status (i.e., the amount of reactive oxygen species and the activity of antioxidant and detoxifying enzymes) and oxidative damage (i.e., lipid peroxidation) were explored. Moreover, the total caloric content as well as the content of protein, carbohydrate and lipid content assess were used to investigate the effects on energy reserves. At individual level the changes in swimming activity (i.e., distance moved and swimming speed) were assessed. Our results showed that the exposure to PLA-MPs induced a slight modulation in the oxidative status and energy reserves, leading to an increase in swimming behavior of treated individuals compared to control conspecifics. These results suggest that the exposure to MPs made of a bioplastic polymer can induce adverse effects similar to those caused by conventional polymers.
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Affiliation(s)
- Beatrice De Felice
- University of Milan, Department of Environmental Science and Policy, via Celoria 26, I-20133 Milan, Italy.
| | - Stefano Gazzotti
- University of Milan, Laboratory of Materials and Polymers (LaMPo), Department of Chemistry, via Golgi 19, I-20133 Milan, Italy
| | - Marco Aldo Ortenzi
- University of Milan, Laboratory of Materials and Polymers (LaMPo), Department of Chemistry, via Golgi 19, I-20133 Milan, Italy
| | - Marco Parolini
- University of Milan, Department of Environmental Science and Policy, via Celoria 26, I-20133 Milan, Italy
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5
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Salvail H, Balaji A, Roth A, Breaker RR. A spermidine riboswitch class in bacteria exploits a close variant of an aptamer for the enzyme cofactor S-adenosylmethionine. Cell Rep 2023; 42:113571. [PMID: 38096053 PMCID: PMC10853860 DOI: 10.1016/j.celrep.2023.113571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/16/2023] [Accepted: 11/22/2023] [Indexed: 12/30/2023] Open
Abstract
Natural polyamines such as spermidine and spermine cations have characteristics that make them highly likely to be sensed by riboswitches, such as their general affinity to polyanionic RNA and their broad contributions to cell physiology. Despite previous claims that polyamine riboswitches exist, evidence of their biological functions has remained unconvincing. Here, we report that rare variants of bacterial S-adenosylmethionine-I (SAM-I) riboswitches reject SAM and have adapted to selectively sense spermidine. These spermidine-sensing riboswitch variants are associated with genes whose protein products are directly involved in the production of spermidine and other polyamines. Biochemical and genetic assays demonstrate that representatives of this riboswitch class robustly function as genetic "off" switches, wherein spermidine binding causes premature transcription termination to suppress the expression of polyamine biosynthetic genes. These findings confirm the existence of natural spermidine-sensing riboswitches in bacteria and expand the list of variant riboswitch classes that have adapted to bind different ligands.
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Affiliation(s)
- Hubert Salvail
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520-8103, USA
| | - Aparaajita Balaji
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520-8103, USA
| | - Adam Roth
- Howard Hughes Medical Institute, Yale University, New Haven, CT 06520-8103, USA
| | - Ronald R Breaker
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520-8103, USA; Howard Hughes Medical Institute, Yale University, New Haven, CT 06520-8103, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520-8103, USA.
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6
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Srivastava Y, Blau ME, Jenkins JL, Wedekind JE. Full-Length NAD +-I Riboswitches Bind a Single Cofactor but Cannot Discriminate against Adenosine Triphosphate. Biochemistry 2023; 62:3396-3410. [PMID: 37947391 PMCID: PMC10702441 DOI: 10.1021/acs.biochem.3c00391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 10/19/2023] [Accepted: 10/19/2023] [Indexed: 11/12/2023]
Abstract
Bacterial riboswitches are structured RNAs that bind small metabolites to control downstream gene expression. Two riboswitch classes have been reported to sense nicotinamide adenine dinucleotide (NAD+), which plays a key redox role in cellular metabolism. The NAD+-I (class I) riboswitch stands out because it comprises two homologous, tandemly arranged domains. However, previous studies examined the isolated domains rather than the full-length riboswitch. Crystallography and ligand binding analyses led to the hypothesis that each domain senses NAD+ but with disparate equilibrium binding constants (KD) of 127 μM (domain I) and 3.4 mM (domain II). Here, we analyzed individual domains and the full-length riboswitch by isothermal titration calorimetry to quantify the cofactor affinity and specificity. Domain I senses NAD+ with a KD of 24.6 ± 8.4 μM but with a reduced ligand-to-receptor stoichiometry, consistent with nonproductive domain self-association observed by gel-filtration chromatography; domain II revealed no detectable binding. By contrast, the full-length riboswitch binds a single NAD+ with a KD of 31.5 ± 1.5 μM; dinucleotides NADH and AP2-ribavirin also bind with one-to-one stoichiometry. Unexpectedly, the full-length riboswitch also binds a single ATP equivalent (KD = 11.0 ± 3.5 μM). The affinity trend of the full-length riboswitch is ADP = ATP > NAD+ = AP2-ribavirin > NADH. Although our results support riboswitch sensing of a single NAD+ at concentrations significantly below the intracellular levels of this cofactor, our findings do not support the level of specificity expected for a riboswitch that exclusively senses NAD+. Gene regulatory implications and future challenges are discussed.
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Affiliation(s)
- Yoshita Srivastava
- Department
of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester School of Medicine & Dentistry, Rochester, New York 14642, United States
| | - Maya E. Blau
- Department
of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester School of Medicine & Dentistry, Rochester, New York 14642, United States
| | - Jermaine L. Jenkins
- Department
of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester School of Medicine & Dentistry, Rochester, New York 14642, United States
| | - Joseph E. Wedekind
- Department
of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester School of Medicine & Dentistry, Rochester, New York 14642, United States
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7
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Kulkarni M, Thangappan J, Deb I, Wu S. Comparative analysis of RNA secondary structure accuracy on predicted RNA 3D models. PLoS One 2023; 18:e0290907. [PMID: 37656749 PMCID: PMC10473517 DOI: 10.1371/journal.pone.0290907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 08/18/2023] [Indexed: 09/03/2023] Open
Abstract
RNA structure is conformationally dynamic, and accurate all-atom tertiary (3D) structure modeling of RNA remains challenging with the prevailing tools. Secondary structure (2D) information is the standard prerequisite for most RNA 3D modeling. Despite several 2D and 3D structure prediction tools proposed in recent years, one of the challenges is to choose the best combination for accurate RNA 3D structure prediction. Here, we benchmarked seven small RNA PDB structures (40 to 90 nucleotides) with different topologies to understand the effects of different 2D structure predictions on the accuracy of 3D modeling. The current study explores the blind challenge of 2D to 3D conversions and highlights the performances of de novo RNA 3D modeling from their predicted 2D structure constraints. Our results show that conformational sampling-based methods such as SimRNA and IsRNA1 depend less on 2D accuracy, whereas motif-based methods account for 2D evidence. Our observations illustrate the disparities in available 3D and 2D prediction methods and may further offer insights into developing topology-specific or family-specific RNA structure prediction pipelines.
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Affiliation(s)
- Mandar Kulkarni
- R&D Center, PharmCADD Co. Ltd., Dong-gu, Busan, Republic of Korea
| | | | - Indrajit Deb
- R&D Center, PharmCADD Co. Ltd., Dong-gu, Busan, Republic of Korea
| | - Sangwook Wu
- R&D Center, PharmCADD Co. Ltd., Dong-gu, Busan, Republic of Korea
- Department of Physics, Pukyong National University, Busan, Republic of Korea
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8
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Xu J, Hou J, Ding M, Wang Z, Chen T. Riboswitches, from cognition to transformation. Synth Syst Biotechnol 2023; 8:357-370. [PMID: 37325181 PMCID: PMC10265488 DOI: 10.1016/j.synbio.2023.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/20/2023] [Accepted: 05/25/2023] [Indexed: 06/17/2023] Open
Abstract
Riboswitches are functional RNA elements that regulate gene expression by directly detecting metabolites. Twenty years have passed since it was first discovered, researches on riboswitches are becoming increasingly standardized and refined, which could significantly promote people's cognition of RNA function as well. Here, we focus on some representative orphan riboswitches, enumerate the structural and functional transformation and artificial design of riboswitches including the coupling with ribozymes, hoping to attain a comprehensive understanding of riboswitch research.
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Affiliation(s)
- Jingdong Xu
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, China
- Frontier Science Center for Synthetic Biology, Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin, 300350, China
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin, 300350, China
| | - Junyuan Hou
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, China
- Frontier Science Center for Synthetic Biology, Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin, 300350, China
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin, 300350, China
| | - Mengnan Ding
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, China
- Frontier Science Center for Synthetic Biology, Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin, 300350, China
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin, 300350, China
| | - Zhiwen Wang
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, China
- Frontier Science Center for Synthetic Biology, Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin, 300350, China
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin, 300350, China
| | - Tao Chen
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, China
- Frontier Science Center for Synthetic Biology, Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin, 300350, China
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin, 300350, China
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9
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Deng J, Fang X, Huang L, Li S, Xu L, Ye K, Zhang J, Zhang K, Zhang QC. RNA structure determination: From 2D to 3D. FUNDAMENTAL RESEARCH 2023; 3:727-737. [PMID: 38933295 PMCID: PMC11197651 DOI: 10.1016/j.fmre.2023.06.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 06/04/2023] [Accepted: 06/05/2023] [Indexed: 06/28/2024] Open
Abstract
RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.
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Affiliation(s)
- Jie Deng
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Xianyang Fang
- Beijing Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Key Laboratory of RNA Biology, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Lin Huang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Shanshan Li
- MOE Key Laboratory for Cellular Dynamics and Center for Advanced Interdisciplinary Science and Biomedicine of IHM, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China
| | - Lilei Xu
- Beijing Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Keqiong Ye
- Key Laboratory of RNA Biology, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinsong Zhang
- MOE Key Laboratory of Bioinformatics, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
| | - Kaiming Zhang
- MOE Key Laboratory for Cellular Dynamics and Center for Advanced Interdisciplinary Science and Biomedicine of IHM, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China
| | - Qiangfeng Cliff Zhang
- MOE Key Laboratory of Bioinformatics, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
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10
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Peng X, Liao W, Lin X, Lilley DMJ, Huang L. Crystal structures of the NAD+-II riboswitch reveal two distinct ligand-binding pockets. Nucleic Acids Res 2023; 51:2904-2914. [PMID: 36840714 PMCID: PMC10085692 DOI: 10.1093/nar/gkad102] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 02/01/2023] [Accepted: 02/16/2023] [Indexed: 02/26/2023] Open
Abstract
We present crystal structures of a new NAD+-binding riboswitch termed NAD+-II, bound to nicotinamide mononucleotide (NMN), nicotinamide adenine dinucleotide (NAD+) and nicotinamide riboside (NR). The RNA structure comprises a number of structural features including three helices, one of which forms a triple helix by interacting with an A5 strand in its minor-groove, and another formed from a long-range pseudoknot. The core of the structure (centrally located and coaxial with the triplex and the pseudoknot) includes two consecutive quadruple base interactions. Unusually the riboswitch binds two molecules of ligand, bound at distinct, non-overlapping sites in the RNA. Binding occurs primarily through the nicotinamide moiety of each ligand, held by specific hydrogen bonding and stacking interactions with the pyridyl ring. The mode of binding is the same for NMN, NR and the nicotinamide moiety of NAD+. In addition, when NAD+ is bound into one site it adopts an elongated conformation such that its diphosphate linker occupies a groove on the surface of the RNA, following which the adenine portion inserts into a pocket and makes specific hydrogen bonding interactions. Thus the NAD+-II riboswitch is distinct from the NAD+-I riboswitch in that it binds two molecules of ligand at separate sites, and that binding occurs principally through the nicotinamide moiety.
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Affiliation(s)
- Xuemei Peng
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Wenjian Liao
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Xiaowei Lin
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - David M J Lilley
- Cancer Research UK Nucleic Acid Structure Research Group, MSI/WTB Complex, The University of Dundee, Dow Street, Dundee DD1 5EH, UK
| | - Lin Huang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
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11
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Kavita K, Breaker RR. Discovering riboswitches: the past and the future. Trends Biochem Sci 2023; 48:119-141. [PMID: 36150954 PMCID: PMC10043782 DOI: 10.1016/j.tibs.2022.08.009] [Citation(s) in RCA: 110] [Impact Index Per Article: 55.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 08/18/2022] [Accepted: 08/26/2022] [Indexed: 01/25/2023]
Abstract
Riboswitches are structured noncoding RNA domains used by many bacteria to monitor the concentrations of target ligands and regulate gene expression accordingly. In the past 20 years over 55 distinct classes of natural riboswitches have been discovered that selectively sense small molecules or elemental ions, and thousands more are predicted to exist. Evidence suggests that some riboswitches might be direct descendants of the RNA-based sensors and switches that were likely present in ancient organisms before the evolutionary emergence of proteins. We provide an overview of the current state of riboswitch research, focusing primarily on the discovery of riboswitches, and speculate on the major challenges facing researchers in the field.
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Affiliation(s)
- Kumari Kavita
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520-8103, USA
| | - Ronald R Breaker
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520-8103, USA; Howard Hughes Medical Institute, Yale University, New Haven, CT 06520-8103, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520-8103, USA.
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12
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Xu X, Egger M, Li C, Chen H, Micura R, Ren A. Structure-based investigations of the NAD+-II riboswitch. Nucleic Acids Res 2023; 51:54-67. [PMID: 36610789 PMCID: PMC9841397 DOI: 10.1093/nar/gkac1227] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/07/2022] [Accepted: 12/10/2022] [Indexed: 01/09/2023] Open
Abstract
Riboswitches are conserved non-coding domains in bacterial mRNA with gene regulation function that are essential for maintaining enzyme co-factor metabolism. Recently, the pnuC RNA motif was reported to selectively bind nicotinamide adenine dinucleotide (NAD+), defining a novel class of NAD+ riboswitches (NAD+-II) according to phylogenetic analysis. To reveal the three-dimensional architecture and the ligand-binding mode of this riboswitch, we solved the crystal structure of NAD+-II riboswitch in complex with NAD+. Strikingly and in contrast to class-I riboswitches that form a tight recognition pocket for the adenosine diphosphate (ADP) moiety of NAD+, the class-II riboswitches form a binding pocket for the nicotinamide mononucleotide (NMN) portion of NAD+ and display only unspecific interactions with the adenosine. We support this finding by an additional structure of the class-II RNA in complex with NMN alone. The structures define a novel RNA tertiary fold that was further confirmed by mutational analysis in combination with isothermal titration calorimetry (ITC), and 2-aminopurine-based fluorescence spectroscopic folding studies. Furthermore, we truncated the pnuC RNA motif to a short RNA helical scaffold with binding affinity comparable to the wild-type motif to allude to the potential of engineering the NAD+-II motif for biotechnological applications.
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Affiliation(s)
- Xiaochen Xu
- Department of Gastroenterology/Department of Cardiology of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Michaela Egger
- Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck 6020, Austria
| | - Chunyan Li
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Hao Chen
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Ronald Micura
- Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck 6020, Austria
| | - Aiming Ren
- Department of Gastroenterology/Department of Cardiology of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
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13
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Insertions and deletions mediated functional divergence of Rossmann fold enzymes. Proc Natl Acad Sci U S A 2022; 119:e2207965119. [PMID: 36417431 PMCID: PMC9860332 DOI: 10.1073/pnas.2207965119] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Nucleobase-containing coenzymes are hypothesized to be relics of an early RNA-based world that preceded the emergence of proteins. Despite the importance of coenzyme-protein synergisms, their emergence and evolution remain understudied. An excellent target to address this issue is the Rossmann fold, the most catalytically diverse and abundant protein architecture in nature. We investigated two main Rossmann lineages: the nicotinamide adenine dinucleotide phosphate (NAD(P)) and the S-adenosyl methionine (SAM)- binding superfamilies. To identify the evolutionary changes that lead to a coenzyme specificity switch on these superfamilies, we performed structural and sequence-based Hidden Markov model analysis to systematically search for key motifs in their coenzyme-binding pockets. Our analyses revealed that through insertions and deletions (InDels) and a residue substitution, the ancient β1-loop-α1 coenzyme-binding structure of NAD(P) could be reshaped into the SAM-binding β1-loop-α1 structure. To experimentally prove this obsevation, we removed three amino acids from the NAD(P)-binding pocket and solved the structure of the resulting mutant, revealing the characteristic loop features of the SAM-binding pocket. To confirm the binding to SAM, we performed isothermal titration calorimetry measurements. Molecular dynamics simulations also corroborated the role of InDels in abolishing NAD binding and acquiring SAM binding. Our results uncovered how nature may have utilized insertions and deletions to optimize the different coenzyme-binding pockets and the distinct functionalities observed for Rossmann superfamilies. This work also proposes a general mechanism by which protein templates could have been recycled through the course of evolution to adopt different coenzymes and confer distinct chemistries.
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14
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Möller L, Guerci L, Isert C, Atz K, Schneider G. Translating from proteins to ribonucleic acids for ligand-binding site detection. Mol Inform 2022; 41:e2200059. [PMID: 35577762 DOI: 10.1002/minf.202200059] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 05/16/2022] [Indexed: 11/10/2022]
Abstract
Identifying druggable ligand-binding sites on the surface of the macromolecular targets is an important process in structure-based drug discovery. Deep-learning models have been shown to successfully predict ligand-binding sites of proteins. As a step toward predicting binding sites in RNA and RNA-protein complexes, we employ three-dimensional convolutional neural networks. We introduce a dataset splitting approach to minimize structure-related bias in training data, and investigate the influence of protein-based neural network pre-training before fine-tuning on RNA structures. Models that were pre-trained on proteins considerably outperformed the models that were trained exclusively on RNA structures. Overall, 71% of the known RNA binding sites were correctly located within 4 Å of their true centres with a structural overlap of at least 25%.
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15
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Abstract
More than 55 distinct classes of riboswitches that respond to small metabolites or elemental ions have been experimentally validated to date. The ligands sensed by these riboswitches are biased in favor of fundamental compounds or ions that are likely to have been relevant to ancient forms of life, including those that might have populated the "RNA World", which is a proposed biochemical era that predates the evolutionary emergence of DNA and proteins. In the following text, I discuss the various types of ligands sensed by some of the most common riboswitches present in modern bacterial cells and consider implications for ancient biological processes centered on the proven capabilities of these RNA-based sensors. Although most major biochemical aspects of metabolism are represented by known riboswitch classes, there are striking sensory gaps in some key areas. These gaps could reveal weaknesses in the performance capabilities of RNA that might have hampered RNA World evolution, or these could highlight opportunities to discover additional riboswitch classes that sense essential metabolites.
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Affiliation(s)
- Ronald R. Breaker
- Corresponding Author: Ronald R. Breaker - Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520-8103, United States; Phone: 203-432-9389; , Twitter: @RonBreaker
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16
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Sherlock ME, Higgs G, Yu D, Widner DL, White NA, Sudarsan N, Sadeeshkumar H, Perkins KR, Mirihana Arachchilage G, Malkowski SN, King CG, Harris KA, Gaffield G, Atilho RM, Breaker RR. Architectures and complex functions of tandem riboswitches. RNA Biol 2022; 19:1059-1076. [PMID: 36093908 PMCID: PMC9481103 DOI: 10.1080/15476286.2022.2119017] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 08/23/2022] [Indexed: 11/16/2022] Open
Abstract
Riboswitch architectures that involve the binding of a single ligand to a single RNA aptamer domain result in ordinary dose-response curves that require approximately a 100-fold change in ligand concentration to cover nearly the full dynamic range for gene regulation. However, by using multiple riboswitches or aptamer domains in tandem, these ligand-sensing structures can produce additional, complex gene control outcomes. In the current study, we have computationally searched for tandem riboswitch architectures in bacteria to provide a more complete understanding of the diverse biological and biochemical functions of gene control elements that are made exclusively of RNA. Numerous different arrangements of tandem homologous riboswitch architectures are exploited by bacteria to create more 'digital' gene control devices, which operate over a narrower ligand concentration range. Also, two heterologous riboswitch aptamers are sometimes employed to create two-input Boolean logic gates with various types of genetic outputs. These findings illustrate the sophisticated genetic decisions that can be made by using molecular sensors and switches based only on RNA.
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Affiliation(s)
- Madeline E. Sherlock
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
- Department of Biochemistry and Molecular Genetics, University of Colorado, Anschutz Medical Campus, Research-1S, Aurora, CO, USA
| | - Gadareth Higgs
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Diane Yu
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Danielle L. Widner
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Neil A. White
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | | | - Harini Sadeeshkumar
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Kevin R. Perkins
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Gayan Mirihana Arachchilage
- Howard Hughes Medical Institute, Yale University, New Haven, CT, USA
- PTC Therapeutics, Inc, South Plainfield, NJ, USA
| | | | - Christopher G. King
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | | | - Glenn Gaffield
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Ruben M. Atilho
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Ronald R. Breaker
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
- Howard Hughes Medical Institute, Yale University, New Haven, CT, USA
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17
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Ariza-Mateos A, Nuthanakanti A, Serganov A. Riboswitch Mechanisms: New Tricks for an Old Dog. BIOCHEMISTRY (MOSCOW) 2021; 86:962-975. [PMID: 34488573 DOI: 10.1134/s0006297921080071] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Discovered almost twenty years ago, riboswitches turned out to be one of the most common regulatory systems in bacteria, with representatives found in eukaryotes and archaea. Unlike many other regulatory elements, riboswitches are entirely composed of RNA and capable of modulating expression of genes by direct binding of small cellular molecules. While bacterial riboswitches had been initially thought to control production of enzymes and transporters associated with small organic molecules via feedback regulatory circuits, later findings identified riboswitches directing expression of a wide range of genes and responding to various classes of molecules, including ions, signaling molecules, and others. The 5'-untranslated mRNA regions host a vast majority of riboswitches, which modulate transcription or translation of downstream genes through conformational rearrangements in the ligand-sensing domains and adjacent expression-controlling platforms. Over years, the repertoire of regulatory mechanisms employed by riboswitches has greatly expanded; most recent studies have highlighted the importance of alternative mechanisms, such as RNA degradation, for the riboswitch-mediated genetic circuits. This review discusses the plethora of bacterial riboswitch mechanisms and illustrates how riboswitches utilize different features and approaches to elicit various regulatory responses.
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Affiliation(s)
- Ascensión Ariza-Mateos
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Ashok Nuthanakanti
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Alexander Serganov
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA.
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18
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Wilson TJ, Lilley DMJ. The potential versatility of RNA catalysis. WILEY INTERDISCIPLINARY REVIEWS. RNA 2021; 12:e1651. [PMID: 33949113 DOI: 10.1002/wrna.1651] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/26/2021] [Accepted: 03/01/2021] [Indexed: 01/21/2023]
Abstract
It is commonly thought that in the early development of life on this planet RNA would have acted both as a store of genetic information and as a catalyst. While a number of RNA enzymes are known in contemporary cells, they are largely confined to phosphoryl transfer reactions, whereas an RNA based metabolism would have required a much greater chemical diversity of catalysis. Here we discuss how RNA might catalyze a wider variety of chemistries, and particularly how information gleaned from riboswitches could suggest how ribozymes might recruit coenzymes to expand their chemical range. We ask how we might seek such activities in modern biology. This article is categorized under: RNA-Based Catalysis > Miscellaneous RNA-Catalyzed Reactions Regulatory RNAs/RNAi/Riboswitches > Riboswitches RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry.
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Affiliation(s)
- Timothy J Wilson
- Cancer Research UK Nucleic Acid Structure Research Group, MSI/WTB Complex, The University of Dundee, Dundee, UK
| | - David M J Lilley
- Cancer Research UK Nucleic Acid Structure Research Group, MSI/WTB Complex, The University of Dundee, Dundee, UK
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19
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Xu X, Egger M, Chen H, Bartosik K, Micura R, Ren A. Insights into xanthine riboswitch structure and metal ion-mediated ligand recognition. Nucleic Acids Res 2021; 49:7139-7153. [PMID: 34125892 PMCID: PMC8266621 DOI: 10.1093/nar/gkab486] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 04/29/2021] [Accepted: 05/27/2021] [Indexed: 12/26/2022] Open
Abstract
Riboswitches are conserved functional domains in mRNA that mostly exist in bacteria. They regulate gene expression in response to varying concentrations of metabolites or metal ions. Recently, the NMT1 RNA motif has been identified to selectively bind xanthine and uric acid, respectively, both are involved in the metabolic pathway of purine degradation. Here, we report a crystal structure of this RNA bound to xanthine. Overall, the riboswitch exhibits a rod-like, continuously stacked fold composed of three stems and two internal junctions. The binding-pocket is determined by the highly conserved junctional sequence J1 between stem P1 and P2a, and engages a long-distance Watson-Crick base pair to junction J2. Xanthine inserts between a G-U pair from the major groove side and is sandwiched between base triples. Strikingly, a Mg2+ ion is inner-sphere coordinated to O6 of xanthine and a non-bridging oxygen of a backbone phosphate. Two further hydrated Mg2+ ions participate in extensive interactions between xanthine and the pocket. Our structure model is verified by ligand binding analysis to selected riboswitch mutants using isothermal titration calorimetry, and by fluorescence spectroscopic analysis of RNA folding using 2-aminopurine-modified variants. Together, our study highlights the principles of metal ion-mediated ligand recognition by the xanthine riboswitch.
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Affiliation(s)
- Xiaochen Xu
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Michaela Egger
- Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck 6020, Austria
| | - Hao Chen
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Karolina Bartosik
- Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck 6020, Austria
| | - Ronald Micura
- Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck 6020, Austria
| | - Aiming Ren
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
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20
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Brewer KI, Greenlee EB, Higgs G, Yu D, Mirihana Arachchilage G, Chen X, King N, White N, Breaker RR. Comprehensive discovery of novel structured noncoding RNAs in 26 bacterial genomes. RNA Biol 2021; 18:2417-2432. [PMID: 33970790 PMCID: PMC8632094 DOI: 10.1080/15476286.2021.1917891] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/30/2022] Open
Abstract
Comparative sequence analysis methods are highly effective for uncovering novel classes of structured noncoding RNAs (ncRNAs) from bacterial genomic DNA sequence datasets. Previously, we developed a computational pipeline to more comprehensively identify structured ncRNA representatives from individual bacterial genomes. This search process exploits the fact that genomic regions serving as templates for the transcription of structured RNAs tend to be present in longer than average noncoding 'intergenic regions' (IGRs) that are enriched in G and C nucleotides compared to the remainder of the genome. In the present study, we apply this computational pipeline to identify structured ncRNA candidates from 26 diverse bacterial species. Numerous novel structured ncRNA motifs were discovered, including several riboswitch candidates, one whose ligand has been identified and others that have yet to be experimentally validated. Our findings support recent predictions that hundreds of novel ribo-switch classes and other ncRNAs remain undiscovered among the limited number of bacterial species whose genomes have been completely sequenced.
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Affiliation(s)
- Kenneth I Brewer
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Etienne B Greenlee
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Gadareth Higgs
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Diane Yu
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | | | - Xi Chen
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Nicholas King
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
| | - Neil White
- Howard Hughes Medical Institute, Yale University, New Haven, CT, USA
| | - Ronald R Breaker
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.,Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.,Howard Hughes Medical Institute, Yale University, New Haven, CT, USA
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21
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Panchapakesan SSS, Corey L, Malkowski SN, Higgs G, Breaker RR. A second riboswitch class for the enzyme cofactor NAD . RNA (NEW YORK, N.Y.) 2021; 27:99-105. [PMID: 33087526 PMCID: PMC7749635 DOI: 10.1261/rna.077891.120] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 10/19/2020] [Indexed: 06/01/2023]
Abstract
A bacterial noncoding RNA motif almost exclusively associated with pnuC genes was uncovered using comparative sequence analysis. Some PnuC proteins are known to transport nicotinamide riboside (NR), which is a component of the ubiquitous and abundant enzyme cofactor nicotinamide adenine dinucleotide (NAD+). Thus, we speculated that the newly found "pnuC motif" RNAs might function as aptamers for a novel class of NAD+-sensing riboswitches. RNA constructs that encompass the conserved nucleotides and secondary structure features that define the motif indeed selectively bind NAD+, nicotinamide mononucleotide (NMN), and NR. Mutations that disrupt strictly conserved nucleotides of the aptamer also disrupt ligand binding. These bioinformatic and biochemical findings indicate that pnuC motif RNAs are likely members of a second riboswitch class that regulates gene expression in response to NAD+ binding.
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Affiliation(s)
- Shanker S S Panchapakesan
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
| | - Lukas Corey
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
| | - Sarah N Malkowski
- Department of Chemistry, Yale University, New Haven, Connecticut 06520-8103, USA
| | - Gadareth Higgs
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
| | - Ronald R Breaker
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520-8103, USA
- Howard Hughes Medical Institute, Yale University, New Haven, Connecticut 06520-8103, USA
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22
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Chen H, Egger M, Xu X, Flemmich L, Krasheninina O, Sun A, Micura R, Ren A. Structural distinctions between NAD+ riboswitch domains 1 and 2 determine differential folding and ligand binding. Nucleic Acids Res 2020; 48:12394-12406. [PMID: 33170270 PMCID: PMC7708056 DOI: 10.1093/nar/gkaa1029] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 10/12/2020] [Accepted: 10/16/2020] [Indexed: 11/13/2022] Open
Abstract
Riboswitches are important gene regulatory elements frequently encountered in bacterial mRNAs. The recently discovered nadA riboswitch contains two similar, tandemly arrayed aptamer domains, with the first domain possessing high affinity for nicotinamide adenine dinucleotide (NAD+). The second domain which comprises the ribosomal binding site in a putative regulatory helix, however, has withdrawn from detection of ligand-induced structural modulation thus far, and therefore, the identity of the cognate ligand and the regulation mechanism have remained unclear. Here, we report crystal structures of both riboswitch domains, each bound to NAD+. Furthermore, we demonstrate that ligand binding to domain 2 requires significantly higher concentrations of NAD+ (or ADP retaining analogs) compared to domain 1. Using a fluorescence spectroscopic approach, we further shed light on the structural features which are responsible for the different ligand affinities, and describe the Mg2+-dependent, distinct folding and pre-organization of their binding pockets. Finally, we speculate about possible scenarios for nadA RNA gene regulation as a putative two-concentration sensor module for a time-controlled signal that is primed and stalled by the gene regulation machinery at low ligand concentrations (domain 1), and finally triggers repression of translation as soon as high ligand concentrations are reached in the cell (domain 2).
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Affiliation(s)
- Hao Chen
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Michaela Egger
- Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck, 6020, Austria
| | - Xiaochen Xu
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Laurin Flemmich
- Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck, 6020, Austria
| | - Olga Krasheninina
- Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck, 6020, Austria
| | - Aiai Sun
- School of Chemistry and Materials Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, 1 Sub-lane Xiangshan, Hangzhou 310024, China
| | - Ronald Micura
- Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck, 6020, Austria
| | - Aiming Ren
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
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23
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Malkowski SN, Atilho RM, Greenlee EB, Weinberg CE, Breaker RR. A rare bacterial RNA motif is implicated in the regulation of the purF gene whose encoded enzyme synthesizes phosphoribosylamine. RNA (NEW YORK, N.Y.) 2020; 26:1838-1846. [PMID: 32843366 PMCID: PMC7668255 DOI: 10.1261/rna.077313.120] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 08/14/2020] [Indexed: 05/31/2023]
Abstract
The Fibro-purF motif is a putative structured noncoding RNA domain that was discovered previously in species of Fibrobacter by using comparative sequence analysis methods. An updated bioinformatics search yielded a total of only 30 unique-sequence representatives, exclusively found upstream of the purF gene that codes for the enzyme amidophosphoribosyltransferase. This enzyme synthesizes the compound 5-phospho-D-ribosylamine (PRA), which is the first committed step in purine biosynthesis. The consensus model for Fibro-purF motif RNAs includes a predicted three-stem junction that carries numerous conserved nucleotide positions within the regions joining the stems. This architecture appears to be of sufficient size and complexity for the formation of the ligand-binding aptamer portion of a riboswitch. In this study, we conducted biochemical analyses of a representative Fibro-purF motif RNA to confirm that the RNA generally folds according to the predicted consensus model. However, due to the instability of PRA, binding of this ligand candidate by the RNA could not be directly assessed. Genetic analyses were used to demonstrate that Fibro-purF motif RNAs regulate gene expression in accordance with predicted PRA concentrations. These findings indicate that Fibro-purF motif RNAs are genetic regulation elements that likely suppress PRA biosynthesis when sufficient levels of this purine precursor are present.
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Affiliation(s)
- Sarah N Malkowski
- Department of Chemistry, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
| | - Ruben M Atilho
- Department of Molecular Biophysics and Biochemistry, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
| | - Etienne B Greenlee
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
| | - Christina E Weinberg
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
| | - Ronald R Breaker
- Department of Molecular Biophysics and Biochemistry, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520-8103, USA
- Howard Hughes Medical Institute, Yale University, New Haven, Connecticut 06520-8103, USA
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24
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Micura R, Höbartner C. Fundamental studies of functional nucleic acids: aptamers, riboswitches, ribozymes and DNAzymes. Chem Soc Rev 2020; 49:7331-7353. [PMID: 32944725 DOI: 10.1039/d0cs00617c] [Citation(s) in RCA: 126] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
This review aims at juxtaposing common versus distinct structural and functional strategies that are applied by aptamers, riboswitches, and ribozymes/DNAzymes. Focusing on recently discovered systems, we begin our analysis with small-molecule binding aptamers, with emphasis on in vitro-selected fluorogenic RNA aptamers and their different modes of ligand binding and fluorescence activation. Fundamental insights are much needed to advance RNA imaging probes for detection of exo- and endogenous RNA and for RNA process tracking. Secondly, we discuss the latest gene expression-regulating mRNA riboswitches that respond to the alarmone ppGpp, to PRPP, to NAD+, to adenosine and cytidine diphosphates, and to precursors of thiamine biosynthesis (HMP-PP), and we outline new subclasses of SAM and tetrahydrofolate-binding RNA regulators. Many riboswitches bind protein enzyme cofactors that, in principle, can catalyse a chemical reaction. For RNA, however, only one system (glmS ribozyme) has been identified in Nature thus far that utilizes a small molecule - glucosamine-6-phosphate - to participate directly in reaction catalysis (phosphodiester cleavage). We wonder why that is the case and what is to be done to reveal such likely existing cellular activities that could be more diverse than currently imagined. Thirdly, this brings us to the four latest small nucleolytic ribozymes termed twister, twister-sister, pistol, and hatchet as well as to in vitro selected DNA and RNA enzymes that promote new chemistry, mainly by exploiting their ability for RNA labelling and nucleoside modification recognition. Enormous progress in understanding the strategies of nucleic acids catalysts has been made by providing thorough structural fundaments (e.g. first structure of a DNAzyme, structures of ribozyme transition state mimics) in combination with functional assays and atomic mutagenesis.
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Affiliation(s)
- Ronald Micura
- Institute of Organic Chemistry and Center for Molecular Biosciences Innsbruck CMBI, Leopold-Franzens University Innsbruck, Innsbruck, Austria.
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25
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Abstract
Biocatalysis is dominated by protein enzymes, and only a few classes of ribozymes are known to contribute to the task of promoting biochemical transformations. The RNA World theory encompasses the notion that earlier forms of life made use of a much greater diversity of ribozymes and other functional RNAs to guide complex metabolic states long before proteins had emerged in evolution. In recent years, the discoveries of various classes of ribozymes, riboswitches, and other noncoding RNAs in bacteria have provided additional support for the hypothesis that RNA molecules indeed have the catalytic competence to promote diverse chemical reactions without the aid of protein enzymes. Herein, some of the most striking observations made from examinations of natural riboswitches that bind small ligands are highlighted and used as a basis to imagine the characteristics and functions of long-extinct ribozymes from the RNA World.
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Affiliation(s)
- Ronald R Breaker
- Department of Molecular, Cellular and Developmental Biology, Department of Molecular Biophysics and Biochemistry, Howard Hughes Medical Institute, Department of Chemistry, Yale University, 260 Whitney Avenue, New Haven, Connecticut 06520, United States
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26
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Huang L, Liao TW, Wang J, Ha T, Lilley DMJ. Crystal structure and ligand-induced folding of the SAM/SAH riboswitch. Nucleic Acids Res 2020; 48:7545-7556. [PMID: 32520325 PMCID: PMC7367207 DOI: 10.1093/nar/gkaa493] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 05/25/2020] [Accepted: 05/30/2020] [Indexed: 01/09/2023] Open
Abstract
While most SAM riboswitches strongly discriminate between SAM and SAH, the SAM/SAH riboswitch responds to both ligands with similar apparent affinities. We have determined crystal structures of the SAM/SAH riboswitch bound to SAH, SAM and other variant ligands at high resolution. The riboswitch forms an H-type pseudoknot structure with coaxial alignment of the stem–loop helix (P1) and the pseudoknot helix (PK). An additional three base pairs form at the non-open end of P1, and the ligand is bound at the interface between the P1 extension and the PK helix. The adenine nucleobase is stacked into the helix and forms a trans Hoogsteen–Watson–Crick base pair with a uridine, thus becoming an integral part of the helical structure. The majority of the specific interactions are formed with the adenosine. The methionine or homocysteine chain lies in the groove making a single hydrogen bond, and there is no discrimination between the sulfonium of SAM or the thioether of SAH. Single-molecule FRET analysis reveals that the riboswitch exists in two distinct conformations, and that addition of SAM or SAH shifts the population into a stable state that likely corresponds to the form observed in the crystal. A model for translational regulation is presented whereby in the absence of ligand the riboswitch is largely unfolded, lacking the PK helix so that translation can be initiated at the ribosome binding site. But the presence of ligand stabilizes the folded conformation that includes the PK helix, so occluding the ribosome binding site and thus preventing the initiation of translation.
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Affiliation(s)
- Lin Huang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, P. R. China.,RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, P. R. China.,Cancer Research UK Nucleic Acid Structure Research Group, MSI/WTB Complex, The University of Dundee, Dow Street, Dundee DD1 5EH, UK
| | | | - Jia Wang
- Cancer Research UK Nucleic Acid Structure Research Group, MSI/WTB Complex, The University of Dundee, Dow Street, Dundee DD1 5EH, UK
| | - Taekjip Ha
- Department of Biophysics.,Department of Biophysics and Biophysical Chemistry.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA.,Howard Hughes Medical Institute, Baltimore, MD, USA
| | - David M J Lilley
- Cancer Research UK Nucleic Acid Structure Research Group, MSI/WTB Complex, The University of Dundee, Dow Street, Dundee DD1 5EH, UK
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