1
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Gribling-Burrer AS, Bohn P, Smyth RP. Isoform-specific RNA structure determination using Nano-DMS-MaP. Nat Protoc 2024; 19:1835-1865. [PMID: 38347203 DOI: 10.1038/s41596-024-00959-3] [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: 08/01/2023] [Accepted: 12/12/2023] [Indexed: 06/12/2024]
Abstract
RNA structure determination is essential to understand how RNA carries out its diverse biological functions. In cells, RNA isoforms are readily expressed with partial variations within their sequences due, for example, to alternative splicing, heterogeneity in the transcription start site, RNA processing or differential termination/polyadenylation. Nanopore dimethyl sulfate mutational profiling (Nano-DMS-MaP) is a method for in situ isoform-specific RNA structure determination. Unlike similar methods that rely on short sequencing reads, Nano-DMS-MaP employs nanopore sequencing to resolve the structures of long and highly similar RNA molecules to reveal their previously hidden structural differences. This Protocol describes the development and applications of Nano-DMS-MaP and outlines the main considerations for designing and implementing a successful experiment: from bench to data analysis. In cell probing experiments can be carried out by an experienced molecular biologist in 3-4 d. Data analysis requires good knowledge of command line tools and Python scripts and requires a further 3-5 d.
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Affiliation(s)
- Anne-Sophie Gribling-Burrer
- Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany.
| | - Patrick Bohn
- Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany.
| | - Redmond P Smyth
- Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany.
- Faculty of Medicine, University of Würzburg, Würzburg, Germany.
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2
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Rinaldi S, Moroni E, Rozza R, Magistrato A. Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation. J Chem Theory Comput 2024; 20:993-1018. [PMID: 38287883 DOI: 10.1021/acs.jctc.3c01239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.
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Affiliation(s)
- Silvia Rinaldi
- National Research Council of Italy (CNR) - Institute of Chemistry of OrganoMetallic Compounds (ICCOM), c/o Area di Ricerca CNR di Firenze Via Madonna del Piano 10, 50019 Sesto Fiorentino, Florence, Italy
| | - Elisabetta Moroni
- National Research Council of Italy (CNR) - Institute of Chemical Sciences and Technologies (SCITEC), via Mario Bianco 9, 20131 Milano, Italy
| | - Riccardo Rozza
- National Research Council of Italy (CNR) - Institute of Material Foundry (IOM) c/o International School for Advanced Studies (SISSA), Via Bonomea, 265, 34136 Trieste, Italy
| | - Alessandra Magistrato
- National Research Council of Italy (CNR) - Institute of Material Foundry (IOM) c/o International School for Advanced Studies (SISSA), Via Bonomea, 265, 34136 Trieste, Italy
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3
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Lee WH, Li K, Lu Z. Chemical crosslinking and ligation methods for in vivo analysis of RNA structures and interactions. Methods Enzymol 2023; 691:253-281. [PMID: 37914449 PMCID: PMC10994722 DOI: 10.1016/bs.mie.2023.02.020] [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] [Indexed: 03/14/2023]
Abstract
RNA structures and interactions in living cells drive a variety of biological processes and play critical roles in physiology and disease states. However, studies of RNA structures and interactions have been challenging due to limitations in available technologies. Direct determination of structures in vitro has been only possible to a small number of RNAs with limited sizes and conformations. We recently introduced two chemical crosslink-ligation techniques that enabled studies of transcriptome-wide secondary and tertiary structures and their dynamics. In a dramatically improved version of the psoralen analysis of RNA interactions and structures (PARIS2) method, we detailed the synthesis and use of amotosalen, a highly soluble psoralen analogue, and enhanced enzymology for higher efficiency duplex capture. We also introduced spatial 2'-hydroxyl acylation reversible crosslinking (SHARC) with exonuclease (exo) trimming, a method which utilizes a novel crosslinker class that targets the 2'-OH to capture three-dimensional (3D) structures. Both are powerful orthogonal approaches for solving in vivo RNA structure and interactions, integrating crosslinking, exo trimming, proximity ligation, and high throughput sequencing. In this chapter, we present a detailed protocol for the methods and highlight steps that outperform existing crosslink-ligation approaches.
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Affiliation(s)
- Wilson H Lee
- Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences
| | - Kongpan Li
- Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences
| | - Zhipeng Lu
- Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, United States.
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4
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Steinmetzger C, Höbartner C. Probing of Fluorogenic RNA Aptamers via Supramolecular Förster Resonance Energy Transfer with a Universal Fluorescent Nucleobase Analog. Methods Mol Biol 2023; 2570:155-173. [PMID: 36156781 DOI: 10.1007/978-1-0716-2695-5_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Fluorogenic RNA aptamers are synthetic RNAs that have been evolved by in vitro selection methods to bind and light up conditionally fluorescent organic ligands. Compared with other probes for RNA detection, they are less invasive than hybridization-based methods (FISH, molecular beacons) and are considerably smaller than fluorescent protein-recruiting systems (MS2, Pumilio variants). Fluorogenic aptamers have therefore found widespread use as genetically encodable tags for RNA detection in live cells and have also been used in combination with riboswitches to construct versatile metabolite sensors for in vitro use. Their success builds on a fundamental understanding of their three-dimensional structure to explain the mechanisms of ligand interaction and to rationally design functional aptamer devices. In this protocol, we describe a supramolecular FRET-based structure probing method for fluorogenic aptamers that exploits distance- and orientation-dependent energy transfer efficiencies between site-specifically incorporated fluorescent nucleoside analogs and non-covalently bound ligands, exemplified by 4-cyanoindol riboside (4CI) and the DMHBI+-binding RNA aptamer Chili. This method yields structural restraints that bridge the gap between traditional low-resolution secondary structure probing methods and more elaborate high-resolution methods such as X-ray crystallography and NMR spectroscopy.
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Affiliation(s)
- Christian Steinmetzger
- Institute of Organic Chemistry, Julius Maximilians University Würzburg, Würzburg, Germany
| | - Claudia Höbartner
- Institute of Organic Chemistry, Julius Maximilians University Würzburg, Würzburg, Germany. .,Center for Nanosystems Chemistry (CNC), Julius Maximilians University Würzburg, Würzburg, Germany.
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5
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RNA secondary structure packages evaluated and improved by high-throughput experiments. Nat Methods 2022; 19:1234-1242. [PMID: 36192461 PMCID: PMC9839360 DOI: 10.1038/s41592-022-01605-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 08/10/2022] [Indexed: 01/17/2023]
Abstract
Despite the popularity of computer-aided study and design of RNA molecules, little is known about the accuracy of commonly used structure modeling packages in tasks sensitive to ensemble properties of RNA. Here, we demonstrate that the EternaBench dataset, a set of more than 20,000 synthetic RNA constructs designed on the RNA design platform Eterna, provides incisive discriminative power in evaluating current packages in ensemble-oriented structure prediction tasks. We find that CONTRAfold and RNAsoft, packages with parameters derived through statistical learning, achieve consistently higher accuracy than more widely used packages in their standard settings, which derive parameters primarily from thermodynamic experiments. We hypothesized that training a multitask model with the varied data types in EternaBench might improve inference on ensemble-based prediction tasks. Indeed, the resulting model, named EternaFold, demonstrated improved performance that generalizes to diverse external datasets including complete messenger RNAs, viral genomes probed in human cells and synthetic designs modeling mRNA vaccines.
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6
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Li Q, Gloudemans MJ, Geisinger JM, Fan B, Aguet F, Sun T, Ramaswami G, Li YI, Ma JB, Pritchard JK, Montgomery SB, Li JB. RNA editing underlies genetic risk of common inflammatory diseases. Nature 2022; 608:569-577. [PMID: 35922514 PMCID: PMC9790998 DOI: 10.1038/s41586-022-05052-x] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 06/29/2022] [Indexed: 12/12/2022]
Abstract
A major challenge in human genetics is to identify the molecular mechanisms of trait-associated and disease-associated variants. To achieve this, quantitative trait locus (QTL) mapping of genetic variants with intermediate molecular phenotypes such as gene expression and splicing have been widely adopted1,2. However, despite successes, the molecular basis for a considerable fraction of trait-associated and disease-associated variants remains unclear3,4. Here we show that ADAR-mediated adenosine-to-inosine RNA editing, a post-transcriptional event vital for suppressing cellular double-stranded RNA (dsRNA)-mediated innate immune interferon responses5-11, is an important potential mechanism underlying genetic variants associated with common inflammatory diseases. We identified and characterized 30,319 cis-RNA editing QTLs (edQTLs) across 49 human tissues. These edQTLs were significantly enriched in genome-wide association study signals for autoimmune and immune-mediated diseases. Colocalization analysis of edQTLs with disease risk loci further pinpointed key, putatively immunogenic dsRNAs formed by expected inverted repeat Alu elements as well as unexpected, highly over-represented cis-natural antisense transcripts. Furthermore, inflammatory disease risk variants, in aggregate, were associated with reduced editing of nearby dsRNAs and induced interferon responses in inflammatory diseases. This unique directional effect agrees with the established mechanism that lack of RNA editing by ADAR1 leads to the specific activation of the dsRNA sensor MDA5 and subsequent interferon responses and inflammation7-9. Our findings implicate cellular dsRNA editing and sensing as a previously underappreciated mechanism of common inflammatory diseases.
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Affiliation(s)
- Qin Li
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Michael J. Gloudemans
- Department of Pathology, Stanford University, Stanford, CA, USA.,Biomedical Informatics Training Program, Stanford University, Stanford, CA, USA
| | | | - Boming Fan
- State Key Laboratory of Genetic Engineering, Department of Biochemistry and Biophysics, School of Life Sciences, Fudan University, Shanghai, China
| | | | - Tao Sun
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Gokul Ramaswami
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Yang I. Li
- Department of Genetics, Stanford University, Stanford, CA, USA.,Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Jin-Biao Ma
- State Key Laboratory of Genetic Engineering, Department of Biochemistry and Biophysics, School of Life Sciences, Fudan University, Shanghai, China
| | - Jonathan K. Pritchard
- Department of Genetics, Stanford University, Stanford, CA, USA.,Department of Biology, Stanford University, Stanford, CA, USA
| | - Stephen B. Montgomery
- Department of Genetics, Stanford University, Stanford, CA, USA.,Department of Pathology, Stanford University, Stanford, CA, USA.,These authors contributed equally: Stephen B. Montgomery, Jin Billy Li
| | - Jin Billy Li
- Department of Genetics, Stanford University, Stanford, CA, USA.
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7
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Abstract
Recent events have pushed RNA research into the spotlight. Continued discoveries of RNA with unexpected diverse functions in healthy and diseased cells, such as the role of RNA as both the source and countermeasure to a severe acute respiratory syndrome coronavirus 2 infection, are igniting a new passion for understanding this functionally and structurally versatile molecule. Although RNA structure is key to function, many foundational characteristics of RNA structure are misunderstood, and the default state of RNA is often thought of and depicted as a single floppy strand. The purpose of this perspective is to help adjust mental models, equipping the community to better use the fundamental aspects of RNA structural information in new mechanistic models, enhance experimental design to test these models, and refine data interpretation. We discuss six core observations focused on the inherent nature of RNA structure and how to incorporate these characteristics to better understand RNA structure. We also offer some ideas for future efforts to make validated RNA structural information available and readily used by all researchers.
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Affiliation(s)
- Quentin Vicens
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, School of Medicine, Aurora, CO 80045
- RNA BioScience Initiative, University of Colorado Denver School of Medicine, Aurora, CO 80045
| | - Jeffrey S. Kieft
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, School of Medicine, Aurora, CO 80045
- RNA BioScience Initiative, University of Colorado Denver School of Medicine, Aurora, CO 80045
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8
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Chemical reversible crosslinking enables measurement of RNA 3D distances and alternative conformations in cells. Nat Commun 2022; 13:911. [PMID: 35177610 PMCID: PMC8854666 DOI: 10.1038/s41467-022-28602-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 01/19/2022] [Indexed: 02/06/2023] Open
Abstract
Three-dimensional (3D) structures dictate the functions of RNA molecules in a wide variety of biological processes. However, direct determination of RNA 3D structures in vivo is difficult due to their large sizes, conformational heterogeneity, and dynamics. Here we present a method, Spatial 2′-Hydroxyl Acylation Reversible Crosslinking (SHARC), which uses chemical crosslinkers of defined lengths to measure distances between nucleotides in cellular RNA. Integrating crosslinking, exonuclease (exo) trimming, proximity ligation, and high throughput sequencing, SHARC enables transcriptome-wide tertiary structure contact maps at high accuracy and precision, revealing heterogeneous RNA structures and interactions. SHARC data provide constraints that improves Rosetta-based RNA 3D structure modeling at near-nanometer resolution. Integrating SHARC-exo with other crosslinking-based methods, we discover compact folding of the 7SK RNA, a critical regulator of transcriptional elongation. These results establish a strategy for measuring RNA 3D distances and alternative conformations in their native cellular context. Determination of RNA 3D structures in vivo is a challenging problem. Here, the authors describe a chemical crosslinking method (SHARC) that they use in combination with RNA sequencing to measure distances between nucleotides in RNA 3D structures.
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9
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Ye L, Gribling-Burrer AS, Bohn P, Kibe A, Börtlein C, Ambi UB, Ahmad S, Olguin-Nava M, Smith M, Caliskan N, von Kleist M, Smyth RP. Short- and long-range interactions in the HIV-1 5' UTR regulate genome dimerization and packaging. Nat Struct Mol Biol 2022; 29:306-319. [PMID: 35347312 PMCID: PMC9010304 DOI: 10.1038/s41594-022-00746-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 02/14/2022] [Indexed: 11/09/2022]
Abstract
RNA dimerization is the noncovalent association of two human immunodeficiency virus-1 (HIV-1) genomes. It is a conserved step in the HIV-1 life cycle and assumed to be a prerequisite for binding to the viral structural protein Pr55Gag during genome packaging. Here, we developed functional analysis of RNA structure-sequencing (FARS-seq) to comprehensively identify sequences and structures within the HIV-1 5' untranslated region (UTR) that regulate this critical step. Using FARS-seq, we found nucleotides important for dimerization throughout the HIV-1 5' UTR and identified distinct structural conformations in monomeric and dimeric RNA. In the dimeric RNA, key functional domains, such as stem-loop 1 (SL1), polyadenylation signal (polyA) and primer binding site (PBS), folded into independent structural motifs. In the monomeric RNA, SL1 was reconfigured into long- and short-range base pairings with polyA and PBS, respectively. We show that these interactions disrupt genome packaging, and additionally show that the PBS-SL1 interaction unexpectedly couples the PBS with dimerization and Pr55Gag binding. Altogether, our data provide insights into late stages of HIV-1 life cycle and a mechanistic explanation for the link between RNA dimerization and packaging.
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Affiliation(s)
- Liqing Ye
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany
| | - Anne-Sophie Gribling-Burrer
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany
| | - Patrick Bohn
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany
| | - Anuja Kibe
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany
| | - Charlene Börtlein
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany
| | - Uddhav B. Ambi
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany
| | - Shazeb Ahmad
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany
| | - Marco Olguin-Nava
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany
| | - Maureen Smith
- grid.13652.330000 0001 0940 3744P5 Systems Medicine of Infectious Disease, Robert Koch-Institute, Berlin, Germany
| | - Neva Caliskan
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany ,grid.8379.50000 0001 1958 8658Faculty of Medicine, University of Würzburg, Würzburg, Germany
| | - Max von Kleist
- grid.13652.330000 0001 0940 3744P5 Systems Medicine of Infectious Disease, Robert Koch-Institute, Berlin, Germany
| | - Redmond P. Smyth
- grid.498164.6Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany ,grid.8379.50000 0001 1958 8658Faculty of Medicine, University of Würzburg, Würzburg, Germany
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10
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Identifying proximal RNA interactions from cDNA-encoded crosslinks with ShapeJumper. PLoS Comput Biol 2021; 17:e1009632. [PMID: 34905538 PMCID: PMC8670686 DOI: 10.1371/journal.pcbi.1009632] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 11/11/2021] [Indexed: 01/07/2023] Open
Abstract
SHAPE-JuMP is a concise strategy for identifying close-in-space interactions in RNA molecules. Nucleotides in close three-dimensional proximity are crosslinked with a bi-reactive reagent that covalently links the 2'-hydroxyl groups of the ribose moieties. The identities of crosslinked nucleotides are determined using an engineered reverse transcriptase that jumps across crosslinked sites, resulting in a deletion in the cDNA that is detected using massively parallel sequencing. Here we introduce ShapeJumper, a bioinformatics pipeline to process SHAPE-JuMP sequencing data and to accurately identify through-space interactions, as observed in complex JuMP datasets. ShapeJumper identifies proximal interactions with near-nucleotide resolution using an alignment strategy that is optimized to tolerate the unique non-templated reverse-transcription profile of the engineered crosslink-traversing reverse-transcriptase. JuMP-inspired strategies are now poised to replace adapter-ligation for detecting RNA-RNA interactions in most crosslinking experiments.
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11
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Manigrasso J, Marcia M, De Vivo M. Computer-aided design of RNA-targeted small molecules: A growing need in drug discovery. Chem 2021. [DOI: 10.1016/j.chempr.2021.05.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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12
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Developing an Updated Strategy for Estimating the Free-Energy Parameters in RNA Duplexes. Int J Mol Sci 2021; 22:ijms22189708. [PMID: 34575896 PMCID: PMC8467000 DOI: 10.3390/ijms22189708] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/01/2021] [Accepted: 09/02/2021] [Indexed: 12/12/2022] Open
Abstract
For the last 20 years, it has been common lore that the free energy of RNA duplexes formed from canonical Watson-Crick base pairs (bps) can be largely approximated with dinucleotide bp parameters and a few simple corrective constants that are duplex independent. Additionally, the standard benchmark set of duplexes used to generate the parameters were GC-rich in the shorter duplexes and AU-rich in the longer duplexes, and the length of the majority of the duplexes ranged between 6 and 8 bps. We were curious if other models would generate similar results and whether adding longer duplexes of 17 bps would affect the conclusions. We developed a gradient-descent fitting program for obtaining free-energy parameters-the changes in Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS), and the melting temperature (Tm)-directly from the experimental melting curves. Using gradient descent and a genetic algorithm, the duplex melting results were combined with the standard benchmark data to obtain bp parameters. Both the standard (Turner) model and a new model that includes length-dependent terms were tested. Both models could fit the standard benchmark data; however, the new model could handle longer sequences better. We developed an updated strategy for fitting the duplex melting data.
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13
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Zhao Q, Zhao Z, Fan X, Yuan Z, Mao Q, Yao Y. Review of machine learning methods for RNA secondary structure prediction. PLoS Comput Biol 2021; 17:e1009291. [PMID: 34437528 PMCID: PMC8389396 DOI: 10.1371/journal.pcbi.1009291] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Secondary structure plays an important role in determining the function of noncoding RNAs. Hence, identifying RNA secondary structures is of great value to research. Computational prediction is a mainstream approach for predicting RNA secondary structure. Unfortunately, even though new methods have been proposed over the past 40 years, the performance of computational prediction methods has stagnated in the last decade. Recently, with the increasing availability of RNA structure data, new methods based on machine learning (ML) technologies, especially deep learning, have alleviated the issue. In this review, we provide a comprehensive overview of RNA secondary structure prediction methods based on ML technologies and a tabularized summary of the most important methods in this field. The current pending challenges in the field of RNA secondary structure prediction and future trends are also discussed.
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Affiliation(s)
- Qi Zhao
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning, China
| | - Zheng Zhao
- School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, China
| | - Xiaoya Fan
- School of Software, Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, Liaoning, China
| | - Zhengwei Yuan
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Qian Mao
- College of Light Industry, Liaoning University, Shenyang, Liaoning, China
- Key Laboratory of Agroproducts Processing Technology, Changchun University, Changchun, Jilin, China
| | - Yudong Yao
- Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, New Jersey, United States of America
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14
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Ganser LR, Chu CC, Bogerd HP, Kelly ML, Cullen BR, Al-Hashimi HM. Probing RNA Conformational Equilibria within the Functional Cellular Context. Cell Rep 2021; 30:2472-2480.e4. [PMID: 32101729 DOI: 10.1016/j.celrep.2020.02.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 12/24/2019] [Accepted: 01/31/2020] [Indexed: 12/17/2022] Open
Abstract
Low-abundance short-lived non-native conformations referred to as excited states (ESs) are increasingly observed in vitro and implicated in the folding and biological activities of regulatory RNAs. We developed an approach for assessing the relative abundance of RNA ESs within the functional cellular context. Nuclear magnetic resonance (NMR) spectroscopy was used to estimate the degree to which substitution mutations bias conformational equilibria toward the inactive ES in vitro. The cellular activity of the ES-stabilizing mutants was used as an indirect measure of the conformational equilibria within the functional cellular context. Compensatory mutations that restore the ground-state conformation were used to control for changes in sequence. Using this approach, we show that the ESs of two regulatory RNAs from HIV-1, the transactivation response element (TAR) and the Rev response element (RRE), likely form in cells with abundances comparable to those measured in vitro, and their targeted stabilization may provide an avenue for developing anti-HIV therapeutics.
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Affiliation(s)
- Laura R Ganser
- Department of Biochemistry, Duke University Medical Center, Durham, NC 27710, USA
| | - Chia-Chieh Chu
- Department of Biochemistry, Duke University Medical Center, Durham, NC 27710, USA
| | - Hal P Bogerd
- Department of Molecular Genetics and Microbiology, Center for Virology, Duke University Medical Center, Durham, NC 27710, USA
| | - Megan L Kelly
- Department of Biochemistry, Duke University Medical Center, Durham, NC 27710, USA
| | - Bryan R Cullen
- Department of Molecular Genetics and Microbiology, Center for Virology, Duke University Medical Center, Durham, NC 27710, USA.
| | - Hashim M Al-Hashimi
- Department of Biochemistry, Duke University Medical Center, Durham, NC 27710, USA.
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15
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Ehrhardt JE, Weeks KM. Time-Resolved, Single-Molecule, Correlated Chemical Probing of RNA. J Am Chem Soc 2020; 142:18735-18740. [PMID: 33095984 DOI: 10.1021/jacs.0c06221] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Capturing the folding dynamics of large, functionally important RNAs has relied primarily on global measurements of structure or on per-nucleotide chemical probing. These approaches infer, but do not directly measure, through-space structural interactions. Here we introduce trimethyloxonium (TMO) as a chemical probe for RNA. TMO alkylates RNA at high levels in seconds, and thereby enables time-resolved, single-molecule, through-space probing of RNA folding using the RING-MaP correlated chemical probing framework. Time-resolved correlations in the RNase P RNA-a functional RNA with a complex structure stabilized by multiple noncanonical interactions-revealed that a long-range tertiary interaction guides native RNA folding for both secondary and tertiary structure. This unanticipated nonhierarchical folding mechanism was directly validated by examining the consequences of concise disruption of the through-space interaction. Single-molecule, time-resolved RNA structure probing with TMO is poised to reveal a wide range of dynamic RNA folding processes and principles of RNA folding.
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Affiliation(s)
- Jeffrey E Ehrhardt
- Department of Chemistry, University of North Carolina, Chapel Hill, North Carolina 27599-3290, United States
| | - Kevin M Weeks
- Department of Chemistry, University of North Carolina, Chapel Hill, North Carolina 27599-3290, United States
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16
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Alaidi O, Aboul‐ela F. Statistical mechanical prediction of ligand perturbation to RNA secondary structure and application to riboswitches. J Comput Chem 2020; 41:1521-1537. [DOI: 10.1002/jcc.26195] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 01/03/2020] [Accepted: 03/09/2020] [Indexed: 02/04/2023]
Affiliation(s)
- Osama Alaidi
- Biocomplexity for Research and Consulting Cairo Egypt
| | - Fareed Aboul‐ela
- Center for X‐Ray Determination of the Structure of MatterZewail City of Science and Technology Giza Egypt
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17
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Zhang Z, Xiong P, Zhang T, Wang J, Zhan J, Zhou Y. Accurate inference of the full base-pairing structure of RNA by deep mutational scanning and covariation-induced deviation of activity. Nucleic Acids Res 2020; 48:1451-1465. [PMID: 31872260 PMCID: PMC7026644 DOI: 10.1093/nar/gkz1192] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 12/10/2019] [Accepted: 12/11/2019] [Indexed: 11/12/2022] Open
Abstract
Despite the large number of noncoding RNAs in human genome and their roles in many diseases include cancer, we know very little about them due to lack of structural clues. The centerpiece of the structural clues is the full RNA base-pairing structure of secondary and tertiary contacts that can be precisely obtained only from costly and time-consuming 3D structure determination. Here, we performed deep mutational scanning of self-cleaving CPEB3 ribozyme by error-prone PCR and showed that a library of <5 × 104 single-to-triple mutants is sufficient to infer 25 of 26 base pairs including non-nested, nonhelical, and noncanonical base pairs with both sensitivity and precision at 96%. Such accurate inference was further confirmed by a twister ribozyme at 100% precision with only noncanonical base pairs as false negatives. The performance was resulted from analyzing covariation-induced deviation of activity by utilizing both functional and nonfunctional variants for unsupervised classification, followed by Monte Carlo (MC) simulated annealing with mutation-derived scores. Highly accurate inference can also be obtained by combining MC with evolution/direct coupling analysis, R-scape or epistasis analysis. The results highlight the usefulness of deep mutational scanning for high-accuracy structural inference of self-cleaving ribozymes with implications for other structured RNAs that permit high-throughput functional selections.
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Affiliation(s)
- Zhe Zhang
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, P. R. China
- University of Chinese Academy of Sciences, Beijing 101408, P. R. China
- Institute for Glycomics, Griffith University, Parklands Drive, Southport, QLD 4222, Australia
| | - Peng Xiong
- Institute for Glycomics, Griffith University, Parklands Drive, Southport, QLD 4222, Australia
| | - Tongchuan Zhang
- Institute for Glycomics, Griffith University, Parklands Drive, Southport, QLD 4222, Australia
| | - Junfeng Wang
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, P. R. China
- Institute of Physical Science and Information Technology, Anhui University, Hefei 230031, Anhui, P. R. China
| | - Jian Zhan
- Institute for Glycomics, Griffith University, Parklands Drive, Southport, QLD 4222, Australia
| | - Yaoqi Zhou
- Institute for Glycomics, Griffith University, Parklands Drive, Southport, QLD 4222, Australia
- School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, QLD 4222, Australia
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18
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Singh J, Hanson J, Paliwal K, Zhou Y. RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning. Nat Commun 2019; 10:5407. [PMID: 31776342 PMCID: PMC6881452 DOI: 10.1038/s41467-019-13395-9] [Citation(s) in RCA: 148] [Impact Index Per Article: 29.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 11/01/2019] [Indexed: 01/03/2023] Open
Abstract
The majority of our human genome transcribes into noncoding RNAs with unknown structures and functions. Obtaining functional clues for noncoding RNAs requires accurate base-pairing or secondary-structure prediction. However, the performance of such predictions by current folding-based algorithms has been stagnated for more than a decade. Here, we propose the use of deep contextual learning for base-pair prediction including those noncanonical and non-nested (pseudoknot) base pairs stabilized by tertiary interactions. Since only [Formula: see text]250 nonredundant, high-resolution RNA structures are available for model training, we utilize transfer learning from a model initially trained with a recent high-quality bpRNA dataset of [Formula: see text]10,000 nonredundant RNAs made available through comparative analysis. The resulting method achieves large, statistically significant improvement in predicting all base pairs, noncanonical and non-nested base pairs in particular. The proposed method (SPOT-RNA), with a freely available server and standalone software, should be useful for improving RNA structure modeling, sequence alignment, and functional annotations.
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Affiliation(s)
- Jaswinder Singh
- Signal Processing Laboratory, School of Engineering and Built Environment, Griffith University, Brisbane, QLD, 4111, Australia
| | - Jack Hanson
- Signal Processing Laboratory, School of Engineering and Built Environment, Griffith University, Brisbane, QLD, 4111, Australia
| | - Kuldip Paliwal
- Signal Processing Laboratory, School of Engineering and Built Environment, Griffith University, Brisbane, QLD, 4111, Australia.
| | - Yaoqi Zhou
- Institute for Glycomics and School of Information and Communication Technology, Griffith University, Parklands Dr., Southport, QLD, 4222, Australia.
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19
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Wang F, Sun LZ, Sun T, Chang S, Xu X. Helix-Based RNA Landscape Partition and Alternative Secondary Structure Determination. ACS OMEGA 2019; 4:15407-15413. [PMID: 31572840 PMCID: PMC6761681 DOI: 10.1021/acsomega.9b01430] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 09/03/2019] [Indexed: 06/10/2023]
Abstract
RNA is a versatile macromolecule with the ability to fold into and interconvert between multiple functional conformations. The elucidation of the RNA folding landscape, especially the knowledge of alternative structures, is critical to uncover the physical mechanism of RNA functions. Here, we introduce a helix-based strategy for RNA folding landscape partition and alternative secondary structure determination. The benchmark test of 27 RNAs involving alternative stable structures shows that the model has the ability to divide the whole landscape into distinct partitions at the secondary structure level and predict the representative structures for each partition. Furthermore, the predicted structures and equilibrium populations of metastable conformations for the 2'dG-sensing riboswitch reveal the allosteric conformational switch on transcript length, which is consistent with the experimental study, indicating the importance of metastable states for RNA-based gene regulation. The model delivers a starting point for the landscape-based strategy toward the RNA folding mechanism and functions.
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Affiliation(s)
- Fengfei Wang
- Institute
of Bioinformatics and Medical Engineering, School of Mathematics and
Physics, Jiangsu University of Technology, Changzhou, Jiangsu 213001, China
| | - Li-Zhen Sun
- Department
of Applied Physics, Zhejiang University
of Technology, Hangzhou, Zhejiang 310023, China
| | - Tingting Sun
- Department
of Physics, Zhejiang University of Science
and Technology, Hangzhou, Zhejiang 310023, China
| | - Shan Chang
- Institute
of Bioinformatics and Medical Engineering, School of Mathematics and
Physics, Jiangsu University of Technology, Changzhou, Jiangsu 213001, China
| | - Xiaojun Xu
- Institute
of Bioinformatics and Medical Engineering, School of Mathematics and
Physics, Jiangsu University of Technology, Changzhou, Jiangsu 213001, China
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20
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Yesselman JD, Tian S, Liu X, Shi L, Li JB, Das R. Updates to the RNA mapping database (RMDB), version 2. Nucleic Acids Res 2019; 46:D375-D379. [PMID: 30053264 PMCID: PMC5753257 DOI: 10.1093/nar/gkx873] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2017] [Accepted: 09/19/2017] [Indexed: 12/20/2022] Open
Abstract
Chemical mapping is a broadly utilized technique for probing the structure and function of RNAs. The volume of chemical mapping data continues to grow as more researchers routinely employ this information and as experimental methods increase in throughput and information content. To create a central location for these data, we established an RNA mapping database (RMDB) 5 years ago. The RMDB, which is available at http://rmdb.stanford.edu, now contains chemical mapping data for over 800 entries, involving 134 000 natural and engineered RNAs, in vitro and in cellulo. The entries include large data sets from multidimensional techniques that focus on RNA tertiary structure and co-transcriptional folding, resulting in over 15 million residues probed. The database interface has been redesigned and now offers interactive graphical browsing of structural, thermodynamic and kinetic data at single-nucleotide resolution. The front-end interface now uses the force-directed RNA applet for secondary structure visualization and other JavaScript-based views of bar graphs and annotations. A new interface also streamlines the process for depositing new chemical mapping data to the RMDB.
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Affiliation(s)
- Joseph D Yesselman
- Department of Biochemistry, Stanford University School of Medicine, Stanford CA 94305, USA
| | - Siqi Tian
- Department of Biochemistry, Stanford University School of Medicine, Stanford CA 94305, USA
| | - Xin Liu
- Department of Genetics, Stanford University School of Medicine, Stanford CA 94305, USA
| | | | - Jin Billy Li
- Department of Genetics, Stanford University School of Medicine, Stanford CA 94305, USA
| | - Rhiju Das
- Department of Biochemistry, Stanford University School of Medicine, Stanford CA 94305, USA.,Department of Physics, Stanford University, Stanford, CA 94305, USA
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21
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Chu CC, Plangger R, Kreutz C, Al-Hashimi HM. Dynamic ensemble of HIV-1 RRE stem IIB reveals non-native conformations that disrupt the Rev-binding site. Nucleic Acids Res 2019; 47:7105-7117. [PMID: 31199872 PMCID: PMC6649712 DOI: 10.1093/nar/gkz498] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 05/21/2019] [Accepted: 06/07/2019] [Indexed: 01/01/2023] Open
Abstract
The HIV-1 Rev response element (RRE) RNA element mediates the nuclear export of intron containing viral RNAs by forming an oligomeric complex with the viral protein Rev. Stem IIB and nearby stem II three-way junction nucleate oligomerization through cooperative binding of two Rev molecules. Conformational flexibility at this RRE region has been shown to be important for Rev binding. However, the nature of the flexibility has remained elusive. Here, using NMR relaxation dispersion, including a new strategy for directly observing transient conformational states in large RNAs, we find that stem IIB alone or when part of the larger RREII three-way junction robustly exists in dynamic equilibrium with non-native excited state (ES) conformations that have a combined population of ∼20%. The ESs disrupt the Rev-binding site by changing local secondary structure, and their stabilization via point substitution mutations decreases the binding affinity to the Rev arginine-rich motif (ARM) by 15- to 80-fold. The ensemble clarifies the conformational flexibility observed in stem IIB, reveals long-range conformational coupling between stem IIB and the three-way junction that may play roles in cooperative Rev binding, and also identifies non-native RRE conformational states as new targets for the development of anti-HIV therapeutics.
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Affiliation(s)
- Chia-Chieh Chu
- Department of Biochemistry, Duke University School of Medicine, Durham, NC 27710, USA
| | - Raphael Plangger
- Institute of Organic Chemistry and Center for Molecular Biosciences (CMBI), Universität Innsbruck, 6020 Innsbruck, Austria
| | - Christoph Kreutz
- Institute of Organic Chemistry and Center for Molecular Biosciences (CMBI), Universität Innsbruck, 6020 Innsbruck, Austria
| | - Hashim M Al-Hashimi
- Department of Biochemistry, Duke University School of Medicine, Durham, NC 27710, USA
- Department of Chemistry, Duke University, Durham, NC 27708, USA
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22
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Abstract
The three-dimensional structures of RNA molecules provide rich and often critical information for understanding their functions, including how they recognize small molecule and protein partners. Computational modeling of RNA 3D structure is becoming increasingly accurate, particularly with the availability of growing numbers of template structures already solved experimentally and the development of sequence alignment and 3D modeling tools to take advantage of this database. For several recent "RNA puzzle" blind modeling challenges, we have successfully identified useful template structures and achieved accurate structure predictions through homology modeling tools developed in the Rosetta software suite. We describe our semi-automated methodology here and walk through two illustrative examples: an adenine riboswitch aptamer, modeled from a template guanine riboswitch structure, and a SAM I/IV riboswitch aptamer, modeled from a template SAM I riboswitch structure.
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Affiliation(s)
- Andrew M Watkins
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, United States
| | - Ramya Rangan
- Biophysics Program, Stanford University, Stanford, CA, United States
| | - Rhiju Das
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, United States; Biophysics Program, Stanford University, Stanford, CA, United States.
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23
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Thompson RD, Baisden JT, Zhang Q. NMR characterization of RNA small molecule interactions. Methods 2019; 167:66-77. [PMID: 31128236 DOI: 10.1016/j.ymeth.2019.05.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2019] [Revised: 05/17/2019] [Accepted: 05/17/2019] [Indexed: 01/25/2023] Open
Abstract
Exciting discoveries of naturally occurring ligand-sensing and disease-linked noncoding RNAs have promoted significant interests in understanding RNA-small molecule interactions. NMR spectroscopy is a powerful tool for characterizing intermolecular interactions. In this review, we describe protocols and approaches for applying NMR spectroscopy to investigate interactions between RNA and small molecules. We review protocols for RNA sample preparation, methods for identifying RNA-binding small molecules, approaches for mapping RNA-small molecule interactions, determining complex structures, and characterizing binding kinetics. We hope this review will provide a guideline to streamline NMR applications in studying RNA-small molecule interactions, facilitating both basic mechanistic understandings of RNA functions and translational efforts in developing RNA-targeted therapeutics.
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Affiliation(s)
- Rhese D Thompson
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jared T Baisden
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Qi Zhang
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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24
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Unveiling the druggable RNA targets and small molecule therapeutics. Bioorg Med Chem 2019; 27:2149-2165. [PMID: 30981606 PMCID: PMC7126819 DOI: 10.1016/j.bmc.2019.03.057] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 03/25/2019] [Accepted: 03/29/2019] [Indexed: 12/15/2022]
Abstract
The increasing appreciation for the crucial roles of RNAs in infectious and non-infectious human diseases makes them attractive therapeutic targets. Coding and non-coding RNAs frequently fold into complex conformations which, if effectively targeted, offer opportunities to therapeutically modulate numerous cellular processes, including those linked to undruggable protein targets. Despite the considerable skepticism as to whether RNAs can be targeted with small molecule therapeutics, overwhelming evidence suggests the challenges we are currently facing are not outside the realm of possibility. In this review, we highlight the most recent advances in molecular techniques that have sparked a revolution in understanding the RNA structure-to-function relationship. We bring attention to the application of these modern techniques to identify druggable RNA targets and to assess small molecule binding specificity. Finally, we discuss novel screening methodologies that support RNA drug discovery and present examples of therapeutically valuable RNA targets.
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25
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Zhang H, Keane SC. Advances that facilitate the study of large RNA structure and dynamics by nuclear magnetic resonance spectroscopy. WILEY INTERDISCIPLINARY REVIEWS-RNA 2019; 10:e1541. [PMID: 31025514 PMCID: PMC7169810 DOI: 10.1002/wrna.1541] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 01/18/2019] [Accepted: 04/02/2019] [Indexed: 12/22/2022]
Abstract
The characterization of functional yet nonprotein coding (nc) RNAs has expanded the role of RNA in the cell from a passive player in the central dogma of molecular biology to an active regulator of gene expression. The misregulation of ncRNA function has been linked with a variety of diseases and disorders ranging from cancers to neurodegeneration. However, a detailed molecular understanding of how ncRNAs function has been limited; due, in part, to the difficulties associated with obtaining high-resolution structures of large RNAs. Tertiary structure determination of RNA as a whole is hampered by various technical challenges, all of which are exacerbated as the size of the RNA increases. Namely, RNAs tend to be highly flexible and dynamic molecules, which are difficult to crystallize. Biomolecular nuclear magnetic resonance (NMR) spectroscopy offers a viable alternative to determining the structure of large RNA molecules that do not readily crystallize, but is itself hindered by some technical limitations. Recently, a series of advancements have allowed the biomolecular NMR field to overcome, at least in part, some of these limitations. These advances include improvements in sample preparation strategies as well as methodological improvements. Together, these innovations pave the way for the study of ever larger RNA molecules that have important biological function. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.
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Affiliation(s)
- Huaqun Zhang
- Biophysics Program, University of Michigan, Ann Arbor, Michigan
| | - Sarah C Keane
- Biophysics Program, University of Michigan, Ann Arbor, Michigan.,Department of Chemistry, University of Michigan, Ann Arbor, Michigan
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26
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Eubanks CS, Hargrove AE. RNA Structural Differentiation: Opportunities with Pattern Recognition. Biochemistry 2018; 58:199-213. [PMID: 30513196 DOI: 10.1021/acs.biochem.8b01090] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Our awareness and appreciation of the many regulatory roles of RNA have dramatically increased in the past decade. This understanding, in addition to the impact of RNA in many disease states, has renewed interest in developing selective RNA-targeted small molecule probes. However, the fundamental guiding principles in RNA molecular recognition that could accelerate these efforts remain elusive. While high-resolution structural characterization can provide invaluable insight, examples of well-characterized RNA structures, not to mention small molecule:RNA complexes, remain limited. This Perspective provides an overview of the current techniques used to understand RNA molecular recognition when high-resolution structural information is unavailable. We will place particular emphasis on a new method, pattern recognition of RNA with small molecules (PRRSM), that provides rapid insight into critical components of RNA recognition and differentiation by small molecules as well as into RNA structural features.
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Affiliation(s)
- Christopher S Eubanks
- Department of Chemistry , Duke University , Durham , North Carolina 27708-0354 , United States
| | - Amanda E Hargrove
- Department of Chemistry , Duke University , Durham , North Carolina 27708-0354 , United States
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27
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Hartwick EW, Costantino DA, MacFadden A, Nix JC, Tian S, Das R, Kieft JS. Ribosome-induced RNA conformational changes in a viral 3'-UTR sense and regulate translation levels. Nat Commun 2018; 9:5074. [PMID: 30498211 PMCID: PMC6265322 DOI: 10.1038/s41467-018-07542-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 11/07/2018] [Indexed: 12/22/2022] Open
Abstract
Structured RNA elements, programmed RNA conformational changes, and interactions between different RNA domains underlie many modes of regulating gene expression, mandating studies to understand the foundational principles that govern these phenomena. Exploring the structured 3' untranslated region (UTR) of a viral RNA, we discovered that different contexts of the 3'-UTR confer different abilities to enhance translation of an associated open reading frame. In one context, ribosome-induced conformational changes in a 'sensor' RNA domain affect a separate RNA 'functional' domain, altering translation efficiency. The structure of the entire 3'-UTR reveals that structurally distinct domains use a spine of continuously stacked bases and a strut-like linker to create a conduit for communication within the higher-order architecture. Thus, this 3'-UTR RNA illustrates how RNA can use programmed conformational changes to sense the translation status of an upstream open reading frame, then create a tuned functional response by communicating that information to other RNA elements.
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Affiliation(s)
- Erik W Hartwick
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver School of Medicine, Aurora, CO, 80045, USA.,RNA BioScience Initiative, University of Colorado Denver School of Medicine, Aurora, CO, 80045, USA
| | - David A Costantino
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver School of Medicine, Aurora, CO, 80045, USA
| | - Andrea MacFadden
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver School of Medicine, Aurora, CO, 80045, USA
| | - Jay C Nix
- Molecular Biology Consortium, Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Siqi Tian
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA
| | - Rhiju Das
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA
| | - Jeffrey S Kieft
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver School of Medicine, Aurora, CO, 80045, USA. .,RNA BioScience Initiative, University of Colorado Denver School of Medicine, Aurora, CO, 80045, USA.
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28
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Mailler E, Paillart JC, Marquet R, Smyth RP, Vivet-Boudou V. The evolution of RNA structural probing methods: From gels to next-generation sequencing. WILEY INTERDISCIPLINARY REVIEWS-RNA 2018; 10:e1518. [PMID: 30485688 DOI: 10.1002/wrna.1518] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 09/13/2018] [Accepted: 10/17/2018] [Indexed: 01/09/2023]
Abstract
RNA molecules are important players in all domains of life and the study of the relationship between their multiple flexible states and the associated biological roles has increased in recent years. For several decades, chemical and enzymatic structural probing experiments have been used to determine RNA structure. During this time, there has been a steady improvement in probing reagents and experimental methods, and today the structural biologist community has a large range of tools at its disposal to probe the secondary structure of RNAs in vitro and in cells. Early experiments used radioactive labeling and polyacrylamide gel electrophoresis as read-out methods. This was superseded by capillary electrophoresis, and more recently by next-generation sequencing. Today, powerful structural probing methods can characterize RNA structure on a genome-wide scale. In this review, we will provide an overview of RNA structural probing methodologies from a historical and technical perspective. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry RNA Methods > RNA Analyses in vitro and In Silico RNA Methods > RNA Analyses in Cells.
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Affiliation(s)
- Elodie Mailler
- Architecture et Réactivité de l'ARN, Université de Strasbourg, CNRS, Strasbourg, France
| | | | - Roland Marquet
- Architecture et Réactivité de l'ARN, Université de Strasbourg, CNRS, Strasbourg, France
| | - Redmond P Smyth
- Architecture et Réactivité de l'ARN, Université de Strasbourg, CNRS, Strasbourg, France
| | - Valerie Vivet-Boudou
- Architecture et Réactivité de l'ARN, Université de Strasbourg, CNRS, Strasbourg, France
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29
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Shaytan AK, Xiao H, Armeev GA, Gaykalova DA, Komarova GA, Wu C, Studitsky VM, Landsman D, Panchenko AR. Structural interpretation of DNA-protein hydroxyl-radical footprinting experiments with high resolution using HYDROID. Nat Protoc 2018; 13:2535-2556. [PMID: 30341436 PMCID: PMC6322412 DOI: 10.1038/s41596-018-0048-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Hydroxyl-radical footprinting (HRF) is a powerful method for probing structures of nucleic acid-protein complexes with single-nucleotide resolution in solution. To tap the full quantitative potential of HRF, we describe a protocol, hydroxyl-radical footprinting interpretation for DNA (HYDROID), to quantify HRF data and integrate them with atomistic structural models. The stages of the HYDROID protocol are extraction of the lane profiles from gel images, quantification of the DNA cleavage frequency at each nucleotide and theoretical estimation of the DNA cleavage frequency from atomistic structural models, followed by comparison of experimental and theoretical results. Example scripts for each step of HRF data analysis and interpretation are provided for several nucleosome systems; they can be easily adapted to analyze user data. As input, HYDROID requires polyacrylamide gel electrophoresis (PAGE) images of HRF products and optionally can use a molecular model of the DNA-protein complex. The HYDROID protocol can be used to quantify HRF over DNA regions of up to 100 nucleotides per gel image. In addition, it can be applied to the analysis of RNA-protein complexes and free RNA or DNA molecules in solution. Compared with other methods reported to date, HYDROID is unique in its ability to simultaneously integrate HRF data with the analysis of atomistic structural models. HYDROID is freely available. The complete protocol takes ~3 h. Users should be familiar with the command-line interface, the Python scripting language and Protein Data Bank (PDB) file formats. A graphical user interface (GUI) with basic functionality (HYDROID_GUI) is also available.
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Affiliation(s)
- Alexey K Shaytan
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
- Department of Biology, Lomonosov Moscow State University, Moscow, Russia.
| | - Hua Xiao
- Laboratory of Biochemistry and Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Grigoriy A Armeev
- Department of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Daria A Gaykalova
- Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Galina A Komarova
- Department of Physics, Lomonosov Moscow State University, Moscow, Russia
| | - Carl Wu
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Molecular Biology & Genetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Vasily M Studitsky
- Department of Biology, Lomonosov Moscow State University, Moscow, Russia
- Fox Chase Cancer Center, Philadelphia, PA, USA
| | - David Landsman
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Anna R Panchenko
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
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30
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Abstract
The structure of RNA has been a natural subject for mathematical modeling, inviting many innovative computational frameworks. This single-stranded polynucleotide chain can fold upon itself in numerous ways to form hydrogen-bonded segments, imperfect with single-stranded loops. Illustrating these paired and non-paired interaction networks, known as RNA's secondary (2D) structure, using mathematical graph objects has been illuminating for RNA structure analysis. Building upon such seminal work from the 1970s and 1980s, graph models are now used to study not only RNA structure but also describe RNA's recurring modular units, sample the conformational space accessible to RNAs, predict RNA's three-dimensional folds, and apply the combined aspects to novel RNA design. In this article, we outline the development of the RNA-As-Graphs (or RAG) approach and highlight current applications to RNA structure prediction and design.
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Affiliation(s)
- Tamar Schlick
- Department of Chemistry, 100 Washington Square East, Silver Building, New York University, New York, NY 10003, USA; Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 10012, USA; New York University ECNU - Center for Computational Chemistry at NYU Shanghai, 3663 North Zhongshan Road, Shanghai, 200062, China.
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31
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Baronti L, Karlsson H, Marušič M, Petzold K. A guide to large-scale RNA sample preparation. Anal Bioanal Chem 2018; 410:3239-3252. [PMID: 29546546 PMCID: PMC5937877 DOI: 10.1007/s00216-018-0943-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 01/25/2018] [Accepted: 02/05/2018] [Indexed: 12/30/2022]
Abstract
RNA is becoming more important as an increasing number of functions, both regulatory and enzymatic, are being discovered on a daily basis. As the RNA boom has just begun, most techniques are still in development and changes occur frequently. To understand RNA functions, revealing the structure of RNA is of utmost importance, which requires sample preparation. We review the latest methods to produce and purify a variation of RNA molecules for different purposes with the main focus on structural biology and biophysics. We present a guide aimed at identifying the most suitable method for your RNA and your biological question and highlighting the advantages of different methods. Graphical abstract In this review we present different methods for large-scale production and purification of RNAs for structural and biophysical studies.
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Affiliation(s)
- Lorenzo Baronti
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Scheeles Väg 2, 17177, Stockholm, Sweden
| | - Hampus Karlsson
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Scheeles Väg 2, 17177, Stockholm, Sweden
| | - Maja Marušič
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Scheeles Väg 2, 17177, Stockholm, Sweden
| | - Katja Petzold
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Scheeles Väg 2, 17177, Stockholm, Sweden.
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Šponer J, Bussi G, Krepl M, Banáš P, Bottaro S, Cunha RA, Gil-Ley A, Pinamonti G, Poblete S, Jurečka P, Walter NG, Otyepka M. RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview. Chem Rev 2018; 118:4177-4338. [PMID: 29297679 PMCID: PMC5920944 DOI: 10.1021/acs.chemrev.7b00427] [Citation(s) in RCA: 327] [Impact Index Per Article: 54.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Indexed: 12/14/2022]
Abstract
With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.
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Affiliation(s)
- Jiří Šponer
- Institute of Biophysics of the Czech Academy of Sciences , Kralovopolska 135 , Brno 612 65 , Czech Republic
| | - Giovanni Bussi
- Scuola Internazionale Superiore di Studi Avanzati , Via Bonomea 265 , Trieste 34136 , Italy
| | - Miroslav Krepl
- Institute of Biophysics of the Czech Academy of Sciences , Kralovopolska 135 , Brno 612 65 , Czech Republic
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science , Palacky University Olomouc , 17. listopadu 12 , Olomouc 771 46 , Czech Republic
| | - Pavel Banáš
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science , Palacky University Olomouc , 17. listopadu 12 , Olomouc 771 46 , Czech Republic
| | - Sandro Bottaro
- Structural Biology and NMR Laboratory, Department of Biology , University of Copenhagen , Copenhagen 2200 , Denmark
| | - Richard A Cunha
- Scuola Internazionale Superiore di Studi Avanzati , Via Bonomea 265 , Trieste 34136 , Italy
| | - Alejandro Gil-Ley
- Scuola Internazionale Superiore di Studi Avanzati , Via Bonomea 265 , Trieste 34136 , Italy
| | - Giovanni Pinamonti
- Scuola Internazionale Superiore di Studi Avanzati , Via Bonomea 265 , Trieste 34136 , Italy
| | - Simón Poblete
- Scuola Internazionale Superiore di Studi Avanzati , Via Bonomea 265 , Trieste 34136 , Italy
| | - Petr Jurečka
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science , Palacky University Olomouc , 17. listopadu 12 , Olomouc 771 46 , Czech Republic
| | - Nils G Walter
- Single Molecule Analysis Group and Center for RNA Biomedicine, Department of Chemistry , University of Michigan , Ann Arbor , Michigan 48109 , United States
| | - Michal Otyepka
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science , Palacky University Olomouc , 17. listopadu 12 , Olomouc 771 46 , Czech Republic
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Leppek K, Das R, Barna M. Functional 5' UTR mRNA structures in eukaryotic translation regulation and how to find them. Nat Rev Mol Cell Biol 2018; 19:158-174. [PMID: 29165424 PMCID: PMC5820134 DOI: 10.1038/nrm.2017.103] [Citation(s) in RCA: 470] [Impact Index Per Article: 78.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
RNA molecules can fold into intricate shapes that can provide an additional layer of control of gene expression beyond that of their sequence. In this Review, we discuss the current mechanistic understanding of structures in 5' untranslated regions (UTRs) of eukaryotic mRNAs and the emerging methodologies used to explore them. These structures may regulate cap-dependent translation initiation through helicase-mediated remodelling of RNA structures and higher-order RNA interactions, as well as cap-independent translation initiation through internal ribosome entry sites (IRESs), mRNA modifications and other specialized translation pathways. We discuss known 5' UTR RNA structures and how new structure probing technologies coupled with prospective validation, particularly compensatory mutagenesis, are likely to identify classes of structured RNA elements that shape post-transcriptional control of gene expression and the development of multicellular organisms.
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Affiliation(s)
- Kathrin Leppek
- Department of Developmental Biology, Stanford University, Stanford, California 94305, USA
- Department of Genetics, Stanford University, Stanford, California 94305, USA
| | - Rhiju Das
- Departments of Biochemistry and Physics, Stanford University, Stanford, California 94305, USA
| | - Maria Barna
- Department of Developmental Biology, Stanford University, Stanford, California 94305, USA
- Department of Genetics, Stanford University, Stanford, California 94305, USA
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34
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Tian S, Kladwang W, Das R. Allosteric mechanism of the V. vulnificus adenine riboswitch resolved by four-dimensional chemical mapping. eLife 2018; 7:29602. [PMID: 29446752 PMCID: PMC5847336 DOI: 10.7554/elife.29602] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Accepted: 02/13/2018] [Indexed: 12/23/2022] Open
Abstract
The structural interconversions that mediate the gene regulatory functions of RNA molecules may be different from classic models of allostery, but the relevant structural correlations have remained elusive in even intensively studied systems. Here, we present a four-dimensional expansion of chemical mapping called lock-mutate-map-rescue (LM2R), which integrates multiple layers of mutation with nucleotide-resolution chemical mapping. This technique resolves the core mechanism of the adenine-responsive V. vulnificus add riboswitch, a paradigmatic system for which both Monod-Wyman-Changeux (MWC) conformational selection models and non-MWC alternatives have been proposed. To discriminate amongst these models, we locked each functionally important helix through designed mutations and assessed formation or depletion of other helices via compensatory rescue evaluated by chemical mapping. These LM2R measurements give strong support to the pre-existing correlations predicted by MWC models, disfavor alternative models, and suggest additional structural heterogeneities that may be general across ligand-free riboswitches.
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Affiliation(s)
- Siqi Tian
- Department of Biochemistry, Stanford University, Stanford, United States
| | - Wipapat Kladwang
- Department of Biochemistry, Stanford University, Stanford, United States
| | - Rhiju Das
- Department of Physics, Stanford University, Stanford, United States
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35
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Tian S, Das R. Primerize-2D: automated primer design for RNA multidimensional chemical mapping. Bioinformatics 2018; 33:1405-1406. [PMID: 28453672 DOI: 10.1093/bioinformatics/btw814] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Accepted: 12/23/2016] [Indexed: 11/14/2022] Open
Abstract
Summary Rapid RNA synthesis of comprehensive single mutant libraries and targeted multiple mutant libraries is enabling new multidimensional chemical approaches to solve RNA structures. PCR assembly of DNA templates and in vitro transcription allow synthesis and purification of hundreds of RNA mutants in a cost-effective manner, with sharing of primers across constructs allowing significant reductions in expense. However, these protocols require organization of primer locations across numerous 96 well plates and guidance for pipetting, non-trivial tasks for which informatics and visualization tools can prevent costly errors. We report here an online tool to accelerate synthesis of large libraries of desired mutants through design and efficient organization of primers. The underlying program and graphical interface have been experimentally tested in our laboratory for RNA domains with lengths up to 300 nucleotides and libraries encompassing up to 960 variants. In addition to the freely available Primerize-2D server, the primer design code is available as a stand-alone Python package for broader applications. Availability and Implementation http://primerize2d.stanford.edu. Contact rhiju@stanford.edu. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Rhiju Das
- Department of Biochemistry.,Department of Physics, Stanford University, Stanford, CA 94305, USA
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36
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RNA structure inference through chemical mapping after accidental or intentional mutations. Proc Natl Acad Sci U S A 2017; 114:9876-9881. [PMID: 28851837 DOI: 10.1073/pnas.1619897114] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Despite the critical roles RNA structures play in regulating gene expression, sequencing-based methods for experimentally determining RNA base pairs have remained inaccurate. Here, we describe a multidimensional chemical-mapping method called "mutate-and-map read out through next-generation sequencing" (M2-seq) that takes advantage of sparsely mutated nucleotides to induce structural perturbations at partner nucleotides and then detects these events through dimethyl sulfate (DMS) probing and mutational profiling. In special cases, fortuitous errors introduced during DNA template preparation and RNA transcription are sufficient to give M2-seq helix signatures; these signals were previously overlooked or mistaken for correlated double-DMS events. When mutations are enhanced through error-prone PCR, in vitro M2-seq experimentally resolves 33 of 68 helices in diverse structured RNAs including ribozyme domains, riboswitch aptamers, and viral RNA domains with a single false positive. These inferences do not require energy minimization algorithms and can be made by either direct visual inspection or by a neural-network-inspired algorithm called M2-net. Measurements on the P4-P6 domain of the Tetrahymena group I ribozyme embedded in Xenopus egg extract demonstrate the ability of M2-seq to detect RNA helices in a complex biological environment.
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37
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Schlick T, Pyle AM. Opportunities and Challenges in RNA Structural Modeling and Design. Biophys J 2017; 113:225-234. [PMID: 28162235 PMCID: PMC5529161 DOI: 10.1016/j.bpj.2016.12.037] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Revised: 12/08/2016] [Accepted: 12/19/2016] [Indexed: 01/27/2023] Open
Abstract
We describe opportunities and challenges in RNA structural modeling and design, as recently discussed during the second Telluride Science Research Center workshop organized in June 2016. Topics include fundamental processes of RNA, such as structural assemblies (hierarchical folding, multiple conformational states and their clustering), RNA motifs, and chemical reactivity of RNA, as used for structural prediction and functional inference. We also highlight the software and database issues associated with RNA structures, such as the multiple approaches for motif annotation, the need for frequent database updating, and the importance of quality control of RNA structures. We discuss various modeling approaches for structure prediction, mechanistic analysis of RNA reactions, and RNA design, and the complementary roles that both atomistic and coarse-grained approaches play in such simulations. Collectively, as scientists from varied disciplines become familiar and drawn into these unique challenges, new approaches and collaborative efforts will undoubtedly be catalyzed.
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Affiliation(s)
- Tamar Schlick
- Department of Chemistry, New York University, New York, New York; Courant Institute of Mathematical Sciences, New York University, New York, New York.
| | - Anna Marie Pyle
- Department of Molecular and Cellular and Developmental Biology and Department of Chemistry, Yale University; Howard Hughes Medical Institute, New Haven, Connecticut.
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Miao Z, Adamiak RW, Antczak M, Batey RT, Becka AJ, Biesiada M, Boniecki MJ, Bujnicki JM, Chen SJ, Cheng CY, Chou FC, Ferré-D'Amaré AR, Das R, Dawson WK, Ding F, Dokholyan NV, Dunin-Horkawicz S, Geniesse C, Kappel K, Kladwang W, Krokhotin A, Łach GE, Major F, Mann TH, Magnus M, Pachulska-Wieczorek K, Patel DJ, Piccirilli JA, Popenda M, Purzycka KJ, Ren A, Rice GM, Santalucia J, Sarzynska J, Szachniuk M, Tandon A, Trausch JJ, Tian S, Wang J, Weeks KM, Williams B, Xiao Y, Xu X, Zhang D, Zok T, Westhof E. RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme. RNA (NEW YORK, N.Y.) 2017; 23:655-672. [PMID: 28138060 PMCID: PMC5393176 DOI: 10.1261/rna.060368.116] [Citation(s) in RCA: 132] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2016] [Accepted: 01/26/2017] [Indexed: 05/21/2023]
Abstract
RNA-Puzzles is a collective experiment in blind 3D RNA structure prediction. We report here a third round of RNA-Puzzles. Five puzzles, 4, 8, 12, 13, 14, all structures of riboswitch aptamers and puzzle 7, a ribozyme structure, are included in this round of the experiment. The riboswitch structures include biological binding sites for small molecules (S-adenosyl methionine, cyclic diadenosine monophosphate, 5-amino 4-imidazole carboxamide riboside 5'-triphosphate, glutamine) and proteins (YbxF), and one set describes large conformational changes between ligand-free and ligand-bound states. The Varkud satellite ribozyme is the most recently solved structure of a known large ribozyme. All puzzles have established biological functions and require structural understanding to appreciate their molecular mechanisms. Through the use of fast-track experimental data, including multidimensional chemical mapping, and accurate prediction of RNA secondary structure, a large portion of the contacts in 3D have been predicted correctly leading to similar topologies for the top ranking predictions. Template-based and homology-derived predictions could predict structures to particularly high accuracies. However, achieving biological insights from de novo prediction of RNA 3D structures still depends on the size and complexity of the RNA. Blind computational predictions of RNA structures already appear to provide useful structural information in many cases. Similar to the previous RNA-Puzzles Round II experiment, the prediction of non-Watson-Crick interactions and the observed high atomic clash scores reveal a notable need for an algorithm of improvement. All prediction models and assessment results are available at http://ahsoka.u-strasbg.fr/rnapuzzles/.
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Affiliation(s)
- Zhichao Miao
- Architecture et Réactivité de l'ARN, Université de Strasbourg, Institut de biologie moléculaire et cellulaire du CNRS, 67000 Strasbourg, France;
| | - Ryszard W Adamiak
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
- Poznan University of Technology, Institute of Computing Science, 60-965 Poznan, Poland
| | - Maciej Antczak
- Poznan University of Technology, Institute of Computing Science, 60-965 Poznan, Poland
| | - Robert T Batey
- Department of Chemistry and Biochemistry, University of Colorado at Boulder, Boulder, Colorado 80309-0596, USA
| | - Alexander J Becka
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Marcin Biesiada
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
| | - Michał J Boniecki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Janusz M Bujnicki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
- Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland
| | - Shi-Jie Chen
- Department of Physics and Astronomy, Department of Biochemistry, and Informatics Institute, University of Missouri-Columbia, Columbia, Missouri 65211, USA
| | - Clarence Yu Cheng
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Fang-Chieh Chou
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | | | - Rhiju Das
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Wayne K Dawson
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Feng Ding
- Department of Physics and Astronomy, Clemson University, Clemson, South Carolina 29634, USA
| | - Nikolay V Dokholyan
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Stanisław Dunin-Horkawicz
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Caleb Geniesse
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Kalli Kappel
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Wipapat Kladwang
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Andrey Krokhotin
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Grzegorz E Łach
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - François Major
- Institute for Research in Immunology and Cancer (IRIC), Department of Computer Science and Operations Research, Université de Montréal, Montréal, Québec, H3C 3J7, Canada
| | - Thomas H Mann
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Marcin Magnus
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | | | - Dinshaw J Patel
- Structural Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA
| | - Joseph A Piccirilli
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, Illinois 60637, USA
- Department of Chemistry, The University of Chicago, Chicago, Illinois 60637, USA
| | - Mariusz Popenda
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
| | - Katarzyna J Purzycka
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
| | - Aiming Ren
- Structural Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA
- Life Sciences Institute, Zhejiang University, Hangzhou 310058, China
| | - Greggory M Rice
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-3290, USA
| | - John Santalucia
- Department of Chemistry, Wayne State University, Detroit, Michigan 48202, USA
- DNA Software, Ann Arbor, Michigan 48104, USA
| | - Joanna Sarzynska
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
| | - Marta Szachniuk
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
- Poznan University of Technology, Institute of Computing Science, 60-965 Poznan, Poland
| | - Arpit Tandon
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Jeremiah J Trausch
- Department of Chemistry and Biochemistry, University of Colorado at Boulder, Boulder, Colorado 80309-0596, USA
| | - Siqi Tian
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Jian Wang
- Biomolecular Physics and Modeling Group, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Kevin M Weeks
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-3290, USA
| | - Benfeard Williams
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Yi Xiao
- Biomolecular Physics and Modeling Group, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Xiaojun Xu
- Department of Physics and Astronomy, Department of Biochemistry, and Informatics Institute, University of Missouri-Columbia, Columbia, Missouri 65211, USA
| | - Dong Zhang
- Department of Physics and Astronomy, Department of Biochemistry, and Informatics Institute, University of Missouri-Columbia, Columbia, Missouri 65211, USA
| | - Tomasz Zok
- Poznan University of Technology, Institute of Computing Science, 60-965 Poznan, Poland
| | - Eric Westhof
- Architecture et Réactivité de l'ARN, Université de Strasbourg, Institut de biologie moléculaire et cellulaire du CNRS, 67000 Strasbourg, France;
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Taylor WR, Hamilton RS. Exploring RNA conformational space under sparse distance restraints. Sci Rep 2017; 7:44074. [PMID: 28281575 PMCID: PMC5345030 DOI: 10.1038/srep44074] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 02/01/2017] [Indexed: 11/21/2022] Open
Abstract
We show that the application of a small number of restraints predicted by coevolution analysis can provide a powerful restriction on the conformational freedom of an RNA molecule. The greatest degree of restriction occurs when a contact is predicted between the distal ends of a pair of adjacent stemloops but even with this location additional flexibilities in the molecule can mask the contribution. Multiple cross-links, especially those including a pseudoknot provided the strongest restraint on conformational freedom with the effect being most apparent in topologically simple folds and less so if the fold is more topologically entwined. Little was expected for large structures (over 300 bases) and although a few strong localised restrictions were observed, they contributed little to the restraint of the overall fold. Although contacts predicted using a correlated mutation analysis can provide some powerful restrictions on the conformational freedom of RNA molecules, they are too erratic in their occurrence and distribution to provide a general approach to the problem of RNA 3D structure prediction from sequence.
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Affiliation(s)
- William R. Taylor
- Computational Cell and Molecular Biology, Francis Crick Institute, London, NW1 1AT, UK
| | - Russell S. Hamilton
- Centre for Trophoblast Research (CTR), Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 3DY, UK
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