1
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Gray M, Will S, Jabbari H. SparseRNAfolD: optimized sparse RNA pseudoknot-free folding with dangle consideration. Algorithms Mol Biol 2024; 19:9. [PMID: 38433200 PMCID: PMC11289965 DOI: 10.1186/s13015-024-00256-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/13/2024] [Indexed: 03/05/2024] Open
Abstract
MOTIVATION Computational RNA secondary structure prediction by free energy minimization is indispensable for analyzing structural RNAs and their interactions. These methods find the structure with the minimum free energy (MFE) among exponentially many possible structures and have a restrictive time and space complexity ( O ( n 3 ) time and O ( n 2 ) space for pseudoknot-free structures) for longer RNA sequences. Furthermore, accurate free energy calculations, including dangle contributions can be difficult and costly to implement, particularly when optimizing for time and space requirements. RESULTS Here we introduce a fast and efficient sparsified MFE pseudoknot-free structure prediction algorithm, SparseRNAFolD, that utilizes an accurate energy model that accounts for dangle contributions. While the sparsification technique was previously employed to improve the time and space complexity of a pseudoknot-free structure prediction method with a realistic energy model, SparseMFEFold, it was not extended to include dangle contributions due to the complexity of computation. This may come at the cost of prediction accuracy. In this work, we compare three different sparsified implementations for dangle contributions and provide pros and cons of each method. As well, we compare our algorithm to LinearFold, a linear time and space algorithm, where we find that in practice, SparseRNAFolD has lower memory consumption across all lengths of sequence and a faster time for lengths up to 1000 bases. CONCLUSION Our SparseRNAFolD algorithm is an MFE-based algorithm that guarantees optimality of result and employs the most general energy model, including dangle contributions. We provide a basis for applying dangles to sparsified recursion in a pseudoknot-free model that has the potential to be extended to pseudoknots.
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Affiliation(s)
- Mateo Gray
- Department of Biomedical Engineering, University of Alberta, Street, Edmonton, T6G2R3, AB, Canada.
| | - Sebastian Will
- Department of Computer Science CNRS/LIX (UMR 7161), Institut Polytechnique de Paris, Street, Paris, 10587, France
| | - Hosna Jabbari
- Department of Biomedical Engineering, University of Alberta, Street, Edmonton, T6G2R3, AB, Canada.
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2
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Jin K, Liao YC, Cheng TC, Li X, Lee WJ, Pi F, Jasinski D, Chen LC, Phelps MA, Ho YS, Guo P. In Vitro and In Vivo Evaluation of the Pathology and Safety Aspects of Three- and Four-Way Junction RNA Nanoparticles. Mol Pharm 2024; 21:718-728. [PMID: 38214504 PMCID: PMC10976369 DOI: 10.1021/acs.molpharmaceut.3c00845] [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: 01/13/2024]
Abstract
RNA therapeutics has advanced into the third milestone in pharmaceutical drug development, following chemical and protein therapeutics. RNA itself can serve as therapeutics, carriers, regulators, or substrates in drug development. Due to RNA's motile, dynamic, and deformable properties, RNA nanoparticles have demonstrated spontaneous targeting and accumulation in cancer vasculature and fast excretion through the kidney glomerulus to urine to prevent possible interactions with healthy organs. Furthermore, the negatively charged phosphate backbone of RNA results in general repulsion from negatively charged lipid cell membranes for further avoidance of vital organs. Thus, RNA nanoparticles can spontaneously enrich tumor vasculature and efficiently enter tumor cells via specific targeting, while those not entering the tumor tissue will clear from the body quickly. These favorable parameters have led to the expectation that RNA has low or little toxicity. RNA nanoparticles have been well characterized for their anticancer efficacy; however, little detail on RNA nanoparticle pathology and safety is known. Here, we report the in vitro and in vivo assessment of the pathology and safety aspects of different RNA nanoparticles including RNA three-way junction (3WJ) harboring 2'-F modified pyrimidine, folic acid, and Survivin siRNA, as well as the RNA four-way junction (4WJ) harboring 2'-F modified pyrimidine and 24 copies of SN38. Both animal models and patient serum were investigated. In vitro studies include hemolysis, platelet aggregation, complement activation, plasma coagulation, and interferon induction. In vivo studies include hematoxylin and eosin (H&E) staining, hematological and biochemical analysis as the serum profiling, and animal organ weight study. No significant toxicity, side effect, or immune responses were detected during the extensive safety evaluations of RNA nanoparticles. These results further complement previous cancer inhibition studies and demonstrate RNA nanoparticles as an effective and safe drug delivery vehicle for future clinical translations.
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Affiliation(s)
- Kai Jin
- Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
- Center for RNA Nanotechnology and Nanomedicine, The Ohio State University, Columbus, Ohio 43210, United States
| | - You-Cheng Liao
- Graduate Institute of Medical Sciences, College of Medicine, Taipei Medical University, Taipei 110031, Taiwan
| | - Tzu-Chun Cheng
- Institute of Biochemistry and Molecular Biology, China Medical University, Taichung 406040, Taiwan
| | - Xin Li
- Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
- Center for RNA Nanotechnology and Nanomedicine, The Ohio State University, Columbus, Ohio 43210, United States
| | - Wen-Jui Lee
- Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
- Center for RNA Nanotechnology and Nanomedicine, The Ohio State University, Columbus, Ohio 43210, United States
| | - Fengmei Pi
- Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
- Center for RNA Nanotechnology and Nanomedicine, The Ohio State University, Columbus, Ohio 43210, United States
| | - Daniel Jasinski
- Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
- Center for RNA Nanotechnology and Nanomedicine, The Ohio State University, Columbus, Ohio 43210, United States
| | - Li-Ching Chen
- Department of Biological Science and Technology, China Medical University, Taichung 406040, Taiwan
| | - Mitch A Phelps
- Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
| | - Yuan-Soon Ho
- Institute of Biochemistry and Molecular Biology, China Medical University, Taichung 406040, Taiwan
| | - Peixuan Guo
- Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States
- Center for RNA Nanotechnology and Nanomedicine, The Ohio State University, Columbus, Ohio 43210, United States
- James Comprehensive Cancer Center, College of Medicine, The Ohio State University, Columbus, Ohio 43210, United States
- Dorothy M. Davis Heart and Lung Research Institute, College of Medicine, The Ohio State University, Columbus, Ohio 43210, United States
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3
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Zuber J, Mathews DH. Estimating RNA Secondary Structure Folding Free Energy Changes with efn2. Methods Mol Biol 2024; 2726:1-13. [PMID: 38780725 DOI: 10.1007/978-1-0716-3519-3_1] [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: 05/25/2024]
Abstract
A number of analyses require estimates of the folding free energy changes of specific RNA secondary structures. These predictions are often based on a set of nearest neighbor parameters that models the folding stability of a RNA secondary structure as the sum of folding stabilities of the structural elements that comprise the secondary structure. In the software suite RNAstructure, the free energy change calculation is implemented in the program efn2. The efn2 program estimates the folding free energy change and the experimental uncertainty in the folding free energy change. It can be run through the graphical user interface for RNAstructure, from the command line, or a web server. This chapter provides detailed protocols for using efn2.
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Affiliation(s)
- Jeffrey Zuber
- Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, NY, USA
| | - David H Mathews
- Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, NY, USA.
- Department of Biostatistics & Computational Biology, University of Rochester Medical Center, Rochester, NY, USA.
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4
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Pham TM, Miffin T, Sun H, Sharp KK, Wang X, Zhu M, Hoshika S, Peterson RJ, Benner SA, Kahn JD, Mathews DH. DNA Structure Design Is Improved Using an Artificially Expanded Alphabet of Base Pairs Including Loop and Mismatch Thermodynamic Parameters. ACS Synth Biol 2023; 12:2750-2763. [PMID: 37671922 PMCID: PMC10510751 DOI: 10.1021/acssynbio.3c00358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Indexed: 09/07/2023]
Abstract
We show that in silico design of DNA secondary structures is improved by extending the base pairing alphabet beyond A-T and G-C to include the pair between 2-amino-8-(1'-β-d-2'-deoxyribofuranosyl)-imidazo-[1,2-a]-1,3,5-triazin-(8H)-4-one and 6-amino-3-(1'-β-d-2'-deoxyribofuranosyl)-5-nitro-(1H)-pyridin-2-one, abbreviated as P and Z. To obtain the thermodynamic parameters needed to include P-Z pairs in the designs, we performed 47 optical melting experiments and combined the results with previous work to fit free energy and enthalpy nearest neighbor folding parameters for P-Z pairs and G-Z wobble pairs. We find G-Z pairs have stability comparable to that of A-T pairs and should therefore be included as base pairs in structure prediction and design algorithms. Additionally, we extrapolated the set of loop, terminal mismatch, and dangling end parameters to include the P and Z nucleotides. These parameters were incorporated into the RNAstructure software package for secondary structure prediction and analysis. Using the RNAstructure Design program, we solved 99 of the 100 design problems posed by Eterna using the ACGT alphabet or supplementing it with P-Z pairs. Extending the alphabet reduced the propensity of sequences to fold into off-target structures, as evaluated by the normalized ensemble defect (NED). The NED values were improved relative to those from the Eterna example solutions in 91 of 99 cases in which Eterna-player solutions were provided. P-Z-containing designs had average NED values of 0.040, significantly below the 0.074 of standard-DNA-only designs, and inclusion of the P-Z pairs decreased the time needed to converge on a design. This work provides a sample pipeline for inclusion of any expanded alphabet nucleotides into prediction and design workflows.
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Affiliation(s)
- Tuan M. Pham
- Department
of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York 14642, United States
| | - Terrel Miffin
- Department
of Chemistry & Biochemistry, University
of Maryland, College
Park, Maryland 20742, United States
| | - Hongying Sun
- Department
of Surgery, University of Rochester Medical
Center, Rochester, New York 14642, United States
| | - Kenneth K. Sharp
- Department
of Chemistry & Biochemistry, University
of Maryland, College
Park, Maryland 20742, United States
| | - Xiaoyu Wang
- Department
of Chemistry & Biochemistry, University
of Maryland, College
Park, Maryland 20742, United States
| | - Mingyi Zhu
- Department
of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York 14642, United States
| | - Shuichi Hoshika
- Foundation
for Applied Molecular Evolution, Alachua, Florida 32615, United States
| | | | - Steven A. Benner
- Foundation
for Applied Molecular Evolution, Alachua, Florida 32615, United States
| | - Jason D. Kahn
- Department
of Chemistry & Biochemistry, University
of Maryland, College
Park, Maryland 20742, United States
| | - David H. Mathews
- Department
of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York 14642, United States
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5
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Pham TM, Miffin T, Sun H, Sharp KK, Wang X, Zhu M, Hoshika S, Peterson RJ, Benner SA, Kahn JD, Mathews DH. DNA Structure Design Is Improved Using an Artificially Expanded Alphabet of Base Pairs Including Loop and Mismatch Thermodynamic Parameters. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.06.543917. [PMID: 37333404 PMCID: PMC10274641 DOI: 10.1101/2023.06.06.543917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
We show that in silico design of DNA secondary structures is improved by extending the base pairing alphabet beyond A-T and G-C to include the pair between 2-amino-8-(1'-β-D-2'-deoxyribofuranosyl)-imidazo-[1,2- a ]-1,3,5-triazin-(8 H )-4-one and 6-amino-3-(1'-β-D-2'-deoxyribofuranosyl)-5-nitro-(1 H )-pyridin-2-one, simply P and Z. To obtain the thermodynamic parameters needed to include P-Z pairs in the designs, we performed 47 optical melting experiments and combined the results with previous work to fit a new set of free energy and enthalpy nearest neighbor folding parameters for P-Z pairs and G-Z wobble pairs. We find that G-Z pairs have stability comparable to A-T pairs and therefore should be considered quantitatively by structure prediction and design algorithms. Additionally, we extrapolated the set of loop, terminal mismatch, and dangling end parameters to include P and Z nucleotides. These parameters were incorporated into the RNAstructure software package for secondary structure prediction and analysis. Using the RNAstructure Design program, we solved 99 of the 100 design problems posed by Eterna using the ACGT alphabet or supplementing with P-Z pairs. Extending the alphabet reduced the propensity of sequences to fold into off-target structures, as evaluated by the normalized ensemble defect (NED). The NED values were improved relative to those from the Eterna example solutions in 91 of 99 cases where Eterna-player solutions were provided. P-Z-containing designs had average NED values of 0.040, significantly below the 0.074 of standard-DNA-only designs, and inclusion of the P-Z pairs decreased the time needed to converge on a design. This work provides a sample pipeline for inclusion of any expanded alphabet nucleotides into prediction and design workflows.
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Affiliation(s)
- Tuan M. Pham
- Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, NY
| | - Terrel Miffin
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD
| | - Hongying Sun
- Department of Surgery, University of Rochester Medical Center, Rochester, NY
| | - Kenneth K. Sharp
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD
| | - Xiaoyu Wang
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD
| | - Mingyi Zhu
- Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, NY
| | | | | | | | - Jason D. Kahn
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD
| | - David H. Mathews
- Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, NY
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6
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Szabat M, Prochota M, Kierzek R, Kierzek E, Mathews DH. A Test and Refinement of Folding Free Energy Nearest Neighbor Parameters for RNA Including N 6-Methyladenosine. J Mol Biol 2022; 434:167632. [PMID: 35588868 PMCID: PMC11235186 DOI: 10.1016/j.jmb.2022.167632] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/29/2022] [Accepted: 05/07/2022] [Indexed: 12/26/2022]
Abstract
RNA folding free energy change parameters are widely used to predict RNA secondary structure and to design RNA sequences. These parameters include terms for the folding free energies of helices and loops. Although the full set of parameters has only been traditionally available for the four common bases and backbone, it is well known that covalent modifications of nucleotides are widespread in natural RNAs. Covalent modifications are also widely used in engineered sequences. We recently derived a full set of nearest neighbor terms for RNA that includes N6-methyladenosine (m6A). In this work, we test the model using 98 optical melting experiments, matching duplexes with or without N6-methylation of A. Most experiments place RRACH, the consensus site of N6-methylation, in a variety of contexts, including helices, bulge loops, internal loops, dangling ends, and terminal mismatches. For matched sets of experiments that include either A or m6A in the same context, we find that the parameters for m6A are as accurate as those for A. Across all experiments, the root mean squared deviation between estimated and experimental free energy changes is 0.67 kcal/mol. We used the new experimental data to refine the set of nearest neighbor parameter terms for m6A. These parameters enable prediction of RNA secondary structures including m6A, which can be used to model how N6-methylation of A affects RNA structure.
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Affiliation(s)
- Marta Szabat
- Institute of Bioorganic Chemistry Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
| | - Martina Prochota
- Institute of Bioorganic Chemistry Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
| | - Ryszard Kierzek
- Institute of Bioorganic Chemistry Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
| | - Elzbieta Kierzek
- Institute of Bioorganic Chemistry Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland.
| | - David H Mathews
- Department of Biochemistry & Biophysics and Center for RNA Biology, 601 Elmwood Avenue, Box 712, School of Medicine and Dentistry, University of Rochester, Rochester, NY 14642, United States.
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7
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Aviran S, Incarnato D. Computational approaches for RNA structure ensemble deconvolution from structure probing data. J Mol Biol 2022; 434:167635. [PMID: 35595163 DOI: 10.1016/j.jmb.2022.167635] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 04/29/2022] [Accepted: 05/05/2022] [Indexed: 12/15/2022]
Abstract
RNA structure probing experiments have emerged over the last decade as a straightforward way to determine the structure of RNA molecules in a number of different contexts. Although powerful, the ability of RNA to dynamically interconvert between, and to simultaneously populate, alternative structural configurations, poses a nontrivial challenge to the interpretation of data derived from these experiments. Recent efforts aimed at developing computational methods for the reconstruction of coexisting alternative RNA conformations from structure probing data are paving the way to the study of RNA structure ensembles, even in the context of living cells. In this review, we critically discuss these methods, their limitations and possible future improvements.
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Affiliation(s)
- Sharon Aviran
- Biomedical Engineering Department and Genome Center, University of California, Davis, CA, USA.
| | - Danny Incarnato
- Department of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute (GBB), University of Groningen, Groningen, the Netherlands.
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8
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Zuber J, Schroeder SJ, Sun H, Turner DH, Mathews DH. Nearest neighbor rules for RNA helix folding thermodynamics: improved end effects. Nucleic Acids Res 2022; 50:5251-5262. [PMID: 35524574 PMCID: PMC9122537 DOI: 10.1093/nar/gkac261] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 03/29/2022] [Accepted: 04/08/2022] [Indexed: 12/26/2022] Open
Abstract
Nearest neighbor parameters for estimating the folding stability of RNA secondary structures are in widespread use. For helices, current parameters penalize terminal AU base pairs relative to terminal GC base pairs. We curated an expanded database of helix stabilities determined by optical melting experiments. Analysis of the updated database shows that terminal penalties depend on the sequence identity of the adjacent penultimate base pair. New nearest neighbor parameters that include this additional sequence dependence accurately predict the measured values of 271 helices in an updated database with a correlation coefficient of 0.982. This refined understanding of helix ends facilitates fitting terms for base pair stacks with GU pairs. Prior parameter sets treated 5′GGUC3′ paired to 3′CUGG5′ separately from other 5′GU3′/3′UG5′ stacks. The improved understanding of helix end stability, however, makes the separate treatment unnecessary. Introduction of the additional terms was tested with three optical melting experiments. The average absolute difference between measured and predicted free energy changes at 37°C for these three duplexes containing terminal adjacent AU and GU pairs improved from 1.38 to 0.27 kcal/mol. This confirms the need for the additional sequence dependence in the model.
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Affiliation(s)
- Jeffrey Zuber
- Alnylam Pharmaceuticals, Inc., Cambridge, MA 02142, USA
| | - Susan J Schroeder
- Department of Chemistry and Biochemistry, and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, USA
| | - Hongying Sun
- Department of Biochemistry & Biophysics, University of Rochester, Rochester, NY 14642, USA.,Center for RNA Biology, University of Rochester, Rochester, NY 14642, USA
| | - Douglas H Turner
- Center for RNA Biology, University of Rochester, Rochester, NY 14642, USA.,Department of Chemistry, University of Rochester, Rochester, NY 14627, USA
| | - David H Mathews
- Department of Biochemistry & Biophysics, University of Rochester, Rochester, NY 14642, USA.,Center for RNA Biology, University of Rochester, Rochester, NY 14642, USA.,Department of Biostatistics & Computational Biology, University of Rochester, Rochester, NY 14642, USA
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9
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Secondary structure prediction for RNA sequences including N 6-methyladenosine. Nat Commun 2022; 13:1271. [PMID: 35277476 PMCID: PMC8917230 DOI: 10.1038/s41467-022-28817-4] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 02/10/2022] [Indexed: 01/22/2023] Open
Abstract
There is increasing interest in the roles of covalently modified nucleotides in RNA. There has been, however, an inability to account for modifications in secondary structure prediction because of a lack of software and thermodynamic parameters. We report the solution for these issues for N6-methyladenosine (m6A), allowing secondary structure prediction for an alphabet of A, C, G, U, and m6A. The RNAstructure software now works with user-defined nucleotide alphabets of any size. We also report a set of nearest neighbor parameters for helices and loops containing m6A, using experiments. Interestingly, N6-methylation decreases folding stability for adenosines in the middle of a helix, has little effect on folding stability for adenosines at the ends of helices, and increases folding stability for unpaired adenosines stacked on a helix. We demonstrate predictions for an N6-methylation-activated protein recognition site from MALAT1 and human transcriptome-wide effects of N6-methylation on the probability of adenosine being buried in a helix. RNA folding free energy nearest neighbor parameters were determined for sequences with the nucleotide m6A. The RNAstructure software package can accommodate modified nucleotides, enabling secondary structure prediction of sequences with m6A.
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10
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Bao C, Zhu M, Nykonchuk I, Wakabayashi H, Mathews DH, Ermolenko DN. Specific length and structure rather than high thermodynamic stability enable regulatory mRNA stem-loops to pause translation. Nat Commun 2022; 13:988. [PMID: 35190568 PMCID: PMC8861025 DOI: 10.1038/s41467-022-28600-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 02/03/2022] [Indexed: 11/09/2022] Open
Abstract
AbstractTranslating ribosomes unwind mRNA secondary structures by three basepairs each elongation cycle. Despite the ribosome helicase, certain mRNA stem-loops stimulate programmed ribosomal frameshift by inhibiting translation elongation. Here, using mutagenesis, biochemical and single-molecule experiments, we examine whether high stability of three basepairs, which are unwound by the translating ribosome, is critical for inducing ribosome pauses. We find that encountering frameshift-inducing mRNA stem-loops from the E. coli dnaX mRNA and the gag-pol transcript of Human Immunodeficiency Virus (HIV) hinders A-site tRNA binding and slows down ribosome translocation by 15-20 folds. By contrast, unwinding of first three basepairs adjacent to the mRNA entry channel slows down the translating ribosome by only 2-3 folds. Rather than high thermodynamic stability, specific length and structure enable regulatory mRNA stem-loops to stall translation by forming inhibitory interactions with the ribosome. Our data provide the basis for rationalizing transcriptome-wide studies of translation and searching for novel regulatory mRNA stem-loops.
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11
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Maruggi G, Ulmer JB, Rappuoli R, Yu D. Self-amplifying mRNA-Based Vaccine Technology and Its Mode of Action. Curr Top Microbiol Immunol 2022; 440:31-70. [PMID: 33861374 DOI: 10.1007/82_2021_233] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Self-amplifying mRNAs derived from the genomes of positive-strand RNA viruses have recently come into focus as a promising technology platform for vaccine development. Non-virally delivered self-amplifying mRNA vaccines have the potential to be highly versatile, potent, streamlined, scalable, and inexpensive. By amplifying their genome and the antigen encoding mRNA in the host cell, the self-amplifying mRNA mimics a viral infection, resulting in sustained levels of the target protein combined with self-adjuvanting innate immune responses, ultimately leading to potent and long-lasting antigen-specific humoral and cellular immune responses. Moreover, in principle, any eukaryotic sequence could be encoded by self-amplifying mRNA without the need to change the manufacturing process, thereby enabling a much faster and flexible research and development timeline than the current vaccines and hence a quicker response to emerging infectious diseases. This chapter highlights the rapid progress made in using non-virally delivered self-amplifying mRNA-based vaccines against infectious diseases in animal models. We provide an overview of the unique attributes of this vaccine approach, summarize the growing body of work defining its mechanism of action, discuss the current challenges and latest advances, and highlight perspectives about the future of this promising technology.
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Affiliation(s)
| | | | | | - Dong Yu
- GSK, 14200 Shady Grove Road, Rockville, MD, 20850, USA. .,Dynavax Technologies, 2100 Powell Street Suite, Emeryville, CA, 94608, USA.
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12
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Sakuraba S, Iwakiri J, Hamada M, Kameda T, Tsuji G, Kimura Y, Abe H, Asai K. Free-Energy Calculation of Ribonucleic Inosines and Its Application to Nearest-Neighbor Parameters. J Chem Theory Comput 2020; 16:5923-5935. [PMID: 32786906 DOI: 10.1021/acs.jctc.0c00270] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Can current simulations quantitatively predict the stability of ribonucleic acids (RNAs)? In this research, we apply a free-energy perturbation simulation of RNAs containing inosine, a modified ribonucleic base, to the derivation of RNA nearest-neighbor parameters. A parameter set derived solely from 30 simulations was used to predict the free-energy difference of the RNA duplex with a mean unbiased error of 0.70 kcal/mol, which is a level of accuracy comparable to that obtained with parameters derived from 25 experiments. We further show that the error can be lowered to 0.60 kcal/mol by combining the simulation-derived free-energy differences with experimentally measured differences. This protocol can be used as a versatile method for deriving nearest-neighbor parameters of RNAs with various modified bases.
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Affiliation(s)
- Shun Sakuraba
- Institute for Quantum Life Science, National Institutes for Quantum and Radiological Science and Technology, Kyoto 619-0215, Japan.,Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba 277-8561, Japan
| | - Junichi Iwakiri
- Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba 277-8561, Japan
| | - Michiaki Hamada
- Faculty of Science and Engineering, Waseda University, Shinjuku-ku, Tokyo 169-8555, Japan.,Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL), National Institute of Advanced Industrial Science and Technology (AIST), Shinjuku-ku, Tokyo 169-8555, Japan
| | - Tomoshi Kameda
- Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo 135-0064, Japan
| | - Genichiro Tsuji
- Department of Chemistry, Graduate School of Science, Nagoya University, Furo, Chikusa, Nagoya 464-8602, Japan.,Division of Organic Chemistry, National Institute of Health Sciences, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 210-9501, Japan
| | - Yasuaki Kimura
- Department of Chemistry, Graduate School of Science, Nagoya University, Furo, Chikusa, Nagoya 464-8602, Japan
| | - Hiroshi Abe
- Department of Chemistry, Graduate School of Science, Nagoya University, Furo, Chikusa, Nagoya 464-8602, Japan
| | - Kiyoshi Asai
- Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba 277-8561, Japan.,Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo 135-0064, Japan
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13
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Yang M, Woolfenden HC, Zhang Y, Fang X, Liu Q, Vigh ML, Cheema J, Yang X, Norris M, Yu S, Carbonell A, Brodersen P, Wang J, Ding Y. Intact RNA structurome reveals mRNA structure-mediated regulation of miRNA cleavage in vivo. Nucleic Acids Res 2020; 48:8767-8781. [PMID: 32652041 PMCID: PMC7470952 DOI: 10.1093/nar/gkaa577] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 06/11/2020] [Accepted: 06/24/2020] [Indexed: 12/18/2022] Open
Abstract
MicroRNA (miRNA)-mediated cleavage is involved in numerous essential cellular pathways. miRNAs recognize target RNAs via sequence complementarity. In addition to complementarity, in vitro and in silico studies have suggested that RNA structure may influence the accessibility of mRNAs to miRNA-induced silencing complexes (miRISCs), thereby affecting RNA silencing. However, the regulatory mechanism of mRNA structure in miRNA cleavage remains elusive. We investigated the role of in vivo RNA secondary structure in miRNA cleavage by developing the new CAP-STRUCTURE-seq method to capture the intact mRNA structurome in Arabidopsis thaliana. This approach revealed that miRNA target sites were not structurally accessible for miRISC binding prior to cleavage in vivo. Instead, we found that the unfolding of the target site structure plays a key role in miRISC activity in vivo. We found that the single-strandedness of the two nucleotides immediately downstream of the target site, named Target Adjacent nucleotide Motif, can promote miRNA cleavage but not miRNA binding, thus decoupling target site binding from cleavage. Our findings demonstrate that mRNA structure in vivo can modulate miRNA cleavage, providing evidence of mRNA structure-dependent regulation of biological processes.
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Affiliation(s)
- Minglei Yang
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Hugh C Woolfenden
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Yueying Zhang
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Xiaofeng Fang
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Qi Liu
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Maria L Vigh
- Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200, Copenhagen N, Denmark
| | - Jitender Cheema
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Xiaofei Yang
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Matthew Norris
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Sha Yu
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
- National Key Laboratory of Plant Molecular Genetics (NKLPMG), CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology (SIPPE), Shanghai Institutes for Biological Sciences (SIBS), Shanghai 200032, People's Republic of China
| | - Alberto Carbonell
- Instituto de Biología Molecular y Celular de Plantas (Consejo Superior de Investigaciones Científicas-Universidad Politécnica de Valencia), Valencia, 46022, Spain
| | - Peter Brodersen
- Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200, Copenhagen N, Denmark
| | - Jiawei Wang
- National Key Laboratory of Plant Molecular Genetics (NKLPMG), CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology (SIPPE), Shanghai Institutes for Biological Sciences (SIBS), Shanghai 200032, People's Republic of China
- ShanghaiTech University, Shanghai 200031, People’s Republic of China
| | - Yiliang Ding
- Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
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Accuracy of MD solvent models in RNA structure refinement assessed via liquid-crystal NMR and spin relaxation data. J Struct Biol 2019; 207:250-259. [PMID: 31279068 DOI: 10.1016/j.jsb.2019.07.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 06/24/2019] [Accepted: 07/01/2019] [Indexed: 11/20/2022]
Abstract
Molecular dynamics (MD) simulations play an important role in characterizing Ribonucleic Acid (RNA) structure, augmenting information from experimental techniques such as Nuclear Magnetic Resonance (NMR). In this work, we examine the accuracy of structural representation resulting from application of a number of explicit and implicit solvent models and refinement protocols against experimental data ranging from high density of residual dipolar coupling (RDC) restraints to completely unrestrained simulations. For a prototype A-form RNA helix, our results indicate that AMBER RNA force field with either implicit or explicit solvent can produce a realistic dynamic representation of RNA helical structure, accurately cross-validating with respect to a diverse array of NMR observables. In refinement against NMR distance restraints, modern MD force fields are found to be equally adequate, with high fidelity cross-validation to the residual dipolar couplings (RDCs) and residual chemical shift anisotropies (RCSAs), while slightly over-estimating structural order as monitored via NMR relaxation data. With restraints trimmed to encode only for base pairing information, cross-validation quality significantly deteriorates, now exhibiting a pronounced dependence on the choice of the solvent model. This deterioration is found to be partially reversible by increasing planarity restraints on the nucleobase geometry. For completely unrestrained MD simulations, the choice of water model becomes very important, with the best-performing TIP4P-Ew accurately reproducing both the RDC and RCSA data, while closely matching the NMR-derived order parameters. The information provided here will serve as a foundation for MD-based refinement of solution state NMR structures of RNA.
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15
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Martini PGV, Guey LT. A New Era for Rare Genetic Diseases: Messenger RNA Therapy. Hum Gene Ther 2019; 30:1180-1189. [PMID: 31179759 DOI: 10.1089/hum.2019.090] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Exogenous delivery of messenger RNA (mRNA) is emerging as a new class of medicine with broad applicability including the potential to treat rare monogenic disorders. Recent advances in mRNA technology, including modifications to the mRNA itself along with improvements to the delivery vehicle, have transformed the utility of mRNA as a potential therapy to restore or replace different types of therapeutic proteins. Preclinical proof-of-concept has been demonstrated for mRNA therapy for three different rare metabolic disorders: methylmalonic acidemia, acute intermittent porphyria, and Fabry disease. Herein, we review those preclinical efficacy and safety studies in multiple animal models. For all three disorders, mRNA therapy restored functional protein to therapeutically relevant levels in target organs, led to sustained and reproducible pharmacology following each dose administration of mRNA, and was well tolerated as supported by liver function tests evaluated in animal models including nonhuman primates. These data provide compelling support for the clinical development of mRNA therapy as a treatment for various rare metabolic disorders.
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Affiliation(s)
| | - Lin T Guey
- Rare Diseases, Moderna, Inc., Cambridge, Massachusetts
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16
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Zuber J, Mathews DH. Estimating uncertainty in predicted folding free energy changes of RNA secondary structures. RNA (NEW YORK, N.Y.) 2019; 25:747-754. [PMID: 30952689 PMCID: PMC6521603 DOI: 10.1261/rna.069203.118] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 04/02/2019] [Indexed: 06/09/2023]
Abstract
Nearest neighbor parameters for estimating the folding stability of RNA are commonly used in secondary structure prediction, for generating folding ensembles of structures, and for analyzing RNA function. Previously, we demonstrated that we could quantify the uncertainties in each nearest neighbor parameter by perturbing the underlying optical melting data within experimental error and rederiving the parameters, which accounts for the substantial correlations that exist between the parameters. In this contribution, we describe a method to estimate uncertainty in the estimated folding stabilities of RNA structures, accounting for correlations in the nearest neighbor parameters. This method is incorporated in the RNA structure software package.
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Affiliation(s)
- Jeffrey Zuber
- Department of Biochemistry and Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York, 14642, USA
| | - David H Mathews
- Department of Biochemistry and Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York, 14642, USA
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York, 14642, USA
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17
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Abstract
Interactions between RNA and proteins are pervasive in biology, driving fundamental processes such as protein translation and participating in the regulation of gene expression. Modeling the energies of RNA-protein interactions is therefore critical for understanding and repurposing living systems but has been hindered by complexities unique to RNA-protein binding. Here, we bring together several advances to complete a calculation framework for RNA-protein binding affinities, including a unified free energy function for bound complexes, automated Rosetta modeling of mutations, and use of secondary structure-based energetic calculations to model unbound RNA states. The resulting Rosetta-Vienna RNP-ΔΔG method achieves root-mean-squared errors (RMSEs) of 1.3 kcal/mol on high-throughput MS2 coat protein-RNA measurements and 1.5 kcal/mol on an independent test set involving the signal recognition particle, human U1A, PUM1, and FOX-1. As a stringent test, the method achieves RMSE accuracy of 1.4 kcal/mol in blind predictions of hundreds of human PUM2-RNA relative binding affinities. Overall, these RMSE accuracies are significantly better than those attained by prior structure-based approaches applied to the same systems. Importantly, Rosetta-Vienna RNP-ΔΔG establishes a framework for further improvements in modeling RNA-protein binding that can be tested by prospective high-throughput measurements on new systems.
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18
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Smith LG, Tan Z, Spasic A, Dutta D, Salas-Estrada LA, Grossfield A, Mathews DH. Chemically Accurate Relative Folding Stability of RNA Hairpins from Molecular Simulations. J Chem Theory Comput 2018; 14:6598-6612. [PMID: 30375860 DOI: 10.1021/acs.jctc.8b00633] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
To benchmark RNA force fields, we compared the folding stabilities of three 12-nucleotide hairpin stem loops estimated by simulation to stabilities determined by experiment. We used umbrella sampling and a reaction coordinate of end-to-end (5' to 3' hydroxyl oxygen) distance to estimate the free energy change of the transition from the native conformation to a fully extended conformation with no hydrogen bonds between non-neighboring bases. Each simulation was performed four times using the AMBER FF99+bsc0+χOL3 force field, and each window, spaced at 1 Å intervals, was sampled for 1 μs, for a total of 552 μs of simulation. We compared differences in the simulated free energy changes to analogous differences in free energies from optical melting experiments using thermodynamic cycles where the free energy change between stretched and random coil sequences is assumed to be sequence-independent. The differences between experimental and simulated ΔΔ G° are, on average, 0.98 ± 0.66 kcal/mol, which is chemically accurate and suggests that analogous simulations could be used predictively. We also report a novel method to identify where replica free energies diverge along a reaction coordinate, thus indicating where additional sampling would most improve convergence. We conclude by discussing methods to more economically perform these simulations.
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Affiliation(s)
- Louis G Smith
- Department of Biochemistry & Biophysics , University of Rochester , Rochester , New York 14642 , United States.,Center for RNA Biology , University of Rochester , Rochester , New York 14642 , United States
| | - Zhen Tan
- Department of Biochemistry & Biophysics , University of Rochester , Rochester , New York 14642 , United States.,Center for RNA Biology , University of Rochester , Rochester , New York 14642 , United States
| | - Aleksandar Spasic
- Department of Biochemistry & Biophysics , University of Rochester , Rochester , New York 14642 , United States.,Center for RNA Biology , University of Rochester , Rochester , New York 14642 , United States
| | - Debapratim Dutta
- Department of Biochemistry & Biophysics , University of Rochester , Rochester , New York 14642 , United States.,Center for RNA Biology , University of Rochester , Rochester , New York 14642 , United States
| | - Leslie A Salas-Estrada
- Department of Biochemistry & Biophysics , University of Rochester , Rochester , New York 14642 , United States
| | - Alan Grossfield
- Department of Biochemistry & Biophysics , University of Rochester , Rochester , New York 14642 , United States
| | - David H Mathews
- Department of Biochemistry & Biophysics , University of Rochester , Rochester , New York 14642 , United States.,Department of Biostatistics and Computational Biology , University of Rochester , Rochester , New York 14642 , United States.,Center for RNA Biology , University of Rochester , Rochester , New York 14642 , United States
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