51
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Ignatova Z, Narberhaus F. Systematic probing of the bacterial RNA structurome to reveal new functions. Curr Opin Microbiol 2017; 36:14-19. [DOI: 10.1016/j.mib.2017.01.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2016] [Revised: 01/06/2017] [Accepted: 01/11/2017] [Indexed: 12/15/2022]
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52
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Choudhary K, Deng F, Aviran S. Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions. QUANTITATIVE BIOLOGY 2017; 5:3-24. [PMID: 28717530 PMCID: PMC5510538 DOI: 10.1007/s40484-017-0093-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2016] [Revised: 12/08/2016] [Accepted: 12/15/2016] [Indexed: 12/30/2022]
Abstract
BACKGROUND Structure profiling experiments provide single-nucleotide information on RNA structure. Recent advances in chemistry combined with application of high-throughput sequencing have enabled structure profiling at transcriptome scale and in living cells, creating unprecedented opportunities for RNA biology. Propelled by these experimental advances, massive data with ever-increasing diversity and complexity have been generated, which give rise to new challenges in interpreting and analyzing these data. RESULTS We review current practices in analysis of structure profiling data with emphasis on comparative and integrative analysis as well as highlight emerging questions. Comparative analysis has revealed structural patterns across transcriptomes and has become an integral component of recent profiling studies. Additionally, profiling data can be integrated into traditional structure prediction algorithms to improve prediction accuracy. CONCLUSIONS To keep pace with experimental developments, methods to facilitate, enhance and refine such analyses are needed. Parallel advances in analysis methodology will complement profiling technologies and help them reach their full potential.
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Affiliation(s)
| | | | - Sharon Aviran
- Department of Biomedical Engineering and Genome Center, University of California at Davis, Davis, CA 95616, USA
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53
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Lee B, Flynn RA, Kadina A, Guo JK, Kool ET, Chang HY. Comparison of SHAPE reagents for mapping RNA structures inside living cells. RNA (NEW YORK, N.Y.) 2017; 23:169-174. [PMID: 27879433 PMCID: PMC5238792 DOI: 10.1261/rna.058784.116] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 11/20/2016] [Indexed: 05/10/2023]
Abstract
Recent advances in SHAPE technology have converted the classic primer extension method to next-generation sequencing platforms, allowing transcriptome-level analysis of RNA secondary structure. In particular, icSHAPE and SHAPE-MaP, using NAI-N3 and 1M7 reagents, respectively, are methods that claim to measure in vivo structure with high-throughput sequencing. However, these compounds have not been compared on an unbiased, raw-signal level. Here, we directly compare several in vivo SHAPE acylation reagents using the simple primer extension assay. We conclude that while multiple SHAPE technologies are effective at measuring purified RNAs in vitro, acylimidazole reagents NAI and NAI-N3 give markedly greater signals with lower background than 1M7 for in vivo measurement of the RNA structurome.
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Affiliation(s)
- Byron Lee
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, California 94305, USA
| | - Ryan A Flynn
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, California 94305, USA
| | - Anastasia Kadina
- Department of Chemistry, Stanford University, Stanford, California 94305, USA
| | - Jimmy K Guo
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, California 94305, USA
| | - Eric T Kool
- Department of Chemistry, Stanford University, Stanford, California 94305, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, California 94305, USA
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54
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Hoynes-O’Connor A, Moon TS. Development of Design Rules for Reliable Antisense RNA Behavior in E. coli. ACS Synth Biol 2016; 5:1441-1454. [PMID: 27434774 DOI: 10.1021/acssynbio.6b00036] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A key driver of synthetic biology is the development of designable genetic parts with predictable behaviors that can be quickly implemented in complex genetic systems. However, the intrinsic complexity of gene regulation can make the rational design of genetic parts challenging. This challenge is apparent in the design of antisense RNA (asRNA) regulators. Though asRNAs are well-known regulators, the literature governing their design is conflicting and leaves the synthetic biology community without clear asRNA design rules. The goal of this study is to perform a comprehensive experimental characterization and statistical analysis of 121 unique asRNA regulators in order to resolve the conflicts that currently exist in the literature. asRNAs usually consist of two regions, the Hfq binding site and the target binding region (TBR). First, the behaviors of several high-performing Hfq binding sites were compared, in terms of their ability to improve repression efficiencies and their orthogonality. Next, a large-scale analysis of TBR design parameters identified asRNA length, the thermodynamics of asRNA-mRNA complex formation, and the percent of target mismatch as key parameters for TBR design. These parameters were used to develop simple asRNA design rules. Finally, these design rules were applied to construct both a simple and a complex genetic circuit containing different asRNAs, and predictable behavior was observed in both circuits. The results presented in this study will drive synthetic biology forward by providing useful design guidelines for the construction of asRNA regulators with predictable behaviors.
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Affiliation(s)
- Allison Hoynes-O’Connor
- Department
of Energy, Environmental
and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Tae Seok Moon
- Department
of Energy, Environmental
and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
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55
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Choudhary K, Shih NP, Deng F, Ledda M, Li B, Aviran S. Metrics for rapid quality control in RNA structure probing experiments. Bioinformatics 2016; 32:3575-3583. [PMID: 27497441 DOI: 10.1093/bioinformatics/btw501] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Revised: 07/02/2016] [Accepted: 07/26/2016] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION The diverse functionalities of RNA can be attributed to its capacity to form complex and varied structures. The recent proliferation of new structure probing techniques coupled with high-throughput sequencing has helped RNA studies expand in both scope and depth. Despite differences in techniques, most experiments face similar challenges in reproducibility due to the stochastic nature of chemical probing and sequencing. As these protocols expand to transcriptome-wide studies, quality control becomes a more daunting task. General and efficient methodologies are needed to quantify variability and quality in the wide range of current and emerging structure probing experiments. RESULTS We develop metrics to rapidly and quantitatively evaluate data quality from structure probing experiments, demonstrating their efficacy on both small synthetic libraries and transcriptome-wide datasets. We use a signal-to-noise ratio concept to evaluate replicate agreement, which has the capacity to identify high-quality data. We also consider and compare two methods to assess variability inherent in probing experiments, which we then utilize to evaluate the coverage adjustments needed to meet desired quality. The developed metrics and tools will be useful in summarizing large-scale datasets and will help standardize quality control in the field. AVAILABILITY AND IMPLEMENTATION The data and methods used in this article are freely available at: http://bme.ucdavis.edu/aviranlab/SPEQC_software CONTACT: saviran@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Krishna Choudhary
- Department of Biomedical Engineering and Genome Center, University of California at Davis, Davis, CA, USA
| | - Nathan P Shih
- Department of Biomedical Engineering and Genome Center, University of California at Davis, Davis, CA, USA
| | - Fei Deng
- Department of Biomedical Engineering and Genome Center, University of California at Davis, Davis, CA, USA
| | - Mirko Ledda
- Department of Biomedical Engineering and Genome Center, University of California at Davis, Davis, CA, USA
| | - Bo Li
- Center for RNA Systems Biology, University of California at Berkeley, Berkeley, CA, USA
| | - Sharon Aviran
- Department of Biomedical Engineering and Genome Center, University of California at Davis, Davis, CA, USA
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56
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Takahashi MK, Watters KE, Gasper PM, Abbott TR, Carlson PD, Chen AA, Lucks JB. Using in-cell SHAPE-Seq and simulations to probe structure-function design principles of RNA transcriptional regulators. RNA (NEW YORK, N.Y.) 2016; 22:920-33. [PMID: 27103533 PMCID: PMC4878617 DOI: 10.1261/rna.054916.115] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 03/18/2016] [Indexed: 05/25/2023]
Abstract
Antisense RNA-mediated transcriptional regulators are powerful tools for controlling gene expression and creating synthetic gene networks. RNA transcriptional repressors derived from natural mechanisms called attenuators are particularly versatile, though their mechanistic complexity has made them difficult to engineer. Here we identify a new structure-function design principle for attenuators that enables the forward engineering of new RNA transcriptional repressors. Using in-cell SHAPE-Seq to characterize the structures of attenuator variants within Escherichia coli, we show that attenuator hairpins that facilitate interaction with antisense RNAs require interior loops for proper function. Molecular dynamics simulations of these attenuator variants suggest these interior loops impart structural flexibility. We further observe hairpin flexibility in the cellular structures of natural RNA mechanisms that use antisense RNA interactions to repress translation, confirming earlier results from in vitro studies. Finally, we design new transcriptional attenuators in silico using an interior loop as a structural requirement and show that they function as desired in vivo. This work establishes interior loops as an important structural element for designing synthetic RNA gene regulators. We anticipate that the coupling of experimental measurement of cellular RNA structure and function with computational modeling will enable rapid discovery of structure-function design principles for a diverse array of natural and synthetic RNA regulators.
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Affiliation(s)
- Melissa K Takahashi
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14850, USA
| | - Kyle E Watters
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14850, USA
| | - Paul M Gasper
- Department of Chemistry and RNA Institute, University at Albany, Albany, New York 12222, USA
| | - Timothy R Abbott
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14850, USA
| | - Paul D Carlson
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14850, USA
| | - Alan A Chen
- Department of Chemistry and RNA Institute, University at Albany, Albany, New York 12222, USA
| | - Julius B Lucks
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14850, USA
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57
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Strobel EJ, Watters KE, Loughrey D, Lucks JB. RNA systems biology: uniting functional discoveries and structural tools to understand global roles of RNAs. Curr Opin Biotechnol 2016; 39:182-191. [PMID: 27132125 DOI: 10.1016/j.copbio.2016.03.019] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Revised: 03/24/2016] [Accepted: 03/31/2016] [Indexed: 12/11/2022]
Abstract
RNAs assume sophisticated structures that are active in myriad cellular processes. In this review, we highlight newly identified ribozymes, riboswitches, and small RNAs, some of which control the function of cellular metabolic and gene expression networks. We then examine recent developments in genome-wide RNA structure probing technologies that are yielding new insights into the structural landscape of the transcriptome. Finally, we discuss how these RNA 'structomic' methods can address emerging questions in RNA systems biology, from the mechanisms behind long non-coding RNAs to new bases for human diseases.
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Affiliation(s)
- Eric J Strobel
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY, United States
| | - Kyle E Watters
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY, United States
| | - David Loughrey
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY, United States
| | - Julius B Lucks
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY, United States.
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58
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Watters KE, Yu AM, Strobel EJ, Settle AH, Lucks JB. Characterizing RNA structures in vitro and in vivo with selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq). Methods 2016; 103:34-48. [PMID: 27064082 DOI: 10.1016/j.ymeth.2016.04.002] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Revised: 04/01/2016] [Accepted: 04/04/2016] [Indexed: 01/08/2023] Open
Abstract
RNA molecules adopt a wide variety of structures that perform many cellular functions, including, among others, catalysis, small molecule sensing, and cellular defense. Our ability to characterize, predict, and design RNA structures are key factors for understanding and controlling the biological roles of RNAs. Fortunately, there has been rapid progress in this area, especially with respect to experimental methods that can characterize RNA structures in a high throughput fashion using chemical probing and next-generation sequencing. Here, we describe one such method, selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq), which measures nucleotide resolution flexibility information for RNAs in vitro and in vivo. We outline the process of designing and performing a SHAPE-Seq experiment and describe methods for using experimental SHAPE-Seq data to restrain computational folding algorithms to generate more accurate predictions of RNA secondary structure. We also provide a number of examples of SHAPE-Seq reactivity spectra obtained in vitro and in vivo and discuss important considerations for performing SHAPE-Seq experiments, both in terms of collecting and analyzing data. Finally, we discuss improvements and extensions of these experimental and computational techniques that promise to deepen our knowledge of RNA folding and function.
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Affiliation(s)
- Kyle E Watters
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States
| | - Angela M Yu
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States; Tri-Institutional Program in Computational Biology and Medicine, Cornell University, Ithaca, New York, Weill Cornell Medical College, New York, New York, Memorial Sloan-Kettering Cancer Center, New York, New York, United States; Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, United States
| | - Eric J Strobel
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States
| | - Alex H Settle
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States
| | - Julius B Lucks
- School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States.
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59
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McKeague M, Wong RS, Smolke CD. Opportunities in the design and application of RNA for gene expression control. Nucleic Acids Res 2016; 44:2987-99. [PMID: 26969733 PMCID: PMC4838379 DOI: 10.1093/nar/gkw151] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Accepted: 02/29/2016] [Indexed: 12/15/2022] Open
Abstract
The past decade of synthetic biology research has witnessed numerous advances in the development of tools and frameworks for the design and characterization of biological systems. Researchers have focused on the use of RNA for gene expression control due to its versatility in sensing molecular ligands and the relative ease by which RNA can be modeled and designed compared to proteins. We review the recent progress in the field with respect to RNA-based genetic devices that are controlled through small molecule and protein interactions. We discuss new approaches for generating and characterizing these devices and their underlying components. We also highlight immediate challenges, future directions and recent applications of synthetic RNA devices in engineered biological systems.
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Affiliation(s)
- Maureen McKeague
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Remus S Wong
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Christina D Smolke
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
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60
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Smola MJ, Calabrese JM, Weeks KM. Detection of RNA-Protein Interactions in Living Cells with SHAPE. Biochemistry 2015; 54:6867-75. [PMID: 26544910 DOI: 10.1021/acs.biochem.5b00977] [Citation(s) in RCA: 125] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
SHAPE-MaP is unique among RNA structure probing strategies in that it both measures flexibility at single-nucleotide resolution and quantifies the uncertainties in these measurements. We report a straightforward analytical framework that incorporates these uncertainties to allow detection of RNA structural differences between any two states, and we use it here to detect RNA-protein interactions in healthy mouse trophoblast stem cells. We validate this approach by analysis of three model cytoplasmic and nuclear ribonucleoprotein complexes, in 2 min in-cell probing experiments. In contrast, data produced by alternative in-cell SHAPE probing methods correlate poorly (r = 0.2) with those generated by SHAPE-MaP and do not yield accurate signals for RNA-protein interactions. We then examine RNA-protein and RNA-substrate interactions in the RNase MRP complex and, by comparing in-cell interaction sites with disease-associated mutations, characterize these noncoding mutations in terms of molecular phenotype. Together, these results reveal that SHAPE-MaP can define true interaction sites and infer RNA functions under native cellular conditions with limited preexisting knowledge of the proteins or RNAs involved.
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Affiliation(s)
- Matthew J Smola
- Department of Chemistry, University of North Carolina , Chapel Hill, North Carolina 27599-3290, United States
| | - J Mauro Calabrese
- Department of Pharmacology and Lineberger Comprehensive Cancer Center, University of North Carolina , Chapel Hill, North Carolina 27599, United States
| | - Kevin M Weeks
- Department of Chemistry, University of North Carolina , Chapel Hill, North Carolina 27599-3290, United States
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