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Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo
When a ribonucleic acid (RNA) molecule folds, it often does not adopt a single, well-defined conformation. The folding energy landscape of an RNA is highly dependent on its nucleotide sequence and molecular environment. Cellular molecules sometimes alter the energy landscape, thereby changing the en...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Biophysical Society
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529173/ https://www.ncbi.nlm.nih.gov/pubmed/28625696 http://dx.doi.org/10.1016/j.bpj.2017.05.031 |
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author | Woods, Chanin T. Lackey, Lela Williams, Benfeard Dokholyan, Nikolay V. Gotz, David Laederach, Alain |
author_facet | Woods, Chanin T. Lackey, Lela Williams, Benfeard Dokholyan, Nikolay V. Gotz, David Laederach, Alain |
author_sort | Woods, Chanin T. |
collection | PubMed |
description | When a ribonucleic acid (RNA) molecule folds, it often does not adopt a single, well-defined conformation. The folding energy landscape of an RNA is highly dependent on its nucleotide sequence and molecular environment. Cellular molecules sometimes alter the energy landscape, thereby changing the ensemble of likely low-energy conformations. The effects of these energy landscape changes on the conformational ensemble are particularly challenging to visualize for large RNAs. We have created a robust approach for visualizing the conformational ensemble of RNAs that is well suited for in vitro versus in vivo comparisons. Our method creates a stable map of conformational space for a given RNA sequence. We first identify single point mutations in the RNA that maximally sample suboptimal conformational space based on the ensemble’s partition function. Then, we cluster these diverse ensembles to identify the most diverse partition functions for Boltzmann stochastic sampling. By using, to our knowledge, a novel nestedness distance metric, we iteratively add mutant suboptimal ensembles to converge on a stable 2D map of conformational space. We then compute the selective 2′ hydroxyl acylation by primer extension (SHAPE)-directed ensemble for the RNA folding under different conditions, and we project these ensembles on the map to visualize. To validate our approach, we established a conformational map of the Vibrio vulnificus add adenine riboswitch that reveals five classes of structures. In the presence of adenine, projection of the SHAPE-directed sampling correctly identified the on-conformation; without the ligand, only off-conformations were visualized. We also collected the whole-transcript in vitro and in vivo SHAPE-MaP for human β-actin messenger RNA that revealed similar global folds in both conditions. Nonetheless, a comparison of in vitro and in vivo data revealed that specific regions exhibited significantly different SHAPE-MaP profiles indicative of structural rearrangements, including rearrangement consistent with binding of the zipcode protein in a region distal to the stop codon. |
format | Online Article Text |
id | pubmed-5529173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Biophysical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-55291732018-07-25 Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo Woods, Chanin T. Lackey, Lela Williams, Benfeard Dokholyan, Nikolay V. Gotz, David Laederach, Alain Biophys J Articles When a ribonucleic acid (RNA) molecule folds, it often does not adopt a single, well-defined conformation. The folding energy landscape of an RNA is highly dependent on its nucleotide sequence and molecular environment. Cellular molecules sometimes alter the energy landscape, thereby changing the ensemble of likely low-energy conformations. The effects of these energy landscape changes on the conformational ensemble are particularly challenging to visualize for large RNAs. We have created a robust approach for visualizing the conformational ensemble of RNAs that is well suited for in vitro versus in vivo comparisons. Our method creates a stable map of conformational space for a given RNA sequence. We first identify single point mutations in the RNA that maximally sample suboptimal conformational space based on the ensemble’s partition function. Then, we cluster these diverse ensembles to identify the most diverse partition functions for Boltzmann stochastic sampling. By using, to our knowledge, a novel nestedness distance metric, we iteratively add mutant suboptimal ensembles to converge on a stable 2D map of conformational space. We then compute the selective 2′ hydroxyl acylation by primer extension (SHAPE)-directed ensemble for the RNA folding under different conditions, and we project these ensembles on the map to visualize. To validate our approach, we established a conformational map of the Vibrio vulnificus add adenine riboswitch that reveals five classes of structures. In the presence of adenine, projection of the SHAPE-directed sampling correctly identified the on-conformation; without the ligand, only off-conformations were visualized. We also collected the whole-transcript in vitro and in vivo SHAPE-MaP for human β-actin messenger RNA that revealed similar global folds in both conditions. Nonetheless, a comparison of in vitro and in vivo data revealed that specific regions exhibited significantly different SHAPE-MaP profiles indicative of structural rearrangements, including rearrangement consistent with binding of the zipcode protein in a region distal to the stop codon. The Biophysical Society 2017-07-25 2017-06-15 /pmc/articles/PMC5529173/ /pubmed/28625696 http://dx.doi.org/10.1016/j.bpj.2017.05.031 Text en © 2017 Biophysical Society. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Articles Woods, Chanin T. Lackey, Lela Williams, Benfeard Dokholyan, Nikolay V. Gotz, David Laederach, Alain Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo |
title | Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo |
title_full | Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo |
title_fullStr | Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo |
title_full_unstemmed | Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo |
title_short | Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo |
title_sort | comparative visualization of the rna suboptimal conformational ensemble in vivo |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529173/ https://www.ncbi.nlm.nih.gov/pubmed/28625696 http://dx.doi.org/10.1016/j.bpj.2017.05.031 |
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