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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...

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Autores principales: Woods, Chanin T., Lackey, Lela, Williams, Benfeard, Dokholyan, Nikolay V., Gotz, David, Laederach, Alain
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Biophysical Society 2017
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.
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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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