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Rich RNA Structure Landscapes Revealed by Mutate-and-Map Analysis.

Cordero P, Das R - PLoS Comput. Biol. (2015)

Bottom Line: In experimental benchmarks, M2-REEFFIT recovers the structure landscapes of a 35-nt MedLoop hairpin, a 110-nt 16S rRNA four-way junction with an excited state, a 25-nt bistable hairpin, and a 112-nt three-state adenine riboswitch with its expression platform, molecules whose characterization previously required expert mutational analysis and specialized NMR or chemical mapping experiments.An artificial flavin mononucleotide riboswitch and a randomly generated RNA sequence are found to interconvert between three or more states, including structures for which there was no design, but that could be stabilized through mutations.These results highlight the likely pervasiveness of rich landscapes with multiple secondary structures in both natural and artificial RNAs and demonstrate an automated chemical/computational route for their empirical characterization.

View Article: PubMed Central - PubMed

Affiliation: Biomedical Informatics Program, Stanford University, Stanford, California, United States of America.

ABSTRACT
Landscapes exhibiting multiple secondary structures arise in natural RNA molecules that modulate gene expression, protein synthesis, and viral infection [corrected]. We report herein that high-throughput chemical experiments can isolate an RNA's multiple alternative secondary structures as they are stabilized by systematic mutagenesis (mutate-and-map, M2) and that a computational algorithm, REEFFIT, enables unbiased reconstruction of these states' structures and populations. In an in silico benchmark on non-coding RNAs with complex landscapes, M2-REEFFIT recovers 95% of RNA helices present with at least 25% population while maintaining a low false discovery rate (10%) and conservative error estimates. In experimental benchmarks, M2-REEFFIT recovers the structure landscapes of a 35-nt MedLoop hairpin, a 110-nt 16S rRNA four-way junction with an excited state, a 25-nt bistable hairpin, and a 112-nt three-state adenine riboswitch with its expression platform, molecules whose characterization previously required expert mutational analysis and specialized NMR or chemical mapping experiments. With this validation, M2-REEFFIT enabled tests of whether artificial RNA sequences might exhibit complex landscapes in the absence of explicit design. An artificial flavin mononucleotide riboswitch and a randomly generated RNA sequence are found to interconvert between three or more states, including structures for which there was no design, but that could be stabilized through mutations. These results highlight the likely pervasiveness of rich landscapes with multiple secondary structures in both natural and artificial RNAs and demonstrate an automated chemical/computational route for their empirical characterization.

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(a) RNA molecules can have diverse structural landscapes that are linked to their biological functions. Some structural landscapes, such as those for stable ribosome domains, can have a single, stable structure that is critical for function. Others may have been selected to have an equilibrium of two or three structures, such as riboswitches, that enables them to fine tune their response to small molecules or macromolecular partners. There may be other RNAs with a heterogeneous landscape, such as random RNA sequences, that may require this heterogeneity for function. (b) Chemical mapping (footprinting) experiments for probing RNA structure can be conceptualized as linear combinations of the underlying structures in the RNA’s structural ensemble. The chemical mapping profiles of an ensemble of two structures, represented here as one-dimensional heat maps, are scaled by their respective Boltzmann weights, W1 and W2, and added together with experimental noise to form the observed chemical mapping pro?le of an RNA. (c) Mutate-and-map (M2) experiments are measurements of perturbed versions of an underlying structural landscape. A novel method, REEFFIT uses a blind source separation framework to automatically reconstruct this landscape by joint estimation of hidden reactivity profiles and fractions for a set of structures.
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pcbi.1004473.g001: (a) RNA molecules can have diverse structural landscapes that are linked to their biological functions. Some structural landscapes, such as those for stable ribosome domains, can have a single, stable structure that is critical for function. Others may have been selected to have an equilibrium of two or three structures, such as riboswitches, that enables them to fine tune their response to small molecules or macromolecular partners. There may be other RNAs with a heterogeneous landscape, such as random RNA sequences, that may require this heterogeneity for function. (b) Chemical mapping (footprinting) experiments for probing RNA structure can be conceptualized as linear combinations of the underlying structures in the RNA’s structural ensemble. The chemical mapping profiles of an ensemble of two structures, represented here as one-dimensional heat maps, are scaled by their respective Boltzmann weights, W1 and W2, and added together with experimental noise to form the observed chemical mapping pro?le of an RNA. (c) Mutate-and-map (M2) experiments are measurements of perturbed versions of an underlying structural landscape. A novel method, REEFFIT uses a blind source separation framework to automatically reconstruct this landscape by joint estimation of hidden reactivity profiles and fractions for a set of structures.

Mentions: RNAs are deeply involved in gene expression, gene regulation, and structural scaffolding and are forming the basis of novel approaches to control these processes [1–3]. Several of RNA’s natural and engineered roles rely on its ability to fold into and interconvert between multiple functional structures. Ribozymes, riboswitches, and protein-complexed RNAs transition between several states to detect and respond to small molecules and other macromolecules; to proceed through numerous steps of RNA splicing reactions; to initiate, catalyze, and proof-read protein translation; to activate logical circuits in cells; and to package, release, and replicate RNA viruses [4–9]. The number of structures and equilibrium fractions that constitute these ‘dynamic structure landscapes’ are linked to the biological function of the RNA (Fig 1a). Rationally dissecting and re-engineering these landscapes depends on knowledge of the alternative states of an RNA’s structural ensemble [10,11].


Rich RNA Structure Landscapes Revealed by Mutate-and-Map Analysis.

Cordero P, Das R - PLoS Comput. Biol. (2015)

(a) RNA molecules can have diverse structural landscapes that are linked to their biological functions. Some structural landscapes, such as those for stable ribosome domains, can have a single, stable structure that is critical for function. Others may have been selected to have an equilibrium of two or three structures, such as riboswitches, that enables them to fine tune their response to small molecules or macromolecular partners. There may be other RNAs with a heterogeneous landscape, such as random RNA sequences, that may require this heterogeneity for function. (b) Chemical mapping (footprinting) experiments for probing RNA structure can be conceptualized as linear combinations of the underlying structures in the RNA’s structural ensemble. The chemical mapping profiles of an ensemble of two structures, represented here as one-dimensional heat maps, are scaled by their respective Boltzmann weights, W1 and W2, and added together with experimental noise to form the observed chemical mapping pro?le of an RNA. (c) Mutate-and-map (M2) experiments are measurements of perturbed versions of an underlying structural landscape. A novel method, REEFFIT uses a blind source separation framework to automatically reconstruct this landscape by joint estimation of hidden reactivity profiles and fractions for a set of structures.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4643908&req=5

pcbi.1004473.g001: (a) RNA molecules can have diverse structural landscapes that are linked to their biological functions. Some structural landscapes, such as those for stable ribosome domains, can have a single, stable structure that is critical for function. Others may have been selected to have an equilibrium of two or three structures, such as riboswitches, that enables them to fine tune their response to small molecules or macromolecular partners. There may be other RNAs with a heterogeneous landscape, such as random RNA sequences, that may require this heterogeneity for function. (b) Chemical mapping (footprinting) experiments for probing RNA structure can be conceptualized as linear combinations of the underlying structures in the RNA’s structural ensemble. The chemical mapping profiles of an ensemble of two structures, represented here as one-dimensional heat maps, are scaled by their respective Boltzmann weights, W1 and W2, and added together with experimental noise to form the observed chemical mapping pro?le of an RNA. (c) Mutate-and-map (M2) experiments are measurements of perturbed versions of an underlying structural landscape. A novel method, REEFFIT uses a blind source separation framework to automatically reconstruct this landscape by joint estimation of hidden reactivity profiles and fractions for a set of structures.
Mentions: RNAs are deeply involved in gene expression, gene regulation, and structural scaffolding and are forming the basis of novel approaches to control these processes [1–3]. Several of RNA’s natural and engineered roles rely on its ability to fold into and interconvert between multiple functional structures. Ribozymes, riboswitches, and protein-complexed RNAs transition between several states to detect and respond to small molecules and other macromolecules; to proceed through numerous steps of RNA splicing reactions; to initiate, catalyze, and proof-read protein translation; to activate logical circuits in cells; and to package, release, and replicate RNA viruses [4–9]. The number of structures and equilibrium fractions that constitute these ‘dynamic structure landscapes’ are linked to the biological function of the RNA (Fig 1a). Rationally dissecting and re-engineering these landscapes depends on knowledge of the alternative states of an RNA’s structural ensemble [10,11].

Bottom Line: In experimental benchmarks, M2-REEFFIT recovers the structure landscapes of a 35-nt MedLoop hairpin, a 110-nt 16S rRNA four-way junction with an excited state, a 25-nt bistable hairpin, and a 112-nt three-state adenine riboswitch with its expression platform, molecules whose characterization previously required expert mutational analysis and specialized NMR or chemical mapping experiments.An artificial flavin mononucleotide riboswitch and a randomly generated RNA sequence are found to interconvert between three or more states, including structures for which there was no design, but that could be stabilized through mutations.These results highlight the likely pervasiveness of rich landscapes with multiple secondary structures in both natural and artificial RNAs and demonstrate an automated chemical/computational route for their empirical characterization.

View Article: PubMed Central - PubMed

Affiliation: Biomedical Informatics Program, Stanford University, Stanford, California, United States of America.

ABSTRACT
Landscapes exhibiting multiple secondary structures arise in natural RNA molecules that modulate gene expression, protein synthesis, and viral infection [corrected]. We report herein that high-throughput chemical experiments can isolate an RNA's multiple alternative secondary structures as they are stabilized by systematic mutagenesis (mutate-and-map, M2) and that a computational algorithm, REEFFIT, enables unbiased reconstruction of these states' structures and populations. In an in silico benchmark on non-coding RNAs with complex landscapes, M2-REEFFIT recovers 95% of RNA helices present with at least 25% population while maintaining a low false discovery rate (10%) and conservative error estimates. In experimental benchmarks, M2-REEFFIT recovers the structure landscapes of a 35-nt MedLoop hairpin, a 110-nt 16S rRNA four-way junction with an excited state, a 25-nt bistable hairpin, and a 112-nt three-state adenine riboswitch with its expression platform, molecules whose characterization previously required expert mutational analysis and specialized NMR or chemical mapping experiments. With this validation, M2-REEFFIT enabled tests of whether artificial RNA sequences might exhibit complex landscapes in the absence of explicit design. An artificial flavin mononucleotide riboswitch and a randomly generated RNA sequence are found to interconvert between three or more states, including structures for which there was no design, but that could be stabilized through mutations. These results highlight the likely pervasiveness of rich landscapes with multiple secondary structures in both natural and artificial RNAs and demonstrate an automated chemical/computational route for their empirical characterization.

Show MeSH
Related in: MedlinePlus