A novel SHAPE reagent enables the analysis of RNA structure in living cells with unprecedented accuracy.

Tycho Marinus,Craig A Ogle,Danny Incarnato,Adam B Fessler

doi:10.1093/nar/gkaa1255

A novel SHAPE reagent enables the analysis of RNA structure in living cells with unprecedented accuracy.

Tycho Marinus, Craig A Ogle + Show 2 more

Open Access

https://doi.org/10.1093/nar/gkaa1255

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Abstract

Due to the mounting evidence that RNA structure plays a critical role in regulating almost any physiological as well as pathological process, being able to accurately define the folding of RNA molecules within living cells has become a crucial need. We introduce here 2-aminopyridine-3-carboxylic acid imidazolide (2A3), as a general probe for the interrogation of RNA structures in vivo. 2A3 shows moderate improvements with respect to the state-of-the-art selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) reagent NAI on naked RNA under in vitro conditions, but it significantly outperforms NAI when probing RNA structure in vivo, particularly in bacteria, underlining its increased ability to permeate biological membranes. When used as a restraint to drive RNA structure prediction, data derived by SHAPE-MaP with 2A3 yields more accurate predictions than NAI-derived data. Due to its extreme efficiency and accuracy, we can anticipate that 2A3 will rapidly take over conventional SHAPE reagents for probing RNA structures both in vitro and in vivo.

Highlights

For the synthesis of NAI, I6, I5, 1-methylimidazole-4-carboxylic acid imidazolide (1M4), benzotriazole-5-carboxylic acid imidazolide (B5), 6-aminopyridine-3-carboxylic acid imidazolide (6A3), nicotinic acid imidazolide (NIC) and 2-aminopyridine-3-carboxylic acid imidazolide (2A3), respectively 137.14, 173.17, 163.17, 126.11, 163.13, 138.12, 123.11 and 138.12 mg were resuspended in 500 ␮l DMSO anhydrous (Sigma Aldrich, cat. 276855). ∼1.3 g of CDI were resuspended in 4 ml DMSO anhydrous and 500 ␮l of this solution were added to each 500 ␮l of carboxylic acids in DMSO while constantly stirring, over a period of 5 min
Analysis of the distribution of per-base mutation frequencies across 16S and 23S rRNAs showed that, while TGIRT-III has lower background mutation frequencies compared to SuperScript II (SSII) as previously reported [22], SSII shows a higher and more significant increase in the mutation rates measured in the NAI treated sample with respect to the DMSO control
Receiver Operating Characteristic (ROC) curves built with respect to unpaired versus paired residues from E. coli rRNAs revealed nearly comparable accuracies for 6A3, B5, NIC and 2A3, with NIC and 2A3 showing a slightly higher area under the curve (AUC), independently of DMSO background signal subtraction (Figure 1B and Supplementary Figure S2A)

Summary

Introduction

In light of its importance, being able to define the structure of an RNA molecule is a key need towards understanding its mechanism of action It is still impossible for most RNAs to define their secondary structures starting solely from their primary sequence. The accuracy of thermodynamics-driven RNA structure determination algorithms can be improved by incorporating experimental constraints from RNA footprinting experiments These experiments are based on the use of specific chemicals or nucleases to probe the conformation of RNA residues. When informed with these experimentally-derived constraints, the accuracy of RNA structure prediction algorithms greatly improves [8,9,10,11,12]

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