Evidence map›Paper›PMID 35802676›Full record

ArticlePloS one2022

Enzymatic incorporation of an isotope-labeled adenine into RNA for the study of conformational dynamics by NMR.

Hannes Feyrer, Cenk Onur Gurdap, Maja Marušič, Judith Schlagnitweit, Katja Petzold

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hannes FeyrerDepartment of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden.ORCID 0000-0001-5281-7248
Cenk Onur GurdapDepartment of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden.ORCID 0000-0002-5327-2523
Maja MarušičDepartment of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden.
Judith SchlagnitweitDepartment of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden.
Katja PetzoldDepartment of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden.ORCID 0000-0001-9470-0347

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Solution NMR spectroscopy is a well-established tool with unique advantages for structural studies of RNA molecules. However, for large RNA sequences, the NMR resonances often overlap severely. A reliable way to perform resonance assignment and allow further analysis despite spectral crowding is the use of site-specific isotope labeling in sample preparation. While solid-phase oligonucleotide synthesis has several advantages, RNA length and availability of isotope-labeled building blocks are persistent issues. Purely enzymatic methods represent an alternative and have been presented in the literature. In this study, we report on a method in which we exploit the preference of T7 RNA polymerase for nucleotide monophosphates over triphosphates for the 5' position, which allows 5'-labeling of RNA. Successive ligation to an unlabeled RNA strand generates a site-specifically labeled RNA. We show the successful production of such an RNA sample for NMR studies, report on experimental details and expected yields, and present the surprising finding of a previously hidden set of peaks which reveals conformational exchange in the RNA structure. This study highlights the feasibility of site-specific isotope-labeling of RNA with enzymatic methods.

Indexed as

AdenineRNAIsotope LabelingIsotopesMagnetic Resonance SpectroscopyNuclear Magnetic Resonance, BiomolecularNucleic Acid ConformationAdenineIsotopesRNA

Identifiers

PMID35802676
PMCPMC9269771

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.