Evidence map›Paper›PMID 42862243›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2027

Fast Analysis of RNA from Transcription and Rho-Dependent Termination Assays Using Automated Capillary Electrophoresis.

Gabriel Pino-Peco, Konstantin Brodolin

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Article in Methods in molecular biology (Clifton, N.J.), 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Gabriel Pino-PecoInstitut de Recherche en Infectiologie de Montpellier, Univ Montpellier, CNRS, Montpellier, France.
Konstantin BrodolinInstitut de Recherche en Infectiologie de Montpellier, Univ Montpellier, CNRS, Montpellier, France. konstantin.brodolin@inserm.fr.ORCID http://orcid.org/0000-0003-3124-7586

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional analysis of RNA products synthesized by bacterial RNA polymerase (RNAP) in in vitro transcription assays relies on radioactive labeling, followed by separation of labeled RNAs by denaturing urea-polyacrylamide gel electrophoresis (PAGE). This approach provides excellent resolution across a wide range of RNA lengths (from 2 nt to several hundred nucleotides), but the use of radioisotopes requires specialized facilities, strict waste-disposal procedures, and is often restricted. To circumvent these limitations, we adapted a standard in vitro transcription assay for use with the Agilent 2100 Bioanalyzer capillary electrophoresis system. Here, we describe the application of this method to analyze run-off transcription by Mycobacterium tuberculosis (Mtb) RNAP and its transcription termination products generated by the Mtb Rho factor. We demonstrate that RNAs produced in in vitro transcription reactions can be detected and quantified without radioactive labeling, simplifying and accelerating the workflow. Although capillary electrophoresis lacks the single-nucleotide resolution of denaturing urea-PAGE, it provides a practical alternative that is compatible with any laboratory environment. This protocol is broadly applicable for analyzing RNA products generated by in vitro transcription with any bacterial RNAP, in the presence or absence of RNA remodeling factors such as the Rho protein.

Indexed as

Rho FactorRNARNA, BacterialTranscription, GeneticTranscription Termination, GeneticDNA-Directed RNA PolymerasesElectrophoresis, CapillaryMycobacterium tuberculosisDNA-Directed RNA PolymerasesRho FactorRNARNA, BacterialCapillary electrophoresisMycobacterium tuberculosisRhoRNA polymeraseTerminationTranscription

Identifiers

PMID42862243

What OpenQuestion holds

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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.