Evidence map›Paper›PMID 34085241›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2021

miCLIP-MaPseq Identifies Substrates of Radical SAM RNA-Methylating Enzyme Using Mechanistic Cross-Linking and Mismatch Profiling.

Vanja Stojković, David E Weinberg, Danica Galonić Fujimori

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Review
  2. Review
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

3 authors.

Vanja StojkovićDepartment of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA.
David E WeinbergDepartment of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA.
Danica Galonić FujimoriDepartment of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA. danica.fujimori@ucsf.edu.

Funding

Radical SAM-dependent methylation in antibiotic resistanceR01AI137270 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Danica Galonic Fujimori · 2018 to 2026
$3.8M
Formation and regulation of the translating mRNPDP5OD017895 · OD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WEINBERG, DAVID ERIC · 2013 to 2017
$1.9M
NIAID NIH HHS R01 AI137270NIH HHS DP5 OD017895
6 · The paper itself

Abstract

The family of radical SAM RNA-methylating enzymes comprises a large group of proteins that contains only a few functionally characterized members. Several enzymes in this family have been implicated in the regulation of translation and antibiotic susceptibility, emphasizing their significance in bacterial physiology and their relevance to human health. While few characterized enzymes have been shown to modify diverse RNA substrates, highlighting potentially broad substrate scope within the family, many enzymes in this class have no known substrates. The precise knowledge of RNA substrates and modification sites for uncharacterized family members is important for unraveling their biological function. Here, we describe a strategy for substrate identification that takes advantage of mechanism-based cross-linking between the enzyme and its RNA substrates, which we named individual-nucleotide-resolution cross-linking and immunoprecipitation combined with mutational profiling with sequencing (miCLIP-MaPseq). Identification of the position of the modification site is achieved using thermostable group II intron reverse transcriptase (TGIRT), which introduces a mismatch at the site of the cross-link.

Indexed as

Escherichia coliEscherichia coli ProteinsImmunoprecipitationMethylationMutationRNARNA-Directed DNA PolymeraseSequence Analysis, RNAEscherichia coli ProteinsRNARNA-Directed DNA PolymeraseCfrMethyl adenosineRadical SAMRlmNRNA methylationSubstrate identificationTGIRT

Identifiers

PMID34085241
PMCPMC8245296

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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.