Evidence map›Paper›PMID 40835813›Full record

ArticleNature communications2025

Nanopore sequencing of intact aminoacylated tRNAs.

Laura K White, Aleksandar Radakovic, Marcin P Sajek, Kezia Dobson, Kent A Riemondy, Samantha Del Pozo, Jack W Szostak, Jay R Hesselberth

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. The impact of psuedouridine modification on human tRNA.Biochemical Society transactions · 2026
    Review
  4. Pseudouridylation landscape across 42bioRxiv : the preprint server for biology · 2026
    Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Laura K White *Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA. laura.k.white@cuanschutz.edu.ORCID http://orcid.org/0000-0003-2909-6627
Aleksandar Radakovic *Department of Genetics, Harvard Medical School, Boston, MA, USA.
Marcin P SajekDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA.ORCID http://orcid.org/0000-0002-4115-4191
Kezia DobsonDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA.
Kent A RiemondyDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA.
Samantha Del PozoDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA.ORCID http://orcid.org/0009-0006-4339-6975
Jack W SzostakDepartment of Chemistry, Howard Hughes Medical Institute, The University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0003-4131-1203
Jay R HesselberthDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA. jay.hesselberth@cuanschutz.edu.ORCID http://orcid.org/0000-0002-6299-179X

Funding

Nanopore analysis of transfer RNA forms and functionsR35GM119550 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI Jay R Hesselberth · 2016 to 2026
$4.5M
Predoctoral Training Program in Molecular and Cellular Biology (Supplement: Mentoring in the Research Environment)T32GM136444 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI MICHAEL A MCMURRAY, Rytis Prekeris · 2020 to 2026
$3.7M
National Science Foundation (NSF) 2330283NIGMS NIH HHS R35 GM119550NIGMS NIH HHS T32 GM136444
6 · The paper itself

Abstract

The intricate landscape of tRNA modification presents persistent analytical challenges, which have impeded efforts to simultaneously resolve sequence, modification, and aminoacylation state at the level of individual tRNAs. To address these challenges, we introduce "aa-tRNA-seq", an integrated method that uses chemical ligation to sandwich the amino acid of a charged tRNA in between the body of the tRNA and an adaptor oligonucleotide, followed by high throughput nanopore sequencing. Our approach reveals the identity of the amino acids attached to all tRNAs in a cellular sample, at the single molecule level. We describe machine learning models that enable the accurate identification of amino acid identities based on the unique signal distortions generated by the interactions between the amino acid in the RNA backbone and the nanopore motor protein and reader head. We apply aa-tRNA-seq to characterize the impact of the loss of specific tRNA modification enzymes, confirming the hypomodification-associated instability of specific tRNAs, and identifying additional candidate targets of modification. Our studies lay the groundwork for understanding the efficiency and fidelity of tRNA aminoacylation as a function of tRNA sequence, modification, and environmental conditions.

Indexed as

AminoacylationNanopore SequencingRNA, TransferSequence Analysis, RNABlotting, NorthernMachine LearningNucleotidesRNA StabilitySaccharomyces cerevisiaeStress, PhysiologicalNucleotidesRNA, Transfer

Identifiers

PMID40835813
PMCPMC12368100

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.