Evidence map›Paper›PMID 31614688›Full record

ArticleViruses2019

High Fidelity Deep Sequencing Reveals No Effect of ATM, ATR, and DNA-PK Cellular DNA Damage Response Pathways on Adenovirus Mutation Rate.

Jennifer Risso-Ballester, Rafael Sanjuán

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2019. 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
0.2field-weighted citation impact, top 36% of its field
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 citations in OpenAlex.

  1. 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

2 authors at 2 institutions in 1 country.

Jennifer Risso-BallesterInstitute for Integrative Systems Biology (I2SysBio), Universitat de València-CSIC, Paterna, 46980 València, Spain. jennyrisso@mail.ucv.es.
Rafael SanjuánInstitute for Integrative Systems Biology (I2SysBio), Universitat de València-CSIC, Paterna, 46980 València, Spain. rafael.sanjuan@uv.es.
Institute for Integrative Systems Biology · ESUniversitat de València · ES

Funding

European Research Council 281191-VIRMUT
6 · The paper itself

Abstract

Most DNA viruses exhibit relatively low rates of spontaneous mutation. However, the molecular mechanisms underlying DNA virus genetic stability remain unclear. In principle, mutation rates should not depend solely on polymerase fidelity, but also on factors such as DNA damage and repair efficiency. Most eukaryotic DNA viruses interact with the cellular DNA damage response (DDR), but the role of DDR pathways in preventing mutations in the virus has not been tested empirically. To address this goal, we serially transferred human adenovirus type 5 in cells in which the telangiectasia-mutated PI3K-related protein kinase (ATM), the ATM/Rad3-related (ATR) kinase, and the DNA-dependent protein kinase (DNA-PK) were chemically inactivated, as well as in control cells displaying normal DDR pathway functioning. High-fidelity deep sequencing of these viral populations revealed mutation frequencies in the order of one-millionth, with no detectable effect of the inactivation of DDR mediators ATM, ATR, and DNA-PK on adenovirus sequence variability. This suggests that these DDR pathways do not play a major role in determining adenovirus genetic diversity.

Indexed as

Mutation RateAdenoviruses, HumanAtaxia Telangiectasia Mutated ProteinsCell LineDNA-Activated Protein KinaseDNA DamageDNA RepairHigh-Throughput Nucleotide SequencingHumansSignal TransductionAtaxia Telangiectasia Mutated ProteinsATM protein, humanATR protein, humanDNA-Activated Protein KinaseDNA damage responseexperimental evolutionHuman Adenovirus Type 5.mutation rate

Identifiers

PMID31614688
PMCPMC6832117
OpenAlexW2979800804

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.