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Record W3087368284 · doi:10.1093/nar/gkaa735

Detection of preQ0 deazaguanine modifications in bacteriophage CAjan DNA using Nanopore sequencing reveals same hypermodification at two distinct DNA motifs

2020· article· en· W3087368284 on OpenAlexaff
Witold Kot, Nikoline S. Olsen, Tue Kjærgaard Nielsen, Geoffrey Hutinet, Valérie de Crécy‐Lagard, Cui Liang, Peter C. Dedon, Alexander Byth Carstens, Sylvain Moineau, Manal A. Swairjo, Lars Hestbjerg Hansen

Bibliographic record

VenueNucleic Acids Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversité Laval
FundersNational Institute of General Medical SciencesNational Research FoundationNational Research Foundation SingaporeHuman Frontier Science ProgramVillum Fonden
KeywordsBiologyDNAGeneticsGenomeGeneCRISPRBacteriophageMobile genetic elementsDNA sequencingComputational biologyGenome editingRestriction enzymeEscherichia coli

Abstract

fetched live from OpenAlex

In the constant evolutionary battle against mobile genetic elements (MGEs), bacteria have developed several defense mechanisms, some of which target the incoming, foreign nucleic acids e.g. restriction-modification (R-M) or CRISPR-Cas systems. Some of these MGEs, including bacteriophages, have in turn evolved different strategies to evade these hurdles. It was recently shown that the siphophage CAjan and 180 other viruses use 7-deazaguanine modifications in their DNA to evade bacterial R-M systems. Among others, phage CAjan genome contains a gene coding for a DNA-modifying homolog of a tRNA-deazapurine modification enzyme, together with four 7-cyano-7-deazaguanine synthesis genes. Using the CRISPR-Cas9 genome editing tool combined with the Nanopore Sequencing (ONT) we showed that the 7-deazaguanine modification in the CAjan genome is dependent on phage-encoded genes. The modification is also site-specific and is found mainly in two separate DNA sequence contexts: GA and GGC. Homology modeling of the modifying enzyme DpdA provides insight into its probable DNA binding surface and general mode of DNA recognition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.087
GPT teacher head0.345
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations34
Published2020
Admission routes1
Has abstractyes

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