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Record W2254857578 · doi:10.1073/pnas.1522325113

Strand-biased cytosine deamination at the replication fork causes cytosine to thymine mutations in <i>Escherichia coli</i>

2016· article· en· W2254857578 on OpenAlexfundno aff
Ashok S. Bhagwat, Weilong Hao, Jesse P. Townes, Heewook Lee, Haixu Tang, Patricia L. Foster

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
FundersArmy Research OfficeInstitute of GeneticsNational Institute of General Medical SciencesMultidisciplinary University Research InitiativeU.S. ArmyBroad InstituteWashington State UniversityNational Institutes of HealthWayne State University
KeywordsCytosineDeaminationBiologyGeneticsThymineDNADNA replicationGenomeSomatic hypermutationCytidine deaminaseGeneEnzymeBiochemistry

Abstract

fetched live from OpenAlex

The rate of cytosine deamination is much higher in single-stranded DNA (ssDNA) than in double-stranded DNA, and copying the resulting uracils causes C to T mutations. To study this phenomenon, the catalytic domain of APOBEC3G (A3G-CTD), an ssDNA-specific cytosine deaminase, was expressed in an Escherichia coli strain defective in uracil repair (ung mutant), and the mutations that accumulated over thousands of generations were determined by whole-genome sequencing. C:G to T:A transitions dominated, with significantly more cytosines mutated to thymine in the lagging-strand template (LGST) than in the leading-strand template (LDST). This strand bias was present in both repair-defective and repair-proficient cells and was strongest and highly significant in cells expressing A3G-CTD. These results show that the LGST is accessible to cellular cytosine deaminating agents, explains the well-known GC skew in microbial genomes, and suggests the APOBEC3 family of mutators may target the LGST in the human genome.

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)0.001
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 score0.047
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.026
GPT teacher head0.297
Teacher spread0.270 · 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

Citations103
Published2016
Admission routes1
Has abstractyes

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