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Record W2572639191 · doi:10.1371/journal.pgen.1006570

Anaerobically Grown Escherichia coli Has an Enhanced Mutation Rate and Distinct Mutational Spectra

2017· article· en· W2572639191 on OpenAlexaff
Sonal Shewaramani, Thomas J. Finn, Sinead C. Leahy, Rees Kassen, Paul B. Rainey, Christina D. Moon

Bibliographic record

VenuePLoS Genetics · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of Ottawa
FundersMarsden FundMassey UniversityRoyal Society Te ApārangiRoyal Society
KeywordsBiologyMutation rateEscherichia coliMutation AccumulationMutationGeneticsAnaerobic exerciseGeneFacultative

Abstract

fetched live from OpenAlex

Oxidative stress is a major cause of mutation but little is known about how growth in the absence of oxygen impacts the rate and spectrum of mutations. We employed long-term mutation accumulation experiments to directly measure the rates and spectra of spontaneous mutation events in Escherichia coli populations propagated under aerobic and anaerobic conditions. To detect mutations, whole genome sequencing was coupled with methods of analysis sufficient to identify a broad range of mutational classes, including structural variants (SVs) generated by movement of repetitive elements. The anaerobically grown populations displayed a mutation rate nearly twice that of the aerobic populations, showed distinct asymmetric mutational strand biases, and greater insertion element activity. Consistent with mutation rate and spectra observations, genes for transposition and recombination repair associated with SVs were up-regulated during anaerobic growth. Together, these results define differences in mutational spectra affecting the evolution of facultative anaerobes.

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)0.000
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 score0.393
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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

Citations80
Published2017
Admission routes1
Has abstractyes

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