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Record W4313650033 · doi:10.1016/j.mrfmmm.2023.111814

Mutagenesis induced by protonation of single-stranded DNA is linked to glycolytic sugar metabolism

2023· article· en· W4313650033 on OpenAlexafffund
Suzana P. Gelova, Kin Chan

Bibliographic record

VenueMutation research. Fundamental and molecular mechanisms of mutagenesis · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of OttawaAgriculture and Agri-Food Canada
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMutagenesisBiologyBiochemistryMutationDNASaccharomyces cerevisiaeGlycolysisDNA damageYeastGeneticsMetabolismGene

Abstract

fetched live from OpenAlex

Mutagenesis can be thought of as random, in the sense that the occurrence of each mutational event cannot be predicted with precision in space or time. However, when sufficiently large numbers of mutations are analyzed, recurrent patterns of base changes called mutational signatures can be identified. To date, some 60 single base substitution or SBS signatures have been derived from analysis of cancer genomics data. We recently reported that the ubiquitous signature SBS5 matches the pattern of single nucleotide polymorphisms (SNPs) in humans and has analogs in many species. Using a temperature-sensitive single-stranded DNA (ssDNA) mutation reporter system, we also showed that a similar mutational pattern in yeast is dependent on error-prone translesion DNA synthesis (TLS) and glycolytic sugar metabolism. Here, we further investigated mechanisms that are responsible for this form of mutagenesis in yeast. We first confirmed that excess sugar metabolism leads to increased mutation rate, which was detectable by fluctuation assay. Since glycolysis is known to produce excess protons, we then investigated the effects of experimental manipulations on pH and mutagenesis. We hypothesized that yeast metabolizing 8% glucose would produce more excess protons than cells metabolizing 2% glucose. Consistent with this, cells metabolizing 8% glucose had lower intracellular and extracellular pH values. Similarly, deletion of vma3 (encoding a vacuolar H+-ATPase subunit) increased mutagenesis. We also found that treating cells with edelfosine (which renders membranes more permeable, including to protons) or culturing in low pH media increased mutagenesis. Analysis of the mutational pattern attributable to 20 µM edelfosine treatment revealed similarity to the SBS5-like TLS- and glycolysis-dependant mutational patterns previously observed in ssDNA. Altogether, our results agree with multiple biochemical studies showing that protonation of nitrogenous bases can alter base pairing so as to stabilize some mispairs, and shed new light on a common form of intrinsic mutagenesis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.038
GPT teacher head0.317
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes2
Has abstractyes

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