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Record W3143471491 · doi:10.1101/2021.03.31.437844

A DNA repair-independent role for alkyladenine DNA glycosylase in alkylation-induced unfolded protein response

2021· preprint· en· W3143471491 on OpenAlexaff
Larissa Milano, Clara Forrer Charlier, Rafaela Rafognatto Andreguetti, Thomas C. Cox, Eleanor Healing, Marcos Paulo Machado Thomé, Ruan Elliott, Leona D. Samson, Jean‐Yves Masson, Guido Lenz, João Antônio Pêgas Henriques, Axel Nohturfft, Lisiane B. Meira

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsUniversité LavalHôtel-Dieu de Québec
FundersNational Institutes of HealthUniversidade Federal do Rio Grande do SulNational Institute of Environmental Health SciencesConselho Nacional de Desenvolvimento Científico e TecnológicoRoyal Society
KeywordsUnfolded protein responseXBP1DNA damageDNA glycosylaseDNA repairGene knockdownChemistryMutantMolecular biologyBiologyCell biologyBiochemistryEndoplasmic reticulumDNAGene

Abstract

fetched live from OpenAlex

Abstract Alkylating agents damage DNA and proteins and are widely used in cancer chemotherapy. While the cellular responses to alkylation-induced DNA damage have been explored, knowledge of how alkylation damage affects global cellular stress responses is still sparse. Here, we examined the effects of the alkylating agent methylmethane sulfonate (MMS) on gene expression in mouse liver taking advantage of mice deficient in alkyladenine DNA glycosylase (Aag), the enzyme that initiates the repair of alkylated DNA bases. MMS induced a robust transcriptional response in wild-type liver that included markers of the endoplasmic reticulum (ER) stress/unfolded protein response (UPR) known to be controlled by the transcription factor XBP1, a key UPR effector. Importantly, this response is significantly reduced in the Aag knockout. To investigate a potential role for AAG in alkylation-induced UPR, the expression of UPR markers after MMS treatment was interrogated in human glioblastoma cell lines expressing different AAG levels. Alkylation induced the UPR in cells expressing AAG; conversely, AAG knock-down compromised UPR induction and led to a defect in XBP1 activation plus a decrease in the expression of the ER chaperone BiP. To verify that the DNA repair activity of AAG is required for this response, AAG knockdown cells were complemented with wild-type Aag or with a mutant version of the Aag gene producing a glycosylase-deficient AAG protein. As expected, the glycosylase-defective mutant Aag does not fully protect AAG knockdown cells against MMS-induced cytotoxicity. Remarkably, however, alkylation-induced XBP1 activation is fully complemented by the catalytically inactive AAG enzyme. This work establishes that, in addition to its enzymatic activity, AAG has non-canonical functions in alkylation-induced UPR that contribute to the overall cellular response to alkylation. Significance Statement Stress response pathways, such as the DNA damage response (DDR) and the UPR, are critical in both the etiology and treatment of cancer and other chronic diseases. Knowledge of an interplay between ER stress and genome damage repair is emerging, but evidence linking defective DNA repair and impaired ER stress response is lacking. Here, we show that AAG is necessary for UPR activation in response to alkylating agents. AAG-deficient mice and human cancer cells are impaired in alkylation-induced UPR. Strikingly, this defect can be complemented by an AAG variant defective in glycosylase activity. Our studies suggest AAG has non-canonical functions and identify AAG as a point of convergence for stress response pathways. This knowledge could be explored to improve cancer treatment.

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 score0.004

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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