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Record W4200167216 · doi:10.1371/journal.pgen.1009958

Cell competition is driven by Xrp1-mediated phosphorylation of eukaryotic initiation factor 2α

2021· article· en· W4200167216 on OpenAlexfundno aff
Naotaka Ochi, Mai Nakamura, Rina Nagata, Naoki Wakasa, Ryosuke Nakano, Tatsushi Igaki

Bibliographic record

VenuePLoS Genetics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and TechnologyTakeda Science FoundationJapan Agency for Medical Research and DevelopmentInstitute of GeneticsNaito Foundation
KeywordsBiologyCell biologyCellPhosphorylationUnfolded protein responseInitiation factorEukaryotic initiation factorEndoplasmic reticulumTranscription factorProtein kinase AGeneticsRNARibosomeGene

Abstract

fetched live from OpenAlex

Cell competition is a context-dependent cell elimination via cell-cell interaction whereby unfit cells ('losers') are eliminated from the tissue when confronted with fitter cells ('winners'). Despite extensive studies, the mechanism that drives loser's death and its physiological triggers remained elusive. Here, through a genetic screen in Drosophila, we find that endoplasmic reticulum (ER) stress causes cell competition. Mechanistically, ER stress upregulates the bZIP transcription factor Xrp1, which promotes phosphorylation of the eukaryotic translation initiation factor eIF2α via the kinase PERK, leading to cell elimination. Surprisingly, our genetic data show that different cell competition triggers such as ribosomal protein mutations or RNA helicase Hel25E mutations converge on upregulation of Xrp1, which leads to phosphorylation of eIF2α and thus causes reduction in global protein synthesis and apoptosis when confronted with wild-type cells. These findings not only uncover a core pathway of cell competition but also open the way to understanding the physiological triggers of cell competition.

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 score0.032
Threshold uncertainty score0.580

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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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

Citations42
Published2021
Admission routes1
Has abstractyes

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