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Record W4415101981 · doi:10.1038/s41556-025-01774-y

MAPL regulates gasdermin-mediated release of mtDNA from lysosomes to drive pyroptotic cell death

2025· article· en· W4415101981 on OpenAlexaff
Benjamin Nguyen, Jack J. Collier, Olesia Ignatenko, Geneviève Morin, Vanessa Goyon, Alexandre Janer, Camila Tiefensee Ribeiro, Austen J. Milnerwood, Sidong Huang, Michel Desjardins, Heidi M. McBride

Bibliographic record

VenueNature Cell Biology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsUniversité de MontréalMcGill UniversityMontreal Neurological Institute and Hospital
FundersEuropean Molecular Biology Organization
KeywordsProgrammed cell deathMitochondrial fissionMitochondrionPyroptosismitochondrial fusionMitochondrial DNACellApoptosis

Abstract

fetched live from OpenAlex

Mitochondrial control of cell death is of central importance to disease mechanisms from cancer to neurodegeneration. Mitochondrial anchored protein ligase (MAPL) is an outer mitochondrial membrane small ubiquitin-like modifier ligase that is a key determinant of cell survival, yet how MAPL controls the fate of this process remains unclear. Combining genome-wide functional genetic screening and cell biological approaches, we found that MAPL induces pyroptosis through an inflammatory pathway involving mitochondria and lysosomes. MAPL overexpression promotes mitochondrial DNA trafficking in mitochondrial-derived vesicles to lysosomes, which are permeabilized in a process requiring gasdermin pores. This triggers the release of mtDNA into the cytosol, activating the DNA sensor cGAS, required for cell death. Additionally, multiple Parkinson's disease-related genes, including VPS35 and LRRK2, also regulate MAPL-induced pyroptosis. Notably, depletion of MAPL, LRRK2 or VPS35 inhibited inflammatory cell death in primary macrophages, placing MAPL and the mitochondria-lysosome pathway at the nexus of immune signalling and cell death.

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 score0.067
Threshold uncertainty score0.936

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 integrity0.0010.000
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 head0.002
GPT teacher head0.220
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 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

Citations19
Published2025
Admission routes1
Has abstractyes

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