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Record W2954264023 · doi:10.1016/j.celrep.2020.107902

Mitochondria-Associated Degradation Pathway (MAD) Function beyond the Outer Membrane

2020· article· en· W2954264023 on OpenAlexaff
Pin‐Chao Liao, Dana M. Alessi Wolken, Edith Serrano, Pallavi Srivastava, Liza A. Pon

Bibliographic record

VenueCell Reports · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of Alberta
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Institute on AgingNational Institutes of Health
KeywordsMitophagyMitochondrionCell biologyProteostasisTranslocase of the inner membraneBiologyBacterial outer membraneInner membraneMitochondrial membrane transport proteinInner mitochondrial membraneUbiquitinMitochondrial apoptosis-induced channelAutophagyBiochemistryApoptosisGene

Abstract

fetched live from OpenAlex

The mitochondria-associated degradation pathway (MAD) mediates ubiquitination and degradation of mitochondrial outer membrane (MOM) proteins by the proteasome. We find that the MAD, but not other quality-control pathways including macroautophagy, mitophagy, or mitochondrial chaperones and proteases, is critical for yeast cellular fitness under conditions of paraquat (PQ)-induced oxidative stress in mitochondria. Specifically, inhibition of the MAD increases PQ-induced defects in growth and mitochondrial quality and decreases chronological lifespan. We use mass spectrometry analysis to identify possible MAD substrates as mitochondrial proteins that exhibit increased ubiquitination in response to PQ treatment and inhibition of the MAD. We identify candidate substrates in the mitochondrial matrix and inner membrane and confirm that two matrix proteins are MAD substrates. Our studies reveal a broader function for the MAD in mitochondrial protein surveillance beyond the MOM and a major role for the MAD in cellular and mitochondrial fitness in response to chronic, low-level oxidative stress in mitochondria.

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 score0.420
Threshold uncertainty score0.494

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 head0.013
GPT teacher head0.208
Teacher spread0.195 · 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

Citations52
Published2020
Admission routes1
Has abstractyes

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