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Record W4389941417 · doi:10.1038/s44319-023-00009-1

MTCH2 cooperates with MFN2 and lysophosphatidic acid synthesis to sustain mitochondrial fusion

2023· article· en· W4389941417 on OpenAlexaff
Andrés Goldman, Michael Mullokandov, Yehudit Zaltsman, Limor Regev, Smadar Levin‐Zaidman, Atan Gross

Bibliographic record

VenueEMBO Reports · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersIsrael Science Foundation
Keywordsmitochondrial fusionLysophosphatidic acidCell biologyMFN2Cell fusionBiologyMitochondrial DNAComputational biologyGeneticsCellGene

Abstract

fetched live from OpenAlex

Fusion of the outer mitochondrial membrane (OMM) is regulated by mitofusin 1 (MFN1) and 2 (MFN2), yet the differential contribution of each of these proteins is less understood. Mitochondrial carrier homolog 2 (MTCH2) also plays a role in mitochondrial fusion, but its exact function remains unresolved. MTCH2 overexpression enforces MFN2-independent mitochondrial fusion, proposedly by modulating the phospholipid lysophosphatidic acid (LPA), which is synthesized by glycerol-phosphate acyl transferases (GPATs) in the endoplasmic reticulum (ER) and the OMM. Here we report that MTCH2 requires MFN1 to enforce mitochondrial fusion and that fragmentation caused by loss of MTCH2 can be specifically counterbalanced by overexpression of MFN2 but not MFN1, partially independent of its GTPase activity and mitochondrial localization. Pharmacological inhibition of GPATs (GPATi) or silencing ER-resident GPATs suppresses MFN2's ability to compensate for the loss of MTCH2. Loss of either MTCH2, MFN2, or GPATi does not impair stress-induced mitochondrial fusion, whereas the combined loss of MTCH2 and GPATi or the combined loss of MTCH2 and MFN2 does. Taken together, we unmask two cooperative mechanisms that sustain mitochondrial fusion.

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)0.001
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 score0.137
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.007
GPT teacher head0.231
Teacher spread0.224 · 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

Citations22
Published2023
Admission routes1
Has abstractyes

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