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Record W4391022720 · doi:10.1016/j.isci.2024.108970

mtDNA extramitochondrial replication mediates mitochondrial defect effects

2024· article· en· W4391022720 on OpenAlexfundno aff
Zhaoliang Shan, Shengnan Li, Yuxue Gao, Chunhua Jian, Xiuxiu Ti, Hui Zuo, Ying Wang, Guochun Zhao, Yan Wang, Qing Zhang

Bibliographic record

VenueiScience · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesNational University's Basic Research Foundation of ChinaInstitute of GeneticsNational Natural Science Foundation of China
KeywordsMitochondrial DNAReplication (statistics)BiologyGeneticsComputational biologyEvolutionary biologyGene

Abstract

fetched live from OpenAlex

A high ratio of severe mitochondrial defects causes multiple human mitochondrial diseases. However, until now, the in vivo rescue signal of such mitochondrial defect effects has not been clear. Here, we built fly mitochondrial defect models by knocking down the essential mitochondrial genes dMterf4 and dMrps23 . Following genome-wide RNAi screens, we found that knockdown of Med8/Tfb4/mtSSB/PolG2/mtDNA-helicase rescued dMterf4/dMrps23 RNAi-mediated mitochondrial defect effects. Extremely surprisingly, they drove mtDNA replication outside mitochondria through the Med8/Tfb4-mtSSB/PolG2/mtDNA-helicase axis to amplify cytosolic mtDNA, leading to activation of the cGAS-Sting-like IMD pathway to partially mediate dMterf4 / dMrps23 RNAi-triggered effects. Moreover, we found that the Med8/Tfb4-mtSSB/PolG2/mtDNA-helicase axis also mediated other fly mitochondrial gene defect-triggered dysfunctions and Drosophila aging. Overall, our study demarcates the Med8/Tfb4-mtSSB/PolG2/mtDNA-helicase axis as a candidate mechanism to mediate mitochondrial defect effects through driving mtDNA extramitochondrial replication; dysfunction of this axis might be used for potential treatments for many mitochondrial and age-related diseases.

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 score0.334
Threshold uncertainty score0.510

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 head0.010
GPT teacher head0.270
Teacher spread0.260 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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