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Record W3014867075 · doi:10.1038/s41467-020-15539-8

Mild proteasomal stress improves photosynthetic performance in Arabidopsis chloroplasts

2020· article· en· W3014867075 on OpenAlexaff
Julia Grimmer, Stefan Helm, Dirk Dobritzsch, Gerd Hause, Gerta Shema, René P. Zahedi, Sacha Baginsky

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsJewish General Hospital
FundersEuropean Regional Development FundDeutsche ForschungsgemeinschaftEuropean Commission
KeywordsCytosolPlastidChloroplastThylakoidProteasomeCell biologyOrganelleArabidopsisBiogenesisProtein degradationBiologyProtein turnoverProtein targetingPhotosynthesisTransport proteinBiochemistryCellular compartmentMutantProtein biosynthesisMembrane proteinGeneCellEnzymeMembrane

Abstract

fetched live from OpenAlex

The proteasome is an essential protein-degradation machinery in eukaryotic cells that controls protein turnover and thereby the biogenesis and function of cell organelles. Chloroplasts import thousands of nuclear-encoded precursor proteins from the cytosol, suggesting that the bulk of plastid proteins is transiently exposed to the cytosolic proteasome complex. Therefore, there is a cytosolic equilibrium between chloroplast precursor protein import and proteasomal degradation. We show here that a shift in this equilibrium, induced by mild genetic proteasome impairment, results in elevated precursor protein abundance in the cytosol and significantly increased accumulation of functional photosynthetic complexes in protein import-deficient chloroplasts. Importantly, a proteasome lid mutant shows improved photosynthetic performance, even in the absence of an import defect, signifying that functional precursors are continuously degraded. Hence, turnover of plastid precursors in the cytosol represents a mechanism to constrain thylakoid membrane assembly and photosynthetic electron transport.

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 score0.045
Threshold uncertainty score0.578

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 science0.0010.001
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 head0.254
Teacher spread0.240 · 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

Citations31
Published2020
Admission routes1
Has abstractyes

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