Molecular Topology of the Transit Peptide during Chloroplast Protein Import
Bibliographic record
Abstract
Chloroplast protein import is directed by the interaction of the targeting signal (transit peptide) of nucleus-encoded preproteins with translocons at the outer (TOC) and inner (TIC) chloroplast envelope membranes. Studies of the energetics and determinants of transit peptide binding have led to the hypothesis that import occurs through sequential recognition of transit peptides by components of TOC and TIC during protein import. To test this hypothesis, we employed a site-specific cross-linking approach to map transit peptide topology in relation to TOC-TIC components at specific stages of import in Arabidopsis thaliana and pea (Pisum sativum). We demonstrate that the transit peptide is in contact with Tic20 at the inner envelope in addition to TOC complex components at the earliest stages of chloroplast binding. Low levels of ATP hydrolysis catalyze the commitment of the preprotein to import by promoting further penetration across the envelope membranes and stabilizing the association of the preprotein with TOC-TIC. GTP hydrolysis at the TOC receptors serves as a checkpoint to regulate the ATP-dependent commitment of the preprotein to import and is not essential to drive preprotein import. Our results demonstrate the close cooperativity of the TOC and TIC machinery at each stage of transit peptide recognition and membrane translocation during protein import.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".