Diacidic Motifs Influence the Export of Transmembrane Proteins from the Endoplasmic Reticulum in Plant Cells
Bibliographic record
Abstract
In yeast and mammals, amino acid motifs in the cytosolic tails of transmembrane domains play a role in protein trafficking by facilitating export from the endoplasmic reticulum (ER). However, little is known about ER export signals of membrane proteins in plants. Therefore, we investigated the role of diacidic motifs in the ER export of Golgi-localized membrane proteins. We show that diacidic motifs perform a significant function in the export of transmembrane proteins to the Golgi apparatus, as mutations of these signals impede the efficient anterograde transport of multispanning, type II, and type I proteins. Furthermore, we demonstrate that diacidic motifs instigate the export of proteins that reside in the ER due to the lengths of their transmembrane domains. However, not all of the diacidic motifs in the cytosolic tails of the proteins studied were equally important in ER export. Transport of Golgi proteins was disrupted only by mutagenesis of specific diacidic signals, suggesting that the protein environment of these signals affects their function. Our findings indicate that diacidic ER export motifs are present and functional in plant membrane proteins and that they are dominant over transmembrane domain length in determining the export of proteins from the ER in plant cells.
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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 | 0.001 | 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".