Localized translation of cell junction mRNAs is required for epithelial cell polarity
Bibliographic record
Abstract
ABSTRACT Epithelial cells exhibit a highly polarized organization along their apico-basal axis, a feature that is critical to their function and frequently perturbed in cancer. One less explored process modulating epithelial cell polarity is the subcellular localization of mRNA molecules. In the present study, we report that several mRNAs encoding evolutionarily conserved epithelial polarity regulatory proteins, including Zo-1 , Afdn and Scrib , are localized to cell junction regions in Drosophila epithelial tissues and human epithelial cells. Targeting of these mRNAs is coincident with the robust junctional distribution of their encoded proteins, and we demonstrate that they are locally translated at cell junction regions. To identify RNA binding proteins (RBPs) potentially implicated in junctional mRNA regulation, we performed systematic immuno-labeling with a collection of validated RBP antibodies, identifying a dozen RBPs with consistent junctional distribution patterns, several of which directly bind junctional transcripts. Strikingly, depletion of these RBP candidates, including MAGOH, a core component of the exon-junction complex (EJC), perturbed the junctional distribution and localized translation of Zo-1 and Scrib mRNAs, as well as the junctional accumulation of their protein products. Functional disruption of MAGO, or its interaction partner Y14, in Drosophila follicular epithelial cells perturbs the distribution of junctional transcripts and proteins. Finally, tissue microarray analysis of ovarian cancer tumor specimens revealed that expression of MAGOH and ZO-1 is positively correlated and that both proteins are potential biomarkers of good prognosis. Altogether, this work reveals that localized mRNA translation at cell junction regions is important for modulating epithelial cell polarity. HIGHLIGHTS Cell junction mRNA targeting is conserved between tissues and species These mRNAs undergo localized translation at areas of cell-cell contact A diversity of RBPs localize to cell junction regions and interact with junctional transcripts. Disruption of junctional RBPs impacts epithelial cell polarity and localized translation MAGOH and ZO-1 expression is correlated in ovarian tumor specimens and are potential biomarkers of good prognosis
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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 | 0.001 |
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".