Differential Subcellular Distribution and Translocation of Seven 14-3-3 Isoforms in Response to EGF and During the Cell Cycle
Bibliographic record
Abstract
Multiple isoforms of 14-3-3 proteins exist in different organisms. In mammalian cells, 14-3-3 protein has seven isoforms (α/β, ε, η, γ, σ, θ/τ, and δ/ζ), with α and δ representing the phosphorylated versions of β and ζ, respectively. While the existence of multiple isoforms may represent one more level of regulation in 14-3-3 signaling, our knowledge regarding the isoform-specific functions of 14-3-3 proteins is very limited. Determination of the subcellular localization of the different 14-3-3 isoforms could give us important clues of their specific functions. In this study, by using indirect immunofluorescence, subcellular fractionation, and immunoblotting, we studied the subcellular localization of the total 14-3-3 protein and each of the seven 14-3-3 isoforms; their redistribution throughout the cell cycle; and their translocation in response to EGF in Cos-7 cells. We showed that 14-3-3 proteins are broadly distributed throughout the cell and associated with many subcellular structures/organelles, including the plasma membrane (PM), mitochondria, ER, nucleus, microtubules, and actin fibers. This broad distribution underlines the multiple functions identified for 14-3-3 proteins. The different isoforms of 14-3-3 proteins have distinctive subcellular localizations, which suggest their distinctive cellular functions. Most notably, 14-3-3ƞ is almost exclusively localized to the mitochondria, 14-3-3γ is only localized to the nucleus, and 14-3-3σ strongly and specifically associated with the centrosome during mitosis. We also examined the subcellular localization of the seven 14-3-3 isoforms in other cells, including HEK-293, MDA-MB-231, and MCF-7 cells, which largely confirmed our findings with Cos-7 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 | 0.001 | 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) | 0.000 | 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".