Mechanisms of cytosolic targeting of matrix metalloproteinase‐2
Bibliographic record
Abstract
Matrix metalloproteinase-2 (MMP-2) is best understood for its biological actions outside the cell. However, MMP-2 also localizes to intracellular compartments and the cytosol where it has several substrates, including troponin I (TnI). Despite a growing list of cytosolic substrates, we currently do not know the mechanism(s) that give rise to the equilibrium between intracellular and secreted MMP-2 moieties. Therefore, we explored how cells achieve the unique distribution of this protease. Our data show that endogenous MMP-2 targets inefficiently to the endoplasmic reticulum (ER) and shows significant amounts in the cytosol. Transfection of canonical MMP-2 essentially reproduces this targeting pattern, suggesting it is the quality of the MMP-2 signal sequence that predominantly determines MMP-2 targeting. However, we also found that human cardiomyocytes express an MMP-2 splice variant which entirely lacks the signal sequence. Like the fraction of ER-excluded, full-length MMP-2, this variant MMP-2 is restricted to the cytosol and specifically enhances TnI cleavage upon hypoxia-reoxygenation injury in cardiomyocytes. Together, our findings describe for the first time a set of mechanisms that cells utilize to equilibrate MMP-2 both in the extracellular milieu and intracellular, cytosolic locations. Our results also suggest approaches to specifically investigate the overlooked intracellular biology of MMP-2.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".