Activity-Based Labeling of Matrix Metalloproteinases in Living Vertebrate Embryos
Bibliographic record
Abstract
Extracellular matrix (ECM) remodeling is a physiologically and developmentally essential process mediated by a family of zinc-dependent extracellular proteases called matrix metalloproteinases (MMPs). In addition to complex transcriptional control, MMPs are subject to extensive post-translational regulation. Because of this, classical biochemical, molecular and histological techniques that detect the expression of specific gene products provide useful but limited data regarding the biologically relevant activity of MMPs. Using benzophenone-bearing hydroxamate-based probes that interact with the catalytic zinc ion in MMPs, active proteases can be covalently 'tagged' by UV cross-linking. This approach has been successfully used to tag MMP-2 in vitro in tissue culture supernatants, and we show here that this probe tags proteins with mobilities consistent with known MMPs and detectable gelatinolytic activity in homogenates of zebrafish embryos. Furthermore, because of the transparency of the zebrafish embryo, UV-photocroslinking can be accomplished in vivo, and rhodamated benzophenone probe is detected in striking spatial patterns consistent with known distributions of active matrix remodeling in embryos. Finally, in metamorphosing Xenopus tadpoles, this probe can be used to biotinylate active MMP-2 by injecting it and cross-linking it in vivo, allowing the protein to be subsequently extracted and biochemically identified.
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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 | 0.001 | 0.000 |
| 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".