Mannose-binding Lectin (MBL) Mutants Are Susceptible to Matrix Metalloproteinase Proteolysis
Bibliographic record
Abstract
Mannose-binding lectin (MBL) plays a critical role in innate immunity. Point mutations in the collagen-like domain (R32C, G34D, or G37E) of MBL cause a serum deficiency, predisposing patients to infections and diseases such as rheumatoid arthritis. We examined whether MBL mutants show enhanced susceptibility to proteolysis by matrix metalloproteinases (MMPs), which are important mediators in inflammatory tissue destruction. Human and rat MBL were resistant to proteolysis in the native state but were cleaved selectively within the collagen-like domain by multiple MMPs after heat denaturation. In contrast, rat MBL with mutations homologous to those of the human variants (R23C, G25D, or G28E) was cleaved efficiently without denaturation in the collagen-like domain by MMP-2 and MMP-9 (gelatinases A and B) and MMP-14 (membrane type-1 MMP), as well as by MMP-1 (collagenase-1), MMP-8 (neutrophil collagenase), MMP-3 (stromelysin-1), neutrophil elastase, and bacterial collagenase. Sites and order of cleavage of the rat MBL mutants for MMP-2 and MMP-9 were: Gly(45)-Lys(46) --> Gly(51)-Ser(52) --> Gly(63)-Gln(64) --> Asn(80)-Met(81) which differed from that of MMP-14, Gly(39)-Leu(40) --> Asn(80)-Met(81), revealing that the MMPs were not functionally interchangeable. These sites were homologous to those cleaved in denatured human MBL. Hence, perturbation of the collagen-like structure of MBL by natural mutations or by denaturation renders MBL susceptible to MMP cleavage. MMPs are likely to contribute to MBL deficiency in individuals with variant alleles and may also be involved in clearance of MBL and modulation of the host response in normal individuals.
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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 | 0.000 |
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".