N‐terminomics profiling of naïve and inflamed murine colon reveals proteolytic signatures of legumain
Bibliographic record
Abstract
Legumain is a cysteine protease broadly associated with inflammation. It has been reported to cleave and activate protease-activated receptor 2 to provoke pain associated with oral cancer. Outside of gastric and colon cancer, little has been reported on the roles of legumain within the gastrointestinal tract. Using a legumain-selective activity-based probe, LE28, we report that legumain is activated within colonocytes and macrophages of the murine colon, and that it is upregulated in models of acute experimental colitis. We demonstrated that loss of legumain activity in colonocytes, either through pharmacological inhibition or gene deletion, had no impact on epithelial permeability in vitro. Moreover, legumain inhibition or deletion had no obvious impacts on symptoms or histological features associated with dextran sulfate sodium-induced colitis, suggesting its proteolytic activity is dispensable for colitis initiation. To gain insight into potential functions of legumain within the colon, we performed field asymmetric waveform ion mobility spectrometry-facilitated quantitative proteomics and N-terminomics analyses on naïve and inflamed colon tissue from wild-type and legumain-deficient mice. We identified 16 altered cleavage sites with an asparaginyl endopeptidase signature that may be direct substrates of legumain and a further 16 cleavage sites that may be indirectly mediated by legumain. We also analyzed changes in protein abundance and proteolytic events broadly associated with colitis in the gut, which permitted comparison to recent analyses on mucosal biopsies from patients with inflammatory bowel disease. Collectively, these results shed light on potential functions of legumain and highlight its potential roles in the transition from inflammation to colorectal cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".