Beta-endoproteolysis of the cellular prion protein by dipeptidyl peptidase-4 and fibroblast activation protein
Bibliographic record
Abstract
The cellular prion protein (PrP C ) converts to alternatively folded pathogenic conformations (PrP Sc ) in prion infections and binds neurotoxic oligomers formed by amyloid-β α-synuclein, and tau. β-Endoproteolysis, which splits PrP C into N- and C-terminal fragments (N2 and C2, respectively), is of interest because a protease-resistant, C2-sized fragment (C2 Sc ) accumulates in the brain during prion infections, seemingly comprising the majority of PrP Sc at disease endpoint in mice. However, candidates for the underlying proteolytic mechanism(s) remain unconfirmed in vivo. Here, a cell-based screen of protease inhibitors unexpectedly linked type II membrane proteins of the S9B serine peptidase subfamily to PrP C β-cleavage. Overexpression experiments in cells and assays with recombinant proteins confirmed that fibroblast activation protein (FAP) and its paralog, dipeptidyl peptidase-4 (DPP4), cleave directly at multiple sites within PrP C ’s N-terminal domain. For wild-type mouse and human PrP C substrates expressed in cells, the rank orders of activity were human FAP ~ mouse FAP > mouse DPP4 > human DPP4 and human FAP > mouse FAP > mouse DPP4 >> human DPP4, respectively. C2 levels relative to total PrP C were reduced in several tissues from FAP-null mice, and, while knockout of DPP4 lacked an analogous effect, the combined DPP4/FAP inhibitor linagliptin, but not the FAP-specific inhibitor SP-13786, reduced C2 Sc and total PrP Sc levels in two murine cell-based models of prion infections. Thus, the net activity of the S9B peptidases FAP and DPP4 and their cognate inhibitors/modulators affect the physiology and pathogenic potential of PrP C .
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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) | 0.001 | 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 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".