Revisiting Leishmania GP63 host cell targets reveals a limited spectrum of substrates
Bibliographic record
Abstract
Colonization of host phagocytic cells by Leishmania metacyclic promastigotes involves several parasite effectors, including the zinc-dependent metalloprotease GP63. The major mode of action of this virulence factor entails the cleavage/degradation of host cell proteins. Given the potent proteolytic activity of GP63, identification of its substrates requires the adequate preparation of cell lysates to prevent artefactual degradation during cell processing. In the present study, we re-examined the cleavage/degradation of reported GP63 substrates when GP63 activity was efficiently neutralized during the preparation of cell lysates. To this end, we infected bone marrow-derived macrophages with either wild type, Δgp63, and Δgp63+GP63 L. major metacyclic promastigotes for various time points. We prepared cell lysates in the absence or presence of the zinc-metalloprotease inhibitor 1,10-phenanthroline and examined the levels and integrity of ten previously reported host cell GP63 substrates. Inhibition of GP63 activity with 1,10-phenanthroline during the processing of macrophages prevented the cleavage/degradation of several previously described GP63 targets, including PTP-PEST, mTOR, p65RelA, c-Jun, VAMP3, and NLRP3. Conversely, we confirmed that SHP-1, Synaptotagmin XI, VAMP8, and Syntaxin-5 are bona fide GP63 substrates. These results point to the importance of efficiently inhibiting GP63 activity during the preparation of Leishmania-infected host cell lysates. In addition, our results indicate that the role of GP63 in Leishmania pathogenesis must be re-evaluated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".