Simvastatin Resistance of Leishmania amazonensis Induces Sterol Remodeling and Cross-Resistance to Sterol Pathway and Serine Protease Inhibitors
Bibliographic record
Abstract
The sterol biosynthesis pathway of Leishmania spp. is used as a pharmacological target; however, available information about the mechanisms of the regulation and remodeling of sterol-related genes is scarce. The present study investigated compensatory mechanisms of the sterol biosynthesis pathway using an inhibitor of HMG-CoA reductase (simvastatin) and by developing drug-resistant parasites to evaluate the impact on sterol remodeling, cross-resistance, and gene expression. Simvastatin-resistant L. amazonensis parasites (LaSimR) underwent reprogramming of sterol metabolism manifested as an increase in cholestane- and stigmastane-based sterols and a decrease in ergostane-based sterols. The levels of the transcripts of sterol 24-C-methyltransferase (SMT), sterol C14-α-demethylase (C14DM), and protease subtilisin (SUB) were increased in LaSimR. LaSimR was cross-resistance to ketoconazole (a C14DM inhibitor) and remained sensitive to terbinafine (an inhibitor of squalene monooxygenase). Sensitivity of the LaSimR mutant to other antileishmanial drugs unrelated to the sterol biosynthesis pathway, such as trivalent antimony and pentamidine, was similar to that of the wild-type strain; however, LaSimR was cross-resistant to miltefosine, general serine protease inhibitor N-p-tosyl-l-phenylalanine chloromethyl ketone (TPCK), subtilisin-specific inhibitor 4-[(diethylamino)methyl]-N-[2-(2-methoxyphenyl)ethyl]-N-(3R)-3-pyrrolidinyl-benzamide dihydrochloride (PF-429242), and tunicamycin. The findings on the regulation of the sterol pathway can support the development of drugs and protease inhibitors targeting this route in parasites.
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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".