Drug Uptake and Modulation of Drug Resistance in Leishmania by an Aquaglyceroporin
Bibliographic record
Abstract
Leishmaniasis is a protozoan parasitic disease that affects 12 million people worldwide. The first line choice for the treatment of this disease is antimonial drugs. In the endemic regions, resistance to this class of drugs is a major impediment to treatment. Microbes often become resistant to drugs by mutation or down-regulation of uptake systems, but the uptake system for the antimonial drugs in Leishmania is unknown. In other organisms, aquaglyceroporins have been shown to facilitate uptake of trivalent metalloids. In this study, we report the identification and characterization of aquaglyceroporins from Leishmania major (LmAQP1) and Leishmania tarentolae (LtAQP1), respectively. These Leishmania proteins have the conserved signature motifs of aquaglyceroporins. Transfection of LmAQP1 into three species of Leishmania, L. tarentolae, Leishmania infantum, and L. major, produced hypersensitivity to both As(III) and Sb(III) in all three strains. Increased production of LmAQP1 was detected by immunoblotting. Drug-resistant parasites with various mutations leading to resistance mechanisms became hypersensitive to both metalloids after expression of LmAQP1. Increased rates of uptake of As(III) or Sb(III) correlated with metalloid sensitivity of the wild type and drug-resistant transfectants. Transfection of LmAQP1 in a Pentostam-resistant field isolate also sensitized the parasite in the macrophage-associated amastigote form. One allele of LmAQP1 was disrupted in L. major, and the resulting cells became 10-fold more resistant to Sb(III). This is the first report of the uptake of a metalloid drug by an aquaglyceroporin in Leishmania, suggesting a strategy to reverse resistance in the field.
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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) | 0.000 | 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".