Mutations in an Aquaglyceroporin as a Proven Marker of Antimony Clinical Resistance in the Parasite <i>Leishmania donovani</i>
Bibliographic record
Abstract
BACKGROUND: Antimonial drugs have long been the mainstay to treat visceral leishmaniasis. Their use has been discontinued in the Indian subcontinent because of drug resistance, but they are still clinically useful elsewhere. The goal of this study was to find markers of antimony resistance in Leishmania donovani clinical isolates and validate experimentally their role in resistance. METHODS: The genomes of sensitive and antimony-resistant clinical isolates were sequenced. The role of a specific gene in contributing to resistance was studied by CRISPR-Cas9-mediated gene editing and intracellular drug sensitivity assays. RESULTS: Both gene copy number variations and single nucleotide variants were associated with antimony resistance. A homozygous insertion of 2 nucleotides was found in the gene coding for the aquaglyceroporin AQP1 in both resistant isolates. Restoring the wild-type AQP1 open reading frame re-sensitized the 2 independent resistant isolates to antimonials. Alternatively, editing the genome of a sensitive isolate by incorporating the 2-nucleotide insertion in its AQP1 gene led to antimony-resistant parasites. CONCLUSIONS: Through genomic analysis and CRISPR-Cas9-mediated genome editing we have proven the role of the AQP1 mutations in antimony clinical resistance in L. donovani.
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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".