Evidence that a naturally occurring single nucleotide polymorphism in the RagC gene of Leishmania donovani contributes to reduced virulence
Bibliographic record
Abstract
Leishmaniasis is a widespread neglected tropical disease transmitted by infected sand flies resulting in either benign cutaneous infection or fatal visceral disease. Leishmania donovani is the principal species responsible for visceral leishmaniasis, yet an atypical L. donovani has become attenuated in several countries including Sri Lanka and causes cutaneous leishmaniasis. Previous studies have identified 91 genes altered in the atypical cutaneous L. donovani compared to typical visceral disease associated L. donovani including mutations in the RagC and Raptor genes that are part of the eukaryotic conserved TOR pathway and its upstream sensing pathway. In the present study, we investigate whether the RagC R231C mutation present in atypical cutaneous L. donovani introduced into the virulent L. donovani 1S2D chromosome by CRISPR gene editing could affect virulence for survival in visceral organs. Through bioinformatic analysis, we further investigated the presence of sensing pathway components upstream of TOR in L. donovani including RagC complexing proteins, RagA and Raptor. L. donovani 1S2D edited to express mutant RagC R231C were viable in promastigote but had reduced visceral parasitemia in infected BALB/c mice. The RagC R231C mutant retained the ability to interact with RagA and gene knockout experiments revealed that although the RagA gene was essential, the RagC gene was not essential under promastigote culture conditions but was essential for survival in the liver of experimentally infected mice. These results provide evidence that the TOR associated sensing pathway plays a prominent role in L. donovani visceral disease and the RagC R231C mutation contributed to the atypical pathology of cutaneous L. donovani in Sri Lanka.
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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) | 0.002 | 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".