High-throughput Cos-Seq screen with intracellular Leishmania infantum for the discovery of novel drug-resistance mechanisms
Bibliographic record
Abstract
Increasing drug resistance towards first line antimony-derived compounds has forced the introduction of novel therapies in leishmaniasis endemic areas including amphotericin B and miltefosine. However, their use is threatened by the emergence and spread of drug-resistant strains. In order to discover stage-dependent resistance genes, we have adapted the Cos-Seq approach through the introduction of macrophage infections in the pipeline. A L. infantum intracellular amastigote population complemented with a L. infantum cosmid library was submitted to increasing concentrations of miltefosine, amphotericin B and pentavalent antimonials in experimental infections of THP-1 cells. For each step of selection, amastigotes were extracted and cosmids were isolated and submitted to next-generation sequencing, followed by subsequent gene-enrichment analyses. Cos-Seq screen in amastigotes revealed four highly enriched loci for antimony, five for miltefosine and one for amphotericin B. Of these, a total of seven cosmids were recovered and tested for resistance in both promastigotes and amastigotes. Candidate genes within the pinpointed genomic regions were validated using single gene overexpression in wild-type parasites and/or gene disruption by means of a CRISPR-Cas9-based approach. This led to the identification and validation of a stage-independent antimony-resistance gene (LinJ.06.1010) coding for a putative leucine rich repeat protein and a novel amastigote-specific miltefosine-resistance gene (LinJ.32.0050) coding for a member of the SEC13 family of WD-repeat proteins. This study further reinforces the power of Cos-Seq approach to discover novel drug-resistance genes, some of which are life-stages specific.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".