Optimization and biological validation of an <i>in vitro</i> assay using the transfected Dm28c/pLacZ <i>Trypanosoma cruzi</i> strain
Bibliographic record
Abstract
Abstract There is an urgent need to develop safer and more effective drugs for Chagas disease, as the current treatment relies on benznidazole (BZ) and nifurtimox (NFX). Using the Trypanosoma cruzi Dm28c strain genetically engineered to express the Escherichia coli β-galactosidase gene, lacZ, we have adapted and validated an easy, quick and reliable in vitro assay suitable for high-throughput screening for candidate compounds with anti-T. cruzi activity. In vitro studies were conducted to determine trypomastigotes sensitivity to BZ and NFX from Dm28c/pLacZ strain by comparing the conventional labour-intensive microscopy counting method with the colourimetric assay. Drug concentrations producing the lysis of 50% of trypomastigotes (lytic concentration 50%) were 41.36 and 17.99 µM for BZ and NFX, respectively, when measured by microscopy and 44.74 and 38.94 µM, for the colourimetric method, respectively. The optimal conditions for the amastigote development inhibitory assay were established considering the parasite–host relationship (i.e. multiplicity of infection) and interaction time, the time for colourimetric readout and the incubation time with the β-galactosidase substrate. The drug concentrations resulting in 50% amastigote development inhibition obtained with the colourimetric assay were 2.31 µM for BZ and 0.97 µM for NFX, similar to the reported values for the Dm28c wild strain (2.80 and 1.5 µM, respectively). In summary, a colourimetric assay using the Dm28c/pLacZ strain of T. cruzi has been set up, obtaining biologically meaningful sensibility values with the reference compounds on both trypomastigotes and amastigotes forms. This development could be applied to high-throughput screening programmes aiming to identify compounds with anti-T. cruzi in vitro activity.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".