Using a Genetically Encoded Sensor to Identify Inhibitors of Toxoplasma gondii Ca2+ Signaling
Bibliographic record
Abstract
The life cycles of apicomplexan parasites progress in accordance with fluxes in cytosolic Ca(2+) Such fluxes are necessary for events like motility and egress from host cells. We used genetically encoded Ca(2+) indicators (GCaMPs) to develop a cell-based phenotypic screen for compounds that modulate Ca(2+) signaling in the model apicomplexan Toxoplasma gondii In doing so, we took advantage of the phosphodiesterase inhibitor zaprinast, which we show acts in part through cGMP-dependent protein kinase (protein kinase G; PKG) to raise levels of cytosolic Ca(2+) We define the pool of Ca(2+) regulated by PKG to be a neutral store distinct from the endoplasmic reticulum. Screening a library of 823 ATP mimetics, we identify both inhibitors and enhancers of Ca(2+) signaling. Two such compounds constitute novel PKG inhibitors and prevent zaprinast from increasing cytosolic Ca(2+) The enhancers identified are capable of releasing intracellular Ca(2+) stores independently of zaprinast or PKG. One of these enhancers blocks parasite egress and invasion and shows strong antiparasitic activity against T. gondii The same compound inhibits invasion of the most lethal malaria parasite, Plasmodium falciparum Inhibition of Ca(2+)-related phenotypes in these two apicomplexan parasites suggests that depletion of intracellular Ca(2+) stores by the enhancer may be an effective antiparasitic strategy. These results establish a powerful new strategy for identifying compounds that modulate the essential parasite signaling pathways regulated by Ca(2+), underscoring the importance of these pathways and the therapeutic potential of their inhibition.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".