Invasion of <i>Toxoplasma gondii</i> bradyzoites: Molecular dissection of the moving junction proteins and effective vaccination targets
Bibliographic record
Abstract
Toxoplasmosis is a neglected parasitic disease necessitating public health control. Host cell invasion by Toxoplasma occurs at different stages of the parasite’s life cycle and is crucial for survival and establishment of infection. In tachyzoites, which are responsible for acute toxoplasmosis, invasion involves the formation of a molecular bridge between the parasite and host cell membranes, referred to as the moving junction (MJ). The MJ is shaped by the assembly of AMA1 and RON2, as part of a complex involving additional RONs. While this essential process is well characterized in tachyzoites, the invasion process remains unexplored in bradyzoites, which form cysts and are responsible for chronic toxoplasmosis and contribute to the dissemination of the parasite between hosts. Here, we show that bradyzoites invade host cells in an MJ-dependent fashion but differ in protein composition from the tachyzoite MJ, relying instead on the paralogs AMA2 and AMA4. Functional characterization of AMA4 reveals its key role for cysts burden during the onset of chronic infection, while being dispensable for the acute phase. Immunizations with AMA1 and AMA4, alone or in complex with their rhoptry neck respective partners RON2 and RON2 L1 , showed that the AMA1–RON2 pair induces strong protection against acute and chronic infection, while the AMA4–RON2 L1 complex targets more selectively the chronic form. Our study provides important insights into the molecular players of bradyzoite invasion and indicates that invasion of cyst-forming bradyzoites contributes to cyst burden. Furthermore, we validate AMA–RON complexes as potential vaccine candidates to protect against toxoplasmosis.
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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 | 0.001 |
| 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".