Propulsive cell entry diverts pathogens from immune degradation by remodeling the phagocytic synapse
Bibliographic record
Abstract
Abstract Phagocytosis is a critical immune function for infection control and tissue homeostasis. This process is typically described as non-moving pathogens being internalized and degraded in phagolysosomes. For pathogens that evade immune degradation, the prevailing view is that virulence factors that biochemically disrupt the biogenesis of phagoslysosomes are required. In contrast, here we report that physical forces exerted by pathogens during cell entry divert them away from the canonical phagolysosomal degradation pathway, and this altered intracellular fate is determined at the time of phagocytic synapse formation. We used the eukaryotic parasite Toxoplasma gondii as a model because live Toxoplasma uses gliding motility to actively invade into host cells. To differentiate the effect of physical forces from that of virulence factors in phagocytosis, we developed a strategy that used magnetic forces to induce propulsive entry of inactivated Toxoplasma into macrophage cells. Experiments and computer simulations collectively reveal that large propulsive forces suppress productive activation of receptors by hindering their spatial segregation from phosphatases at the phagocytic synapse. Consequently, the inactivated parasites, instead of being degraded in phagolysosomes, are engulfed into vacuoles that fail to mature into degradative units, following an intracellular pathway strikingly similar to that of the live motile parasite. Using opsonized beads, we further confirmed that this mechanism is general, not specific to the parasite used. These results reveal previously unknown aspects of immune evasion by demonstrating how physical forces exerted during active cell entry, independent of virulence factors, can help pathogens circumvent phagolysosomal degradation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".