Bacterial outer membrane vesicles provide an alternative pathway for trafficking of type III secreted effectors into epithelial cells
Bibliographic record
Abstract
ABSTRACT Outer membrane vesicles (OMVs) are proteo-liposomes universally shed by Gram-negative bacteria. Their secretion is significantly enhanced by the transition into the intra-host milieu and OMVs have been shown to play critical roles during pathogenesis. Enterohemorrhagic Escherichia coli O157 (EHEC), causes diarrheal disease in humans, and soluble toxins including Shiga-like toxins that contribute to disease severity and clinical complications including hemolytic uremic syndrome, have been shown to be OMV associated. In addition to Shiga-like toxins, EHEC produces a type III secretion system (T3SS), and T3SS effectors are associated with colonization and disease severity in vivo . Here, we show that type III secreted substrates including translocators and effectors are incorporated into OMVs independent of type III secretion activity. EHEC strains with non-functional type III secretion systems shed more OMVs and vesicles enter host cells with accelerated kinetics compared to vesicles shed from wild type EHEC. The T3SS effector translocated intimin receptor (Tir) is trafficked from OMVs into host cells and localizes to the membrane. However, its clustering on the host membrane and co-localization with bacterial pedestals is intimin-dependent. We further show that OMV-delivered Tir can cross-complement an effector-deficient EHEC strain, demonstrating that OMV-associated effectors reach the host cell in a biologically intact form. Finally, we observe that the non-LEE encoded E3 ubiquitin ligase effector NleL is also trafficked to host cells via OMVs, where it ubiquitinylates its target kinase JNK. Together, these data demonstrate that trafficking of OMV-associated effectors is a novel and T3SS-independent pathway for the delivery of active effectors to host cells.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".