ipaA triggers vinculin oligomerization to strengthen cell adhesion during <i>Shigella</i> invasion
Bibliographic record
Abstract
Abstract The Shigella effector IpaA co-opts the focal adhesion protein vinculin to promote bacterial invasion. Here, we show that IpaA triggers an unreported mode of vinculin activation through the cooperative binding of its three vinculin-binding sites (VBSs) leading to vinculin oligomerization via its D1 and D2 head subdomains and highly stable adhesions resisting actin relaxing drugs. Using cross-linking mass spectrometry, we found that while IpaA VBSs1-2 bound to D1, IpaA VBS3 interacted with D2, a subdomain masked to other known VBSs. Structural modeling indicated that as opposed to canonical activation linked to interaction with D1, these combined VBSs interactions triggered major allosteric changes leading to D1D2 oligomerization. A cysteine-clamp preventing these changes and D1D2 oligomerization impaired growth of vinculin microclusters and cell adhesion. We propose that D1D2-mediated vinculin oligomerization occurs during the maturation of adhesion structures to enable the scaffolding of high-order vinculin complexes, and is triggered by Shigella IpaA to promote bacterial invasion in the absence of mechanotransduction. Summary The Shigella IpaA effector binds to cryptic vinculin sites leading to oligomerization via its head domain. This vinculin oligomerization mode appears required for the maturation and strengthening of cell adhesion but is co-opted by invasive bacteria independent of actomyosin contractility.
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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 | 0.000 |
| 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".