Biophysical characterization of Eag chaperones suggests the mechanism of effector transmembrane domain release
Bibliographic record
Abstract
ABSTRACT The type VI secretion system (T6SS) is a dynamic protein nanomachine found in Gram- negative bacteria that secretes toxic effectors into prey-cells. For secretion, effectors require chaperones or adaptors for proper loading onto the T6SS. Effector associated genes (Eags) are a family of T6SS chaperones that stabilize N-terminal transmembrane domains (TMDs) found in thousands of effectors. Eags are essential for secretion and inhibit effector TMDs from prematurely adopting a membrane-penetrative conformation. However, the mechanism of TMD release from its cognate Eag chaperone is unknown. Here, we take a biochemical and biophysical approach to probe the mechanism of TMD binding and dissociation from Eag chaperones. Using steady-state fluorescence, stopped-flow measurements, and bacterial competition assays, we compare the thermodynamics, kinetics, and in vivo chaperone function of wild-type and point-variant Eag-TMD complexes. Additionally, we solve an X-ray crystal structure of an Eag-TMD point-variant complex that captures an intermediate state of TMD release. Our data reveals the molecular features and specific residue contacts necessary for TMD binding and demonstrates the Eag conformational change required to initiate rapid release of the TMD. Overall, our work details the stability of Eag-TMD complexes and the energetic pathway for the dissociation of effector TMDs from their Eag chaperones.
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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".