Identification of the Docking Site between a Type III Secretion System ATPase and a Chaperone for Effector Cargo
Bibliographic record
Abstract
A number of Gram-negative pathogens utilize type III secretion systems (T3SSs) to inject bacterial effector proteins into the host. An important component of T3SSs is a conserved ATPase that captures chaperone-effector complexes and energizes their dissociation to facilitate effector translocation. To date, there has been limited work characterizing the chaperone-T3SS ATPase interaction despite it being a fundamental aspect of T3SS function. In this study, we present the 2.1 Å resolution crystal structure of the Salmonella enterica SPI-2-encoded ATPase, SsaN. Our structure revealed a local and functionally important novel feature in helix 10 that we used to define the interaction domain relevant to chaperone binding. We modeled the interaction between the multicargo chaperone, SrcA, and SsaN and validated this model using mutagenesis to identify the residues on both the chaperone and ATPase that mediate the interaction. Finally, we quantified the benefit of this molecular interaction on bacterial fitness in vivo using chromosomal exchange of wild-type ssaN with mutants that retain ATPase activity but no longer capture the chaperone. Our findings provide insight into chaperone recognition by T3SS ATPases and demonstrate the importance of the chaperone-T3SS ATPase interaction for the pathogenesis of Salmonella.
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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".