Coiled-coil domains enhance the membrane association of Salmonella type III effectors
Bibliographic record
Abstract
Coiled-coil domains in eukaryotic and prokaryotic proteins contribute to diverse structural and regulatory functions. Here we have used in silico analysis to predict which proteins in the proteome of the enteric pathogen, Salmonella enterica serovar Typhimurium, harbour coiled-coil domains. We found that coiled-coil domains are especially prevalent in virulence-associated proteins, including type III effectors. Using SopB as a model coiled-coil domain type III effector, we have investigated the role of this motif in various aspects of effector function including chaperone binding, secretion and translocation, protein stability, localization and biological activity. Compared with wild-type SopB, SopB coiled-coil mutants were unstable, both inside bacteria and after translocation into host cells. In addition, the putative coiled-coil domain was required for the efficient membrane association of SopB in host cells. Since many other Salmonella effectors were predicted to contain coiled-coil domains, we also investigated the role of this motif in their intracellular targeting in mammalian cells. Mutation of the predicted coiled-coil domains in PipB2, SseJ and SopD2 also eliminated their membrane localization in mammalian cells. These findings suggest that coiled-coil domains represent a common membrane-targeting determinant for Salmonella type III effectors.
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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".