CesT is a multi‐effector chaperone and recruitment factor required for the efficient type III secretion of both LEE‐ and non‐LEE‐encoded effectors of enteropathogenic <i>Escherichia coli</i>
Bibliographic record
Abstract
Enteropathogenic Escherichia coli (EPEC) is an intestinal attaching and effacing pathogen that utilizes a type III secretion system (T3SS) for the delivery of effectors into host cells. The chaperone CesT has been shown to bind and stabilize the type III translocated effectors Tir and Map in the bacterial cytoplasm prior to their delivery into host cells. In this study we demonstrate a role for CesT in effector recruitment to the membrane embedded T3SS. CesT-mediated effector recruitment was dependent on the presence of the T3SS membrane-associated ATPase EscN. EPEC DeltacesT carrying a C-terminal CesT variant, CesT(E142G), exhibited normal cytoplasmic Tir stability function, but was less efficient in secreting Tir, further implicating CesT in type III secretion. In vivo co-immunoprecipitation studies using CesT-FLAG containing EPEC lysates demonstrated that CesT interacts with Tir and EscN, consistent with the notion of CesT recruiting Tir to the T3SS. CesT was also shown to be required for the efficient secretion of several type III effectors encoded within and outside the locus of enterocyte effacement (LEE) in addition to Tir and Map. Furthermore, a CesT affinity column was shown to specifically retain multiple effector proteins from EPEC culture supernatants. These findings indicate that CesT is centrally involved in recruiting multiple type III effectors to the T3SS via EscN for efficient secretion, and functionally redefine the role of CesT in multiple type III effector interactions.
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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 | 0.001 |
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".