The carboxyl-terminal SH3 domain of the mammalian adaptor CrkII promotes internalization of Listeria monocytogenes through activation of host phosphoinositide 3-kinase
Bibliographic record
Abstract
The intracellular bacterial pathogen Listeria monocytogenes causes food-borne illnesses leading to gastroenteritis, meningitis or abortion. Listeria induces its internalization into some mammalian cells through binding of the bacterial surface protein InlB to its host receptor, the Met Receptor Tyrosine Kinase. InlB-induced activation of Met stimulates host signal transduction pathways that culminate in cell surface changes driving pathogen engulfment. One mammalian protein with the potential to couple Met to downstream signalling is the adaptor CrkII. CrkII contains an unusual carboxyl-terminal SH3 domain (SH3C) that promotes entry of Listeria. However, binding partners or downstream effectors of SH3C remain unknown. Here, we use RNA interference and overexpression studies to demonstrate that SH3C affects bacterial uptake, at least in part, through stimulation of host phosphatidylinositide (PI) 3-kinase. Experiments with latex beads coated with InlB protein indicated that one potential role of SH3C and PI 3 kinase is to promote changes in the F-actin cytoskeleton necessary for particle engulfment. Taken together, our results indicate that the CrkII SH3C domain engages a cellular ligand that regulates PI 3 kinase activity and host cell surface rearrangements.
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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".