Identification of MEK- and phosphoinositide 3-kinase-dependent signalling as essential events during Chlamydia pneumoniae invasion of HEp2 cells
Bibliographic record
Abstract
The ability of Chlamydia pneumoniae to survive and cause disease is predicated on efficient invasion of cellular hosts. While it is recognized that chlamydial determinants are important for mediating attachment and uptake into non-phagocytic cells, little is known about the bacterial ligands and cellular receptors that facilitate invasion or host cell signal transduction pathways implicated in this process. We used transmission and scanning electron microscopy to demonstrate that attachment of bacteria to host cells induced the appearance of microvilli on host cell membranes. Invasion occurred 30-120 min after cell contact with the subsequent loss of membrane microvilli. Using an epithelial cell infection model, C. pneumoniae invasion caused a rapid and sustained increase in MEK-dependent phosphorylation and activation of ERK1/2, followed by PI 3-kinase-dependent phosphorylation and activation of Akt. Tyrosine phosphorylation of focal adhesion kinase (FAK) preceded its appearance in a complex with the p85 subunit of PI 3-kinase during chlamydial invasion and isoform-specific tyrosine phosphorylation of the docking protein Shc also occurred at the time of attachment and entry of bacteria. Chlamydia entry but not attachment could be abrogated with specific inhibitors of MEK, PI 3-kinase and actin polymerization, demonstrating the importance of these signalling pathways and an intact actin cytoskeleton for C. pneumoniae invasion. These results suggest that activation of specific cell signalling pathways is an essential strategy used by C. pneumoniae to invade epithelial cells.
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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".