Rac1, RhoA, and Cdc42 participate in HeLa cell invasion by group B streptococcus
Bibliographic record
Abstract
The group B streptococcus (GBS) is an important human pathogen with the ability to cause invasive disease. To do so, the bacteria must invade host cells. It has been well documented that GBS are able to invade a variety of nonphagocytic host cell types, and this process is thought to involve a number of pathogen-host cell interactions. While some of the molecular aspects of the GBS-host cell invasion process have been characterized, many events still remain unclear. The objective of this investigation was to evaluate the role of the Rho-family GTPases Rac, Rho, and Cdc42 in GBS invasion into epithelial cells. The epithelial cell invasion process was modeled using HeLa 229 cell culture. Treatment of HeLa cells with 10 microM compactin, a pan-GTPase inhibitor, abolished GBS internalization, suggesting that GTPases are involved in the GBS invasion process. The addition of Toxin B or exoenzyme C3 to HeLa cells before GBS infection reduced invasion by 50%, further suggesting that the Rho-family GTPases are involved in GBS entry. Examining invasion of GBS into HeLa cells with altered genetic backgrounds was used to confirm these findings; GBS invasion into HeLa cells transiently transfected with dominant negative Rac1, Cdc42, or RhoA reduced invasion by 75%, 51%, and 42%, respectively. Results of this study suggest that the Rho-family GTPases are required for efficient invasion of HeLa cells by GBS.
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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".