Francisella tularensis Uses Cholesterol and Clathrin-Based Endocytic Mechanisms to Invade Hepatocytes
Bibliographic record
Abstract
Francisella tularensis are highly infectious microbes that cause the disease tularemia. Although much of the bacterial burden is carried in non-phagocytic cells, the strategies these pathogens use to invade these cells remains elusive. To examine these mechanisms we developed two in vitro Francisella-based infection models that recapitulate the non-phagocytic cell infections seen in livers of infected mice. Using these models we found that Francisella novicida exploit clathrin and cholesterol dependent mechanisms to gain entry into hepatocytes. We also found that the clathrin accessory proteins AP-2 and Eps15 co-localized with invading Francisella novicida as well as the Francisella Live Vaccine Strain (LVS) during hepatocyte infections. Interestingly, caveolin, a protein involved in the invasion of Francisella in phagocytic cells, was not required for non-phagocytic cell infections. These results demonstrate a novel endocytic mechanism adopted by Francisella and highlight the divergence in strategies these pathogens utilize between non-phagocytic and phagocytic cell invasion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".