FbpA, a novel multifunctional <i>Listeria monocytogenes</i> virulence factor
Bibliographic record
Abstract
Listeria monocytogenes is a Gram-positive intracellular bacterium responsible for severe opportunistic infections in humans and animals. Signature-tagged mutagenesis (STM) was used to identify a gene named fbpA, required for efficient liver colonization of mice inoculated intravenously. FbpA was also shown to be required for intestinal and liver colonization after oral infection of transgenic mice expressing human E-cadherin. fbpA encodes a 570-amino-acid polypeptide that has strong homologies to atypical fibronectin-binding proteins. FbpA binds to immobilized human fibronectin in a dose-dependent and saturable manner and increases adherence of wild-type L. monocytogenes to HEp-2 cells in the presence of exogenous fibronectin. Despite the lack of conventional secretion/anchoring signals, FbpA is detected using an antibody generated against the recombinant FbpA protein on the bacterial surface by immunofluorescence, and in the membrane compartment by Western blot analysis of cell extracts. Strikingly, FbpA expression affects the protein levels of two virulence factors, listeriolysin O (LLO) and InlB, but not that of InlA or ActA. FbpA co-immunoprecipitates with LLO and InlB, but not with InlA or ActA. Thus, FbpA, in addition to being a fibronectin-binding protein, behaves as a chaperone or an escort protein for two important virulence factors and appears as a novel multifunctional virulence factor of L. monocytogenes.
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".