Characterization of <i>Salmonella</i>‐Induced Filaments (Sifs) Reveals a Delayed Interaction Between <i>Salmonella</i>‐Containing Vacuoles and Late Endocytic Compartments
Bibliographic record
Abstract
Salmonella typhimurium is a facultative intracellular pathogen that colonizes host cells throughout the course of infection. A unique feature of this pathogen is its ability to enter into (invade) epithelial cells and elongate the vacuole within which it resides into tubular structures called Salmonella-induced filaments (Sifs). In this study we sought to characterize the mechanism of Sif formation by immunofluorescence analysis using subcellular markers. The late endosomal lipid lysobisphosphatidic acid associated in a punctate pattern with the Salmonella-containing vacuole, starting 90 min after infection and increasing thereafter. Lysobisphosphatidic acid-rich vesicles were also found to interact with Sifs, at numerous sites along the tubules. Similarly, cholesterol-rich vesicles were also found in association with intracellular bacteria and Sifs. The lysosomal hydrolase cathepsin D was present in Sifs, both in a punctate pattern and, at later times, predominantly in an uninterrupted linear pattern. Rab7 associated with Sifs and expression of the N125I dominant negative mutant of this GTPase inhibited Sif formation. Transfection of HeLa cells with a vector encoding SifA fused to the green fluorescent protein caused swelling and aggregation of lysobisphosphatidic acid-containing compartments, suggesting that this virulence factor directs membrane fusion events involving late endosomes. Our findings demonstrate that Sif formation involves fusion of late endocytic compartments with the Salmonella-containing vacuole, and suggest that SifA modulates this event.
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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".