The Deubiquitinase Activity of the Salmonella Pathogenicity Island 2 Effector, SseL, Prevents Accumulation of Cellular Lipid Droplets
Bibliographic record
Abstract
To cause disease, Salmonella enterica serovar Typhimurium requires two type III secretion systems that are encoded by Salmonella pathogenicity islands 1 and 2 (SPI-1 and -2). These secretion systems serve to deliver specialized proteins (effectors) into the host cell cytosol. While the importance of these effectors to promote colonization and replication within the host has been established, the specific roles of individual secreted effectors in the disease process are not well understood. In this study, we used an in vivo gallbladder epithelial cell infection model to study the function of the SPI-2-encoded type III effector, SseL. The deletion of the sseL gene resulted in bacterial filamentation and elongation and the unusual localization of Salmonella within infected epithelial cells. Infection with the ΔsseL strain also caused dramatic changes in host cell lipid metabolism and led to the massive accumulation of lipid droplets in infected cells. This phenotype was directly attributable to the deubiquitinase activity of SseL, as a Salmonella strain carrying a single point mutation in the catalytic cysteine also resulted in extensive lipid droplet accumulation. The excessive buildup of lipids due to the absence of a functional sseL gene also was observed in murine livers during S. Typhimurium infection. These results suggest that SseL alters host lipid metabolism in infected epithelial cells by modifying the ubiquitination patterns of cellular targets.
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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".