SifA, a Type III Secreted Effector of <i>Salmonella typhimurium</i>, Directs <i>Salmonella</i>‐Induced Filament (Sif) Formation Along Microtubules
Bibliographic record
Abstract
A unique feature of Salmonella enterica serovar typhimurium (S. typhimurium) is its ability to enter into (invade) epithelial cells and elongate the vacuole it occupies into tubular structures called Salmonella-induced filaments (Sifs). This phenotype is dependent on SifA, a Salmonella virulence factor that requires the SPI-2-encoded type III secretion system for delivery into host cells. Previous attempts to study SifA and other type III secreted proteins have been limited by a lack of suitable reagents. We examined SifA function by expressing SifA with two internal hemagglutinin epitope tags. By employing subcellular fractionation techniques, we determined that translocated SifA was membrane associated in infected HeLa cells. Confocal microscopy revealed that SifA associated with the Salmonella vacuole and with Sifs. Our analysis also revealed that microtubules serve as a scaffold for Sifs, and that SifA colocalizes with microtubules at sites of interaction between lysosomal glycoprotein-containing vesicles and Sifs. Treatment with the microtubule inhibitor nocodazole blocked Sif formation but did not prevent SifA translocation into the Salmonella vacuole. While polymerized actin has been observed on Sifs, this phenotype was transient and did not play a role in promoting or maintaining Sif formation. Our findings demonstrate the essential role of microtubule dynamics in the formation of Sifs and the utility of this epitope tagging strategy for the study of bacterial type III secreted proteins.
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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".