A comprehensive study of the contribution of<i>Salmonella enterica</i>serovar Typhimurium SPI2 effectors to bacterial colonization, survival, and replication in typhoid fever, macrophage, and epithelial cell infection models
Bibliographic record
Abstract
Salmonella enterica serovars are Gram-negative bacterial pathogens responsible for human diseases including gastroenteritis and typhoid fever. After ingestion, Salmonella cross the intestinal epithelial barrier, where they are phagocytosed by macrophages and dendritic cells, which then enables their spread to systemic sites during cases of typhoid fever. Salmonella use two type 3 secretion systems encoded by Salmonella pathogenicity islands (SPI) 1 and 2 to inject virulence proteins into host cells to modify cellular functions. SPI1 is involved in host cell invasion and inflammation, whereas SPI2 is required for intracellular survival and replication within phagocytes, and systemic spread. In this study the contribution of nearly all known SPI2 effectors was examined in an in vivo model of murine typhoid fever and cell culture models of macrophage and epithelial cell infection. Unmarked, in-frame deletions of SPI2 effectors were engineered in S. enterica serovar Typhimurium and the ability of the 16 different mutants to colonize and replicate was examined. In the typhoid model, we found that ΔspvB and ΔspiC mutants were attenuated for colonization of intestinal and systemic sites, while the ΔsseF mutant was attenuated in systemic organs. In epithelial cells, all mutants replicated to the same extent as the wild-type. In macrophages, ΔspiC, ΔsteC, ΔspvB, ΔssseK1/K2/K3, ΔsifA, and ΔsifB strains replicated poorly in comparison to wild-type Salmonella. This study provides a thorough screen of the majority of the known SPI2 effectors evaluated under the same conditions in various models of infection, providing a foundation for comparative examination of the roles and interactions of these effectors.
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".