Global Impact of Salmonella Pathogenicity Island 2-secreted Effectors on the Host Phosphoproteome
Bibliographic record
Abstract
During the late stages of infection, Salmonella secretes numerous effectors through a type III secretion system that is encoded within Salmonella pathogenicity island 2 (SPI2). Despite the importance of SPI2 as a major virulence factor leading to the systemic spread of the bacteria and diseases, a global view of its effects on host responses is still lacking. Here, we measured global impacts of SPI2 effectors on the host phosphorylation and protein expression levels in RAW264.7 and in HeLa cells, as macrophage and nonphagocytic models of infection. We observe that SPI2 effectors differentially modulate the host phosphoproteome and cellular processes (e.g. protein trafficking, cytoskeletal regulation, and immune signaling) in a host cell-dependent manner. Our unbiased approach reveals the involvement of many previously unrecognized proteins, including E3 ligases (HERC4, RanBP2, and RAD18), kinases (CDK, SIK3, and WNK1), and histones (H2B1F, H4, and H15), in late stages of Salmonella infection. Furthermore, from this phosphoproteome analysis and other quantitative screens, we identified HSP27 as a direct in vitro and in vivo molecular target of the only type III secreted kinase, SteC. Using biochemical and cell biological assays, we demonstrate that SteC phosphorylates multiple sites in HSP27 and induces actin rearrangement through this protein. Together, these results provide a broader landscape of host players contributing to specific processes/pathways mediated by SPI2 effectors than was previously appreciated.
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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".