NOD1 is super-activated through spatially-selective ubiquitination by the <i>Salmonella</i> effector SspH2
Bibliographic record
Abstract
ABSTRACT As part of its pathogenesis, Salmonella enterica serovar Typhimurium delivers effector proteins into host cells. One effector is SspH2, a member of the novel E3 ubiquitin ligase family, interacts with, and enhances, NOD1 pro-inflammatory signaling, though the underlying mechanisms are unclear. Here, we report the novel discovery that SspH2 interacts with multiple members of the NLRC family to enhance pro-inflammatory signaling that results from targeted ubiquitination. We show that SspH2 modulates host innate immunity by interacting with both NOD1 and NOD2 in mammalian epithelial cell culture. We also show that SspH2 specifically interacts with the NBD and LRR domains of NOD1 and super-activates NOD1- and NOD2-mediated cytokine secretion via the NF-κB pathway. Mass spectrometry analyses identified lysine residues in NOD1 that were ubiquitinated after interaction with SspH2. Through NOD1 mutational analyses, we identified four key lysine residues that are required for NOD1 super-activation by SspH2, but not its basal activity. These critical lysine residues are positioned in the same region of NOD1 and define a surface on NOD1 that is targeted by SspH2. Overall, this work provides evidence for post-translational modification of NOD1 by ubiquitin, and uncovers a unique mechanism of spatially-selective ubiquitination to enhance the activation of an archetypal NLR. SYNOPSIS SspH2 is an E3 ubiquitin ligase injected by Salmonella Typhimurium into host cells that induces pro-inflammatory signaling. The immune receptor, NOD1, is ubiquitinated in the presence of SspH2, resulting in increased pro-inflammatory cytokine secretion. SspH2 super-activates NOD1 and NOD2 to increase pro-inflammatory cytokine secretion, in part, through the NF-κB pathway Ubiquitin modification of NOD1 were identified by mass spectrometry A specific region of NOD1 is targeted by SspH2 to enhance NOD1 activity.
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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) | 0.002 | 0.001 |
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".