Engineered Ubiquitin Variants Mitigate Pathogenic Bacterial Ubiquitin Ligase Function
Bibliographic record
Abstract
Abstract During infection some pathogenic gram-negative bacteria, such as Salmonella , manipulate the host ubiquitination system through the delivery of secreted effectors known as novel E3 ubiquitin ligases (NELs). Despite the presence of NELs amongst these well-studied bacterial species, their unique structure has limited the tools that are available to probe their molecular mechanisms and explore their therapeutic potential. In this work, we report the identification of two high affinity engineered ubiquitin variants that can modulate the activity of the Salmonella enterica serovar Typhimurium encoded NEL, SspH1. We show that these ubiquitin variants suppress SspH1-mediated toxicity phenotypes in Saccharomyces cerevisiae . Additionally, we provide microscopic and flow cytometric evidence that SspH1-mediated toxicity is caused by interference with S. cerevisiae cell cycle progression that can be suppressed in the presence of ubiquitin variants. In vitro ubiquitination assays revealed that these ubiquitin variants increased the amount of SspH1-mediated ubiquitin chain formation. Interestingly, despite the increase in ubiquitin chains, we observe a relative decrease in the formation of SspH1-mediated K48-linked ubiquitin chains on its substrate, PKN1. Taken together our findings suggest that SspH1 toxicity in S. cerevisiae occurs through cell cycle interference and that an engineered ubiquitin variant approach can be used to identify modulators of bacterially encoded ubiquitin ligases. Author Summary Novel E3 ligases (NELs) are a family of secreted effectors found in various pathogenic gram- negative bacteria. During infection these effectors hijack vital host ubiquitin signaling pathways to aid bacterial invasion and persistence. Despite interacting with a protein as highly conserved as ubiquitin, they have a distinct architecture relative to the eukaryotic E3 enzymes. This unique architecture combined with the indispensable role ubiquitin signaling plays in host cell survival has made hindering the contribution of NELs to bacterial infections a difficult task. Here, we applied protein engineering technology to identify two ubiquitin variants (Ubvs) with high affinity for SspH1, a Salmonella -encoded NEL. We provide evidence that these high affinity Ubvs suppress a known SspH1-meidated toxicity phenotype in the eukaryotic model system Saccharomyces cerevisiae . We also show that this suppression occurs without interfering with host ubiquitin signaling. Furthermore, we demonstrate the ability of a Ubv to modulate the activity of SspH1 in vitro , ultimately altering the lysine linkages found in SspH1-mediated ubiquitination. To our knowledge, this is the first evidence that an engineered ubiquitin variant approach can be implemented to modulate the activity of a family of previously untargetable bacterial-encoded E3 ligases.
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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".