Functional diversification of the NleG effector family in enterohemorrhagic <i>Escherichia coli</i>
Bibliographic record
Abstract
The pathogenic strategy of Escherichia coli and many other gram-negative pathogens relies on the translocation of a specific set of proteins, called effectors, into the eukaryotic host cell during infection. These effectors act in concert to modulate host cell processes in favor of the invading pathogen. Injected by the type III secretion system (T3SS), the effector arsenal of enterohemorrhagic E. coli (EHEC) O157:H7 features at least eight individual NleG effectors, which are also found across diverse attaching and effacing pathogens. NleG effectors share a conserved C-terminal U-box E3 ubiquitin ligase domain that engages with host ubiquitination machinery. However, their specific functions and ubiquitination targets have remained uncharacterized. Here, we identify host proteins targeted for ubiquitination-mediated degradation by two EHEC NleG family members, NleG5-1 and NleG2-3. NleG5-1 localizes to the host cell nucleus and targets the MED15 subunit of the Mediator complex, while NleG2-3 resides in the host cytosol and triggers degradation of Hexokinase-2 and SNAP29. Our structural studies of NleG5-1 reveal a distinct N-terminal α/β domain that is responsible for interacting with host protein targets. The core of this domain is conserved across the NleG family, suggesting this domain is present in functionally distinct NleG effectors, which evolved diversified surface residues to interact with specific host proteins. This is a demonstration of the functional diversification and the range of host proteins targeted by the most expanded effector family in the pathogenic arsenal of E. coli .
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".