Glycosylating Effectors of Legionella pneumophila: Finding the Sweet Spots for Host Cell Subversion
Bibliographic record
Abstract
Work over the past two decades clearly defined a significant role of glycosyltransferase effectors in the infection strategy of the Gram-negative, respiratory pathogen Legionella pneumophila. Identification of the glucosyltransferase effectors Lgt1-3, specifically modifying elongation factor eEF1A, disclosed a novel mechanism of host protein synthesis manipulation by pathogens and illuminated its impact on the physiological state of the target cell, in particular cell cycle progression and immune and stress responses. Recent characterization of SetA as a general O-glucosyltransferase with a wide range of targets including the proteins Rab1 and Snx1, mediators of membrane transport processes, and the discovery of new types of glycosyltransferases such as LtpM and SidI indicate that the vast effector arsenal might still hold more so-far unrecognized family members with new catalytic features and substrates. In this article, we review our current knowledge regarding these fascinating biomolecules and discuss their role in introducing new or overriding endogenous post-translational regulatory mechanisms enabling the subversion of eukaryotic cells by L. pneumophila.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".