Faculty Opinions recommendation of A bifunctional O-GlcNAc transferase governs flagellar motility through anti-repression.
Bibliographic record
Abstract
Flagellar motility is an essential mechanism by which bacteria adapt to and survive in diverse environments.Although flagella confer an advantage to many bacterial pathogens for colonization during infection, bacterial flagellins also stimulate host innate immune responses.Consequently, many bacterial pathogens down-regulate flagella production following initial infection.Listeria monocytogenes is a facultative intracellular pathogen that represses transcription of flagellar motility genes at physiological temperatures (37°C and above).Temperature-dependent expression of flagellar motility genes is mediated by the opposing activities of MogR, a DNA-binding transcriptional repressor, and DegU, a response regulator that functions as an indirect antagonist of MogR.In this study, we identify an additional component of the molecular circuitry governing temperature-dependent flagellar gene expression.At low temperatures (30°C and below), MogR repression activity is specifically inhibited by an anti-repressor, GmaR.We demonstrate that GmaR forms a stable complex with MogR, preventing MogR from binding its DNA target sites.GmaR anti-repression activity is temperature dependent due to DegU-dependent transcriptional activation of gmaR at low temperatures.Thus, GmaR production represents the first committed step for flagella production in L. monocytogenes.Interestingly, GmaR also functions as a glycosyltransferase exhibiting O-linked N-acetylglucosamine transferase (OGT) activity for flagellin (FlaA).GmaR is the first OGT to be identified and characterized in prokaryotes that specifically -O-GlcNAcylates a prokaryotic protein.Unlike the well-characterized, highly conserved OGT regulatory protein in eukaryotes, the catalytic activity of GmaR is functionally separable from its anti-repression function.These results establish GmaR as the first known example of a bifunctional protein that transcriptionally regulates expression of its enzymatic substrate.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.270 | 0.122 |
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".