Polar Flagella Glycosylation in Aeromonas: Genomic Characterization and Involvement of a Specific Glycosyltransferase (Fgi-1) in Heterogeneous Flagella Glycosylation
Bibliographic record
Abstract
Polar flagella from mesophilic Aeromonas strains have previously been shown to be modified with a range of glycans. Mass spectrometry studies of purified polar flagellins suggested the glycan typically includes a putative pseudaminic acid like derivative; while some strains are modified with this single monosaccharide, others modified with a heterologous glycan. In the current study, we demonstrate that genes involved in polar flagella glycosylation are clustered in highly polymorphic genomic islands flanked by pseudaminic acid biosynthetic genes ( pse ). Bioinformatic analysis of mesophilic Aeromonas genomes identified three types of polar flagella glycosylation islands (FGIs), denoted Group I, II and III. FGI Groups I and III are small genomic islands present in Aeromonas strains with flagellins modified with a single monosaccharide pseudaminic acid derivative. Group II were large genomic islands, present in strains found to modify polar flagellins with heterogeneous glycan moieties. Group II, in addition to pse genes, contained numerous glycosyltransferases and other biosynthetic enzymes. All Group II strains shared a common glycosyltransferase downstream of luxC that we named flagella glycosylation island 1, fgi-1 , in A. piscicola AH-3. We demonstrate that Fgi-1 transfers the first sugar of the heterogeneous glycan to the pseudaminic acid derivative linked to polar flagellins and could be used as marker for polysaccharidic glycosylation of Aeromonas polar flagella.
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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 | 0.001 |
| 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".