Sequence Divergence in the Arginase Domain of Ornithine Decarboxylase/Arginase in <i>Fusobacteriacea</i> Leads to Loss of Function in Oral Associated Species
Bibliographic record
Abstract
A number of species within the Fusobacteriaceae family of Gram-negative bacteria uniquely encode for an ornithine decarboxylase/arginase (ODA) that ostensibly channels l -ornithine generated by hydrolysis of l -arginine to putrescine formation. However, two aspartate residues required for coordination to a catalytically obligatory manganese cluster of arginases are substituted for a serine and an asparagine. Curiously, these natural substitutions occur only in a clade of Fusobacterium species that inhabit the oral cavity. Herein, we expressed and isolated full-length ODA from the opportunistic oral pathogen Fusobacterium nucleatum along with the individual arginase and ornithine decarboxylase components. The crystal structure of the arginase domain reveals that it adopts the classical α/β arginase-fold, but metal ions are absent in the active site. As expected, the ureohydrolase activity with l -arginine was not detected for wild-type ODA or the isolated arginase domain. However, engineering of the complete metal coordination environment through site-directed mutagenesis restored Mn 2+ binding capacity and arginase activity, although the catalytic efficiency for l -arginine was low (60–100 M –1 s –1 ). Full-length ODA and the isolated ODC component were able to decarboxylate both l -ornithine and l -arginine to form putrescine and agmatine, respectively, but k cat / K M of l -ornithine was ∼20-fold higher compared to l -arginine. We discuss environmental conditions that may have led to the natural selection of an inactive arginase in the oral associated species of Fusobacterium .
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".