Direct Identification of a Bacterial Manganese(II) Oxidase, the Multicopper Oxidase MnxG, from Spores of Several Different Marine <i>Bacillus</i> Species
Bibliographic record
Abstract
Microorganisms catalyze the formation of naturally occurring Mn oxides, but little is known about the biochemical mechanisms of this important biogeochemical process. We used tandem mass spectrometry to directly analyze the Mn(II)-oxidizing enzyme from marine Bacillus spores, identified as an Mn oxide band with an in-gel activity assay. Nine distinct peptides recovered from the Mn oxide band of two Bacillus species were unique to the multicopper oxidase MnxG, and one peptide was from the small hydrophobic protein MnxF. No other proteins were detected in the Mn oxide band, indicating that MnxG (or a MnxF/G complex) directly catalyzes biogenic Mn oxide formation. The Mn(II) oxidase was partially purified and found to be resistant to many proteases and active even at high concentrations of sodium dodecyl sulfate. Comparative analysis of the genes involved in Mn(II) oxidation from three diverse Bacillus species revealed a complement of conserved Cu-binding regions not present in well-characterized multicopper oxidases. Our results provide the first direct identification of a bacterial enzyme that catalyzes Mn(II) oxidation and suggest that MnxG catalyzes two sequential one-electron oxidations from Mn(II) to Mn(III) and from Mn(III) to Mn(IV), a novel type of reaction for a multicopper oxidase.
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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 | 0.000 |
| 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".