Comparison of Nitrogen Oxide Metabolism among Diverse Ammonia-Oxidizing Bacteria
Bibliographic record
Abstract
Ammonia-oxidizing bacteria (AOB) have well characterized genes that encode and express nitrite reductases (NIR) and nitric oxide reductases (NOR). However, the connection between presence or absence of these and other genes for nitrogen transformations with the physiological production of nitric oxide (NO) and nitrous oxide (N2O) has not been tested across AOB isolated from various trophic states, with diverse phylogeny, and with closed genomes. It is therefore unclear if genomic content for nitrogen oxide metabolism is predictive of net N2O production. Instantaneous microrespirometry experiments were utilized to measure NO and N2O emitted by AOB during active oxidation of ammonia (NH3) or hydroxylamine (NH2OH) and through a period of anoxia. This data was used in concert with genomic content and phylogeny to assess whether taxonomic factors were predictive of nitrogen oxide metabolism. Results showed that two oligotrophic AOB strains lacking annotated NOR-encoding genes released large quantities of NO and produced N2O abiologically at the onset of anoxia following NH3-oxidation. Furthermore, high concentrations of N2O were measured during active O2-dependent NH2OH oxidation by the two oligotrophic AOB in contrast to non-oligotrophic strains that only produced N2O at the onset of anoxia. Therefore, complete nitrifier denitrification did not occur in the two oligotrophic strains, but did occur in meso- and eutrophic strains, even in Nitrosomonas communis Nm2 that lacks an annotated NIR-encoding gene. Regardless of mechanism, all AOB strains produced measureable N2O under tested conditions. This work further confirms that AOB require NOR activity to enzymatically reduce NO to N2O in the nitrifier denitrification pathway, and also that abiotic reactions play an important role in N2O formation, in oligotrophic AOB lacking NOR activity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".