Phylogenetics and environmental distribution of nitric oxide-forming nitrite reductases reveal their distinct functional and ecological roles
Bibliographic record
Abstract
Abstract The two evolutionarily unrelated nitric oxide-producing nitrite reductases, NirK and NirS, are best known for their redundant role in denitrification. They are also often found in organisms that do not perform denitrification. To assess the functional roles of the two enzymes and to address the sequence and structural variation within each, we reconstructed robust phylogenies of both proteins with sequences recovered from 6973 isolate and metagenome-assembled genomes and identified 32 well-supported clades of structurally distinct protein lineages. We then inferred the potential niche of each clade by considering other functional genes of the organisms carrying them as well as the relative abundances of each nir gene in 4082 environmental metagenomes across diverse aquatic, terrestrial, host-associated, and engineered biomes. We demonstrate that Nir phylogenies recapitulate ecology distinctly from the corresponding organismal phylogeny. While some clades of the nitrite reductase were equally prevalent across biomes, others had more restricted ranges. Nitrifiers make up a sizeable proportion of the nitrite-reducing community, especially for NirK in marine waters and dry soils. Furthermore, the two reductases showed distinct associations with genes involved in oxidizing and reducing other compounds, indicating that the NirS and NirK activities may be linked to different elemental cycles. Accordingly, the relative abundance and diversity of NirS versus NirK vary between biomes. Our results show the divergent ecological roles NirK and NirS-encoding organisms may play in the environment and provide a phylogenetic framework to distinguish the traits associated with organisms encoding the different lineages of nitrite reductases.
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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 | 0.001 | 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".