Characterization of denitrifying activity by the alphaproteobacterium, Sphingomonas wittichii RW1
Bibliographic record
Abstract
Sphingomonas wittichii RW1 has no reported denitrifying activity yet encodes nitrite and nitric oxide reductases. The aims of this study were to determine conditions under which S. wittichii RW1 consumes nitrite (NO(-) 2) and produces nitrous oxide (N2O), examine expression of putative genes for N-oxide metabolism, and determine the functionality of chromosomal (ch) and plasmid (p) encoded quinol-dependent nitric oxide reductases (NorZ). Batch cultures of wildtype (WT) and a norZ ch mutant of S. wittichii RW1 consumed NO(-) 2 and produced N2O during stationary phase. The norZ ch mutant produced N2O, although at significantly lower levels (c.a. 66-87%) relative to the WT. Rates of N2O production were 2-3 times higher in cultures initiated at low relative to atmospheric O2 per unit biomass, although rates of NO(-) 2 consumption were elevated in cultures initiated with atmospheric O2 and 1 mM NaNO2. Levels of mRNA encoding nitrite reductase (nirK), plasmid-encoded nitric oxide dioxygenase (hmp p) and plasmid-encoded nitric oxide reductase (norZ p) were significantly higher in the norZ ch mutant over a growth curve relative to WT. The presence of NO(-) 2 further increased levels of nirK and hmp p mRNA in both the WT and norZ ch mutant; levels of norZ p mRNA compensated for the loss of norZ ch expression in the norZ ch mutant. Together, the results suggest that S. wittichii RW1 denitrifies NO(-) 2 to N2O and expresses gene products predicted to detoxify N-oxides. So far, only S. wittichii strains within four closely related taxa have been observed to encode both nirK and norZ genes, indicating a species-specific lateral gene transfer that may be relevant to the niche preference of S. wittichii.
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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".