Expression of nitrous oxide reductase from <i>Pseudomonas stutzeri</i> in transgenic tobacco roots using the root‐specific <i>rolD</i> promoter from <i>Agrobacterium rhizogenes</i>
Bibliographic record
Abstract
The nitrous oxide (N(2)O) reduction pathway from a soil bacterium, Pseudomonas stutzeri, was engineered in plants to reduce N(2)O emissions. As a proof of principle, transgenic plants expressing nitrous oxide reductase (N(2)OR) from P. stutzeri, encoded by the nosZ gene, and other transgenic plants expressing N(2)OR along with the more complete operon from P. stutzeri, encoded by nosFLZDY, were generated. Gene constructs were engineered under the control of a root-specific promoter and with a secretion signal peptide. Expression and rhizosecretion of the transgene protein were achieved, and N(2)OR from transgenic Nicotiana tabacum proved functional using the methyl viologen assay. Transgenic plant line 1.10 showed the highest specific activity of 16.7 µmol N(2)O reduced min(-1) g(-1) root protein. Another event, plant line 1.9, also demonstrated high specific activity of N(2)OR, 13.2 µmol N(2)O reduced min(-1) g(-1) root protein. The availability now of these transgenic seed stocks may enable canopy studies in field test plots to monitor whole rhizosphere N flux. By incorporating one bacterial gene into genetically modified organism (GMO) crops (e.g., cotton, corn, and soybean) in this way, it may be possible to reduce the atmospheric concentration of N(2)O that has continued to increase linearly (about 0.26% year(-1)) over the past half-century.
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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) | 0.001 | 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) | 0.000 | 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".