Effect of pH and Temperature on Denitrification Gene Expression and Activity in <i>Pseudomonas mandelii</i>
Bibliographic record
Abstract
Pseudomonas mandelii liquid cultures were studied to determine the effect of pH and temperature on denitrification gene expression, which was quantified by quantitative reverse transcription-PCR. Denitrification was measured by the accumulation of nitrous oxide (N(2)O) in the headspace in the presence of acetylene. Levels of gene expression of nirS and cnorB at pH 5 were 539-fold and 6,190-fold lower, respectively, than the levels of gene expression for cells grown at pH 6, 7, and 8 between 4 h and 8 h. Cumulative denitrification levels were 28 micromol, 63 micromol, and 22 micromol at pH 6, 7, and 8, respectively, at 8 h, whereas negligible denitrification was measured at pH 5. P. mandelii cells grown at 20 degrees C and 30 degrees C exhibited 9-fold and 94-fold increases in levels of cnorB expression between 0 h and 2 h, respectively, and an average 17-fold increase in levels of nirS gene expression. In contrast, induction of cnorB and nirS gene expression for P. mandelii cells grown at 10 degrees C did not occur in the first 4 h. Levels of cumulative denitrification at 10 h were 6.6 micromol for P. mandelii cells grown at 10 degrees C and 20 degrees C and 30 micromol for cells grown at 30 degrees C. Overall, levels of cnorB and nirS expression were relatively insensitive to pH values over the range of pH 6 to 8 but were substantially reduced at pH 5, whereas gene expression was sensitive to temperature, with induction and time to achieve maximum gene expression delayed as the temperature decreased from 30 degrees C. Low pH and temperature negatively affected denitrification activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".