Evidence for post‐translational regulation of NrtA, the <i>Aspergillus nidulans</i> high‐affinity nitrate transporter
Bibliographic record
Abstract
Here, influx and efflux of (13)NO(3)(-), and net fluxes of (14)NO(3)(-) and (14)NO(2)(-), were measured in Aspergillus nidulans mutants niaD171 and niiA5, devoid of nitrate reductase (NR) and nitrite reductase (NiR) activities, respectively. Transcript and protein abundances of NrtA, the A. nidulans principal high-affinity NO(3)(-) transporter, were determined using semiquantitative reverse transcription-polymerase chain reaction and western blots, respectively. (13)NO(3)(-) influx in niaD171 was negligible relative to wild-type values, whereas efflux to influx ratios increased nine-fold. Nevertheless, NrtA mRNA and NrtA protein were expressed at levels more than two-fold and three-fold higher, respectively, in niaD171 than in the wild-type strain. This is the first demonstration of diminished high-affinity NO(3)(-) influx associated with elevated transporter levels, providing evidence that, in addition to transcriptional regulation, control of NrtA expression operates at the post-translational level. This mechanism allows for rapid control of NO(3)(-) transport at the protein level, reduces the extent of futile cycling of NO(3)(-) that would otherwise represent a significant energy drain when influx exceeds the capacity for assimilation or storage, and may be responsible for the rapid switching between the on and off state that is associated with simultaneous provision of NH(4)(+) to mycelia absorbing NO(3)(-).
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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 | 0.001 | 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".