Eliminating the purple acid phosphatase At<scp>PAP</scp>26 in <i>Arabidopsis thaliana</i> delays leaf senescence and impairs phosphorus remobilization
Bibliographic record
Abstract
Limitation of crop productivity by suboptimal phosphorus (P) nutrition is a widespread concern. Enhanced crop P-use efficiency could be achieved by improving P remobilization from senescing leaves to developing tissues and seeds. Transcriptomic studies indicate that hundreds of Arabidopsis thaliana genes are up-regulated during leaf senescence, including that encoding the purple acid phosphatase (PAP) AtPAP26 (At5g34850). In this study, biochemical and functional genomic tools were integrated to test the hypothesis that AtPAP26 participates in P remobilization during leaf senescence. An eightfold increase in acid phosphatase activity of senescing leaves was correlated with the accumulation of AtPAP26 transcripts and immunoreactive AtPAP26 polypeptides. Senescing leaves of an atpap26 T-DNA insertion mutant displayed a > 90% decrease in acid phosphatase activity, markedly impaired P remobilization efficiency and delayed senescence. This was paralleled by reduced seed total P concentrations and germination rates. These results demonstrate that AtPAP26 loss of function causes dramatic effects that cannot be compensated for by any other PAP isozyme, even though Arabidopsis contains 29 different PAP genes. Our current and earlier studies establish that AtPAP26 not only helps to scavenge P from organic P sources when Arabidopsis is cultivated in inorganic orthophosphate (Pi)-deficient soils, but also has an important P remobilization function during leaf senescence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
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".