Molecular and Biochemical Characterization of AtPAP15, a Purple Acid Phosphatase with Phytase Activity, in Arabidopsis
Bibliographic record
Abstract
Purple acid phosphatase (PAP) catalyzes the hydrolysis of phosphate monoesters and anhydrides to release phosphate within an acidic pH range. Among the 29 PAP-like proteins in Arabidopsis (Arabidopsis thaliana), AtPAP15 (At3g07130) displays a greater degree of amino acid identity with soybean (Glycine max; GmPHY) and tobacco (Nicotiana tabacum) PAP (NtPAP) with phytase activity than the other AtPAPs. In this study, transgenic Arabidopsis that expressed an AtPAP15 promoterbeta-glucuronidase (GUS) fusion protein showed that AtPAP15 expression was developmentally and temporally regulated, with strong GUS staining at the early stages of seedling growth and pollen germination. The expression was also organ/tissue specific, with strongest GUS staining in the vasculature, pollen grains, and roots. The recombinant AtPAP purified from transgenic tobacco exhibited broad substrate specificity with moderate phytase activity. AtPAP15 T-DNA insertion lines exhibited a lower phytase and phosphatase activity in seedling and germinating pollen and lower pollen germination rate compared with the wild type and their complementation lines. Therefore, AtPAP15 likely mobilizes phosphorus reserves in plants, particularly during seed and pollen germination. Since AtPAP15 is not expressed in the root hair or in the epidermal cells, it is unlikely to play any role in external phosphorus assimilation.
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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) | 0.001 | 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".