White Lupin Cluster Root Acclimation to Phosphorus Deficiency and Root Hair Development Involve Unique Glycerophosphodiester Phosphodiesterases
Bibliographic record
Abstract
White lupin (Lupinus albus) is a legume that is very efficient in accessing unavailable phosphorus (Pi). It develops short, densely clustered tertiary lateral roots (cluster/proteoid roots) in response to Pi limitation. In this report, we characterize two glycerophosphodiester phosphodiesterase (GPX-PDE) genes (GPX-PDE1 and GPX-PDE2) from white lupin and propose a role for these two GPX-PDEs in root hair growth and development and in a Pi stress-induced phospholipid degradation pathway in cluster roots. Both GPX-PDE1 and GPX-PDE2 are highly expressed in Pi-deficient cluster roots, particularly in root hairs, epidermal cells, and vascular bundles. Expression of both genes is a function of both Pi availability and photosynthate. GPX-PDE1 Pi deficiency-induced expression is attenuated as photosynthate is deprived, while that of GPX-PDE2 is strikingly enhanced. Yeast complementation assays and in vitro enzyme assays revealed that GPX-PDE1 shows catalytic activity with glycerophosphocholine while GPX-PDE2 shows highest activity with glycerophosphoinositol. Cell-free protein extracts from Pi-deficient cluster roots display GPX-PDE enzyme activity for both glycerophosphocholine and glycerophosphoinositol. Knockdown of expression of GPX-PDE through RNA interference resulted in impaired root hair development and density. We propose that white lupin GPX-PDE1 and GPX-PDE2 are involved in the acclimation to Pi limitation by enhancing glycerophosphodiester degradation and mediating root hair development.
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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) | 0.000 | 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".