Targeting Acr3 from<i>Ensifer medicae</i>to the plasma membrane or to the tonoplast of tobacco hairy roots allows arsenic extrusion or improved accumulation. Effect of<i>acr3</i>expression on the root transcriptome
Bibliographic record
Abstract
. Finally, the effects of the heterologous expression of acr3 on the root transcriptome were assessed. Expression at the plasma membrane induced drastic changes in gene expression, with outstanding overexpression of genes related to electron transport, ATP synthesis and ATPases, suggesting that As efflux is the main detoxification mechanism in these lines. In addition, genes encoding heat shock proteins and those related to proline synthesis and drought tolerance were activated. On the other hand, TIP-ACR3 lines showed a similar gene expression profile to that of control roots, with overexpression of the glutathione and phytochelatin synthesis pathways, together with secondary metabolism pathways as the most important resistance mechanisms in TIP-ACR3, for which As allocation into the vacuole allowed better growth and stress management. Our results suggest that modulation of As accumulation can be achieved by subcellular targeting of Acr3: expression at the tonoplast enhances As accumulation in roots, whereas expression at the plasma membrane could promote As efflux. Thus, both approaches open the possibilities for developing safer crops when grown on As-polluted paddy soils, but expression at the tonoplast leads to better growth and less stressed roots, since the high energy cost of As efflux likely compromises growth in ACR3 lines.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".