Modulation of Citrate Metabolism Alters Aluminum Tolerance in Yeast and Transgenic Canola Overexpressing a Mitochondrial Citrate Synthase
Bibliographic record
Abstract
Aluminum (Al) toxicity is a major constraint for crop production in acid soils, although crop cultivars vary in their tolerance to Al. We have investigated the potential role of citrate in mediating Al tolerance in Al-sensitive yeast (Saccharomyces cerevisiae; MMYO11) and canola (Brassica napus cv Westar). Yeast disruption mutants defective in genes encoding tricarboxylic acid cycle enzymes, both upstream (citrate synthase [CS]) and downstream (aconitase [ACO] and isocitrate dehydrogenase [IDH]) of citrate, showed altered levels of Al tolerance. A triple mutant of CS (Deltacit123) showed lower levels of citrate accumulation and reduced Al tolerance, whereas Deltaaco1- and Deltaidh12-deficient mutants showed higher accumulation of citrate and increased levels of Al tolerance. Overexpression of a mitochondrial CS (CIT1) in MMYO11 resulted in a 2- to 3-fold increase in citrate levels, and the transformants showed enhanced Al tolerance. A gene for Arabidopsis mitochondrial CS was overexpressed in canola using an Agrobacterium tumefaciens-mediated system. Increased levels of CS gene expression and enhanced CS activity were observed in transgenic lines compared with the wild type. Root growth experiments revealed that transgenic lines have enhanced levels of Al tolerance. The transgenic lines showed enhanced levels of cellular shoot citrate and a 2-fold increase in citrate exudation when exposed to 150 micro M Al. Our work with yeast and transgenic canola clearly suggest that modulation of different enzymes involved in citrate synthesis and turnover (malate dehydrogenase, CS, ACO, and IDH) could be considered as potential targets of gene manipulation to understand the role of citrate metabolism in mediating Al tolerance.
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 | 0.000 |
| 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".