Comparative metabolite profiling of salt sensitive <i>Oryza sativa</i> and the halophytic wild rice <i>Oryza coarctata</i> under salt stress
Bibliographic record
Abstract
Abstract To better understand the salt tolerance of the wild rice, Oryza coarctata, root tissue‐specific untargeted comparative metabolomic profiling was performed against the salt‐sensitive Oryza sativa. Under control, O. coarctata exhibited abundant levels of most metabolites, while salt caused their downregulation in contrast to metabolites in O. sativa. Under control conditions, itaconate, vanillic acid, threonic acid, eicosanoids, and a group of xanthin compounds were comparatively abundant in O. coarctata. Similarly, eight amino acids showed constitutive abundance in O. coarctata. In contrast, under control, glycerolipid abundances were lower in O. coarctata and salt stress further reduced their abundance. Most phospholipids also showed a distribution similar to the glycerolipids. Fatty acyls were however significantly induced in O. coarctata but organic acids were prominently induced in O. sativa. Changes in metabolite levels suggest that there was upregulation of the arachidonic acid metabolism in O. coarctata. In addition, the phenylpropanoid biosynthesis as well as cutin, suberin, and wax biosynthesis were also more enriched in O. coarctata, likely contributing to its anatomical traits responsible for salt tolerance. The comparative variation in the number of metabolites like gelsemine, allantoin, benzyl alcohol, specific phospholipids, and glycerolipids may play a role in maintaining the superior growth of O. coarctata in salt. Collectively, our results offer a comprehensive analysis of the metabolite profile in the roots of salt‐tolerant O. coarctata and salt‐sensitive O. sativa, which confirm potential targets for metabolic engineering to improve salt tolerance and resilience in commercial rice genotypes.
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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 | 0.000 |
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".