Untargeted metabolomics reveals anion and organ-specific biochemistry of salinity tolerance in willow
Bibliographic record
Abstract
1 Abstract Willows can alleviate soil salinisation while generating sustainable feedstock for biorefinery, yet the metabolomic adaptations underlying their salt tolerance remain poorly understood. Testing two environmentally abundant salts, the response of Salix miyabeana was assessed after treatment with a moderate concentration of NaCl, and both moderate and high concentrations of Na 2 SO 4 in a 12-week pot trial. Willows tolerated salts across all treatments (up to 9.1dS m -1 soil EC e ), maintaining photosynthesis and biomass while selectively partitioning ions, confining Na + to roots and accumulating Cl - and SO 2- in the canopy, and adapting to osmotic stress via reduced stomatal conductance. Untargeted LC-MS/MS captured over 5,000 putative compounds, characterising the baseline willow metabolome, including 278 core compounds constitutively produced across organs. Comparative statistical analyses revealed widespread metabolic reprogramming in response to soil salinity, altering 28% of the overall metabolome, and highlighting organ-tailored regulation. Comparing both salt forms at equimolar sodium, generalised salinity responses were limited to 3% of the metabolome, predominantly in roots. Anion-specific metabolomic responses were more extensive, with NaCl reducing carbohydrates and TCA intermediates, thereby exerting pressure on carbon and energy resources, alongside the accumulation of root structuring compounds, antioxidants flavonoids, and fatty acids. In contrast, Na 2 SO 4 salinity triggered accumulation of sulphur-containing larger peptides, suggesting that excess sulphate incorporation leverage ion toxicity to produce specialized salt-tolerance associated metabolites. This high-depth picture of the willow metabolome underscores the importance of capturing plant adaptations to salt stress at organ-scale and considering ion-specific contributions to soil salinity.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".