Mass spectrometry‐based quantification and spatial localization of small organic acid exudates in plant roots under phosphorus deficiency and aluminum toxicity
Bibliographic record
Abstract
Low-molecular-weight organic acid (OA) extrusion by plant roots is critical for plant nutrition, tolerance to cations toxicity, and plant-microbe interactions. Therefore, methodologies for the rapid and precise quantification of OAs are necessary to be incorporated in the analysis of roots and their exudates. The spatial location of root exudates is also important to understand the molecular mechanisms directing OA production and release into the rhizosphere. Here, we report the development of two complementary methodologies for OA determination, which were employed to evaluate the effect of inorganic ortho-phosphate (Pi) deficiency and aluminum toxicity on OA excretion by Arabidopsis roots. OA exudation by roots is considered a core response to different types of abiotic stress and for the interaction of roots with soil microbes, and for decades has been a target trait to produce plant varieties with increased capacities of Pi uptake and Al tolerance. Using targeted ultra-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UPLC-HRMS/MS), we achieved the quantification of six OAs in root exudates at sub-micromolar detection limits with an analysis time of less than 5 min per sample. We also employed targeted (MS/MS) matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to detect the spatial location of citric and malic acid with high specificity in roots and exudates. Using these methods, we studied OA exudation in response to Al toxicity and Pi deficiency in Arabidopsis seedlings overexpressing genes involved in OA excretion. Finally, we show the transferability of the MALDI-MSI method by analyzing OA excretion in Marchantia polymorpha gemmalings subjected to Pi deficiency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".