Concurrent profiling of indole-3-acetic acid, abscisic acid, and cytokinins and structurally related purines by high-performance-liquid-chromatography tandem electrospray mass spectrometry
Bibliographic record
Abstract
BACKGROUND: Cytokinins (CKs) are a group of plant growth regulators that are involved in several plant developmental processes. Despite the breadth of knowledge surrounding CKs and their diverse functions, much remains to be discovered about the full potential of CKs, including their relationship with the purine salvage pathway, and other phytohormones. The most widely used approach to query unknown facets of CK biology utilized functional genomics coupled with CK metabolite assays and screening of CK associated phenotypes. There are numerous different types of assays for determining CK quantity, however, none of these methods screen for the compendium of metabolites that are necessary for elucidating all roles, including purine salvage pathway enzymes in CK metabolism, and CK cross-talk with other phytohormones. Furthermore, all published analytical methods have drawbacks ranging from the required use of radiolabelled compounds, or hazardous derivatization reagents, poor sensitivity, lack of resolution between CK isomers and lengthy run times. RESULTS: In this paper, a method is described for the concurrent extraction, purification and analysis of several CKs (freebases, ribosides, glucosides, nucleotides), purines (adenosine monophosphate, inosine, adenosine, and adenine), indole-3-acetic acid, and abscisic acid from hundred-milligram (mg) quantities of Arabidopsis thaliana leaf tissue. This method utilizes conventional Bieleski solvents extraction, solid phase purification, and is unique because of its diverse range of detectable analytes, and implementation of a conventional HPLC system with a fused core column that enables good sensitivity without the requirement of a UHPLC system. Using this method we were able to resolve CKs about twice as fast as our previous method. Similarly, analysis of adenosine, indole-3-acetic acid, and abscisic acid, was comparatively rapid. A further enhancement of the method was the utilization of a QTRAP 5500 mass analyzer, which improved upon several aspects of our previous analytical method carried out on a Quattro mass analyzer. Notable improvements included much superior sensitivity, and number of analytes detectable within a single run. Limits of detection ranged from 2 pM for (9G)Z to almost 750 pM for indole-3-acetic acid. CONCLUSIONS: This method is well suited for functional genomics platforms tailored to understanding CK metabolism, CK interrelationships with purine recycling and associated hormonal cross-talk.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".