<i>N</i> -hydroxy pipecolic acid methyl ester is involved in Arabidopsis immunity
Bibliographic record
Abstract
Abstract The biosynthesis of N -hydroxy pipecolic acid (NHP) has been intensively studied, though knowledge on its metabolic turnover is still scarce. To close this gap, we discovered three novel metabolites via metabolite fingerprinting in Arabidopsis thaliana leaves. Exact mass information and fragmentation by mass spectrometry (MSMS) suggest a methylated derivative of NHP (MeNHP), a NHP- O Glc-hexosyl conjugate (NHP- O Glc-Hex) and an additional NHP- O Glc-derivative. All three compounds were formed in wildtype leaves but not present in the NHP deficient mutant fmo1-1 . The identification of these novel NHP-based molecules was possible by a dual-infiltration experiment using a mixture of authentic NHP- and D 9 -NHP-standards for leaf infiltration followed by an UV-C treatment. Interestingly, the signal intensity of MeNHP and other NHP-derived metabolites increased in ugt76b1-1 mutant plants. This suggests a detour, for the inability to synthesize NHP- O -glucoside. For MeNHP, we unequivocally determined the site of methylation at the carboxylic acid function. MeNHP application by leaf infiltration leads to the detection of a MeNHP- O Glc as well as NHP, suggesting MeNHP-hydrolysis to NHP. This is in line with the observation that MeNHP-infiltration is able to rescue the fmo1-1 susceptible phenotype against Hyaloperonospora arabidopsidis Noco 2. Together these data suggest MeNHP as additional storage or transport form of NHP. Highlight In this work, we identify N -hydroxy pipecolic acid (NHP) metabolites including methyl ester and complex glycosides. The application of methyl ester is able to rescue the disease phenotype of the biosynthesis deficient mutant of NHP.
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) | 0.000 | 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) | 0.002 | 0.001 |
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".