Plant Defense Responses in Opium Poppy Cell Cultures Revealed by Liquid Chromatography-Tandem Mass Spectrometry Proteomics
Bibliographic record
Abstract
Opium poppy (Papaver somniferum) produces a diverse array of bioactive benzylisoquinoline alkaloids, including the narcotic analgesic morphine and the antimicrobial agent sanguinarine. In contrast to the plant, cell cultures of opium poppy do not accumulate alkaloids constitutively but produce sanguinarine in response to treatment with certain fungal-derived elicitors. The induction of sanguinarine biosynthesis provides a model platform to characterize the regulation of benzylisoquinoline alkaloid pathways and other defense responses. Proteome analysis of elicitor-treated opium poppy cell cultures by two-dimensional denaturing-polyacrylamide gel electrophoresis coupled with liquid chromatography-tandem mass spectrometry facilitated the identification of 219 of 340 protein spots based on peptide fragment fingerprint searches of a combination of databases. Of the 219 hits, 129 were identified through pre-existing plant proteome databases, 63 were identified by matching predicted translation products in opium poppy-expressed sequence tag databases, and the remainder shared evidence from both databases. Metabolic enzymes represented the largest category of proteins and included S-adenosylmethionine synthetase, several glycolytic, and a nearly complete set of tricarboxylic acid cycle enzymes, one alkaloid, and several other secondary metabolic enzymes. The abundance of chaperones, heat shock proteins, protein degradation factors, and pathogenesis-related proteins provided a comprehensive proteomics view on the coordination of plant defense responses. Qualitative comparison of protein abundance in control and elicitor-treated cell cultures allowed the separation of induced and constitutive or suppressed proteins. DNA microarrays were used to corroborate increases in protein abundance with a corresponding induction in cognate transcript levels.
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) | 0.000 | 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 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".