Cyclotide discovery in Gentianales revisited—identification and characterization of cyclic cystine‐knot peptides and their phylogenetic distribution in Rubiaceae plants
Bibliographic record
Abstract
Cyclotides are a unique class of ribosomally synthesized cysteine-rich miniproteins characterized by a head-to-tail cyclized backbone and three conserved disulfide-bonds in a knotted arrangement. Originally they were discovered in the coffee-family plant Oldenlandia affinis (Rubiaceae) and have since been identified in several species of the violet, cucurbit, pea, potato, and grass families. However, the identification of novel cyclotide-containing plant species still is a major challenge due to the lack of a rapid and accurate analytical workflow in particular for large sampling numbers. As a consequence, their phylogeny in the plant kingdom remains unclear. To gain further insight into the distribution and evolution of plant cyclotides, we analyzed ∼300 species of >40 different families, with special emphasis on plants from the order Gentianales. For this purpose, we have developed a refined screening methodology combining chemical analysis of plant extracts and bioinformatic analysis of transcript databases. Using mass spectrometry and transcriptome-mining, we identified nine novel cyclotide-containing species and their related cyclotide precursor genes in the tribe Palicoureeae. The characterization of novel peptide sequences underlines the high variability and plasticity of the cyclotide framework, and a comparison of novel precursor proteins from Carapichea ipecacuanha illustrated their typical cyclotide gene architectures. Phylogenetic analysis of their distribution within the Psychotria alliance revealed cyclotides to be restricted to Palicourea, Margaritopsis, Notopleura, Carapichea, Chassalia, and Geophila. In line with previous reports, our findings confirm cyclotides to be one of the largest peptide families within the plant kingdom and suggest that their total number may exceed tens of thousands.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".