Peptaibiomics: Screening for Polypeptide Antibiotics (Peptaibiotics) from Plant-ProtectiveTrichoderma Species
Bibliographic record
Abstract
Eight strains of Trichoderma species (T. strigosum, T. erinaceus, T. pubescens, T. stromaticum, and T. spirale as well as T. cf. strigosum, T. cf. pubescens) were selected because of their antagonistic potential against Eutypa dieback and Esca which are fungal diseases of grapevine trunks. These isolates were screened for the production of a group of polypeptide antibiotics named peptaibiotics, including its subgroups peptaibols and lipopeptaibols. Fully-grown fungal cultures on potato-dextrose agar were extracted with CH(2)Cl(2)/MeOH, and these extracts were subjected to SPE using C(18) cartridges. The methanolic eluates were analyzed by on-line LC/ESI-MS(n) coupling--a method which is referred to as 'peptaibiomics'. New seven-, ten-, and eleven-residue lipopeptaibols, with N-terminal alkanoyl, and C-terminal leucinol or isoleucinol residues were found and named lipostrigocins and lipopubescins. Furthermore, new 18-residue peptaibols named trichostromaticins and 19-residue peptaibols named trichostrigocins were discovered. One peptaibiotic carrying a free C-terminal valine (or isovaline) named trichocompactin XII was also sequenced. These results corroborate the hypothesis that peptaibiotics might contribute to the plant-protective action of their fungal producers. The data also point out that comparison of peptaibiotic sequences is of limited relevance in order to establish chemotaxonomic relationships among species of the genus Trichoderma.
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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) | 0.001 | 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 | 0.000 |
| 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".