Carbohydrate-Active Enzymes in Pythium and Their Role in Plant Cell Wall and Storage Polysaccharide Degradation
Bibliographic record
Abstract
Carbohydrate-active enzymes (CAZymes) are involved in the metabolism of glycoconjugates, oligosaccharides, and polysaccharides and, in the case of plant pathogens, in the degradation of the host cell wall and storage compounds. We performed an in silico analysis of CAZymes predicted from the genomes of seven Pythium species (Py. aphanidermatum, Py. arrhenomanes, Py. irregulare, Py. iwayamai, Py. ultimum var. ultimum, Py. ultimum var. sporangiiferum and Py. vexans) using the "CAZymes Analysis Toolkit" and "Database for Automated Carbohydrate-active Enzyme Annotation" and compared them to previously published oomycete genomes. Growth of Pythium spp. was assessed in a minimal medium containing selected carbon sources that are usually present in plants. The in silico analyses, coupled with our in vitro growth assays, suggest that most of the predicted CAZymes are involved in the metabolism of the oomycete cell wall with starch and sucrose serving as the main carbohydrate sources for growth of these plant pathogens. The genomes of Pythium spp. also encode pectinases and cellulases that facilitate degradation of the plant cell wall and are important in hyphal penetration; however, the species examined in this study lack the requisite genes for the complete saccharification of these carbohydrates for use as a carbon source. Genes encoding for xylan, xyloglucan, (galacto)(gluco)mannan and cutin degradation were absent or infrequent in Pythium spp.. Comparative analyses of predicted CAZymes in oomycetes indicated distinct evolutionary histories. Furthermore, CAZyme gene families among Pythium spp. were not uniformly distributed in the genomes, suggesting independent gene loss events, reflective of the polyphyletic relationships among some of the species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".