Gene expression analysis of carbohydrate catabolism in <i>Leucoagaricus gongylophorus</i> LEU18496
Bibliographic record
Abstract
Abstract Transcriptomic profiles were obtained by RNA-seq of Leucoagaricus gongylophorus growing on two carbon sources (glucose and cellulose) during different growth phases (exponential and stationary) with the aim of analyzing the variations in metabolism depending on the substrate and/or growth state. Principal component analysis (PCA) showed that 99.5% of the variation in gene expression is related to the substrate (PC1), clearly separating the experimental conditions, while the differences between growth phases are reflected in secondary components (PC2). Special attention was paid to the differential expression of CAZymes and FOLymes enzymes, demonstrating that, during the exponential phase of cellulose culture, there is an overexpression of enzymes from the GH6 and GH7 families (cellulases and cellobiosehydrolases), related to the degradation of complex polysaccharides such as cellulose. During the exponential phase of growth on glucose, expression of CAZymes enzymes ( β -glucosidase, pectinase and endo- β -1,3-glucanase) was observed, in addition to an overexpression of laccases in this carbon source. Enrichment analysis identified significantly enriched functions related to carbohydrate catabolism and transport, evidence of the metabolic versatility of L. gongylophorus . High expression of the creA repressor factor was found in the presence of glucose, suggesting its regulatory role in the modulation of carbohydrate degradation. In the stationary phase, genes related to the response to oxidative stress and nutrient solubilization were activated under glucose, in contrast to cellulose, where the activation of secondary metabolism pathways was promoted, including the overexpression of trichodiene synthase.
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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 | 0.000 | 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".