Production of Ochratoxin A and Citrinin and the Expression of Their Biosynthetic Genes from <i>Penicillium verrucosum</i> in Liquid Culture
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Penicillium verrucosum is a fungal pathogen capable of producing two mycotoxins of concern, ochratoxin A (OTA) and citrinin (CIT). The production profile of these two mycotoxins is not well understood but could help mitigate co-contamination in the food supply. As such, the production of OTA and CIT from P. verrucosum DAOMC 242724 was investigated under different growing conditions in liquid culture. We found that among the different liquid media chosen, liquid YES (yeast extract sucrose) medium induced the highest production of both OTA and CIT, when P. verrucosum DAOMC 242724 was cultured in stationary mode. Shake culture significantly reduced the amounts of OTA and CIT produced. Among all culture conditions tested, far greater amounts of CIT were produced compared to OTA. Consequently, upon transcriptomic data analysis, a statistically significant increase in the expression of CIT biosynthetic genes was easier to detect than the expression of OTA biosynthetic genes. Our study also revealed that the putative biosynthetic gene clusters of OTA and CIT in P. verrusocum DAOMC 242724 are likely distinct from each other. It appears that despite sharing a highly similar structure, the isocoumarin rings of OTA and CIT are each assembled by a specialized polyketide synthase enzyme. Our data identified a putative nonreducing polyketide synthase responsible for assembling the carbo-skeleton of CIT. In contrast, a highly reducing polyketide synthase appears to be involved in the biosynthesis of OTA.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".