Metal ions modulate gene expression and accumulation of the mycotoxins aflatoxin and zearalenone
Bibliographic record
Abstract
AIMS: To determine the modulating action of some metal ions (Zn+2, Fe+2, Cu+2) on gene expression of enzymes related to fungal growth and accumulation of the mycotoxins aflatoxin and zearalenone. METHODS AND RESULTS: The effect of the metal ions, as single or mixed treatments, was observed in submerged cultures of toxigenic Aspergillus flavus or Fusarium graminearum, which produce the mycotoxins aflatoxin or zearalenone, respectively. The enzyme-linked immunosorbent assay results showed that the single metals Zn+2 or Cu+2 stimulated aflatoxin accumulation while Cu+2 or Fe+2 stimulated zearalenone in fungal cultures. Single Zn+2 treatment also affected conidial differentiation and pigmentation. A cDNA suppression subtractive library was also produced and followed by sequencing of potential metal treatment-specific clones, thus determining induced genes. The genes uncovered included enzymes and regulators of cell growth and division, including many genes with unknown functions were uncovered. A Northern blot analysis was used to verify the expression pattern of the corresponding genes under metal treatment. The metal ions enhanced the expression of alcohol dehydrogenase Adh1 homologue by up to 33-fold in A. flavus and ca fourfold in F. graminearum. Encoding homologues of a neutral amino acid permease, were also used in the Northern analysis. However, the expression of the permease was not significantly affected by metal ion treatments. CONCLUSIONS: The results showed a significant effect of metal ions on expression of gene related to fungal growth, development, conidiation and production of both aflatoxin and zearalenone. SIGNIFICANT AND IMPACT OF THE STUDY: At the molecular and cellular level, the significant effects of metal ions on fungal growth and development, conidiation, and production of both aflatoxin and zearalenone were demonstrated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".