Sorbicillinoids hyperproduction without affecting the cellulosic enzyme production in Trichoderma reesei JNTR5
Bibliographic record
Abstract
Abstract Background Microbial production of bioactive secondary metabolites is challenging as most of the encoding genes are silent; and even if they are activated, the biosynthetic pathways are usually complex. Sorbicillinoids with multifunctional bioactivities are examples of these problems, which if solved can result in a more sustainable, simple supply of these important compounds to the pharmaceutical industry. As an excellent producer of cellulosic enzymes, Trichoderma reesei can secrete various sorbicillinoids. Results Here, we obtained a T. reesei mutant strain JNTR5 from the random mutation during overexpression of gene Tr69957 in T. reesei RUT-C30. JNTR5 exhibited a significant constitutive increase in sorbicillinoids production without affecting the cellulosic enzyme production. Confocal laser scanning microscope (CLSM) results indicated that sorbicillinoids were distributed in both mycelium and spores of JNTR5 with blue and green fluorescence. Compared with RUT-C30, JNTR5 displayed different cell morphology, reduced growth rate, and increased sporulation, but a similar biomass accumulation. Furthermore, transcriptome analysis revealed that all genes belonging to the sorbicillinoid gene cluster were upregulated, while most cellulase-encoding genes were downregulated. The cell wall integrity of JNTR5 was damaged, which might benefit the cellulase secretion and contribute to the almost unchanged cellulase and hemicellulase activity given that the damaged cell wall can enhance the secretion of the enzymes. Conclusions For the first time, we constructed a sorbicillinoids hyperproduction T. reesei platform with comparable cellulosic enzymes production. This outperformance of JNTR5, which is strain-specific, is proposed to be attributed to the overexpression of gene Tr69957, causing the chromosome remodeling and subsequently changing the cell morphology, structure, and the global gene expression as shown by phenotype and the transcriptome analysis of JNTR5. Overall, JNTR5 shows great potential for industrial microbial production of sorbicillinoids from cellulose and serves as an excellent model for investigating the distribution and secretion of yellow pigments in T. reesei.
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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) | 0.000 | 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 | 0.001 |
| 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".