- Gabriel, Raphael;
- Thieme, Nils;
- Liu, Qian;
- Li, Fangya;
- Meyer, Lisa T;
- Harth, Simon;
- Jecmenica, Marina;
- Ramamurthy, Maya;
- Gorman, Jennifer;
- Simmons, Blake A;
- McCluskey, Kevin;
- Baker, Scott E;
- Tian, Chaoguang;
- Schuerg, Timo;
- Singer, Steven W;
- Fleißner, André;
- Benz, J Philipp
Carbohydrate active enzymes (CAZymes) are vital for the lignocellulose-based biorefinery. The development of hypersecreting fungal protein production hosts is therefore a major aim for both academia and industry. However, despite advances in our understanding of their regulation, the number of promising candidate genes for targeted strain engineering remains limited. Here, we resequenced the genome of the classical hypersecreting Neurospora crassa mutant exo-1 and identified the causative point of mutation to reside in the F-box protein-encoding gene, NCU09899. The corresponding deletion strain displayed amylase and invertase activities exceeding those of the carbon catabolite derepressed strain Δcre-1, while glucose repression was still mostly functional in Δexo-1 Surprisingly, RNA sequencing revealed that while plant cell wall degradation genes are broadly misexpressed in Δexo-1, only a small fraction of CAZyme genes and sugar transporters are up-regulated, indicating that EXO-1 affects specific regulatory factors. Aiming to elucidate the underlying mechanism of enzyme hypersecretion, we found the high secretion of amylases and invertase in Δexo-1 to be completely dependent on the transcriptional regulator COL-26. Furthermore, misregulation of COL-26, CRE-1, and cellular carbon and nitrogen metabolism was confirmed by proteomics. Finally, we successfully transferred the hypersecretion trait of the exo-1 disruption by reverse engineering into the industrially deployed fungus Myceliophthora thermophila using CRISPR-Cas9. Our identification of an important F-box protein demonstrates the strength of classical mutants combined with next-generation sequencing to uncover unanticipated candidates for engineering. These data contribute to a more complete understanding of CAZyme regulation and will facilitate targeted engineering of hypersecretion in further organisms of interest.