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Journal article

Bioinformatics based discovery of new keratinases in protease family M36

From

Department of Biotechnology and Biomedicine, Technical University of Denmark1

Enzyme Technology, Section for Protein Chemistry and Enzyme Technology, Department of Biotechnology and Biomedicine, Technical University of Denmark2

Keratinases are proteases that can catalyze the degradation of insoluble keratinous biomass. Keratinases in protease family M36 (MEROPS database) are endo-acting proteases. In total, 687 proteases are classified in family M36. In the present study, new keratinolytic enzymes were identified in protease family M36 using the bioinformatics tool Conserved Unique Peptide Patterns (CUPP).

Via CUPP, M36 family members were classified into 11 groups, with CUPP group 1 containing the three currently known and sequenced family 36 keratinases (derived from the fungi Fusarium oxysporum, Microsporum canis and Onygena corvina) as well as an additional 71 uncharacterized M36 proteases. In order to assess the relevance of CUPP group 1 categorization to keratinolytic function, four uncharacterized M36 proteases and the known keratinase from F. oxysporum (in CUPP group 1) were selected for recombinant expression and keratinolytic activity assessment.

The four hitherto unknown M36 proteases were from Phaeosphaeria nodorum, Aspergillus clavatus, Pseudogymnoascus pannorum and Nectria haematococca, and represent four different fungal taxonomical classes. The genes encoding the selected M36 proteases were individually expressed in Pichia pastoris and all proteases displayed keratinase activity on keratin azure.

Additionally, the activity on different keratinase substrates, optimal reaction conditions and thermal stability were determined for the two most active new keratinases. The results validate the applicability of CUPP for function-based discovery of non-characterized keratinases and present new robust keratinases for potential use in keratin upgrading.

Language: English
Year: 2022
Pages: 19-27
ISSN: 18764347 and 18716784
Types: Journal article
DOI: 10.1016/j.nbt.2022.01.004
ORCIDs: Qiu, Jingwen , Barrett, Kristian , Meyer, Anne S. and Wilkens, Casper

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