An Integrative Bioinformatic Analysis for Keratinase Detection in Marine-Derived Streptomyces

Valencia, Ricardo; Gonzalez, Valentina; Undabarrena, Agustina; Zamora-Leiva, Leonardo ; Ugalde, Juan A.; Camara, Beatriz

Abstract

Keratinases present promising biotechnological applications, due to their ability to degrade keratin. Streptomyces appears as one of the main sources of these enzymes, but complete genome sequences of keratinolytic bacteria are still limited. This article reports the complete genomes of three marine-derived streptomycetes that show different levels of feather keratin degradation, with high (strain G11C), low (strain CHD11), and no (strain Vc74B-19) keratinolytic activity. A multi-step bioinformatics approach is described to explore genes encoding putative keratinases in these genomes. Despite their differential keratinolytic activity, multiplatform annotation reveals similar quantities of ORFs encoding putative proteases in strains G11C, CHD11, and Vc74B-19. Comparative genomics classified these putative proteases into 140 orthologous groups and 17 unassigned orthogroup peptidases belonging to strain G11C. Similarity network analysis revealed three network communities of putative peptidases related to known keratinases of the peptidase families S01, S08, and M04. When combined with the prediction of cellular localization and phylogenetic reconstruction, seven putative keratinases from the highly keratinolytic strain Streptomyces sp. G11C are identified. To our knowledge, this is the first multi-step bioinformatics analysis that complements comparative genomics with phylogeny and cellular localization prediction, for the prediction of genes encoding putative keratinases in streptomycetes.

Más información

Título según WOS: An Integrative Bioinformatic Analysis for Keratinase Detection in Marine-Derived Streptomyces
Título de la Revista: Marine Drugs
Volumen: 19
Número: 6
Editorial: Multidisciplinary Digital Publishing Institute (MDPI)
Fecha de publicación: 2021
DOI:

10.3390/MD19060286

Notas: ISI