Discovery of antimicrobial peptides clostrisin and cellulosin from Clostridium: insights into their structures, co-localized biosynthetic gene clusters, and antibiotic activity

发现来自梭菌的抗菌肽梭菌素和纤维素酶:深入了解它们的结构、共定位的生物合成基因簇和抗生素活性

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作者:Moisés Alejandro Alejo Hernandez, Katia Pamela Villavicencio Sánchez, Rosendo Sánchez Morales, Karla Georgina Hernández-Magro Gil, David Silverio Moreno-Gutiérrez, Eddie Guillermo Sanchez-Rueda, Yanet Teresa-Cruz, Brian Choi, Armando Hernández Garcia, Alba Romero-Rodríguez, Oscar Juárez, Siseth Mart

Abstract

Antimicrobial resistance presents a substantial threat to global public health, demanding urgent attention and action. This study focuses on lanthipeptides, ribosomally encoded peptides that display significant structural diversity and hold promising potential as antibiotics. Genome mining was employed to locate biosynthetic gene clusters (BGCs) containing class II lanthipeptide synthetases encoded by lanM genes. A phylogenetic study analyzing homologous sequences of functional LanM sequences revealed a unique evolutionary clade of 17 LanM proteins associated with 12 Clostridium bacterial genomes. In silico exploration identified nine complete BGCs, including one super-cluster containing two co-localized operons from Clostridium cellulovorans 743B, that encode for two new peptides named clostrisin and cellulosin. Each operon was heterologously expressed in Escherichia coli. Molecular weights associated with the expected post-translational modifications of the purified lanthipeptide were confirmed by MS-MS/MS analysis for cellulosin, while clostrisin was not post-translationally modified. Both peptides demonstrated antimicrobial activity against multidrug-resistant bacteria, such as a clinical strain of Staphylococcus epidermidis MIQ43 and Pseudomonas aeruginosa PA14. This is the first report of lanthipeptides from the Clostridium genus produced with its native biosynthetic machinery, as well as chemically and biologically characterized. This study showcases the immense potential of genome mining in identifying new RiPP synthetases and associated bioactive peptides.

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