Precursor-centric genome-mining approach for lasso peptide discovery.

Area of Science:

• Microbiology
• Biochemistry
• Bioinformatics

Background:

• Lasso peptides are ribosomally synthesized natural products with diverse pharmacological activities.
• Their biosynthesis involves a precursor protein and two enzymes, encoded by a gene cluster.
• Existing methods for identifying lasso peptide gene clusters are limited.

Purpose of the Study:

• To develop a unique genome-mining algorithm for identifying lasso peptide gene clusters in prokaryotes.
• To survey sequenced prokaryotic genomes for putative lasso peptide producers.
• To validate the genome-mining method by characterizing a novel lasso peptide.

Main Methods:

• Development of a genome-mining algorithm based on conserved amino acid patterns in precursor proteins.
• Application of the algorithm to over 3,000 prokaryotic genomes.
• Heterologous expression of a predicted lasso peptide gene cluster in Escherichia coli.
• Characterization of the produced lasso peptide, including structural determination.

Main Results:

• Identification of 76 putative lasso peptide-producing organisms across nine bacterial phyla and one archaeal phylum.
• Successful heterologous expression and isolation of a novel lasso peptide, astexin-1, from Asticcacaulis excentricus.
• Astexin-1 is the largest known lasso peptide (23 aa), highly polar, and exhibits modest antimicrobial activity.
• Determination of astexin-1's unique structure stabilized by hydrogen bonding.

Conclusions:

• The developed genome-mining algorithm enables a global survey of lasso peptide gene clusters.
• The discovery of astexin-1 expands the known diversity of lasso peptides in terms of size, polarity, and structure.
• This work provides a foundation for further exploration of lasso peptide natural products and their potential applications.