Development of a computational tool to screen antimicrobial peptides in metagenomics data associated to a new vector for high-scale production of lasso peptides

• Autor(a) principal: Igor Andrade Figueiredo de Souza
• Data de Publicação: 2020
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Institucional da UFMG
• Texto Completo: http://hdl.handle.net/1843/41503
• topic: antimicrobials; genomics; bioprospecting; computational screening; lasso peptides; Biologia Computacional; Anti-Infecciosos; Genômica; Bioprospecção; Peptídeos

The emergence and development of antimicrobial resistance (AMR) against conventional antimicrobials are the main fears of modern medicine and food security, leading both pharmaceutical and food industries to renew their interest in the discovery of microbial natural products with antimicrobial properties. With the advent of the massive amount and freely available metagenomic data, containing sequences from cultured and uncultured species, the field of natural product discovery is transforming, and new strategies such as peptide mining are being developed. Here, we present the first pattern-matching tool created to prospect lasso peptide directly from short reads of metagenomic data, which is a constraint for the classical genome mining approach based on sequence similarity. The tool receives as input FASTQ or FASTA format files and query patterns. A control test was performed on a mock community containing 27 genomes from known lasso peptide producers and 9 negative genomes. The query patterns were designed based on 35 lasso sequences associated with 27 genomes. The sequences were randomly divided into a group termed training, containing 21 sequences and a testing group with 14 sequences. For the training group, a distance matrix was obtained by multidimensional scaling technique based on the plot of three groups. For each group, a consensus sequence was obtained, and a query pattern was used to screen potential lasso peptides in rumen metagenomics data resulting in 3 new peptides. To validate the potential new lasso peptides, a user-friendly E. coli expression vector containing optimized genes to produce lasso peptides in high yield was designed and synthesized. The vector was able to produce the lasso peptide microcin J25 with the ability to inhibit both gram-negative and gram-positive bacteria. The study presents the potential to access data from whole communities, which are a potentially unique resource for novel antimicrobial peptides.