Data mining of metagenomes to find novel enzymes: a non-computationally intensive method.

ABSTRACT: Currently, there is a need of non-computationally-intensive bioinformatics tools to cope with the increase of large datasets produced by Next Generation Sequencing technologies. We present a simple and robust bioinformatics pipeline to search for novel enzymes in metagenomic sequences. The strategy is based on pattern searching using as reference conserved motifs coded as regular expressions. As a case study, we applied this scheme to search for novel proteases S8A in a publicly available metagenome. Briefly, (1) the metagenome was assembled and translated into amino acids; (2) patterns were matched using regular expressions; (3) retrieved sequences were annotated; and (4) diversity analyses were conducted. Following this pipeline, we were able to identify nine sequences containing an S8 c

SUBMITTER: Gongora-Castillo E 

PROVIDER: S-EPMC6992798 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature