A large‐scale metagenomic study for enzyme profiles using the focused identification of the NGS‐based definitive enzyme research (FINDER) strategy. Issue 11 (2nd August 2021)

• Record Type: Journal Article
• Authors: Sung, Jae‐Yoon; Lee, Yong‐Jik; Cho, Yong‐Joon; Shin, Myeong‐Na; Lee, Sang‐Jae; Lee, Han‐Seung; Koh, Hong; Bae, Jin‐Woo; Shin, Jae‐Ho; Kim, Hyun Jung; Lee, Dong‐Woo
• Is Part Of: Biotechnology and bioengineering. Volume 118:Issue 11(2021)
• Page Start: 4360
• Page End: 4374
• Publication Date: 2021-08-02
• Subjects: enzyme profiling -- FINDER -- metabolic activity -- metagenome -- next‐generation sequencing; Biotechnology -- Periodicals; Bioengineering -- Periodicals; 660.6
• DOI: 10.1002/bit.27904
• Languages: English
• ISSNs: 0006-3592

Abstract

Abstract: Excavating the molecular details of many diverse enzymes from metagenomes remains challenging in agriculture, food, health, and environmental fields. We present a versatile method that accelerates metabolic enzyme discovery for highly selective gene capture in metagenomes using next‐generation sequencing. Culture‐independent enzyme mining of environmental DNA is based on a set of short identifying degenerate sequences specific for a wide range of enzyme superfamilies, followed by multiplexed DNA barcode sequencing. A strategy of 'focused identification of next‐generation sequencing‐based definitive enzyme research' enabled us to generate targeted enzyme datasets from metagenomes, resulting in minimal hands‐on obtention of high‐throughput biological diversity and potential function profiles, without being time‐consuming. This method also provided a targeted inventory of predicted proteins and molecular features of metabolic activities from several metagenomic samples. We suggest that the efficiency and sensitivity of this method will accelerate the decryption of microbial diversity and the signature of proteins and their metabolism from environmental samples. Abstract : Focused identification of next‐generation sequencing‐based definitive enzyme research (FINDER), as a culture‐independent high‐throughput enzyme screening platform technology, enabled us to quickly determine the value of metagenomic samples and to collect a large amount of information regarding useful enzyme profiles. FINDER could also allow us to rapidly characterize environmental microbiota at any given time, and yield established catalogs of functional genes in situ. This large‐scale screening method is a versatile approach for identifying novel biocatalysts and excavating natural deposits of novel enzymes at a metagenomic scale.