Open AccessA Need for Improved Cellulase Identification from Metagenomic Sequence Data
Author(s) -
Rebecca Co,
Laura A. Hug
Publication year - 2020
Publication title -
applied and environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.552
H-Index - 324
eISSN - 1070-6291
pISSN - 0099-2240
DOI - 10.1128/aem.01928-20
Subject(s) - metagenomics , cellulase , identification (biology) , categorization , computational biology , biology , resource (disambiguation) , annotation , computer science , microbiology and biotechnology , data science , bioinformatics , cellulose , gene , genetics , ecology , artificial intelligence , computer network , biochemistry
Improved sequencing technologies and the maturation of metagenomic approaches allow the identification of gene variants with potential industrial applications, including cellulases. Cellulase identification from metagenomic environmental surveys is complicated by inconsistent nomenclature and multiple categorization systems. Here, we summarize the current classification and nomenclature systems, with recommendations for improvements to these systems. Addressing the issues described will strengthen the annotation of cellulose-active enzymes from environmental sequence data sets-a rapidly growing resource in environmental and applied microbiology.