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dbCAN2: a meta server for automated carbohydrate-active enzyme annotation

Complex carbohydrates of plants are the main food sources of animals and microbes, and serve as promising renewable feedstock for biofuel and biomaterial production. Carbohydrate active enzymes (CAZymes) are the most important enzymes for complex carbohydrate metabolism. With an increasing number of...

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Detalles Bibliográficos
Autores principales: Zhang, Han, Yohe, Tanner, Huang, Le, Entwistle, Sarah, Wu, Peizhi, Yang, Zhenglu, Busk, Peter K, Xu, Ying, Yin, Yanbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6031026/
https://www.ncbi.nlm.nih.gov/pubmed/29771380
http://dx.doi.org/10.1093/nar/gky418
Descripción
Sumario:Complex carbohydrates of plants are the main food sources of animals and microbes, and serve as promising renewable feedstock for biofuel and biomaterial production. Carbohydrate active enzymes (CAZymes) are the most important enzymes for complex carbohydrate metabolism. With an increasing number of plant and plant-associated microbial genomes and metagenomes being sequenced, there is an urgent need of automatic tools for genomic data mining of CAZymes. We developed the dbCAN web server in 2012 to provide a public service for automated CAZyme annotation for newly sequenced genomes. Here, dbCAN2 (http://cys.bios.niu.edu/dbCAN2) is presented as an updated meta server, which integrates three state-of-the-art tools for CAZome (all CAZymes of a genome) annotation: (i) HMMER search against the dbCAN HMM (hidden Markov model) database; (ii) DIAMOND search against the CAZy pre-annotated CAZyme sequence database and (iii) Hotpep search against the conserved CAZyme short peptide database. Combining the three outputs and removing CAZymes found by only one tool can significantly improve the CAZome annotation accuracy. In addition, dbCAN2 now also accepts nucleotide sequence submission, and offers the service to predict physically linked CAZyme gene clusters (CGCs), which will be a very useful online tool for identifying putative polysaccharide utilization loci (PULs) in microbial genomes or metagenomes.