dbCAN2: a meta server for automated carbohydrate-active enzyme annotation
By Han Zhang, Tanner Yohe, Le Huang, Sarah Entwistle, Peizhi Wu, Zhenglu Yang, P. Busk, Ying Xu, Yanbin Yin. 2018
1,924 citations recorded by the source corpus.
Abstract 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.
Subfields: Biotechnology, Molecular Biology, Nutrition and Dietetics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
Citations in the corpus
- Insights into Plant Interactions and the Biogeochemical Role of the Globally Widespread Acidobacteriota Phylum (2023, methodology): “Additionally, METABOLIC-G v.4.0 was used to profile metabolic and biogeochemical traits, and functional networks in the Acidobacteriota MAGs and genomes. dbCAN2 (Zhang et al., 2018) within METABOLIC v.4.0 was used to annotate proteins carbohydrate-active enzymes (CAZymes) using default thresholds.”
- DRAM for distilling microbial metabolism to automate the curation of microbiome function (2020, methodology): “The lowest rank (E) represents proteins that had no significant hits to any DRAM database including KEGG (41), UniRef90 (42), dbCAN (48), Pfam (46), MEROPS (43), or only had significant hits to VOGDB.”