dbcan3

dbCAN3 automates carbohydrate-active enzyme (CAZyme) annotation and glycan substrate prediction in (meta-)genome projects.

Key Features:

• CAZyme annotation: Combines multiple tools as a meta server for improved CAZyme annotation inherited from dbCAN2.
• dbCAN-sub: Provides a profile Hidden Markov Model database (HMMdb) for substrate prediction at the CAZyme subfamily level.
• dbCAN-PUL search: Searches against experimentally characterized polysaccharide utilization loci (PULs) with known glycan substrates for substrate prediction at the CAZyme gene cluster (CGC) level.
• Majority voting method: Considers all CAZymes with substrate predicted from dbCAN-sub for substrate prediction at the CGC level.
• CGC-Finder: Identifies CAZyme gene clusters (CGCs) in (meta-)genomes.

Scientific Applications:

• Bioenergy research: Supports genome mining of CAZymes for complex carbohydrate metabolism relevant to bioenergy production.
• Microbiome studies: Enables routine CAZyme annotation in metagenome projects for microbial community analysis.
• Agriculture and nutrition: Facilitates analysis of CAZymes important for agricultural and nutritional applications.
• Global carbon recycling: Aids study of CAZymes involved in global carbon cycling processes.

Methodology:

dbCAN3 uses profile Hidden Markov Models (HMMs) for CAZyme subfamily-level substrate prediction, searches against the dbCAN-PUL database of experimentally characterized polysaccharide utilization loci, and applies a majority voting method for CGC-level substrate prediction.