dbCAN3: automated carbohydrate-active enzyme and substrate annotation

Nucleic Acids Research · 6 authors, 6 centres

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TL;DR

dbCAN3 is an updated meta server that adds three glycan substrate prediction methods—subfamily-level HMM search, BLAST-based PUL matching, and majority voting—to the existing CAZyme annotation pipeline.

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dbCAN3 is a bioinformatics meta server that inherits CAZyme annotation functions from dbCAN2 and adds three new substrate prediction approaches. Approach B searches predicted CAZyme gene clusters (CGCs) against 654 experimentally characterized PULs in dbCAN-PUL using BLAST. Benchmarking used curated ground-truth PUL data from dbCAN-PUL. Approach A achieved 81% coverage and 74% unweighted precision on 642 CAZymes. Approach B achieved 88% coverage and 74% unweighted precision on a 106-test-PUL split. The server and databases are freely available online.

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other

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biomedical research

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AI pipeline

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ORIGINAL PAPER

PMC10320055

dbCAN3: automated carbohydrate-active enzyme and substrate annotation

Nucleic Acids Research

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ABSTRACT

Abstract Carbohydrate active enzymes (CAZymes) are made by various organisms for complex carbohydrate metabolism. Genome mining of CAZymes has become a routine data analysis in (meta-)genome projects, owing to the importance of CAZymes in bioenergy, microbiome, nutrition, agriculture, and global carbon recycling. In 2012, dbCAN was provided as an online web server for automated CAZyme annotation. dbCAN2 ( https://bcb.unl.edu/dbCAN2 ) was further developed in 2018 as a meta server to combine multiple tools for improved CAZyme annotation. dbCAN2 also included CGC-Finder, a tool for identifying CAZyme gene clusters (CGCs) in (meta-)genomes. We have updated the meta server to dbCAN3 with the following new functions and components: (i) dbCAN-sub as a profile Hidden Markov Model database (HMMdb) for substrate prediction at the CAZyme subfamily level; (ii) searching against experimentally characterized polysaccharide utilization loci (PULs) with known glycan substates of the dbCAN-PUL database for substrate prediction at the CGC level; (iii) a majority voting method to consider all CAZymes with substrate predicted from dbCAN-sub for substrate prediction at the CGC level; (iv) improved data browsing and visualization of substrate prediction results on the website. In summary, dbCAN3 not only inherits all the functions of dbCAN2, but also integrates three new methods for glycan substrate prediction.

CITATION EXPORT

Jinfang Zheng, Qiwei Ge, Yuchen Yan et al.. dbCAN3: automated carbohydrate-active enzyme and substrate annotation. Nucleic Acids Research. (2023). https://doi.org/10.1093/nar/gkad328

AUTHORS

6 · 6 CENTRES

Jinfang Zheng, Qiwei Ge, Yuchen Yan, Xinpeng Zhang, Le Huang, Yanbin Yin

Nebraska Food for Health Center, Department of Food Science and Technology, University of Nebraska, Lincoln, NE 68588, USA
School of Computing, University of Nebraska, Lincoln, NE 68588, USA
Nebraska Food for Health Center, Department of Food Science and Technology, University of Nebraska, Lincoln, NE 68588, USA
Nebraska Food for Health Center, Department of Food Science and Technology, University of Nebraska, Lincoln, NE 68588, USA
Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, NC, USA
Nebraska Food for Health Center, Department of Food Science and Technology, University of Nebraska, Lincoln, NE 68588, USA