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Updated: Jul 5, 2025

Metagenomic Analysis of Silage

Metagenomic Analysis of Silage

Published on: January 13, 2017

Carbohydrate-active enzyme annotation in microbiomes using dbCAN.

Jinfang Zheng, Le Huang, Haidong Yi

Biorxiv : the Preprint Server for Biology

|January 23, 2024

Summary

This summary is machine-generated.

This protocol details automated annotation of carbohydrate-active enzymes (CAZymes) in microbiome data using the standalone run_dbcan software. It enables secure, scalable analysis from pre-processing to visualization for researchers.

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Structural Biology and Analytical Chemistry Approaches for Characterizing C-Glycoside Metabolic Enzymes in Human Gut Microbiota

Structural Biology and Analytical Chemistry Approaches for Characterizing C-Glycoside Metabolic Enzymes in Human Gut Microbiota

Published on: May 23, 2025

Area of Science:

Microbiology and Bioinformatics
Enzymology and Genomics

Background:

Carbohydrate-active enzymes (CAZymes) are crucial for gut health, biomass degradation, and carbon cycling.
Automated CAZyme annotation is vital for analyzing complex microbiome datasets.
Existing web servers have limitations in data privacy and scalability for large-scale analyses.

Approach:

A comprehensive computational protocol for automated CAZyme annotation of microbiome sequencing data is presented.
The protocol covers pre-processing, assembly, gene and CAZyme prediction, and data visualization.
It utilizes the standalone run_dbcan software package for secure and scalable local analysis.

Key Points:

The protocol guides users through dataset preparation, metagenome assembly, gene prediction, and CAZyme prediction.
It includes prediction of CAZyme gene clusters (CGCs) and glycan substrates.
Multiple annotation routes (individual assembly, co-assembly, assembly-free) and visualization options are provided.

Conclusions:

This protocol facilitates publication-quality data visualization of CAZyme, CGC, and substrate abundance across multiple samples.
It empowers microbiome researchers to perform rapid, secure, and scalable CAZyme annotation on local servers.
The protocol requires familiarity with the Linux command-line but no programming experience.