cazy_webscraper: local compilation and interrogation of comprehensive CAZyme datasets

Area of Science:

• Bioinformatics
• Biotechnology
• Enzymology

Background:

• Carbohydrate active enzymes (CAZymes) are crucial for biological processes and industrial applications like biofuel production.
• The CAZy database is a key resource for CAZyme research, but lacks automated querying and data integration features.
• Existing limitations hinder large-scale bioinformatic analysis and exploration of CAZyme diversity.

Purpose of the Study:

• To develop a command-line tool, cazy_webscraper, to automate data retrieval and integration from CAZy and other resources.
• To create a local, reproducible database that augments the CAZy database with additional information.
• To facilitate large-scale bioinformatic analysis, candidate screening, and functional studies of CAZymes.

Main Methods:

• Developed cazy_webscraper, a command-line tool for automated data retrieval from CAZy and other online resources.
• Integrated curated CAZyme annotations with protein sequences, taxonomy, and structure data.
• Applied the tool to augment CAZy accessions, explore taxonomic distribution, and investigate potential biotechnological candidates.

Main Results:

• cazy_webscraper successfully augments and updates CAZy data, enabling exploration of CAZyme taxonomic distribution.
• The tool identified under-represented taxa and unusual CAZy class distributions.
• Demonstrated utility in identifying potential biotechnological enzymes and supporting evolutionary studies, including eukaryotic Auxiliary Activities (AA) family expansion.

Conclusions:

• cazy_webscraper provides a powerful, reproducible resource for bioinformatic CAZyme analysis.
• The tool facilitates functional, structural, and evolutionary studies, aiding enzyme discovery for biotechnology.
• Supports ongoing research into CAZyme diversity and function, particularly in eukaryotes.