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dc.contributor.authorHobbs, Emma E. M.
dc.contributor.authorGloster, Tracey
dc.contributor.authorPritchard, Leighton
dc.date.accessioned2023-08-15T08:30:06Z
dc.date.available2023-08-15T08:30:06Z
dc.date.issued2023-08-14
dc.identifier291130680
dc.identifier997e0a96-bd16-45a5-b3e6-00e9e4b62cf4
dc.identifier85168060086
dc.identifier.citationHobbs , E E M , Gloster , T & Pritchard , L 2023 , ' cazy_webscraper : local compilation and interrogation of comprehensive CAZyme datasets ' , Microbial Genomics , vol. 9 , no. 8 , 001086 . https://doi.org/10.1099/mgen.0.001086en
dc.identifier.issn2057-5858
dc.identifier.otherORCID: /0000-0002-8470-4739/work/140829846
dc.identifier.urihttps://hdl.handle.net/10023/28172
dc.descriptionFunding: E.E.M.H. is funded by a BBSRC EASTBIO Doctoral Training Partnership award.en
dc.description.abstractCarbohydrate active enzymes (CAZymes) are pivotal in biological processes including energy metabolism, cell structure maintenance, signalling, and pathogen recognition. Bioinformatic prediction and mining of CAZymes improves our understanding of these activities and enables discovery of candidates of interest for industrial biotechnology, particularly the processing of organic waste for biofuel production. CAZy (www.cazy.org) is a high-quality, manually curated, and authoritative database of CAZymes that is often the starting point for these analyses. Automated querying and integration of CAZy data with other public datasets would constitute a powerful resource for mining and exploring CAZyme diversity. However, CAZy does not itself provide methods to automate queries, or integrate annotation data from other sources (except by following hyperlinks) to support further analysis. To overcome these limitations we developed cazy_webscraper, a command-line tool that retrieves data from CAZy and other online resources to build a local, shareable and reproducible database that augments and extends the authoritative CAZy database. cazy_webscraper’s integration of curated CAZyme annotations with their corresponding protein sequences, up-to-date taxonomy assignments, and protein structure data facilitates automated large-scale and targeted bioinformatic CAZyme family analysis and candidate screening. This tool has found widespread uptake in the community, with over 35 000 downloads (from April 2021 to June 2023). We demonstrate the use and application of cazy_webscraper to: (i) augment, update and correct CAZy database accessions; (ii) explore the taxonomic distribution of CAZymes recorded in CAZy, identifying under-represented taxa and unusual CAZy class distributions; and (iii) investigate three CAZymes having potential biotechnological application for degradation of biomass, but lacking a representative structure in the PDB database. We describe in general how cazy_webscraper facilitates functional, structural and evolutionary studies to aid identification of candidate enzymes for further characterization, and specifically note that CAZy provides supporting evidence for recent expansion of the Auxiliary Activities (AA) CAZy family in eukaryotes, consistent with functions potentially specific to eukaryotic lifestyles.
dc.format.extent23
dc.format.extent5873249
dc.language.isoeng
dc.relation.ispartofMicrobial Genomicsen
dc.subjectCAZyen
dc.subjectCAZymesen
dc.subjectDatabaseen
dc.subjectLignocelluloseen
dc.subjectSoftwareen
dc.subjectCarbohydrateen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectQH301 Biologyen
dc.subjectZA4050 Electronic information resourcesen
dc.subjectDASen
dc.subjectMCCen
dc.subject.lccQA75en
dc.subject.lccQH301en
dc.subject.lccZA4050en
dc.titlecazy_webscraper : local compilation and interrogation of comprehensive CAZyme datasetsen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Biomedical Sciences Research Complexen
dc.identifier.doi10.1099/mgen.0.001086
dc.description.statusPeer revieweden


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