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SACCHARIS v2: Streamlining Prediction of Carbohydrate-Active Enzyme Specificities Within Large Datasets.
Fraser, Alexander S C; Low, Kristin E; Tingley, Jeffrey P; Reintjes, Greta; Thomas, Dallas; Brumer, Harry; Abbott, D Wade.
Afiliación
  • Fraser ASC; Michael Smith Laboratories and Department of Chemistry, University of British Columbia, Vancouver, BC, Canada.
  • Low KE; Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB, Canada.
  • Tingley JP; Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB, Canada.
  • Reintjes G; Department of Chemistry and Biochemistry, University of Lethbridge, Lethbridge, AB, Canada.
  • Thomas D; Microbial-Carbohydrate Interactions Group, University of Bremen, Bremen, Germany.
  • Brumer H; Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB, Canada.
  • Abbott DW; Michael Smith Laboratories and Department of Chemistry, University of British Columbia, Vancouver, BC, Canada.
Methods Mol Biol ; 2836: 299-330, 2024.
Article en En | MEDLINE | ID: mdl-38995547
ABSTRACT
Carbohydrates are chemically and structurally diverse, composed of a wide array of monosaccharides, stereochemical linkages, substituent groups, and intermolecular associations with other biological molecules. A large repertoire of carbohydrate-active enzymes (CAZymes) and enzymatic activities are required to form, dismantle, and metabolize these complex molecules. The software SACCHARIS (Sequence Analysis and Clustering of CarboHydrate Active enzymes for Rapid Informed prediction of Specificity) provides a rapid, easy-to-use pipeline for the prediction of potential CAZyme function in new datasets. We have updated SACCHARIS to (i) simplify its installation by re-writing in Python and packaging for Conda; (ii) enhance its usability through a new (optional) interactive GUI; and (iii) enable semi-automated annotation of phylogenetic tree output via a new R package or the commonly-used webserver iTOL. Significantly, SACCHARIS v2 has been developed with high-throughput omics in mind, with pipeline automation geared toward complex (meta)genome and (meta)transcriptome datasets to reveal the total CAZyme content ("CAZome") of an organism or community. Here, we outline the development and use of SACCHARIS v2 to discover and annotate CAZymes and provide insight into complex carbohydrate metabolisms in individual organisms and communities.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Estados Unidos