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.
摘要：
碳水化合物在化学上和结构上都是多样的,由各种各样的单糖组成，立体化学连接，取代基,以及与其他生物分子的分子间关联。需要大量的碳水化合物活性酶（CAZymes）和酶活性才能形成，拆除,代谢这些复杂的分子。软件SACCHARIS（碳水化合物活性酶的序列分析和聚类，用于快速预测特异性）提供了一种快速，易于使用的管道，用于预测新数据集中潜在的CAZyme函数。我们已经更新了SACCHARIS，以（i）通过在Python中重写和为Conda打包来简化其安装；（ii）通过新的（可选）交互式GUI增强其可用性；（iii）通过新的R包或常用的Web服务器ITOL实现系统发育树输出的半自动注释。重要的是,SACCHARISv2的开发考虑了高通量组学，管道自动化面向复杂（元）基因组和（元）转录组数据集，以揭示生物体或群落的总CAZyme含量（“CAZome”）。这里,我们概述了SACCHARISv2的开发和使用，以发现和注释CAZymes，并提供对单个生物体和群落中复杂碳水化合物代谢的见解。
