dbCAN2: a meta server for automated carbohydrate-active enzyme annotation.

dbCAN2: a meta server for automated carbohydrate-active enzyme annotation.
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DOI:
10.1093/nar/gky418
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发表时间:
2018-07-02
影响因子:
14.9
通讯作者:
Yin Y
Yin Y
中科院分区:
生物学2区
文献类型:
--
作者:
Zhang H;Yohe T;Huang L;Entwistle S;Wu P;Yang Z;Busk PK;Xu Y;Yin Y

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植物复合碳水化合物是动物和微生物的主要食物来源,是生物燃料和生物材料生产中有前景的可再生原料。碳水化合物活性酶(CAZymes)是复杂碳水化合物代谢的重要酶。随着越来越多的植物及植物相关微生物基因组和宏基因组的测序,迫切需要CAZymes基因组数据挖掘的自动化工具。我们于2012年开发了dbCAN web服务器,为新测序基因组的自动CAZyme注释提供公共服务。在这里,dbCAN2 (http://cys.bios.niu.edu/dbCAN2)是一个更新的元服务器,它集成了三种最先进的工具,用于CAZome(基因组的所有CAZymes)注释:(i)针对dbCAN HMM(隐马尔可夫模型)数据库的HMM搜索;(ii)针对CAZy预注释的CAZyme序列数据库进行DIAMOND搜索;(iii)针对保守的CAZyme短肽数据库进行Hotpep搜索。将三种输出结合起来,只去除一种工具发现的CAZymes,可以显著提高CAZome标注的准确性。此外,dbCAN2现在也接受核苷酸序列提交,并提供预测物理连接的CAZyme基因簇(cgc)的服务,这将是一个非常有用的在线工具,用于鉴定微生物基因组或宏基因组中假定的多糖利用位点(PULs)。
Complex carbohydrates of plants are the main food sources of animals and microbes, and serve as promising renewable feedstock for biofuel and biomaterial production. Carbohydrate active enzymes (CAZymes) are the most important enzymes for complex carbohydrate metabolism. With an increasing number of plant and plant-associated microbial genomes and metagenomes being sequenced, there is an urgent need of automatic tools for genomic data mining of CAZymes. We developed the dbCAN web server in 2012 to provide a public service for automated CAZyme annotation for newly sequenced genomes. Here, dbCAN2 (http://cys.bios.niu.edu/dbCAN2) is presented as an updated meta server, which integrates three state-of-the-art tools for CAZome (all CAZymes of a genome) annotation: (i) HMMER search against the dbCAN HMM (hidden Markov model) database; (ii) DIAMOND search against the CAZy pre-annotated CAZyme sequence database and (iii) Hotpep search against the conserved CAZyme short peptide database. Combining the three outputs and removing CAZymes found by only one tool can significantly improve the CAZome annotation accuracy. In addition, dbCAN2 now also accepts nucleotide sequence submission, and offers the service to predict physically linked CAZyme gene clusters (CGCs), which will be a very useful online tool for identifying putative polysaccharide utilization loci (PULs) in microbial genomes or metagenomes.
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影响因子: 4.4
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DOI: 10.1093/nar/gkx894
发表时间: 2018-01-04
影响因子: 14.9
作者:
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通讯作者: Yin Y