taxMyPhage:双链DNA噬菌体基因组在属和种水平上的自动分类法
taxMyPhage: Automated Taxonomy of dsDNA Phage Genomes at the Genus and Species Level.
作者信息
Millard Andrew, Denise Rémi, Lestido Maria, Thomas Moi Taiga, Webster Deven, Turner Dann, Sicheritz-Pontén Thomas
机构信息
Becky Mayer Centre for Phage Research, University of Leicester, Leicester, UK.
APC Microbiome Ireland & School of Microbiology, University College Cork, Co. Cork, Ireland.
出版信息
Phage (New Rochelle). 2025 Mar 17;6(1):5-11. doi: 10.1089/phage.2024.0050. eCollection 2025 Mar.
BACKGROUND
Bacteriophages are classified into genera and species based on genomic similarity, a process regulated by the International Committee on the Taxonomy of Viruses. With the rapid increase in phage genomic data there is a growing need for automated classification systems that can handle large-scale genome analyses and place phages into new or existing genera and species.
MATERIALS AND METHODS
We developed , a tool system for the rapid automated classification of dsDNA bacteriophage genomes. The system integrates a MASH database, built from ICTV-classified phage genomes to identify closely related phages, followed by BLASTn to calculate intergenomic similarity, conforming to ICTV guidelines for genus and species classification. taxMyPhage is available as a git repository at https://github.com/amillard/tax_myPHAGE, a conda package, a pip-installable tool, and a web service at https://phagecompass.ku.dk.
RESULTS
enables rapid classification of bacteriophages to the genus and species level. Benchmarking on 705 genomes pending ICTV classification showed a 96.7% accuracy at the genus level and 97.9% accuracy at the species level. The system also detected inconsistencies in current ICTV classifications, identifying cases where genera did not adhere to ICTV's 70% average nucleotide identity (ANI) threshold for genus classification or 95% ANI for species. The command line version classified 705 genomes within 48 h, demonstrating its scalability for large datasets.
CONCLUSIONS
significantly enhances the speed and accuracy of bacteriophage genome classification at the genus and species levels, making it compatible with current sequencing outputs. The tool facilitates the integration of bacteriophage classification into standard workflows, thereby accelerating research and ensuring consistent taxonomy.
背景
噬菌体根据基因组相似性被分类为属和种,这一过程由国际病毒分类委员会监管。随着噬菌体基因组数据的迅速增加,对能够处理大规模基因组分析并将噬菌体归入新的或现有的属和种的自动化分类系统的需求也日益增长。
材料和方法
我们开发了taxMyPhage,这是一种用于双链DNA噬菌体基因组快速自动分类的工具系统。该系统整合了一个由国际病毒分类委员会分类的噬菌体基因组构建的MASH数据库,以识别密切相关的噬菌体,随后使用BLASTn计算基因组间的相似性,符合国际病毒分类委员会关于属和种分类的指导方针。taxMyPhage可在https://github.com/amillard/tax_myPHAGE作为git仓库获取,也有conda包、可通过pip安装的工具以及在https://phagecompass.ku.dk的网络服务。
结果
taxMyPhage能够将噬菌体快速分类到属和种水平。对705个等待国际病毒分类委员会分类的基因组进行基准测试表明,在属水平上的准确率为96.7%,在种水平上的准确率为97.9%。该系统还检测到当前国际病毒分类委员会分类中的不一致之处,识别出属未遵守国际病毒分类委员会关于属分类的70%平均核苷酸同一性(ANI)阈值或种的95% ANI阈值的情况。命令行版本在48小时内对705个基因组进行了分类,证明了其对大型数据集的可扩展性。
结论
taxMyPhage显著提高了噬菌体基因组在属和种水平上分类的速度和准确性,使其与当前的测序输出兼容。该工具便于将噬菌体分类整合到标准工作流程中,从而加速研究并确保分类法的一致性。
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