Gan Rui, Zhou FengXia, Si Yu, Yang Han, Chen Chuangeng, Ren Chunyan, Wu Jiqiu, Zhang Fan
HIT Center for Life Sciences, School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Department of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.
Front Genet. 2022 Apr 19;13:885048. doi: 10.3389/fgene.2022.885048. eCollection 2022.
As an intracellular form of a bacteriophage in the bacterial host genome, a prophage usually integrates into bacterial DNA with high specificity and contributes to horizontal gene transfer (HGT). With the exponentially increasing number of microbial sequences uncovered in genomic or metagenomics studies, there is a massive demand for a tool that is capable of fast and accurate identification of prophages. Here, we introduce DBSCAN-SWA, a command line software tool developed to predict prophage regions in bacterial genomes. DBSCAN-SWA runs faster than any previous tools. Importantly, it has great detection power based on analysis using 184 manually curated prophages, with a recall of 85% compared with Phage_Finder (63%), VirSorter (74%), and PHASTER (82%) for (Multi-) FASTA sequences. Moreover, DBSCAN-SWA outperforms the existing standalone prophage prediction tools for high-throughput sequencing data based on the analysis of 19,989 contigs of 400 bacterial genomes collected from Human Microbiome Project (HMP) project. DBSCAN-SWA also provides user-friendly result visualizations including a circular prophage viewer and interactive DataTables. DBSCAN-SWA is implemented in Python3 and is available under an open source GPLv2 license from https://github.com/HIT-ImmunologyLab/DBSCAN-SWA/.
作为细菌宿主基因组中噬菌体的一种细胞内形式,原噬菌体通常以高度特异性整合到细菌DNA中,并促进水平基因转移(HGT)。随着基因组学或宏基因组学研究中发现的微生物序列数量呈指数级增长,对能够快速准确识别原噬菌体的工具的需求巨大。在此,我们介绍DBSCAN-SWA,这是一种开发用于预测细菌基因组中原噬菌体区域的命令行软件工具。DBSCAN-SWA运行速度比以往任何工具都快。重要的是,基于对184个手动策划的原噬菌体的分析,它具有强大的检测能力,对于(多)FASTA序列,其召回率为85%,而Phage_Finder为63%,VirSorter为74%,PHASTER为82%。此外,基于对从人类微生物组计划(HMP)项目收集的400个细菌基因组的19,989个重叠群的分析,DBSCAN-SWA在高通量测序数据方面优于现有的独立原噬菌体预测工具。DBSCAN-SWA还提供用户友好的结果可视化,包括圆形原噬菌体查看器和交互式DataTables。DBSCAN-SWA用Python3实现,可在https://github.com/HIT-ImmunologyLab/DBSCAN-SWA/ 以开源GPLv2许可获得。