MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder.

噬菌体（Bacteriophages）是地球上丰度最高的生物实体，但由于其基因组尺寸较小，多数环境中分离获得的遗传物质里，噬菌体来源的组分占比并不高。同时，噬菌体具备极高的遗传多样性与镶嵌型基因组结构，这为其分析与研究带来了显著挑战。本研究提出MetaPhinder——一款用于在宏基因组（metagenomic）数据集中识别噬菌体来源组装基因组片段（即重叠群contigs）的方法。该方法基于全基因组噬菌体序列数据库的比对分析，通过整合多个基因组的比对命中结果，以适配多数噬菌体的镶嵌型基因组结构。经测试，该方法的性能优于基于单序列比对命中的BLAST方法，以及基于k聚体（k-mer）比对的方法。MetaPhinder可通过基因组流行病学中心（Center for Genomic Epidemiology）的在线服务使用，访问地址为https://cge.cbs.dtu.dk/services/MetaPhinder/；其源代码可从https://bitbucket.org/genomicepidemiology/metaphinder或https://github.com/vanessajurtz/MetaPhinder下载。