Bolduc Benjamin, Jang Ho Bin, Doulcier Guilhem, You Zhi-Qiang, Roux Simon, Sullivan Matthew B
Department of Microbiology, Ohio State University, Columbus, OH, United States.
Institut de Biologie de l'ENS (IBENS), École normale supérieure, PSL Research University, Paris, France.
PeerJ. 2017 May 3;5:e3243. doi: 10.7717/peerj.3243. eCollection 2017.
Taxonomic classification of archaeal and bacterial viruses is challenging, yet also fundamental for developing a predictive understanding of microbial ecosystems. Recent identification of hundreds of thousands of new viral genomes and genome fragments, whose hosts remain unknown, requires a paradigm shift away from traditional classification approaches and towards the use of genomes for taxonomy. Here we revisited the use of genomes and their protein content as a means for developing a viral taxonomy for bacterial and archaeal viruses. A network-based analytic was evaluated and benchmarked against authority-accepted taxonomic assignments and found to be largely concordant. Exceptions were manually examined and found to represent areas of viral genome 'sequence space' that are under-sampled or prone to excessive genetic exchange. While both cases are poorly resolved by genome-based taxonomic approaches, the former will improve as viral sequence space is better sampled and the latter are uncommon. Finally, given the largely robust taxonomic capabilities of this approach, we sought to enable researchers to easily and systematically classify new viruses. Thus, we established a tool, vConTACT, as an app at iVirus, where it operates as a fast, highly scalable, user-friendly app within the free and powerful CyVerse cyberinfrastructure.
古菌病毒和细菌病毒的分类学分类具有挑战性,但对于深入理解微生物生态系统也是至关重要的。最近发现了成千上万的新病毒基因组和基因组片段,但其宿主仍不明确,这需要我们从传统分类方法转向利用基因组进行分类。在此,我们重新审视了利用基因组及其蛋白质含量为细菌病毒和古菌病毒建立病毒分类学的方法。我们评估了一种基于网络的分析方法,并将其与权威认可的分类学分类进行了对比,发现两者基本一致。对于不一致的情况,我们进行了人工检查,发现它们代表了病毒基因组“序列空间”中采样不足或易于发生过度基因交换的区域。虽然基于基因组的分类方法对这两种情况的解析能力都较差,但随着病毒序列空间采样的改善,前者的情况会得到改善,而后者并不常见。最后,鉴于这种方法在分类学上具有很强的能力,我们致力于让研究人员能够轻松、系统地对新病毒进行分类。因此,我们在iVirus上建立了一个名为vConTACT的工具,它作为一个快速、高度可扩展且用户友好的应用程序,运行于免费且强大的CyVerse网络基础设施中。