Wang Yajing, Wang Hui, Xu Kunhan, Ni Peixiang, Zhang Huan, Ma Jinmin, Yang Huanming, Xu Feng
College of Biotechnology, Tianjin University of Science and Technology, Tianjin, China; College of Pharmacy, State Key Laboratory of Medicinal Chemical Biology and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin, China.
NERC/Centre for Ecology and Hydrology, Wallingford, Oxfordshire, United Kingdom; Beijing Genome Institute (BGI), Yantian District, Shenzhen, China; Department of Zoology, University of Oxford, Oxford, United Kingdom.
PLoS One. 2014 Aug 21;9(8):e105348. doi: 10.1371/journal.pone.0105348. eCollection 2014.
It is commonly accepted that there are many unknown viruses on the planet. For the known viruses, do we know their prevalence, even in our experimental systems? Here we report a virus survey using recently published small (s)RNA sequencing datasets. The sRNA reads were assembled and contigs were screened for virus homologues against the NCBI nucleotide (nt) database using the BLASTn program. To our surprise, approximately 30% (28 out of 94) of publications had highly scored viral sequences in their datasets. Among them, only two publications reported virus infections. Though viral vectors were used in some of the publications, virus sequences without any identifiable source appeared in more than 20 publications. By determining the distributions of viral reads and the antiviral RNA interference (RNAi) pathways using the sRNA profiles, we showed evidence that many of the viruses identified were indeed infecting and generated host RNAi responses. As virus infections affect many aspects of host molecular biology and metabolism, the presence and impact of viruses needs to be actively investigated in experimental systems.
人们普遍认为地球上存在许多未知病毒。对于已知病毒,即便在我们的实验系统中,我们了解它们的流行情况吗?在此,我们报告一项利用最近发表的小(s)RNA测序数据集进行的病毒调查。对sRNA读数进行组装,并使用BLASTn程序针对NCBI核苷酸(nt)数据库筛选重叠群中的病毒同源物。令我们惊讶的是,约30%(94篇中的28篇)的出版物的数据集中有得分很高的病毒序列。其中,只有两篇出版物报告了病毒感染情况。尽管部分出版物使用了病毒载体,但超过20篇出版物中出现了来源不明的病毒序列。通过利用sRNA图谱确定病毒读数的分布以及抗病毒RNA干扰(RNAi)途径,我们证明了许多鉴定出的病毒确实正在感染并引发宿主RNAi反应。由于病毒感染会影响宿主分子生物学和新陈代谢的多个方面,因此需要在实验系统中积极研究病毒的存在及其影响。