VIRify: An integrated detection, annotation and taxonomic classification pipeline using virus-specific protein profile hidden Markov models.
VIRify: An integrated detection, annotation and taxonomic classification pipeline using virus-specific protein profile hidden Markov models.
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DOI：
10.1371/journal.pcbi.1011422
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发表时间：
2023-08
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
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对病毒群落的研究揭示了这些生物实体对各种生态系统的巨大多样性和影响。这些观察结果引发了人们对开发支持基于测序数据的病毒群落综合表征的计算策略的广泛兴趣。在这里，我们介绍VIRify，一个新的计算管道，旨在提供一个用户友好和准确的功能和分类特征的病毒社区。VIRify从宏基因组组装体中识别病毒重叠群和原噬菌体，并使用病毒特征隐马尔可夫模型（Hidden Markov Models，HALF）的集合对其进行注释。这些包括我们的人工策划的配置文件HALGORITIS，它作为广泛的原核和真核病毒分类群的特异性分类标志物，因此用于可靠地分类病毒重叠群。我们在来自两个微生物模拟社区的组装件上测试了VIRify，一项大型宏基因组学研究，以及一组来自人类肠道的公开可用的病毒基因组序列。结果表明，VIRify能够识别原核和真核病毒的序列，并以86.6%的平均准确率提供从属到科的分类。此外，VIRify允许对243个海洋宏基因组组装体中存在的一系列原核和真核病毒进行检测和分类学分类。最后，VIRify的使用导致分类学分类的人类肠道病毒序列的数量大幅增加，并改进了过时和肤浅的分类学分类。总的来说，我们证明了VIRify是一种新颖而强大的资源，它提供了检测广泛的病毒重叠群并对其进行分类的增强能力。病毒是我们星球上最丰富的生物实体。有些是与公共卫生或农业有关的病原体。尽管如此，许多人也发挥着对维持生态系统至关重要的生态作用。大多数病毒尚未培养，因此它们的鉴定和表征仅取决于对从环境中获得的DNA或RNA的分析。与细胞生物不同，病毒也缺乏通用的遗传标记，无法对环境病毒群落进行分类学分析。我们已经手动策划了一组特定的病毒蛋白模型，作为一个全面的病毒分类群的分类标志物。使用这些蛋白质模型，我们开发了VIRify，这是一种用于检测、注释和分类从环境DNA或RNA中获得的病毒序列的计算管道。我们的新管道在检测和分类模拟微生物群落中的细菌或真核生物的病毒序列，来自世界海洋的样本以及先前组装的人类肠道病毒集合方面非常有效。VIRify是用户友好的，需要与命令行进行最少的交互，并且在开发时考虑了可移植性。VIRify可以加强对自然界病毒多样性的探索，并支持检测具有大流行潜力的病原性病毒。
The study of viral communities has revealed the enormous diversity and impact these biological entities have on various ecosystems. These observations have sparked widespread interest in developing computational strategies that support the comprehensive characterisation of viral communities based on sequencing data. Here we introduce VIRify, a new computational pipeline designed to provide a user-friendly and accurate functional and taxonomic characterisation of viral communities. VIRify identifies viral contigs and prophages from metagenomic assemblies and annotates them using a collection of viral profile hidden Markov models (HMMs). These include our manually-curated profile HMMs, which serve as specific taxonomic markers for a wide range of prokaryotic and eukaryotic viral taxa and are thus used to reliably classify viral contigs. We tested VIRify on assemblies from two microbial mock communities, a large metagenomics study, and a collection of publicly available viral genomic sequences from the human gut. The results showed that VIRify could identify sequences from both prokaryotic and eukaryotic viruses, and provided taxonomic classifications from the genus to the family rank with an average accuracy of 86.6%. In addition, VIRify allowed the detection and taxonomic classification of a range of prokaryotic and eukaryotic viruses present in 243 marine metagenomic assemblies. Finally, the use of VIRify led to a large expansion in the number of taxonomically classified human gut viral sequences and the improvement of outdated and shallow taxonomic classifications. Overall, we demonstrate that VIRify is a novel and powerful resource that offers an enhanced capability to detect a broad range of viral contigs and taxonomically classify them. Viruses are the most abundant biological entities on our planet. Some are relevant pathogens for public health or agriculture. Still, many also play ecological roles that are critical for maintaining ecosystems. Most viruses are yet to be cultured, so their identification and characterisation depend solely on the analysis of DNA or RNA obtained from the environment. Unlike cellular organisms, viruses also lack a universal genetic marker that allows taxonomic profiling of an environmental viral community. We have manually curated a set of specific viral protein models that serve as taxonomic markers for a comprehensive range of viral taxa. Using these protein models, we developed VIRify, a computational pipeline for the detection, annotation, and taxonomic classification of viral sequences obtained from environmental DNA or RNA. Our new pipeline was efficient in detecting and classifying sequences of viruses targeting bacteria or eukaryotic organisms in mock microbial communities, samples from the world’s oceans, and a previously assembled collection of human gut viruses. VIRify is user-friendly, requires minimal interaction with the command line, and was developed with portability in mind. VIRify can enhance the exploration of viral diversity in nature and support the detection of pathogenic viruses with pandemic potential.
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DOI：
10.1038/ismej.2016.89
发表时间：
2017-01
期刊：
The ISME journal
影响因子：
--
作者：
Bolduc B;Youens-Clark K;Roux S;Hurwitz BL;Sullivan MB
通讯作者：
Sullivan MB
影响因子：
14.9
作者：
Federhen S
通讯作者：
Federhen S
影响因子：
3.7
作者：
Amgarten, Deyvid;Braga, Lucas P. P.;Setubal, Joao C.
通讯作者：
Setubal, Joao C.
影响因子：
--
作者：
Bigot, Thomas;Temmam, Sarah;Eloit, Marc
通讯作者：
Eloit, Marc
DOI：
10.1146/annurev-biodatasci-012221-095114
发表时间：
2021-01-01
期刊：
ANNUAL REVIEW OF BIOMEDICAL DATA SCIENCE, VOL 4
影响因子：
--
作者：
Call, Lee;Nayfach, Stephen;Kyrpides, Nikos C.
通讯作者：
Kyrpides, Nikos C.