Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, Jilin Province, China.
College of Animal Science and Technology, Shihezi University, Shihezi, Xinjiang Uyghur Autonomous Region, China.
mSystems. 2022 Aug 30;7(4):e0043022. doi: 10.1128/msystems.00430-22. Epub 2022 Jul 14.
Viral metagenomics is the most powerful tool to profile viromic composition for a given sample. Different viromic methods, including amplification-free ones, have been developed, but choosing them for different purposes requires comprehensive benchmarks. Here, we assessed the performance of four routinely used methods, i.e., multiple displacement amplification (MDA), direct metagenomic sequencing (MTG), sequence-independent single-primer amplification (SIA), and metatranscriptomic sequencing (MTT), using marmot rectal samples as the templates spiked with five known viruses of different genome types. The obtained clean data were differently contaminated by host and bacterial genomes, resulting in MDA having the most, with ~72.1%, but MTT had only ~7.5% data, useful for follow-up viromic analysis. MDA showed a broader spectrum with higher efficiency to profile the DNA virome, and MTT captured almost all RNA viruses with extraordinary sensitivity; hence, they are advisable in richness-based viromic studies. MTG was weak in capturing single-stranded DNA viruses, and SIA could detect both RNA and DNA viruses but with high randomness. Due to biases to certain types of viruses, the four methods caused different alterations to species abundance compared to the initial virus composition. SIA and MDA introduced greater stochastic errors to relative abundances of species, genus, and family taxa, whereas the two amplification-free methods were more tolerant toward such errors and thus are recommendable in abundance-based analyses. In addition, genus taxon is a compromising analytic level that ensures technically supported and biologically and/or ecologically meaningful viromic conclusions. Viral metagenomics can be roughly divided into species richness-based studies and species abundance-based analyses. Viromic methods with different principles have been developed, but rational selection of these techniques according to different purposes requires comprehensive understanding of their properties. By assessing the four most widely used methods using template samples, we found that multiple displacement amplification (MDA) and metatranscriptomic sequencing (MTT) are advisable for species richness-based viromic studies, as they show excellent efficiency to detect DNA and RNA viruses. Meanwhile, metagenomic sequencing (MTG) and MTT are more compatible with stochastic errors of methods introduced into relative abundance of viromic taxa and hence are rational choices in species abundance-based analyses. This study also highlights that MTG needs to tackle host genome contamination and ameliorate the capacity to detect single-stranded DNA viruses in the future, and the MTT method requires an improvement in bacterial rRNA depletion prior to library preparation.
病毒宏基因组学是分析特定样本病毒组组成的最强大工具。已经开发了不同的病毒组学方法,包括无扩增方法,但为了不同的目的选择它们需要全面的基准测试。在这里,我们使用土拨鼠直肠样本作为模板,用五种不同基因组类型的已知病毒进行了常规使用的四种方法(多重置换扩增(MDA)、直接宏基因组测序(MTG)、无序列依赖性单引物扩增(SIA)和宏转录组测序(MTT))的性能评估。获得的清洁数据受到宿主和细菌基因组的不同污染,导致 MDA 受到的污染最多,约为 72.1%,而 MTT 仅受到约 7.5%的数据污染,可用于后续病毒组分析。MDA 显示出更广泛的谱,更高的效率来分析 DNA 病毒组,而 MTT 以极高的灵敏度捕获了几乎所有的 RNA 病毒;因此,它们在基于丰富度的病毒组学研究中是明智的选择。MTG 在捕获单链 DNA 病毒方面较弱,而 SIA 可以检测 RNA 和 DNA 病毒,但具有很高的随机性。由于对某些类型的病毒存在偏见,与初始病毒组成相比,这四种方法导致了物种丰度的不同变化。SIA 和 MDA 对物种、属和科分类群的相对丰度引入了更大的随机误差,而两种无扩增方法对这些误差的容忍度更高,因此在基于丰度的分析中是推荐的。此外,属分类群是一个折衷的分析水平,它确保了基于技术支持和生物和/或生态意义的病毒组结论。病毒宏基因组学大致可分为基于物种丰富度的研究和基于物种丰度的分析。已经开发了具有不同原理的病毒组学方法,但根据不同的目的合理选择这些技术需要全面了解它们的特性。通过对模板样本的四种最广泛使用的方法进行评估,我们发现多重置换扩增(MDA)和宏转录组测序(MTT)适合基于物种丰富度的病毒组学研究,因为它们表现出高效检测 DNA 和 RNA 病毒的能力。同时,宏基因组测序(MTG)和 MTT 与方法引入的相对病毒组分类群丰度的随机误差更兼容,因此是基于物种丰度的分析的合理选择。本研究还强调,MTG 需要解决宿主基因组污染问题,并改善其检测单链 DNA 病毒的能力,而 MTT 方法在准备文库之前需要改进细菌 rRNA 的耗竭。