Institute of Diagnostic Virology, Friedrich-Loeffler-Institut (FLI), Südufer 10, 17493 Greifswald-Insel Riems, Germany.
Institute of Diagnostic Virology, Friedrich-Loeffler-Institut (FLI), Südufer 10, 17493 Greifswald-Insel Riems, Germany.
Int J Parasitol. 2019 Sep;49(10):769-777. doi: 10.1016/j.ijpara.2019.04.007. Epub 2019 Jul 27.
Efficient and reliable identification of emerging pathogens is crucial for the design and implementation of timely and proportionate control strategies. This is difficult if the pathogen is so far unknown or only distantly related with known pathogens. Diagnostic metagenomics - an undirected, broad and sensitive method for the efficient identification of pathogens - was frequently used for virus and bacteria detection, but seldom applied to parasite identification. Here, metagenomics datasets prepared from swine faeces using an unbiased sample processing approach with RNA serving as starting material were re-analysed with respect to parasite detection. The taxonomic identification tool RIEMS, used for initial detection, provided basic hints on potential pathogens contained in the datasets. The suspected parasites/intestinal protists (Blastocystis, Entamoeba, Iodamoeba, Neobalantidium, Tetratrichomonas) were verified using subsequently applied reference mapping analyses on the base of rRNA sequences. Nearly full-length gene sequences could be extracted from the RNA-derived datasets. In the case of Blastocystis, subtyping was possible with subtype (ST)15 discovered for the first known time in swine faeces. Using RIEMS, some of the suspected candidates turned out to be false-positives caused by the poor status of sequences in publicly available databases. Altogether, 11 different species/STs of parasites/intestinal protists were detected in 34 out of 41 datasets extracted from metagenomics data. The approach operates without any primer bias that typically hampers the analysis of amplicon-based approaches, and allows the detection and taxonomic classification including subtyping of protist and metazoan endobionts (parasites, commensals or mutualists) based on an abundant biomarker, the 18S rRNA. The generic nature of the approach also allows evaluation of interdependencies that induce mutualistic or pathogenic effects that are often not clear for many intestinal protists and perhaps other parasites. Thus, metagenomics has the potential for generic pathogen identification beyond the characterisation of viruses and bacteria when starting from RNA instead of DNA.
快速而可靠地识别新出现的病原体对于设计和实施及时且适度的控制策略至关重要。如果病原体尚不清楚或与已知病原体仅有远缘关系，则会面临困难。诊断宏基因组学 - 一种用于高效识别病原体的无定向、广泛且敏感的方法 - 常用于病毒和细菌检测，但很少应用于寄生虫鉴定。在这里，使用无偏样本处理方法（以 RNA 为起始材料）从猪粪便中制备的宏基因组数据集，针对寄生虫检测进行了重新分析。最初检测中使用的分类鉴定工具 RIEMS 提供了数据集中潜在病原体的基本提示。疑似寄生虫/肠道原生动物（Blastocystis、Entamoeba、Iodamoeba、Neobalantidium、Tetratrichomonas）通过随后基于 rRNA 序列的参考映射分析进行验证。从 RNA 衍生数据集中几乎可以提取出全长基因序列。在 Blastocystis 的情况下，可以通过亚型 (ST)15 进行亚分型，这是首次在猪粪便中发现的。使用 RIEMS，一些疑似候选者被证明是由于公共数据库中序列状态不佳而产生的假阳性。总共，在从宏基因组数据中提取的 41 个数据集中的 34 个中检测到 11 种不同的寄生虫/肠道原生动物物种/ST。该方法在操作过程中没有任何引物偏倚，这通常会阻碍基于扩增子的方法的分析，并允许基于丰富的生物标志物 18S rRNA 进行原生动物和后生动物内共生体（寄生虫、共生菌或互惠共生体）的检测和分类，包括亚分型。该方法的通用性还允许评估相互依存关系，这些关系会引起互惠或致病效应，而对于许多肠道原生动物甚至其他寄生虫来说，这些效应往往并不清楚。因此，与从 DNA 开始相比，从 RNA 开始的宏基因组学具有识别通用病原体的潜力，而不仅仅是病毒和细菌的特征。
