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A proficiency testing of metagenomics as a diagnostic tool for the detection of RNA viruses in swine fecal material. Proficiency testing of metagenomics

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/bioproject/PRJEB44508
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Metagenomics next-generation sequencing (mNGS) is widely used as a generic molecular diagnostic tool for detection of the unknown, emerging, or re-emerging pathogens. A typical methodological workflow includes sample disintegration, nucleic acid extraction, double strand cDNA synthesis in case of RNA, library preparation, and data analysis, all of which affect the performance of mNGS diagnostics. This study was undertaken among six European laboratories within METASTAVA One Health European Joint Programme. Modules suitable to build standardized mNGS workflows were selected and tested. For each of the modules, two methods and common procedures for analysis of sequencing data were chosen. To finally evaluate the selected modules in terms of (i) suitability to detect viruses in native samples and (ii) simultaneously assess their reproducibility, a proficiency test (PT) was carried out as part of METASTAVA. For this PT, a pre-analysed swine faecal sample containing a porcine astrovirus and RNA extracted from that sample were distributed among the participants. Most importantly, using the abovementioned methods comprised in the METASTAVA modular mNGS workflow, all participants identified the same viral species belonging to the family Astroviridae in both, the clinical sample and in the distributed RNA. In detail, all participants classified the majority of viral reads to two species of porcine astroviruses (PAstV2 and PAstV4), regardless of the used analysis method (Kraken and Bowtie2). Moreover, participants performed well in terms of repeatability when the faecal sample was tested in duplicate, resulting in a low coefficient of variation. Therefore, this PT showed that the methods selected as METASTAVA mNGS modules are (i) well suited for virus identification even from challenging matrices like faeces and (ii) the selected methods can reproducibly be applied.
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2024-10-29
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