Viral Metagenomics in the Clinical Realm: Lessons Learned from a Swiss-Wide Ring Trial

Genes

Michael Huber¹  Jacques Fellay²  Christian Beuret²  Samuel Cordey³  Florian Laubscher⁴  Thomas Junier⁵  Jakub Kubacki⁶  Alban Ramette⁶  Verena Kufner⁷  Stefan Schmutz⁷  Osvaldo Zagordi⁷  Stefan Neuenschwander⁷  Claudia Bachofen⁸  Weihong Qi⁸  Valérie Barbié⁹  Laurent Kaiser⁹  Aitana Lebrand⁹ 

[1] SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland;University of Geneva Medical School, 1206 Geneva, Switzerland;University of Zurich, 8057 Zurich, Switzerland;;Functional Genomics Center Zurich, Swiss Federal Institute of Technology (ETH Zurich) &;Global Health Institute, Swiss Federal Institute of Technology (ETH Lausanne) &Institute for Infectious Diseases, University of Bern, 3001 Bern, Switzerland;Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland;Institute of Virology, VetSuisse Faculty, University of Zurich, 8057 Zurich, Switzerland;Laboratory of Virology, University Hospitals of Geneva, 1205 Geneva, Switzerland;

关键词: viral metagenomics;    ring trial;    external quality assessment;    EQA;    quality control;   

DOI  :  10.3390/genes10090655

来源: DOAJ

【 摘 要 】

Shotgun metagenomics using next generation sequencing (NGS) is a promising technique to analyze both DNA and RNA microbial material from patient samples. Mostly used in a research setting, it is now increasingly being used in the clinical realm as well, notably to support diagnosis of viral infections, thereby calling for quality control and the implementation of ring trials (RT) to benchmark pipelines and ensure comparable results. The Swiss NGS clinical virology community therefore decided to conduct a RT in 2018, in order to benchmark current metagenomic workflows used at Swiss clinical virology laboratories, and thereby contribute to the definition of common best practices. The RT consisted of two parts (increments), in order to disentangle the variability arising from the experimental compared to the bioinformatics parts of the laboratory pipeline. In addition, the RT was also designed to assess the impact of databases compared to bioinformatics algorithms on the final results, by asking participants to perform the bioinformatics analysis with a common database, in addition to using their own in-house database. Five laboratories participated in the RT (seven pipelines were tested). We observed that the algorithms had a stronger impact on the overall performance than the choice of the reference database. Our results also suggest that differences in sample preparation can lead to significant differences in the performance, and that laboratories should aim for at least 5−10 Mio reads per sample and use depth of coverage in addition to other interpretation metrics such as the percent of coverage. Performance was generally lower when increasing the number of viruses per sample. The lessons learned from this pilot study will be useful for the development of larger-scale RTs to serve as regular quality control tests for laboratories performing NGS analyses of viruses in a clinical setting.

【 授权许可】

Unknown