Benchmark of thirteen bioinformatic pipelines for metagenomic virus diagnostics using datasets from clinical samples.

INTRODUCTION: Metagenomic sequencing is increasingly being used in clinical settings for difficult to diagnose cases. The performance of viral metagenomic protocols relies to a large extent on the bioinformatic analysis. In this study, the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS) initiated a benchmark of metagenomic pipelines currently used in clinical virological laboratories. METHODS: Metagenomic datasets from 13 clinical samples from patients with encephalitis or viral respiratory infections characterized by PCR were selected. The datasets were analyzed with 13 different pipelines currently used in virological diagnostic laboratories of participating ENNGS members. The pipelines and classification tools were: Centrifuge, DAMIAN, DIAMOND, DNASTAR, FEVIR, Genome Detective, Jovian, MetaMIC, MetaMix, One Codex, RIEMS, VirMet, and Taxonomer. Performance, characteristics, clinical use, and user-friendliness of these pipelines were analyzed. RESULTS: Overall, viral pathogens with high loads were detected by all the evaluated metagenomic pipelines. In contrast, lower abundance pathogens and mixed infections were only detected by 3/13 pipelines, namely DNASTAR, FEVIR, and MetaMix. Overall sensitivity ranged from 80% (10/13) to 100% (13/13 datasets). Overall positive predictive value ranged from 71-100%. The majority of the pipelines classified sequences based on nucleotide similarity (8/13), only a minority used amino acid similarity, and 6 of the 13 pipelines assembled sequences de novo. No clear differences in performance were detected that correlated with these classification approaches. Read counts of target viruses varied between the pipelines over a range of 2-3 log, indicating differences in limit of detection. CONCLUSION: A wide variety of viral metagenomic pipelines is currently used in the participating clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implicating the need for standardization and validation of metagenomic analysis for clinical diagnostic use. Future studies should address the selective effects due to the choice of different reference viral databases.

Evidence for an independent third Usutu virus introduction into Germany.

Usutu virus (USUV) is an arbovirus within the genus flavivirus, which was first introduced to Southern Europe approximately twenty years ago causing epizootics among wild and captive birds. In Germany USUV was initially discovered in wild birds, mainly Common blackbirds (Turdus merula), in the Upper Rhine valley in southwest of the country in 2011 and has not spread much northwards since. Phylogenetic analyses revealed that the still ongoing USUV epidemic is caused by two different USUV strains, USUV-Germany belonging to the USUV Europe 3 lineage and USUV-Bonn belonging to the USUV Africa 3 lineage. The two strains were introduced independently. In August 2015 a new USUV strain, named USUV-Berlin, was isolated in Vero cells from two carcasses of juvenile Great grey owls (Strix nebulosa) kept in the Zoological Garden Berlin, which had suffered from a hyperacute fatal systemic infection. Both owls carried high USUV genome loads. Full-length USUV genomes sequences were determined and phylogenetic analysis demonstrated a close relationship with a Spanish mosquito-derived sequence from 2006. Immunohistochemical antigen detection in organ samples of the owls showed the typical USUV infection patterns. According to the phylogenetic analysis, USUV-Berlin belongs to the Africa 2 lineage, and can thus be distinguished from the other strains circulating in Germany. Repeated findings of different USUV strains suggest more frequent introductions into Central Europe and a higher mobility of this virus than assumed to date.

Clustering of classical swine fever virus isolates by codon pair bias.

BACKGROUND: The genetic code consists of non-random usage of synonymous codons for the same amino acids, termed codon bias or codon usage. Codon juxtaposition is also non-random, referred to as codon context bias or codon pair bias. The codon and codon pair bias vary among different organisms, as well as with viruses. Reasons for these differences are not completely understood. For classical swine fever virus (CSFV), it was suggested that the synonymous codon usage does not significantly influence virulence, but the relationship between variations in codon pair usage and CSFV virulence is unknown. Virulence can be related to the fitness of a virus: Differences in codon pair usage influence genome translation efficiency, which may in turn relate to the fitness of a virus. Accordingly, the potential of the codon pair bias for clustering CSFV isolates into classes of different virulence was investigated. RESULTS: The complete genomic sequences encoding the viral polyprotein of 52 different CSFV isolates were analyzed. This included 49 sequences from the GenBank database (NCBI) and three newly sequenced genomes. The codon usage did not differ among isolates of different virulence or genotype. In contrast, a clustering of isolates based on their codon pair bias was observed, clearly discriminating highly virulent isolates and vaccine strains on one side from moderately virulent strains on the other side. However, phylogenetic trees based on the codon pair bias and on the primary nucleotide sequence resulted in a very similar genotype distribution. CONCLUSION: Clustering of CSFV genomes based on their codon pair bias correlate with the genotype rather than with the virulence of the isolates.