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Rapid and Cost-Efficient Enterovirus Genotyping from Clinical Samples Using Flongle Flow Cells

Enteroviruses affect millions of people worldwide and are of significant clinical importance. The standard method for enterovirus identification and genotyping still relies on Sanger sequencing of short diagnostic amplicons. In this study, we assessed the feasibility of nanopore sequencing using the...

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Detalles Bibliográficos
Autores principales: Grädel, Carole, Terrazos Miani, Miguel Angel, Barbani, Maria Teresa, Leib, Stephen L, Suter-Riniker, Franziska, Ramette, Alban
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6770998/
https://www.ncbi.nlm.nih.gov/pubmed/31470607
http://dx.doi.org/10.3390/genes10090659
Descripción
Sumario:Enteroviruses affect millions of people worldwide and are of significant clinical importance. The standard method for enterovirus identification and genotyping still relies on Sanger sequencing of short diagnostic amplicons. In this study, we assessed the feasibility of nanopore sequencing using the new flow cell “Flongle” for fast, cost-effective, and accurate genotyping of human enteroviruses from clinical samples. PCR amplification of partial VP1 gene was performed from multiple patient samples, which were multiplexed together after barcoding PCR and sequenced multiple times on Flongle flow cells. The nanopore consensus sequences obtained from mapping reads to a reference database were compared to their Sanger sequence counterparts. Using clinical specimens sampled over different years, we were able to correctly identify enterovirus species and genotypes for all tested samples, even when doubling the number of barcoded samples on one flow cell. Average sequence identity across sequencing runs was >99.7%. Phylogenetic analysis showed that the consensus sequences achieved with Flongle delivered accurate genotyping. We conclude that the new Flongle-based assay with its fast turnover time, low cost investment, and low cost per sample represents an accurate, reproducible, and cost-effective platform for enterovirus identification and genotyping.