A comparison of five Illumina, Ion Torrent, and nanopore sequencing technology-based approaches for whole genome sequencing of SARS-CoV-2.

Autor: Carbo EC; Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands., Mourik K; Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands., Boers SA; Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands., Munnink BO; Department of Viroscience, Erasmus Medical Centre, Rotterdam, The Netherlands., Nieuwenhuijse D; Department of Viroscience, Erasmus Medical Centre, Rotterdam, The Netherlands., Jonges M; Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands., Welkers MRA; Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands., Matamoros S; Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands., van Harinxma Thoe Slooten J; Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands., Kraakman MEM; Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands., Karelioti E; GenomeScan B.V, Leiden, The Netherlands., van der Meer D; GenomeScan B.V, Leiden, The Netherlands., Veldkamp KE; Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands., Kroes ACM; Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands., Sidorov I; Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands., de Vries JJC; Clinical Microbiological Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands. jjcdevries@lumc.nl.
Jazyk: angličtina
Zdroj: European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology [Eur J Clin Microbiol Infect Dis] 2023 Jun; Vol. 42 (6), pp. 701-713. Date of Electronic Publication: 2023 Apr 05.
DOI: 10.1007/s10096-023-04590-0
Abstrakt: Rapid identification of the rise and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern remains critical for monitoring of the efficacy of diagnostics, therapeutics, vaccines, and control strategies. A wide range of SARS-CoV-2 next-generation sequencing (NGS) methods have been developed over the last years, but cross-sequence technology benchmarking studies have been scarce. In the current study, 26 clinical samples were sequenced using five protocols: AmpliSeq SARS-CoV-2 (Illumina), EasySeq RC-PCR SARS-CoV-2 (Illumina/NimaGen), Ion AmpliSeq SARS-CoV-2 (Thermo Fisher), custom primer sets (Oxford Nanopore Technologies (ONT)), and capture probe-based viral metagenomics (Roche/Illumina). Studied parameters included genome coverage, depth of coverage, amplicon distribution, and variant calling. The median SARS-CoV-2 genome coverage of samples with cycle threshold (Ct) values of 30 and lower ranged from 81.6 to 99.8% for, respectively, the ONT protocol and Illumina AmpliSeq protocol. Correlation of coverage with PCR Ct values varied per protocol. Amplicon distribution signatures differed across the methods, with peak differences of up to 4 log 10 at disbalanced positions in samples with high viral loads (Ct values ≤ 23). Phylogenetic analyses of consensus sequences showed clustering independent of the workflow used. The proportion of SARS-CoV-2 reads in relation to background sequences, as a (cost-)efficiency metric, was the highest for the EasySeq protocol. The hands-on time was the lowest when using EasySeq and ONT protocols, with the latter additionally having the shortest sequence runtime. In conclusion, the studied protocols differed on a variety of the studied metrics. This study provides data that assist laboratories when selecting protocols for their specific setting.
(© 2023. The Author(s).)
Databáze: MEDLINE
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