Automated Library Construction and Analysis for High-Throughput Nanopore Sequencing of SARS-CoV-2

J Appl Lab Med. 2022 Sep 1;7(5):1025-1036. doi: 10.1093/jalm/jfac054.

Abstract

Background: To support the implementation of high-throughput pipelines suitable for SARS-CoV-2 sequencing and analysis in a clinical laboratory, we developed an automated sample preparation and analysis workflow.

Methods: We used the established ARTIC protocol with approximately 400 bp amplicons sequenced on Oxford Nanopore's MinION. Sequences were analyzed using Nextclade, assigning both a clade and quality score to each sample.

Results: A total of 2179 samples on twenty-five 96-well plates were sequenced. Plates of purified RNA were processed within 12 h, sequencing required up to 24 h, and analysis of each pooled plate required 1 h. The use of samples with known threshold cycle (Ct) values enabled normalization, acted as a quality control check, and revealed a strong correlation between sample Ct values and successful analysis, with 85% of samples with Ct < 30 achieving a "good" Nextclade score. Less abundant samples responded to enrichment with the fraction of Ct > 30 samples achieving a "good" classification rising by 60% after addition of a post-ARTIC PCR normalization. Serial dilutions of 3 variant of concern samples, diluted from approximately Ct = 16 to approximately Ct = 50, demonstrated successful sequencing to Ct = 37. The sample set contained a median of 24 mutations per sample and a total of 1281 unique mutations with reduced sequence read coverage noted in some regions of some samples. A total of 10 separate strains were observed in the sample set, including 3 variants of concern prevalent in British Columbia in the spring of 2021.

Conclusions: We demonstrated a robust automated sequencing pipeline that takes advantage of input Ct values to improve reliability.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19* / diagnosis
  • COVID-19* / epidemiology
  • Humans
  • Nanopore Sequencing*
  • Nanopores*
  • Reproducibility of Results
  • SARS-CoV-2 / genetics