A framework for real-time monitoring, analysis and adaptive sampling of viral amplicon nanopore sequencing

Front Genet. 2023 Mar 27:14:1138582. doi: 10.3389/fgene.2023.1138582. eCollection 2023.

Abstract

The ongoing SARS-CoV-2 pandemic demonstrates the utility of real-time sequence analysis in monitoring and surveillance of pathogens. However, cost-effective sequencing requires that samples be PCR amplified and multiplexed via barcoding onto a single flow cell, resulting in challenges with maximising and balancing coverage for each sample. To address this, we developed a real-time analysis pipeline to maximise flow cell performance and optimise sequencing time and costs for any amplicon based sequencing. We extended our nanopore analysis platform MinoTour to incorporate ARTIC network bioinformatics analysis pipelines. MinoTour predicts which samples will reach sufficient coverage for downstream analysis and runs the ARTIC networks Medaka pipeline once sufficient coverage has been reached. We show that stopping a viral sequencing run earlier, at the point that sufficient data has become available, has no negative effect on subsequent down-stream analysis. A separate tool, SwordFish, is used to automate adaptive sampling on Nanopore sequencers during the sequencing run. This enables normalisation of coverage both within (amplicons) and between samples (barcodes) on barcoded sequencing runs. We show that this process enriches under-represented samples and amplicons in a library as well as reducing the time taken to obtain complete genomes without affecting the consensus sequence.

Keywords: bioinformactics; genomics; nanopore sequencing; oxford nanopore minION; oxford nanopore technologies (ONT); pipeline; software; viral sequence analysis.

Grants and funding

Work on minoTour has been funded by BBSRC (BB/M020061/1) as well as additional support from the Defence Science and Technology Laboratory (DSTLX-1000138444). RM is supported by a BBSRC iCASE studentship. The sequencing data used to develop the ARTIC components of minoTour were generated as part of COG-UK, itself supported by funding from the Medical Research Council (MRC) part of UK Research and Innovation (UKRI), the National Institute of Health Research (NIHR) (grant code: MC_PC_19027), and Genome Research Limited, operating as the Wellcome Sanger Institute.