SARS-CoV-2 within-host diversity and transmission

Lythgoe, Katrina A., Hall, Matthew, Ferretti, Luca, de Cesare, Mariateresa, MacIntyre-Cockett, George, Trebes, Amy, Andersson, Monique, Otecko, Newton, Wise, Emma L., Moore, Nathan, Lynch, Jessica, Kidd, Stephen, Cortes, Nicholas, Mori, Matilde, Williams, Rebecca, Vernet, Gabrielle, Justice, Anita, Green, Angie, Nicholls, Samuel M., Ansari, M. Azim, Abeler-Dörner, Lucie, Moore, Catrin E., Peto, Timothy E. A., Eyre, David W., Shaw, Robert, Simmonds, Peter, Buck, David, Todd, John A., Connor, Thomas R. ORCID: https://orcid.org/0000-0003-2394-6504, Ashraf, Shirin, da Silva Filipe, Ana, Shepherd, James, Thomson, Emma C., Bonsall, David, Fraser, Christophe, Golubchik, Tanya, The COVID-19 Genomics UK (COG-UK) Consortium, Bresner, Catherine ORCID: https://orcid.org/0000-0003-2673-9762, Fuller, William, Guest, Martyn, Kitchen, Christine, Marchbank, Angela, Merrick, Ian, Munn, Robert, Price, Anna, Southgate, Joel and Workman, Trudy 2021. SARS-CoV-2 within-host diversity and transmission. Science 372 (6539) , eabg0821. 10.1126/science.abg0821

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Abstract

INTRODUCTION Genome sequencing at an unprecedented scale during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is helping to track spread of the virus and to identify new variants. Most of this work considers a single consensus sequence for each infected person. Here, we looked beneath the consensus to analyze genetic variation within viral populations making up an infection and studied the fate of within-host mutations when an infection is transmitted to a new individual. Within-host diversity offers the means to help confirm direct transmission and identify new variants of concern. RATIONALE We sequenced 1313 SARS-CoV-2 samples from the first wave of infection in the United Kingdom. We characterized within-host diversity and dynamics in the context of transmission and ongoing viral evolution. RESULTS Within-host diversity can be described by the number of intrahost single nucleotide variants (iSNVs) occurring above a given minor allele frequency (MAF) threshold. We found that in lower-viral-load samples, stochastic sampling effects resulted in a higher variance in MAFs, leading to more iSNVs being detected at any threshold. Based on a subset of 27 pairs of high-viral-load replicate RNA samples (>50,000 uniquely mapped veSEQ reads, corresponding to a cycle threshold of ~22), iSNVs with a minimum 3% MAF were highly reproducible. Comparing samples from two time points from 41 individuals, taken on average 6 days apart (interquartile ratio 2 to 10), we observed a dynamic process of iSNV generation and loss. Comparing iSNVs among 14 household contact pairs, we estimated transmission bottleneck sizes of one to eight viruses. Consensus differences between individuals in the same household, where sample depth allowed iSNV detection, were explained by the presence of an iSNV at the same site in the paired individual, consistent with direct transmission leading to fixation. We next focused on a set of 563 high-confidence iSNV sites that were variant in at least one high-viral-load sample (>50,000 uniquely mapped); low-confidence iSNVs unlikely to represent genomic diversity were excluded. Within-host diversity was limited in high-viral-load samples (mean 1.4 iSNVs per sample). Two exceptions, each with >14 iSNVs, showed variant frequencies consistent with coinfection or contamination. Overall, we estimated that 1 to 2% of samples in our dataset were coinfected and/or contaminated. Additionally, one sample was coinfected with another coronavirus (OC43), with no detectable impact on diversity. The ratio of nonsynonymous to synonymous (dN/dS) iSNVs was consistent with within-host purifying selection when estimated across the whole genome [dN/dS = 0.55, 95% confidence interval (95% CI) = 0.49 to 0.61] and for the Spike gene (dN/dS = 0.60, 95% CI = 0.45 to 0.82). Nevertheless, we observed Spike variants in multiple samples that have been shown to increase viral infectivity (L5F) or resistance to antibodies (G446V and A879V). We observed a strong association between high-confidence iSNVs and a consensus change on the phylogeny (153 cases), consistent with fixation after transmission or de novo mutations reaching consensus. Shared variants that never reached consensus (261 cases) were not phylogenetically associated. CONCLUSION Using robust methods to call within-host variants, we uncovered a consistent pattern of low within-host diversity, purifying selection, and narrow transmission bottlenecks. Within-host emergence of vaccine and therapeutic escape mutations is likely to be relatively rare, at least during early infection, when viral loads are high, but the observation of immune-escape variants in high-viral-load samples underlines the need for continued vigilance.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) Biosciences University IT
Additional Information:	C. Bresner, W. Fuller, M. Guest, C. Kitchen, A. Marchbank, I. Merrick, R. Munn, A. Price, J. Southgate and T. Workman are members of the The COVID-19 Genomics UK (COG-UK) Consortium
Publisher:	American Association for the Advancement of Science
ISSN:	0036-8075
Date of First Compliant Deposit:	17 May 2021
Date of Acceptance:	3 March 2021
Last Modified:	19 Sep 2024 01:25
URI:	https://orca.cardiff.ac.uk/id/eprint/141381

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