Limited SARS-CoV-2 diversity within hosts and following passage in cell culture

Abstract

Since the first reports of pneumonia associated with a novel coronavirus (COVID-19) emerged in Wuhan, Hubei province, China, there have been considerable efforts to sequence the causative virus, SARS-CoV-2 (also referred to as hCoV-19) and to make viral genomic information available quickly on shared repositories. As of 30 March 2020, 7,680 consensus sequences have been shared on GISAID, the principal repository for SARS-CoV-2 genetic information. These sequences are primarily consensus sequences from clinical and passaged samples, but few reports have looked at diversity of virus populations within individual hosts or cultures. Understanding such diversity is essential to understanding viral evolutionary dynamics. Here, we characterize within-host viral diversity from a primary isolate and passaged samples, all originally deriving from an individual returning from Wuhan, China, who was diagnosed with COVID-19 and subsequently sampled in Wisconsin, United States. We use a metagenomic approach with Oxford Nanopore Technologies (ONT) GridION in combination with Illumina MiSeq to capture minor within-host frequency variants ≥1%. In a clinical swab obtained from the day of hospital presentation, we identify 15 single nucleotide variants (SNVs) ≥1% frequency, primarily located in the largest gene – ORF1a. While viral diversity is low overall, the dominant genetic signatures are likely secondary to population size changes, with some evidence for mild purifying selection throughout the genome. We see little to no evidence for positive selection or ongoing adaptation of SARS-CoV-2 within cell culture or in the primary isolate evaluated in this study.Author SummaryWithin-host variants are critical for addressing molecular evolution questions, identifying selective pressures imposed by vaccine-induced immunity and antiviral therapeutics, and characterizing interhost dynamics, including the stringency and character of transmission bottlenecks. Here, we sequenced SARS-CoV-2 viruses isolated from a human host and from cell culture on three distinct Vero cell lines using Illumina and ONT technologies. We show that SARS-CoV-2 consensus sequences can remain stable through at least two serial passages on Vero 76 cells, suggesting SARS-CoV-2 can be propagated in cell culture in preparation for in-vitro and in-vivo studies without dramatic alterations of its genotype. However, we emphasize the need to deep-sequence viral stocks prior to use in experiments to characterize sub-consensus diversity that may alter outcomes.

Haploflow: Strain-resolvedde novoassembly of viral genomes

“…Haploflow identified two strains in nine samples, consistent with in-sample variation [36][37][38] . The assembled contigs were assessed with QUAST 39 using the Wuhan-Hu-1 isolate strain (RefSeq NC_045512.2) as reference genome.…”

Early transmission of SARS-CoV-2 in South Africa: An epidemiological and phylogenetic report

“…The 21 KZN whole genomes (20 KRISP and one NICD) were assigned to SARS-CoV-2 sub-lineages according to the nomenclature proposed and lineage classification obtained from >5000 genomes analyzed by Rambaut et al ( Rambaut et al, 2020 ). Given uncertainties pertaining to the low diversity of this virus ( Moreno et al, 2020 ), we restricted lineage assignment to the four most prominent subgroups (A, B, B·1 and B·2). Of the 21 KZN isolates being investigated in the present study, one was assigned to lineage B ( KRISP-006 ) and one to sub-lineage B·2 ( KRISP-002 ) ( Fig.…”

Guidelines for accurate genotyping of SARS-CoV-2 using amplicon-based sequencing of clinical samples

“…Even if several studies report variants found at frequencies below 0.1 (25,27,37-39) only a few evaluated the confidence of such calls (26,40). We found that the number of variants with VAF>0.1 detected in samples with at least 1000 g.c.p.r is similar between contemporaneous samples and increases with time since the start of the outbreak, as expected.…”

“…Previous efforts to genotype the Zika virus using amplicon-based approaches suggested that the fraction at which a variant can be confidently separated from technical noise is no lower than 3% even when sufficient input material, sequencing depth and replicates are used (24). However, some of the variants considered in the analysis of SARS-CoV-2 intra-host genome variability were reported at lower fractions (25-27). Furthermore, data generated by different laboratories might contain specific biases, compromising their direct comparison and the validity of downstream analysis (11,12).…”