Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts

Abstract

Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified viral load as a critical factor in variant identification. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.

Acute SARS-CoV-2 infections harbor limited within-host diversity and transmit via tight transmission bottlenecks

“…Samples with low viral RNA copy numbers can sometimes result in an excess of spuriously detected iSNVs [ 22 ], so we wanted to ensure that we did not detect a greater number of iSNVs in samples in our dataset with low RNA concentrations. Using input data from two different clinical assay platforms, we find no correlation between viral input copies and the number of intersection iSNVs detected, consistent with findings reported by others, and supporting the robustness of our iSNV calls to RNA copy numbers [ 21 , 32 ] ( S3D and S3E Fig ).…”

SARS-CoV-2 Genomic Surveillance Reveals Little Spread From a Large University Campus to the Surrounding Community

“…We sequenced SARS-CoV-2 genomes as described in Valesano et al [ 20 ]. Briefly, we extracted RNA from nasopharyngeal specimens with the PureLink RNA kit and reverse-transcribed RNA with SuperScript IV.…”

The evolution of cheating in viruses

“…Social dynamics could help to explain why variants that arise during individual clinical infections often fail to spread between hosts to become dominant on an epidemiological scale 128 , 129 . One possibility is that some of these variants could be short-sighted cheats, which can spread within a host, but which are unlikely to co-transmit with cooperative viruses between hosts, due to small between-host bottlenecks 103 , 104 .…”