SARS-CoV-2 Within-Host and in vitro Genomic Variability and Sub-Genomic RNA Levels Indicate Differences in Viral Expression Between Clinical Cohorts and in vitro Culture

Abstract

BackgroundLow frequency intrahost single nucleotide variants (iSNVs) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) have been increasingly recognised as predictive indicators of positive selection. Particularly as growing numbers of SARS-CoV-2 variants of interest (VOI) and concern (VOC) emerge. However, the dynamics of subgenomic RNA (sgRNA) expression and its impact on genomic diversity and infection outcome remain poorly understood. This study aims to investigate and quantify iSNVs and sgRNA expression in single and longitudinally sampled cohorts over the course of mild and severe SARS-CoV-2 infection, benchmarked against an in vitro infection model.MethodsTwo clinical cohorts of SARS-CoV-2 positive cases in New South Wales, Australia collected between March 2020 and August 2021 were sequenced. Longitudinal samples from cases hospitalised due to SARS-CoV-2 infection (severe) (n = 16) were analysed and compared with cases that presented with SARS-CoV-2 symptoms but were not hospitalised (mild) (n = 23). SARS-CoV-2 genomic diversity profiles were also examined from daily sampling of culture experiments for three SARS-CoV-2 variants (Lineage A, B.1.351, and B.1.617.2) cultured in VeroE6 C1008 cells (n = 33).ResultsIntrahost single nucleotide variants were detected in 83% (19/23) of the mild cohort cases and 100% (16/16) of the severe cohort cases. SNP profiles remained relatively fixed over time, with an average of 1.66 SNPs gained or lost, and an average of 4.2 and 5.9 low frequency variants per patient were detected in severe and mild infection, respectively. sgRNA was detected in 100% (25/25) of the mild genomes and 92% (24/26) of the severe genomes. Total sgRNA expressed across all genes in the mild cohort was significantly higher than that of the severe cohort. Significantly higher expression levels were detected in the spike and the nucleocapsid genes. There was significantly less sgRNA detected in the culture dilutions than the clinical cohorts.Discussion and ConclusionThe positions and frequencies of iSNVs in the severe and mild infection cohorts were dynamic overtime, highlighting the importance of continual monitoring, particularly during community outbreaks where multiple SARS-CoV-2 variants may co-circulate. sgRNA levels can vary across patients and the overall level of sgRNA reads compared to genomic RNA can be less than 1%. The relative contribution of sgRNA to the severity of illness warrants further investigation given the level of variation between genomes. Further monitoring of sgRNAs will improve the understanding of SARS-CoV-2 evolution and the effectiveness of therapeutic and public health containment measures during the pandemic.

Comparative subgenomic mRNA profiles of SARS-CoV-2 Alpha, Delta and Omicron BA.1, BA.2 and BA.5 sub-lineages using Danish COVID-19 genomic surveillance data

“…Similar to the observations made from our previous study 14 and other works 19,35 , we were not able to detect any subgenomic Orf10. Among the eight screened subgenomic mRNAs, four were expressed in relatively higher abundance: Spike (S), M, Orf6, and Orf9 (N and any 3'-end open reading frames).…”

“…That differed from other works which linked subgenomic RNA levels with active viral infection. A study reported for example decreased subgenomic RNA levels in severe cases 19 while others described a correlation between genomic and subgenomic RNA levels, which was being interpretated in these studies as a surrogate of viral activation and transcription [15][16][17][18] . In particular, the previously described apparent correlation between genomic and subgenomic Orf7 18 could be explained by the presence of subgenomic RNA roughly in the same proportion throughout the infection course synchronously with the presence of genomic RNA.…”

“…The clearance of subgenomic RNAs is currently debated, and several studies have suggested that these are markers of acute infection and active replication 2,6,7, 15-18 , while some have indicated higher subgenomic RNA levels in patients with mild disease compared to severe cases 19,20 . We have recently reported that subgenomic RNAs are relatively stable and can be detected in samples up to 19 days post symptom onset and are correlated with the amount of genomic length RNA present within a sample 14,20 .…”

SARS-CoV-2 quasi-species analysis from patients with persistent nasopharyngeal shedding

“…They detected, among 15,289 Sars-CoV-2 genomes analyzed, high frequency intra-host variability on codon 194, 215, 261, 655, 1254, 1258 and 1259 in spike domain, that represent a close region to our super variant codons and seems to be in similar distribution, close to key mutations E484, N501 per example. Agius et al identified kinds of high variables clouds near to the mean VOC mutations, considering a potential role of those variability strand in deep mutational process, linked with strong interactions with our immune system 27 . In their interesting works, intra-host variability was the most important in ORF1a domain and in spike domain as we found for spike and NSP3 domain.…”

On the Evolutionary Trajectory of SARS-CoV-2: Host Immunity as a Driver of Adaptation in RNA Viruses

“…RNA viruses tend to mutate at rates very close to this threshold [ 4 , 5 , 8 ] and replicate with relatively low fidelity compared to DNA viruses. As such, RNA viruses can diverge considerably even during a short infection [ 2 , 3 , 4 , 5 , 9 ] and generally exist in a host as a collection of genetically similar variants, termed quasispecies [ 10 , 11 ]. The ability of RNA viruses to diversify so rapidly represents a fitness advantage when infecting a biologically diverse host population [ 12 ].…”