In a recent study posted to the medRxiv* preprint server, researchers examined the intra-host evolution and genetic diversity of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) B.1.517 variant in an immunosuppressed person with chronic coronavirus disease 2019 (COVID-19).
Intrahost SARS-CoV-2 replication could cause faster SARS-CoV-2 evolution than interhost SARS-CoV-2 replication, as the abundance of SARS-CoV-2 in the host would be subject to fewer genetic barriers, and this could increase SARS-CoV replication. 2 recombination chances. Studies have reported on viral presence in chronically ill neighborhood residents; however, detailed genetic analyzes investigating the dynamics of SARS-CoV-2 evolution within the host in individuals with chronic SARS-CoV-2 infections are lacking.
About the study
In the present study, researchers examined intra-host B.1.517 evolution and genomic diversity during a chronic SARS-CoV-2 infection lasting 471 days (and counting) with high viral loads to investigate whether chronic SARS-CoV-2 2 infections SARS-CoV-2 variant emergence.
The team discovered the B.1.517 variant in Connecticut through March 2022 through a dataset from SARS-CoV-2 genomic surveillance. B.1,517 genetic sequences were traced to a subject immunosuppressed with chronic COVID-19 for > 1 year, from whom 30 nasopharyngeal swabs were obtained to sequence the SARS-CoV-2 genome. Whole-genome sequencing (WGS) was used for sequencing between day 79 and day 471 to assess SARS-CoV-2 infection, and 12 swabs were also subjected to in vitro testing for viable SARS-CoV-2.
SARS-CoV-2 ribonucleic acid (RNA) titers were measured by reverse transcription-polymerase chain reaction (RT-PCR), and within-host genomic diversity, recombination and the spectrum and frequency of mutations were characterized. Phylogenetic analyzes were performed to investigate the genetic diversification of SARS-CoV-2 in chronic infections and to assess intra-host SARS-CoV-2 evolution. To evaluate the increase in the genetic diversity of SARS-CoV-2 within the host over time, deep RNA sequencing was performed and the frequencies of intrahost single nucleotide variants (iSNVs) were quantified and validated by SARS-CoV -2 spike (S) gene sequencing using unique molecular identifiers (UMIs).
The person was in his 60s, had B lymphocyte lymphoma and had undergone a stem cell transplant in 2019. The disease relapsed in early 2020 and November 2022, after which chemotherapy and palliation radiotherapy were started, respectively. The subject’s immunoglobulin G (IgG) titres were close to or within normal ranges during intravenous Ig (IVIG) infusion therapy up to day 205, when they decreased. IgA titers and T lymphocyte counts were low before and after infection, reflecting immunocompromised status. In the late asymptomatic stage, only bamlanivimab infusion was administered to the patient on day 90.
In the RT-PCR analysis, swabs obtained between day 79 and day 471 after diagnosis of COVID-19 had a mean cycle threshold (Ct) of 25.5, reflecting ~3.1 × 108 SARS-CoV-2 copies in each ml; However, SARS-CoV-2 copies decreased over time. Of the 12 samples tested for viable SARS-CoV-2 presence, virus was detected at 10 sampling time points between day 79 and day 401, except for day 394 and day 471, which corresponded to higher Ct values of respectively 34 and 31 .
During the chronic SARS-CoV-2 infection, an accelerated rate of SARS-CoV-2 intrahost evolution was observed (35.6 mutations per year or 1.2 × 10-3 nt mutations for each site for each year (s/s/y), nearly double the global evolution rate of SARS-CoV-2 (5.8 × 10-04 s/s/y). The evolution within the host gave rise to >3 genetically different genotypes.
The reseeded genotypes can be considered new variants if they are transferred to the community. The first genotype had 24 nucleotide (nt) mutations [13 mutations of amino acids (aa)] to day 379. The second genotype had 40 nt mutations (28 aa mutations) between day 281 and day 471. The third genotype diverged from the first genotype into two subgenotypes between day 394 and day 401. Subgenotype 1 had 37 nt mutations (30 aa mutations) and subgenotype 2 had 29 nt substitutions (27 aa mutations).
Despite fluctuations, the iSNV frequencies obtained by WGS analysis largely correlated with those of the UMI sequenced S gene. The iSNVs increased over time in the identified genotypes with a mean number of iSNVs of 32.1. The second genotype had more iSNVs than the first, and the number of iSNVs positively correlated with sampling periods.
The mean iSNV persistence of different SARS-CoV-2 genes was similar during the infection course regardless of their frequency. The three most commonly observed iSNVs (in 88% samples) were S:Q493K, S:T1027I and ORF1ab:L2144P. Furthermore, three S-gene iSNVs associated with bamlanivimab resistance were detected, viz. Q493R, L452R and E484K.
The estimated effective SARS-CoV-2 population size (Ne) reflected the number of iSNVs, especially in the early stage of infection. The estimated SARS-CoV-2 build-up rate was 37.5 iSNVs per year, consistent with the SARS-CoV-2 evolution rates estimated from the nt mutations. Most of the mutations were detected at the positions of the first codon (22% non-synonymous changes) and the second codon (38% non-synonymous changes).
Non-synonymous changes were more abundant than synonymous changes in SARS-CoV-2 S (88%), nucleocapsid (66%) and envelope (100%) structural genes. Similarly, non-synonymous aa changes were more abundant in non-structural genes such as the open reading frame 10 (ORF10, 100%) and ORF1ab (58%).
In conclusion, based on the study results, chronic infections may accelerate the evolution of SARS-CoV-2 and thereby give rise to genetically diverse and potentially more transmissible and immune-evasive SARS-CoV-2 variants.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be considered conclusive, that should guide clinical practice/health-related behavior or be treated as established information.
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