From one to many: The within-host rise of viral variants

Bessière, Pierre; Volmer, Romain

doi:10.1371/journal.ppat.1009811

Cited by 12 publications

(11 citation statements)

References 19 publications

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“…The lack of inter-relationship of iSNV diversity and route of exposure, dose, or time after infection may suggest that intrinsic virus–host interactions play a larger role in determining within-host virus diversity of these H7N3 viruses in turkeys and chickens. Potentially, within-host diversity can be modulated by differences in host cell requirements for viral replication or innate antiviral responses and could also explain the differences in susceptibility between turkeys and chickens [ 3 , 77 ]. Further investigation will be needed to determine if such host factors play a role.…”

Section: Discussionmentioning

confidence: 99%

“…Under the appropriate conditions, variants that are present at a low frequency can replicate exponentially and quickly become predominant in the population. The existence of such variants in a population allows for rapid response to prevailing circumstances and thereby can potentially lead to the emergence of new viral strains [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

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Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens

Leyson

Criado

Youk

et al. 2022

Viruses

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Within-host viral diversity offers a view into the early stages of viral evolution occurring after a virus infects a host. In recent years, advances in deep sequencing have allowed for routine identification of low-frequency variants, which are important sources of viral genetic diversity and can potentially emerge as a major virus population under certain conditions. We examined within-host viral diversity in turkeys and chickens experimentally infected with closely related H7N3 avian influenza viruses (AIVs), specifically one high pathogenicity AIV (HPAIV) and two low pathogenicity AIV (LPAIVs) with different neuraminidase protein stalk lengths. Consistent with the high mutation rates of AIVs, an abundance of intra-host single nucleotide variants (iSNVs) at low frequencies of 2–10% was observed in all samples collected. Furthermore, a small number of common iSNVs were observed between turkeys and chickens, and between directly inoculated and contact-exposed birds. Notably, the LPAIVs have significantly higher iSNV diversities and frequencies of nonsynonymous changes than the HPAIV in both turkeys and chickens. These findings highlight the dynamics of AIV populations within hosts and the potential impact of genetic changes, including mutations in the hemagglutinin gene that confers the high pathogenicity pathotype, on AIV virus populations and evolution.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens

Leyson

Criado

Youk

et al. 2022

Viruses

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“…Implicitly each VOC contender is a potential new pandemic [29,34,[39][40][41]. Consequently, a new local R 0 can be projected for that VOC.…”

Section: P R E -P R I N Tmentioning

confidence: 99%

Basic reproduction number projection for novel pandemics and variants. Ancestral SARS-CoV2 R0 projection

Benjamin¹

2022

Preprint

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The recently derived Hybrid-Incidence Susceptible-Transmissible-Removed (HI-STR) prototype is a deterministic epidemic compartment model and an alternative to the Susceptible-Infected-Removed (SIR) model prototype. The HI-STR predicts that pathogen transmission depends on host population characteristics including population size, population density and some common host behavioural characteristics. The HI-STR prototype is applied to the ancestral Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) to show that the original estimates of the Coronavirus Disease 2019 (COVID-19) basic reproduction number ($\mathcal{R}_0$) for the United Kingdom (UK) could have been projected on the individual states of the United States of America (USA) prior to being detected in the USA. The Imperial College London (ICL) R0 estimate for the UK is projected onto each USA state. The difference between these projections and ICL estimates for USA states is either not statistically significant on the paired student t-test or epidemiologically insignificant. Projection provides a baseline for evaluating the real-time impact of an intervention. Sensitivity analysis was conducted because of considerable variance in parameter estimates across studies. Although the HI-STR predicts that increasing symptomatic ratio and inherently immune ratio reduce R0, relative to the uncertainty in the estimates of R0 for the ancestral SARS-CoV2, the projection is insensitive to the inherently immune ratio and the symptomatic ratio.

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“…In India, more than 34 million cases with around half a million deaths were reported in this period ( Coronavirus Disease [COVID‐19], n.d .). Viruses (especially RNA viruses) constantly change through mutations (Bessière & Volmer, 2021 ); a variant has one or more mutations that differentiate it from others in circulation. Owing to the great efforts of many researchers worldwide who are generating and sharing virus whole‐genome sequences publicly, multiple variants of SARS‐CoV‐2 have been documented globally throughout this pandemic.…”

Section: Introductionmentioning

confidence: 99%

SARS‐CoV‐2 variants and spike mutations involved in second wave of COVID‐19 pandemic in India

Muttineni

Binitha²,

Putty

et al. 2022

Transbounding Emerging Dis

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Against the backdrop of the second wave of COVID‐19 pandemic in India that started in March 2021, we have monitored the spike (S) protein mutations in all the reported (GISAID portal) whole‐genome sequences of SARS‐CoV‐2 circulating in India from 1 January 2021 to 31 August 2021. In the 43,102 SARS‐CoV‐2 genomic sequences analysed, we have identified 24,260 amino acid mutations in the S protein, based on which 265 Pango lineages could be categorized. The dominant lineage in most of the 28 states of India and its 8 union territories was B.1.617.2 (the delta variant). However, the states Madhya Pradesh, Jammu & Kashmir, and Punjab had B.1.1.7 (alpha variant) as the major lineage, while the Himachal Pradesh state reported B.1.36 as the dominating lineage. A detailed analysis of various domains of S protein was carried out for detecting mutations having a prevalence of >1%; 70, 18, 7, 3, 9, 4, and 1 ( N = 112) such mutations were observed in the N‐terminal domain, receptor binding domain, C ‐terminal domain, fusion peptide region, heptapeptide repeat (HR)‐1 domains, signal peptide domain, and transmembrane region, respectively. However, no mutations were recorded in the HR‐2 and cytoplasmic domains of the S protein. Interestingly, 13.39% ( N = 15) of these mutations were reported to increase the infectivity and pathogenicity of the virus; 2% ( N = 3) were known to be vaccine breakthrough mutations, and 0.89% ( N = 1) were known to escape neutralizing antibodies. The biological significance of 82% ( N = 92) of the reported mutations is yet unknown. As SARS‐CoV‐2 variants are emerging rapidly, it is critical to continuously monitor local viral mutations to understand national trends of virus circulation. This can tremendously help in designing better preventive regimens in the country, and avoid vaccine breakthrough infections.

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From one to many: The within-host rise of viral variants

Cited by 12 publications

References 19 publications

Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens

Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens

Basic reproduction number projection for novel pandemics and variants. Ancestral SARS-CoV2 R0 projection

SARS‐CoV‐2 variants and spike mutations involved in second wave of COVID‐19 pandemic in India

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