SARS-CoV-2: An Overview of the Genetic Profile and Vaccine Effectiveness of the Five Variants of Concern

Dumache, Raluca; Enache, Alexandra; Macaşoi, Ioana; Dehelean, Cristina; Dumitrașcu, Victor; Mihailescu, Alexandra; Popescu, Roxana; Vlad, Daliborca; Vlad, Cristian Sebastian; Muresan, Camelia

doi:10.3390/pathogens11050516

Cited by 11 publications

(6 citation statements)

References 166 publications

(189 reference statements)

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“…When compared to the wild-type strain, these variants are generally associated with an increase in infectiousness, a greater virulence or disease presentation, or a decrease in the effectiveness of diagnostics, vaccines, and therapeutics [ 3 ]. The first notable mutation was a single spike substitution, the D614G mutation, that was first identified in January 2020 and is now present in all SARS-CoV-2 VOCs [ 4 ]. This early mutation type has been recognized to significantly generate a variant with more functional S protein and increase virus infectivity compared to wild-type [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Infection kinetics, syncytia formation, and inflammatory biomarkers as predictive indicators for the pathogenicity of SARS-CoV-2 Variants of Concern in Calu-3 cells

Purwono,

Vacharathit,

Manopwisedjaroen

et al. 2024

PLoS ONE

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The ongoing COVID-19 pandemic has led to the emergence of new SARS-CoV-2 variants as a result of continued host-virus interaction and viral genome mutations. These variants have been associated with varying levels of transmissibility and disease severity. We investigated the phenotypic profiles of six SARS-CoV-2 variants (WT, D614G, Alpha, Beta, Delta, and Omicron) in Calu-3 cells, a human lung epithelial cell line. In our model demonstrated that all variants, except for Omicron, had higher efficiency in virus entry compared to the wild-type. The Delta variant had the greatest phenotypic advantage in terms of early infection kinetics and marked syncytia formation, which could facilitate cell-to-cell spreading, while the Omicron variant displayed slower replication and fewer syncytia formation. We also identified the Delta variant as the strongest inducer of inflammatory biomarkers, including pro-inflammatory cytokines/chemokines (IP-10/CXCL10, TNF-α, and IL-6), anti-inflammatory cytokine (IL-1RA), and growth factors (FGF-2 and VEGF-A), while these inflammatory mediators were not significantly elevated with Omicron infection. These findings are consistent with the observations that there was a generally more pronounced inflammatory response and angiogenesis activity within the lungs of COVID-19 patients as well as more severe symptoms and higher mortality rate during the Delta wave, as compared to less severe symptoms and lower mortality observed during the current Omicron wave in Thailand. Our findings suggest that early infectivity kinetics, enhanced syncytia formation, and specific inflammatory mediator production may serve as predictive indicators for the virulence potential of future SARS-CoV-2 variants.

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Section: Introductionmentioning

confidence: 99%

Infection kinetics, syncytia formation, and inflammatory biomarkers as predictive indicators for the pathogenicity of SARS-CoV-2 Variants of Concern in Calu-3 cells

Purwono,

Vacharathit,

Manopwisedjaroen

et al. 2024

PLoS ONE

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“…The emerging SARS-CoV-2 variants are classified into five groups such as variants of concern (VOC), VOC lineages under monitoring (VOC-LUM); variants of interest (VOI); variants under monitoring (VUM) and formerly monitored variants (FMV) by World Health Organization (WHO) [ 8 ]. The five variants of concern (VOC) of SARS-CoV-2 namely Alpha B.1.1.7, Beta B.1.351, Gamma P.1, Delta B.1.617.2, and Omicron B.1.1.529 lead to an understanding of the impacts of variants such as transmissibility, risk of reinfection, disease severity and impacts on vaccine and diagnostics performance [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Mosaic Recombination Inflicted Various SARS-CoV-2 Lineages to Emerge into Novel Virus Variants: a Review Update

et al. 2022

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Human Coronaviruses (hCoVs) belongs to the enormous and dissimilar family of positive-sense, non-segmented, single-stranded RNA viruses. The RNA viruses are prone to high rates of mutational recombination resulting in emergence of evolutionary variant to alter various features including transmissibility and severity. The evolutionary changes affect the immune escape and reduce effectiveness of diagnostic and therapeutic measures by becoming undetectable by the currently available diagnostics and refractory to therapeutics and vaccines. Whole genome sequencing studies from various countries have adequately reported mosaic recombination between different lineage strain of SARS-CoV-2 whereby RNA dependent RNA polymerase (RdRp) gene reconnects with a homologous RNA strand at diverse position. This all lead to evolutionary emergence of new variant/ lineage as evident with the emergence of XBB in India at the time of writing this review. The continuous periodical genomic surveillance is utmost required for understanding the various lineages involved in recombination to emerge into hybrid variant. This may further help in assessing virus transmission dynamics, virulence and severity factor to help health authorities take appropriate timely action for prevention and control of any future COVID-19 outbreak.

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“…Research indicated that distinct SARS-CoV-2 lineages could play a pivotal role in developing drugs and designing vaccines by altering pathogenesis in infected hosts or virus tropism [14,15]. Therefore, the rapid identification of SARS-CoV-2 lineages, associated with different medical conditions and symptoms, has assisted in the long-term surveillance of this pathogen and is of utmost importance for updating SARS-CoV-2 vaccines [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Towards Efficient and Accurate SARS-CoV-2 Genome Sequence Typing Based on Supervised Learning Approaches

Miao

Clercq

2022

Microorganisms

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Despite the active development of SARS-CoV-2 surveillance methods (e.g., Nextstrain, GISAID, Pangolin), the global emergence of various SARS-CoV-2 viral lineages that potentially cause antiviral and vaccine failure has driven the need for accurate and efficient SARS-CoV-2 genome sequence classifiers. This study presents an optimized method that accurately identifies the viral lineages of SARS-CoV-2 genome sequences using existing schemes. For Nextstrain and GISAID clades, a template matching-based method is proposed to quantify the differences between viral clades and to play an important role in classification evaluation. Furthermore, to improve the typing accuracy of SARS-CoV-2 genome sequences, an ensemble model that integrates a combination of machine learning-based methods (such as Random Forest and Catboost) with optimized weights is proposed for Nextstrain, Pangolin, and GISAID clades. Cross-validation is applied to optimize the parameters of the machine learning-based method and the weight settings of the ensemble model. To improve the efficiency of the model, in addition to the one-hot encoding method, we have proposed a nucleotide site mutation-based data structure that requires less computational resources and performs better in SARS-CoV-2 genome sequence typing. Based on an accumulated database of >1 million SARS-CoV-2 genome sequences, performance evaluations show that the proposed system has a typing accuracy of 99.879%, 97.732%, and 96.291% for Nextstrain, Pangolin, and GISAID clades, respectively. A single prediction only takes an average of <20 ms on a portable laptop. Overall, this study provides an efficient and accurate SARS-CoV-2 genome sequence typing system that benefits current and future surveillance of SARS-CoV-2 variants.

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SARS-CoV-2: An Overview of the Genetic Profile and Vaccine Effectiveness of the Five Variants of Concern

Cited by 11 publications

References 166 publications

Infection kinetics, syncytia formation, and inflammatory biomarkers as predictive indicators for the pathogenicity of SARS-CoV-2 Variants of Concern in Calu-3 cells

Infection kinetics, syncytia formation, and inflammatory biomarkers as predictive indicators for the pathogenicity of SARS-CoV-2 Variants of Concern in Calu-3 cells

Mosaic Recombination Inflicted Various SARS-CoV-2 Lineages to Emerge into Novel Virus Variants: a Review Update

Towards Efficient and Accurate SARS-CoV-2 Genome Sequence Typing Based on Supervised Learning Approaches

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