SARS-CoV-2 Amino Acid Mutations Detection in Greek Patients Infected in the First Wave of the Pandemic

Vassilaki, Niki; Papadimitriou, Konstantinos; Ioannidis, Anastassios; Παπανδρεου, Νικολαοσ; Milona, Raphaela S.; Iconomidou, Vassiliki A.; Chatzipanagiotou, Stylianos

doi:10.3390/microorganisms10071430

Cited by 3 publications

(2 citation statements)

References 133 publications

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“…These mutations include D155Y, G172V, G196V, G224C, G251V, H93Y, L106F, L108F, L140F, L94P, P104S, P42S Q185H, Q57H, T151I, T223I, T229I, T32I, T9K and G172C. Substituting some of these mutations leads to the loss of a putative epitope associated with B-cells 74 . Consequently, this loss of recognition and neutralization ability by B-cells may provide a pathway for the spread of the virus.…”

Section: Orf3amentioning

confidence: 99%

Bridging Computational Predictions and Empirical Data: Insights into SARS-CoV-2 Mutational Impacts and Evolution

Shaukat,

Nguyen,

Hsu

et al. 2024

Preprint

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The emergence of SARS-CoV-2 has unleashed a global health crisis, demanding advanced research into its genomic mutations and their consequences. Our study combines computational models and empirical validation to predict the effects of these mutations, aiming to understand their impact on the virus's behaviour, including its transmissibility and immune escape mechanisms. Utilising advanced prediction tools, we analysed mutations across the virus's genome, focusing on changes to both structural and non-structural proteins. This approach identified key mutations likely to influence protein functionality and the virus's evolution. Our findings, integrating computational predictions with real-world data, offer insights into SARS-CoV-2's evolutionary path and its implications for developing vaccines and therapies. We highlight the necessity of ongoing genomic surveillance and the combined use of computational and empirical methods to stay ahead of viral mutations. This study not only deepens our understanding of SARS-CoV-2 but also lays groundwork for future research on viral evolution and pandemic response strategies, emphasizing our approach's potential to inform public health decisions and research priorities.

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Section: Orf3amentioning

confidence: 99%

Bridging Computational Predictions and Empirical Data: Insights into SARS-CoV-2 Mutational Impacts and Evolution

Shaukat,

Nguyen,

Hsu

et al. 2024

Preprint

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“…Refs. [ 10 , 29 , 36 , 70 , 85 , 86 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 ] are cited in Supplementary Materials file.…”

mentioning

confidence: 99%

Progressive Evolutionary Dynamics of Gene-Specific ω Led to the Emergence of Novel SARS-CoV-2 Strains Having Super-Infectivity and Virulence with Vaccine Neutralization

Maiti

2024

IJMS

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An estimation of the proportion of nonsynonymous to synonymous mutation (dn/ds, ω) of the SARS-CoV-2 genome would indicate the evolutionary dynamics necessary to evolve into novel strains with increased infection, virulence, and vaccine neutralization. A temporal estimation of ω of the whole genome, and all twenty-nine SARS-CoV-2 genes of major virulent strains of alpha, delta and omicron demonstrates that the SARS-CoV-2 genome originally emerged (ω ~ 0.04) with a strong purifying selection (ω < 1) and reached (ω ~ 0.85) in omicron towards diversifying selection (ω > 1). A marked increase in the ω occurred in the spike gene from alpha (ω = 0.2) to omicron (ω = 1.97). The ω of the replication machinery genes including RDRP, NSP3, NSP4, NSP7, NSP8, NSP10, NSP13, NSP14, and ORF9 are markedly increased, indicating that these genes/proteins are yet to be evolutionary stabilized and are contributing to the evolution of novel virulent strains. The delta-specific maximum increase in ω in the immunomodulatory genes of NSP8, NSP10, NSP16, ORF4, ORF5, ORF6, ORF7A, and ORF8 compared to alpha or omicron indicates delta-specific vulnerabilities for severe COVID-19 related hospitalization and death. The maximum values of ω are observed for spike (S), NSP4, ORF8 and NSP15, which indicates that the gene-specific temporal estimation of ω identifies specific genes for its super-infectivity and virulency that could be targeted for drug development.

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Substitutions in the nonactive site of the passenger domain on the activity of Haemophilus influenzae immunoglobulin A1 protease

Chen,

2024

Infect Immun

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Immunoglobulin A1 (IgA1) protease is a critical virulence factor of Haemophilus influenzae that facilitates bacterial mucosal infection. This study investigates the effect of iga gene polymorphism on the enzymatic activity of H. influenzae IgA1 protease. The IgA1 protease activity was examined in the H. influenzae Rd KW20 strain and 51 isolates. Genetic variations in iga and deduced amino acid substitutions affecting IgA1 protease activity were assessed. Machine learning tools and functional complementation assays were used to analyze the effects of identified substitutions on the stability and activity of IgA1 protease, respectively. All 51 isolates exhibited similar iga expression levels. No igaB expression was detected. According to comparisons with the reference Rd KW20 strain, four substitutions in the protease domain, 26 in the nonprotease passenger domain, and two in the β-barrel domain were associated with the change in IgA1 protease activity. No substitutions in the catalytic site of IgA1 protease were observed. Logistic regression, receiver operating characteristic curves, Venn diagrams, and protein stability analyses revealed that the substitutions Asn352Lys, Pro353Ala, Lys356Asn, Gln916Lys, and Gly917Ser, which were located in the nonactive site of the passenger domain, were associated with decreases in IgA1 protease activity and stability, whereas Asn914Lys was associated with an increase in these events. Functional complementation assays revealed that the Asn914Lys substitution increased IgA1 protease activity in the Rd KW20 strain. This study identified substitutions in the nonactive site of the passenger domain that affect both the activity and stability of H. influenzae IgA1 protease.

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SARS-CoV-2 Amino Acid Mutations Detection in Greek Patients Infected in the First Wave of the Pandemic

Cited by 3 publications

References 133 publications

Bridging Computational Predictions and Empirical Data: Insights into SARS-CoV-2 Mutational Impacts and Evolution

Bridging Computational Predictions and Empirical Data: Insights into SARS-CoV-2 Mutational Impacts and Evolution

Progressive Evolutionary Dynamics of Gene-Specific ω Led to the Emergence of Novel SARS-CoV-2 Strains Having Super-Infectivity and Virulence with Vaccine Neutralization

Substitutions in the nonactive site of the passenger domain on the activity of Haemophilus influenzae immunoglobulin A1 protease

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