Different mutations in SARS-CoV-2 associate with severe and mild outcome

Prediction models for COVID-19 disease outcomes

SARS-CoV-2 has caused over 6.9 million deaths and continues to produce lasting health consequences. COVID-19 manifests broadly from no symptoms to death. In a retrospective cross-sectional study, we developed personalized risk assessment models that predict clinical outcomes for individuals with COVID-19 and inform targeted interventions. We sequenced viruses from SARS-CoV-2-positive nasopharyngeal swab samples between July 2020 and July 2022 from 4450 individuals in Missouri and retrieved associated disease courses, clinical history, and urban-rural classification. We integrated this data to develop machine learning-based predictive models to predict hospitalization, ICU admission, and long COVID.The mean age was 38.3 years (standard deviation = 21.4) with 55.2% (N = 2453) females and 44.8% (N = 1994) males (not reported, N = 4). Our analyses revealed a comprehensive set of predictors for each outcome, encompassing human, environment, and virus genome-wide genetic markers. Immunosuppression, cardiovascular disease, older age, cardiac, gastrointestinal, and constitutional symptoms, rural residence, and specific amino acid substitutions were associated with hospitalization. ICU admission was associated with acute respiratory distress syndrome, ventilation, bacterial co-infection, rural residence, and non-wild type SARS-CoV-2 variants. Finally, long COVID was associated with hospital admission, ventilation, and female sex.Overall, we developed risk assessment models that offer the capability to identify patients with COVID-19 necessitating enhanced monitoring or early interventions. Of importance, we demonstrate the value of including key elements of virus, host, and environmental factors to predict patient outcomes, serving as a valuable platform in the field of personalized medicine with the potential for adaptation to other infectious diseases.

A method of identifying the high-risk mutations of sudden cardiac death at KCNQ1 and KCNH2 genes

Sudden Cardiac Death (SCD) often shows negative anatomy results after a systemic autopsy and the gene mutations of potassium channel play a key role in the etiology of SCD. We established a feasible system to detect SCD-related mutations and investigated the mutations at KCNQ1 and KCNH2 genes in the Chinese population. We established a mutation detection system combined with multiplex PCR, SNaPshot technique, and capillary electrophoresis. We genotyped 101 putative mutations at KCNQ1 and KCNH2 genes in 60 SCD of negative anatomy and 50 controls using the established assay and compared Odd Ratio (OR). Four coding variants were identified in the KCNQ1 gene: S546S, I145I, P448R, and G643S. The mutations of I145I and S546S did not differ significantly in the SCD compared with controls. 21 SCD individuals (35 %) and 1 control individual (2 %) showed a genotype of C/G at P448R (OR = 17.5, 95 % CI [2.40-127.82]). 24 SCD individuals (40 %) and 1 control individual (2 %) showed a genotype of C/G at G643S (OR = 20.0, 95 % CI [2.75-145.25]). We established a robust assay for rapid screening the putative SCD-related mutations in KCNQ1 and KCNH2 genes. The new assay in our study is easily amenable to the majority of laboratories without the need for new specialized equipment. Our method will meet the increasing requirement of mutation screening for SCD in regular DNA laboratories and will help screen mutations in those dead of SCD and their relatives.

Associations between epidemiological and laboratory parameters and disease severity in hospitalized patients with COVID-19 during first and second epidemic waves in middle south Mato Grosso

BACKGROUND

COVID-19 is a multisystemic disease characterized by respiratory distress. Disease severity is associated with several factors. Here we characterize virological findings and evaluate the association of laboratorial, epidemiological, virological findings and clinical outcomes of 251 patients during the first and second epidemic waves of COVID-19.

METHODS

This transversal study used biological samples and data from patients hospitalized with COVID-19 between May 2020 and August 2021 in the metropolitan region of Cuiabá, Mato Grosso Brazil. Biological samples were subjected to RT-qPCR and MinION sequencing. Univariate and multivariate logistic regression and Odds ratio were used to correlate clinical, laboratorial, epidemiological data.

FINDINGS

Patients were represented by males (61.7%) with mean age of 52.4 years, mild to moderate disease (49,0%), overweight/obese (69.3%), with comorbidities (66.1%) and evolving to death (55.38%). Severe cases showing symptoms for prolonged time, ≥ 25% of ground-glass opacities in the lungs and fatality rate increased significantly in second wave. Fatality was statistically associated to > 61 years of age,>25% ground-glass opacities in the lungs, immune, cardiac, or metabolic comorbidities. Higher viral load (p < 0.01/p = 0.02 in each wave), decreased erythrocyte (p < 0.01), hemoglobin (p < 0.05/p < 0.01), hematocrit (p < 0.01), RDW (p < 0.01), lymphocyte (p < 0.01), increased leucocyte (p < 0.01), neutrophil (p < 0.01) and CRP levels (p < 0.01) showed significant association with fatality in both waves, as did Neutrophil/Platelet (NPR; p < 0.01), Neutrophil/Lymphocyte (NLR; p < 0.01) and Monocyte/Lymphocyte ratio (MLR; p < 0.01). SARS-CoV-2 genomes from lineage B.1.1.33(n = 8) and Gamma/P.1(n = 15) shared 6/7 and 20/23 lineage-defining mutations, respectively.

MAIN CONCLUSIONS

Severity and mortality of COVID-19 associated with a panel of epidemiological and laboratorial findings, being second wave, caused by Gamma variant, more severe in this in-hospital population.

NSP6 inhibits the production of ACE2-containing exosomes to promote SARS-CoV-2 infectivity

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered a global pandemic, which severely endangers public health. Our and others' works have shown that the angiotensin-converting enzyme 2 (ACE2)-containing exosomes (ACE2-exos) have superior antiviral efficacies, especially in response to emerging variants. However, the mechanisms of how the virus counteracts the host and regulates ACE2-exos remain unclear. Here, we identified that SARS-CoV-2 nonstructural protein 6 (NSP6) inhibits the production of ACE2-exos by affecting the protein level of ACE2 as well as tetraspanin-CD63 which is a key factor for exosome biogenesis. We further found that the protein stability of CD63 and ACE2 is maintained by the deubiquitination of proteasome 26S subunit, non-ATPase 12 (PSMD12). NSP6 interacts with PSMD12 and counteracts its function, consequently promoting the degradation of CD63 and ACE2. As a result, NSP6 diminishes the antiviral efficacy of ACE2-exos and facilitates the virus to infect healthy bystander cells. Overall, our study provides a valuable target for the discovery of promising drugs for the treatment of coronavirus disease 2019.

IMPORTANCE

The outbreak of coronavirus disease 2019 (COVID-19) severely endangers global public health. The efficacy of vaccines and antibodies declined with the rapid emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutants. Angiotensin-converting enzyme 2-containing exosomes (ACE2-exos) therapy exhibits a broad neutralizing activity, which could be used against various viral mutations. Our study here revealed that SARS-CoV-2 nonstructural protein 6 inhibited the production of ACE2-exos, thereby promoting viral infection to the adjacent bystander cells. The identification of a new target for blocking SARS-CoV-2 depends on fully understanding the virus-host interaction networks. Our study sheds light on the mechanism by which the virus resists the host exosome defenses, which would facilitate the study and design of ACE2-exos-based therapeutics for COVID-19.

SARS-CoV-2 ORF8 as a Modulator of Cytokine Induction: Evidence and Search for Molecular Mechanisms

Severe cases of SARS-CoV-2 infection are characterized by an immune response that leads to the overproduction of pro-inflammatory cytokines, resulting in lung damage, cardiovascular symptoms, hematologic symptoms, acute kidney injury and multiple organ failure that can lead to death. This remarkable increase in cytokines and other inflammatory molecules is primarily caused by viral proteins, and particular interest has been given to ORF8, a unique accessory protein specific to SARS-CoV-2. Despite plenty of research, the precise mechanisms by which ORF8 induces proinflammatory cytokines are not clear. Our investigations demonstrated that ORF8 augments production of IL-6 induced by Poly(I:C) in human embryonic kidney (HEK)-293 and monocyte-derived dendritic cells (mono-DCs). We discuss our findings and the multifaceted roles of ORF8 as a modulator of cytokine response, focusing on type I interferon and IL-6, a key component of the immune response to SARS-CoV-2. In addition, we explore the hypothesis that ORF8 may act through pattern recognition receptors of dsRNA such as TLRs.

Endoplasmic reticulum-associated SARS-CoV-2 ORF3a elicits heightened cytopathic effects despite robust ER-associated degradation

IMPORTANCE

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has tragically claimed millions of lives through coronavirus disease 2019 (COVID-19), and there remains a critical gap in our understanding of the precise molecular mechanisms responsible for the associated fatality. One key viral factor of interest is the SARS-CoV-2 ORF3a protein, which has been identified as a potent inducer of host cellular proinflammatory responses capable of triggering the catastrophic cytokine storm, a primary contributor to COVID-19-related deaths. Moreover, ORF3a, much like the spike protein, exhibits a propensity for frequent mutations, with certain variants linked to the severity of COVID-19. Our previous research unveiled two distinct types of ORF3a mutant proteins, categorized by their subcellular localizations, setting the stage for a comparative investigation into the functional and mechanistic disparities between these two types of ORF3a variants. Given the clinical significance and functional implications of the natural ORF3a mutations, the findings of this study promise to provide invaluable insights into the potential roles undertaken by these mutant ORF3a proteins in the pathogenesis of COVID-19.

SARS-CoV-2 ORF3a Protein as a Therapeutic Target against COVID-19 and Long-Term Post-Infection Effects

The COVID-19 pandemic caused by SARS-CoV-2 has posed unparalleled challenges due to its rapid transmission, ability to mutate, high mortality and morbidity, and enduring health complications. Vaccines have exhibited effectiveness, but their efficacy diminishes over time while new variants continue to emerge. Antiviral medications offer a viable alternative, but their success has been inconsistent. Therefore, there remains an ongoing need to identify innovative antiviral drugs for treating COVID-19 and its post-infection complications. The ORF3a (open reading frame 3a) protein found in SARS-CoV-2, represents a promising target for antiviral treatment due to its multifaceted role in viral pathogenesis, cytokine storms, disease severity, and mortality. ORF3a contributes significantly to viral pathogenesis by facilitating viral assembly and release, essential processes in the viral life cycle, while also suppressing the body's antiviral responses, thus aiding viral replication. ORF3a also has been implicated in triggering excessive inflammation, characterized by NF-κB-mediated cytokine production, ultimately leading to apoptotic cell death and tissue damage in the lungs, kidneys, and the central nervous system. Additionally, ORF3a triggers the activation of the NLRP3 inflammasome, inciting a cytokine storm, which is a major contributor to the severity of the disease and subsequent mortality. As with the spike protein, ORF3a also undergoes mutations, and certain mutant variants correlate with heightened disease severity in COVID-19. These mutations may influence viral replication and host cellular inflammatory responses. While establishing a direct link between ORF3a and mortality is difficult, its involvement in promoting inflammation and exacerbating disease severity likely contributes to higher mortality rates in severe COVID-19 cases. This review offers a comprehensive and detailed exploration of ORF3a's potential as an innovative antiviral drug target. Additionally, we outline potential strategies for discovering and developing ORF3a inhibitor drugs to counteract its harmful effects, alleviate tissue damage, and reduce the severity of COVID-19 and its lingering complications.

Mutational analysis of SARS-CoV-2 ORF6-KPNA2 binding interface and identification of potent small molecule inhibitors to recuse the host immune system

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surfaced on 31 December, 2019, and was identified as the causative agent of the global COVID-19 pandemic, leading to a pneumonia-like disease. One of its accessory proteins, ORF6, has been found to play a critical role in immune evasion by interacting with KPNA2 to antagonize IFN signaling and production pathways, resulting in the inhibition of IRF3 and STAT1 nuclear translocation. Since various mutations have been observed in ORF6, therefore, a comparative binding, biophysical, and structural analysis was used to reveal how these mutations affect the virus's ability to evade the human immune system. Among the identified mutations, the V9F, V24A, W27L, and I33T, were found to have a highly destabilizing effect on the protein structure of ORF6. Additionally, the molecular docking analysis of wildtype and mutant ORF6 and KPNA2 revealed the docking score of - 53.72 kcal/mol for wildtype while, -267.90 kcal/mol, -258.41kcal/mol, -254.51 kcal/mol and -268.79 kcal/mol for V9F, V24A, W27L, and I33T respectively. As compared to the wildtype the V9F showed a stronger binding affinity with KPNA2 which is further verified by the binding free energy (-42.28 kcal/mol) calculation. Furthermore, to halt the binding interface of the ORF6-KPNA2 complex, we used a computational molecular search of potential natural products. A multi-step virtual screening of the African natural database identified the top 5 compounds with best docking scores of -6.40 kcal/mol, -6.10 kcal/mol, -6.09 kcal/mol, -6.06 kcal/mol, and -6.03 kcal/mol for tophit1-5 respectively. Subsequent all-atoms simulations of these top hits revealed consistent dynamics, indicating their stability and their potential to interact effectively with the interface residues. In conclusion, our study represents the first attempt to establish a foundation for understanding the heightened infectivity of new SARS-CoV-2 variants and provides a strong impetus for the development of novel drugs against them.

Overview of Nucleocapsid-Targeting Vaccines against COVID-19

The new SARS-CoV-2 coronavirus, which emerged in late 2019, is a highly variable causative agent of COVID-19, a contagious respiratory disease with potentially severe complications. Vaccination is considered the most effective measure to prevent the spread and complications of this infection. Spike (S) protein-based vaccines were very successful in preventing COVID-19 caused by the ancestral SARS-CoV-2 strain; however, their efficacy was significantly reduced when coronavirus variants antigenically different from the original strain emerged in circulation. This is due to the high variability of this major viral antigen caused by escape from the immunity caused by the infection or vaccination with spike-targeting vaccines. The nucleocapsid protein (N) is a much more conserved SARS-CoV-2 antigen than the spike protein and has therefore attracted the attention of scientists as a promising target for broad-spectrum vaccine development. Here, we summarized the current data on various N-based COVID-19 vaccines that have been tested in animal challenge models or clinical trials. Despite the high conservatism of the N protein, escape mutations gradually occurring in the N sequence can affect its protective properties. During the three years of the pandemic, at least 12 mutations have arisen in the N sequence, affecting more than 40 known immunogenic T-cell epitopes, so the antigenicity of the N protein of recent SARS-CoV-2 variants may be altered. This fact should be taken into account as a limitation in the development of cross-reactive vaccines based on N-protein.

Insights into the evolution of mutations in SARS-CoV-2 non-spike proteins

The COVID-19 pandemic has been driven by the emergence of SARS-CoV-2 variants with mutations across all the viral proteins. Although mutations in the spike protein have received significant attention, understanding the prevalence and potential impact of mutations in other viral proteins is essential for comprehending the evolution of SARS-CoV-2. Here, we conducted a comprehensive analysis of approximately 14 million sequences of SARS-CoV-2 deposited in the GISAID database until December 2022 to identify prevalent mutations in the non-spike proteins at the global and country levels. Additionally, we evaluated the energetics of each mutation to better understand their impact on protein stability. While the consequences of many mutations remain unclear, we discuss potential structural and functional significance of some mutations. Our study highlights the ongoing evolutionary process of SARS-CoV-2 and underscores the importance of understanding changes in non-spike proteins.

An overview of SARS-CoV-2 variants circulating in the 2020-2022 period in Lombardy

Since the beginning of the pandemic, SARS-CoV-2 has shown genetic variability. All the variants that have sustained pandemic waves have shown several mutations, especially in the Spike protein that could affect viral pathogenesis. A total of 15,729 respiratory samples, collected between December 2020 and August 2022, have been included in this study. We report the circulation of SARS-CoV-2 variants in the Lombardy region, Italy, in a 2-year study period. Alpha, Delta, and Omicron variants became predominant causing the majority of cases whereas Beta or Gamma variants mostly caused local outbreaks. Next-generation sequencing revealed several mutations and few deletions in all of the main variants. For example, 147 mutations were observed in the Spike protein of Omicron sublineages; 20% of these mutations occurred in the receptor-binding domain region.

Public Health Response Measures for COVID-19 in Kazakhstan

The article describes measures developed to counter the spread of coronavirus infection in the Republic of Kazakhstan. The first cases of coronavirus disease 2019 (COVID-19) in Kazakhstan were detected on March 13, 2020, among people who arrived from Germany. After declaring the state of emergency in the country, the Ministry of Healthcare of the Republic of Kazakhstan began to formulate and implement a comprehensive package of measures aimed at slowing down and stopping the transmission of infection, preventing outbreaks, ensuring optimal care for all patients, especially the seriously ill, minimizing the negative impact of the pandemic on health systems, social services, and economic activities. Developed set of restrictive measures was approved by the Country Office of Word Health Organization (WHO) in Kazakhstan, being later adapted by the European Union (EU) countries and applied in Kyrgyzstan. In addition, article identifies Kazakhstan's experience in creating epidemiological surveillance systems, studying virus mutations, and the clinical aspects of dealing with it to combat the infection. It also indicates the impact of the epidemic on health-care workers and the development of measures to protect them, strengthening infection prevention, and control in medical organizations.

Epidemiological and Genomic Analysis of Asymptomatic SARS-CoV-2 Infections during the Delta and Omicron Epidemic Waves in São Paulo City, Brazil

We examined the asymptomatic rates of SARS-CoV-2 infection during the Delta and Omicron waves in the city of São Paulo. Nasopharyngeal swabs were collected at strategic points of the city (open-air markets, bus terminals, airports) for SARS-CoV-2 RNA testing. Applying the questionnaire, the symptomatic individuals were excluded, and only asymptomatic cases were analyzed. During the Delta wave, a total of 4315 samples were collected, whereas 2372 samples were collected during the first Omicron wave. The incidence of the asymptomatic SARS-CoV-2 infection was 0.6% during the Delta wave and 0.8% during the Omicron wave. No statistical differences were found in the threshold amplification cycle. However, there was a statistical difference observed in the sublineage distribution between asymptomatic and symptomatic individuals. Our study determined the incidence of asymptomatic infection by monitoring individuals who remained symptom-free, thereby providing a reliable evaluation of asymptomatic SARS-CoV-2 carriage. Our findings reveal a relatively low proportion of asymptomatic cases, which could be attributed to our rigorous monitoring protocol for the presence of clinical symptoms. Investigating asymptomatic infection rates is crucial to develop and implement effective disease control strategies.

Surveillance of SARS-CoV-2 immunogenicity: loss of immunodominant HLA-A*02-restricted epitopes that activate CD8+ T cells

Introduction and methods

In this present work, coronavirus subfamilies and SARS-CoV-2 Variants of Concern (VOCs) were investigated for the presence of MHC-I immunodominant viral peptides using in silico and in vitro tools.

Results

In our results, HLA-A*02 haplotype showed the highest number of immunodominant epitopes but with the lowest combined prediction score. Furthermore, a decrease in combined prediction score was observed for HLA-A*02-restricted epitopes when the original strain was compared to the VOCs, indicating that the mutations on the VOCs are promoting escape from HLA-A2-mediated antigen presentation, which characterizes a immune evasion process. Additionally, epitope signature analysis revealed major immunogenic peptide loss for structural (S) and non-structural (ORF8) proteins of VOCs in comparison to the Wuhan sequence.

Discussion

These results may indicate that the antiviral CD8+ T-cell responses generated by original strains could not be sufficient for clearance of variants in either newly or reinfection with SARS-CoV-2. In contrast, N epitopes remain the most conserved and reactive peptides across SARS-CoV-2 VOCs. Overall, our data could contribute to the rational design and development of new vaccinal platforms to induce a broad cellular CD8+ T cell antiviral response, aiming at controlling viral transmission of future SARS-CoV-2 variants.

A novel mutation-proof, next-generation vaccine to fight against upcoming SARS-CoV-2 variants and subvariants, designed through AI enabled approaches and tools, along with the machine learning based immune simulation: A vaccine breakthrough

Emerging SARS-CoV-2 variants and subvariants are great concerns for their significant mutations, which are also responsible for vaccine escape. Therefore, the study was undertaken to develop a mutation-proof, next-generation vaccine to protect against all upcoming SARS-CoV-2 variants. We used advanced computational and bioinformatics approaches to develop a multi-epitopic vaccine, especially the AI model for mutation selection and machine learning (ML) strategies for immune simulation. AI-enabled and the top-ranked antigenic selection approaches were used to select nine mutations from 835 RBD mutations. We selected twelve common antigenic B cell and T cell epitopes (CTL and HTL) containing the nine RBD mutations and joined them with the adjuvants, PADRE sequence, and suitable linkers. The constructs' binding affinity was confirmed through docking with TLR4/MD2 complex and showed significant binding free energy (-96.67 kcal mol^-1) with positive binding affinity. Similarly, the calculated eigenvalue (2.428517e-05) from the NMA of the complex reveals proper molecular motion and superior residues' flexibility. Immune simulation shows that the candidate can induce a robust immune response. The designed mutation-proof, multi-epitopic vaccine could be a remarkable candidate for upcoming SARS-CoV-2 variants and subvariants. The study method might guide researchers in developing AI-ML and immunoinformatics-based vaccines for infectious disease.

Analysis of SARS-CoV-2 Spike Protein Variants with Recombinant Reporter Viruses Created from a Bacmid System

SARS-CoV-2, the causative agent of COVID-19, has spread around the world with more than 700 million cases and 6.8 million deaths. Various variants of concern (VoC) have emerged due to mutations and recombination and concurrent selection for increased viral fitness and immune evasion. The viral protein that primarily determines the pathogenicity, infectivity, and transmissibility is the Spike protein. To analyze the specific impact of variant Spike proteins on infection dynamics, we constructed SARS-CoV-2 with a uniform B.1 backbone but with alternative Spike proteins. In addition, ORF6 was replaced by EYFP as a biological safety measure, and for use of this well-established reporter. We show that namely the delta variant Spike proteins cause a distinct phenotype from the wild type (B.1, D614G) and other variants of concern. Furthermore, we demonstrate that the omicron BA.1 Spike results in lower viral loads and a less efficient spread in vitro. Finally, we utilized viruses with the two different reporters EYFP and mCherry to establish a competitive growth assay, demonstrating that most but not all Spike variant viruses were able to outcompete wild type SARS-CoV-2 B.1.

The multiple roles of nsp6 in the molecular pathogenesis of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve and adapt after its emergence in late 2019. As the causative agent of the coronavirus disease 2019 (COVID-19), the replication and pathogenesis of SARS-CoV-2 have been extensively studied by the research community for vaccine and therapeutics development. Given the importance of viral spike protein in viral infection/transmission and vaccine development, the scientific community has thus far primarily focused on studying the structure, function, and evolution of the spike protein. Other viral proteins are understudied. To fill in this knowledge gap, a few recent studies have identified nonstructural protein 6 (nsp6) as a major contributor to SARS-CoV-2 replication through the formation of replication organelles, antagonism of interferon type I (IFN-I) responses, and NLRP3 inflammasome activation (a major factor of severe disease in COVID-19 patients). Here, we review the most recent progress on the multiple roles of nsp6 in modulating SARS-CoV-2 replication and pathogenesis.

Mutations in SARS-CoV-2 variant nsp6 enhance type-I interferon antagonism

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve after its emergence. Given its importance in viral infection and vaccine development, mutations in the viral Spike gene have been studied extensively; however, the impact of mutations outside the Spike gene are poorly understood. Here, we report that a triple deletion (ΔSGF or ΔLSG) in nonstructural protein 6 (nsp6) independently acquired in Alpha and Omicron sublineages of SARS-CoV-2 augments nsp6-mediated antagonism of type-I interferon (IFN-I) signaling. Specifically, these triple deletions enhance the ability of mutant nsp6 to suppress phosphorylation of STAT1 and STAT2. A parental SARS-CoV-2 USA-WA1/2020 strain containing the nsp6 ΔSGF deletion (ΔSGF-WA1) shows reduced susceptibility to IFN-I treatment in vitro, outcompetes the parental strain in human primary airway cultures, and increases virulence in mice; however, the ΔSGF-WA1 virus is less virulent than the Alpha variant (which has the nsp6 ΔSGF deletion and additional mutations in other genes). Analyses of host responses from ΔSGF-WA1-infected mice and primary airway cultures reveal activation of pathways indicative of a cytokine storm. These results provide evidence that mutations outside the Spike protein affect virus-host interactions and may alter pathogenesis of SARS-CoV-2 variants in humans.

SARS-CoV-2 Variants by Whole-Genome Sequencing in a University Hospital in Bangkok: First to Third COVID-19 Waves

BACKGROUND

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants emerged globally during the recent coronavirus disease (COVID-19) pandemic. From April 2020 to April 2021, Thailand experienced three COVID-19 waves, and each wave was driven by different variants. Therefore, we aimed to analyze the genetic diversity of circulating SARS-CoV-2 using whole-genome sequencing analysis.

METHODS

A total of 33 SARS-CoV-2 positive samples from three consecutive COVID-19 waves were collected and sequenced by whole-genome sequencing, of which, 8, 10, and 15 samples were derived from the first, second, and third waves, respectively. The genetic diversity of variants in each wave and the correlation between mutations and disease severity were explored.

RESULTS

During the first wave, A.6, B, B.1, and B.1.375 were found to be predominant. The occurrence of mutations in these lineages was associated with low asymptomatic and mild symptoms, providing no transmission advantage and resulting in extinction after a few months of circulation. B.1.36.16, the predominant lineage of the second wave, caused more symptomatic COVID-19 cases and contained a small number of key mutations. This variant was replaced by the VOC alpha variant, which later became dominant in the third wave. We found that B.1.1.7 lineage-specific mutations were crucial for increasing transmissibility and infectivity, but not likely associated with disease severity. There were six additional mutations found only in severe COVID-19 patients, which might have altered the virus phenotype with an inclination toward more highly pathogenic SARS-CoV-2.

CONCLUSION

The findings of this study highlighted the importance of whole-genome analysis in tracking newly emerging variants, exploring the genetic determinants essential for transmissibility, infectivity, and pathogenicity, and helping better understand the evolutionary process in the adaptation of viruses in humans.

Clinical and Virological Features of SARS-CoV-2 Variants during the Four Waves of the Pandemic in the Mexican Southeast

We conducted a retrospective study using a population of patients who were hospitalized at Dr. Juan Graham Casasus Hospital in Villahermosa (Tabasco, Mexico) and had a positive RT-PCR test for SARS-CoV-2 between June 2020 and January 2022. We analyzed all medical records, including demographic data, SARS-CoV-2 exposure history, underlying comorbidities, symptoms, signs at admission, laboratory findings during the hospital stay, outcome, and whole-genome sequencing data. Finally, the data were analyzed in different sub-groups according to distribution during waves of the COVID-19 pandemic regarding Mexican reports from June 2020 to January 2022. Of the 200 patients who tested positive via PCR for SARS-CoV-2, only 197 had samples that could be sequenced. Of the samples, 58.9% (n = 116) were males and 41.1% (n = 81) females, with a median age of 61.7 ± 17.0 years. Comparisons between the waves of the pandemic revealed there were significant differences in the fourth wave: the age of patients was higher (p = 0.002); comorbidities such as obesity were lower (p = 0.000), while CKD was higher (p = 0.011); and hospital stays were shorter (p = 0.003). The SARS-CoV-2 sequences revealed the presence of 11 clades in the study population. Overall, we found that adult patients admitted to a third-level Mexican hospital had a wide range of clinical presentations. The current study provides evidence for the simultaneous circulation of SARS-CoV-2 variants during the four pandemic waves.

Sequence analysis of SARS-CoV-2 Delta variant isolated from Makassar, South Sulawesi, Indonesia

Introduction

This study aimed to perform mutation and phylogenetic analyses of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Delta variants and analyze the characteristic signs and symptoms of patients infected with SARS-CoV-2 Delta variant originated from Makassar during the Delta outbreak.Methods: We collected samples from patients who were infected with coronavirus disease 2019 (COVID-19) between June and October 2021. We selected the Quantitative Reverse Transcription-Polymerase Chain Reaction (PCR)-positive samples with a cycle threshold value of <30 for whole genome sequencing. Total viral ribonucleic acid (RNA) was isolated from 34 PCR-positive nasopharyngeal swab samples, and whole genome sequencing was performed using the Oxford Nanopore GridlON sequencer. Phylogenetic and maximum clade credibility analyses were performed using the Bayesian Markov chain Monte Carlo method.

Results

It was found that 33 patients were infected with the SARS-CoV-2 Delta variant in this cohort study, among whom 63.6% (21) patients were female. According to the clinical data, 24 (72.7%), 7 (21.2%), and 2 (6.1%) patients had mild, moderate, and severe COVID-19 infections. Phylogenetic analysis based on the spike and RNA-dependent RNA polymerase (RdRp) genes showed that the collected samples were clustered in the main lineage of B.1.617.2 (Delta variant). The Delta variants had a high frequency of distinct mutations in the spike protein region, including T19R (94.12%), L452R (88.23%), T478K (91.17%), D614G (97%), P681R (97%), and D950 N (97%). Other unique mutations found in a smaller frequency in our samples were present in the N-terminal domain, including A27T (2.94%) and A222V (14.70%), and in the receptor-binding domain, including Q414K (5.88%), G446V (2.94%), and T470 N (2.94%).

Conclusion

This study revealed the unique mutations in the S protein region of Delta variants. T19R, L452R, T478K/T478R, D614G, P681R, and D950 N were the most common substitutions in Makassar's Delta variant.

Human 14-3-3 Proteins Site-selectively Bind the Mutational Hotspot Region of SARS-CoV-2 Nucleoprotein Modulating its Phosphoregulation

Phosphorylation of SARS-CoV-2 nucleoprotein recruits human cytosolic 14-3-3 proteins playing a well-recognized role in replication of many viruses. Here we use genetic code expansion to demonstrate that 14-3-3 binding is triggered by phosphorylation of SARS-CoV-2 nucleoprotein at either of two pseudo-repeats centered at Ser197 and Thr205. According to fluorescence anisotropy measurements, the pT205-motif,presentin SARS-CoV-2 but not in SARS-CoV, is preferred over the pS197-motif by all seven human 14-3-3 isoforms, which collectively display an unforeseen pT205/pS197 peptide binding selectivity hierarchy. Crystal structures demonstrate that pS197 and pT205 are mutually exclusive 14-3-3-binding sites, whereas SAXS and biochemical data obtained on the full protein-protein complex indicate that 14-3-3 binding occludes the Ser/Arg-rich region of the nucleoprotein, inhibiting its dephosphorylation. This Ser/Arg-rich region is highly prone to mutations, as exemplified by the Omicron and Delta variants, with our data suggesting that the strength of 14-3-3/nucleoprotein interaction can be linked with the replicative fitness of the virus.

Assessment of Immunogenic and Antigenic Properties of Recombinant Nucleocapsid Proteins of Five SARS-CoV-2 Variants in a Mouse Model

COVID-19 cases caused by new variants of highly mutable SARS-CoV-2 continue to be identified worldwide. Effective control of the spread of new variants can be achieved through targeting of conserved viral epitopes. In this regard, the SARS-CoV-2 nucleocapsid (N) protein, which is much more conserved than the evolutionarily influenced spike protein (S), is a suitable antigen. The recombinant N protein can be considered not only as a screening antigen but also as a basis for the development of next-generation COVID-19 vaccines, but little is known about induction of antibodies against the N protein via different SARS-CoV-2 variants. In addition, it is important to understand how antibodies produced against the antigen of one variant can react with the N proteins of other variants. Here, we used recombinant N proteins from five SARS-CoV-2 strains to investigate their immunogenicity and antigenicity in a mouse model and to obtain and characterize a panel of hybridoma-derived monoclonal anti-N antibodies. We also analyzed the variable epitopes of the N protein that are potentially involved in differential recognition of antiviral antibodies. These results will further deepen our knowledge of the cross-reactivity of the humoral immune response in COVID-19.

Variability in the Clinical Course of COVID-19 in a Retrospective Analysis of a Large Real-World Database

The COVID-19 pandemic proceeds in waves, with variable characteristics of the clinical picture resulting from the evolution of the SARS-CoV-2 virus. This study aimed to compare the epidemiological characteristics, symptomatology, and outcomes of the disease in patients hospitalized for COVID-19 during periods of different variants dominance. Comparing the periods of dominance of variants preceding the Delta variant, the Delta period was characterized by a higher share of hospitalized females, less frequent comorbidities among patients, and a different age distribution. The lowest need for oxygen therapy and mechanical ventilation was observed under Omicron dominance. The triad of classic COVID-19 symptoms, cough, fever, dyspnoea, and fatigue, were most prevalent during the Delta period, and significantly less common under the Omicron dominance. During the Omicron period, nearly twice as many patients as in the previous periods could be discharged from the hospital within 7 days; the overall 28-day mortality was significantly lower compared to that of the Delta period. It also did not differ between periods that were dominated by the BA.1 and BA.2 subvariants. The study indicates that the Omicron SARS-CoV-2 variant that dominated between January and June 2022 caused a disease which resembled the common cold, and was caused by seasonal alpha and beta-coronaviruses with a low pathogenicity for humans. However, one should note that this effect may not only have been related to biological features of the Omicron lineage, but may additionally have been driven by the increased levels of immunization through natural infections and vaccinations, for which we could not account for due to a lack of sufficient data.

Emergence of a unique SARS-CoV-2 Delta sub-cluster harboring a constellation of co-appearing non-Spike mutations

Accumulation of diverse mutations across the structural and nonstructural genes is leading to rapid evolution of SARS-CoV-2, altering its pathogenicity. We performed whole genome sequencing of 239 SARS-CoV-2 RNA samples collected from both adult and pediatric patients across eastern India (West Bengal), during the second pandemic wave in India (April-May 2021). In addition to several common spike mutations within the Delta variant, a unique constellation of eight co-appearing non-Spike mutations was identified, which revealed a high degree of positive mutual correlation. Our results also demonstrated the dynamics of SARS-CoV-2 variants among unvaccinated pediatric patients. 41.4% of our studied Delta strains harbored this signature set of eight co-appearing non-Spike mutations and phylogenetically out-clustered other Delta sub-lineages like 21J, 21A, or 21I. This is the first report from eastern India that portrayed a landscape of co-appearing mutations in the non-Spike proteins, which might have led to the evolution of a distinct Delta subcluster. Accumulation of such mutations in SARS-CoV-2 may lead to the emergence of "vaccine-evading variants." Hence, monitoring of such non-Spike mutations will be significant in the formulation of any future vaccines against those SARS-CoV-2 variants that might evade the current vaccine-induced immunity, among both the pediatric and adult populations.

Characterization of SARS-CoV-2 omicron variants from Iran and evaluation of the effect of mutations on the spike, nucleocapsid, ORF8, and ORF9b proteins function

The SARS-CoV-2 'Omicron' strain, with 15 mutations in the receptor binding domain (RBD), was detected in South Africa and rapidly spread worldwide. SARS-CoV-2 ORF9b protein by binding to the TOM70 receptor and ORF8 protein by binding to MHC-I, IF3 receptors inhibit the host's immune response. In this study, genomics variations were evaluated for 96 samples isolated from Iran from March to July 2022 using the Nextclade web server and informatics tools. We identified the mutations occurring in the SARS-CoV-2 proteins. We also evaluated the effect of mutations on spike protein interaction with the ACE2 receptor, ORF9b protein interaction with the TOM70 receptor, and structural stability of ORF8 and nucleocapsid proteins using docking and molecular dynamics. Results indicated that during March and April 2022, the BA.2 strain was dominant in the south of Iran, while during June 2022, the BA.5 strain was dominant. BF.5 strain had the most divergence among SARS-CoV-2 strains reported from south of Iran. The binding affinity of BA.5 and BF.5 strains spike protein to ACE2 receptor is similar, and compared to BA.2 strain, was stronger. The BF.5 ORF9b K40R mutation causes a better binding affinity of the protein to the TOM70 receptor. Also, mutations that occurred in the ORF8 protein led to instability in the dimer formation of this protein and improved immune response for mutations that occurred in BA.2 strain, while this mutation did not occur in BF.5 strain. The mutations that were detected in nucleocapsid protein CTD and NTD domains caused the stability of these domains.Communicated by Ramaswamy H. Sarma.

ViralVar: A Web Tool for Multilevel Visualization of SARS-CoV-2 Genomes

The unprecedented growth of publicly available SARS-CoV-2 genome sequence data has increased the demand for effective and accessible SARS-CoV-2 data analysis and visualization tools. The majority of the currently available tools either require computational expertise to deploy them or limit user input to preselected subsets of SARS-CoV-2 genomes. To address these limitations, we developed ViralVar, a publicly available, point-and-click webtool that gives users the freedom to investigate and visualize user-selected subsets of SARS-CoV-2 genomes obtained from the GISAID public database. ViralVar has two primary features that enable: (1) the visualization of the spatiotemporal dynamics of SARS-CoV-2 lineages and (2) a structural/functional analysis of genomic mutations. As proof-of-principle, ViralVar was used to explore the evolution of the SARS-CoV-2 pandemic in the USA in pediatric, adult, and elderly populations (n > 1.7 million genomes). Whereas the spatiotemporal dynamics of the variants did not differ between these age groups, several USA-specific sublineages arose relative to the rest of the world. Our development and utilization of ViralVar to provide insights on the evolution of SARS-CoV-2 in the USA demonstrates the importance of developing accessible tools to facilitate and accelerate the large-scale surveillance of circulating pathogens.

Statistical analysis supports UTR (untranslated region) deletion theory in SARS-CoV-2

It was noticed that the mortality rate of SARS-CoV-2 infection experienced a significant declination in the early stage of the epidemic. We suspect that the sharp deterioration of virus toxicity is related to the deletion of the untranslated region (UTR) of the virus genome. It was found that the genome length of SARS-CoV-2 engaged a significant truncation due to UTR deletion after a mega-sequence analysis. Sequence similarity analysis further indicated that short UTR strains originated from its long UTR ancestors after an irreversible deletion. A good correlation was discovered between genome length and mortality, which demonstrated that the deletion of the virus UTR significantly affected the toxicity of the virus. This correlation was further confirmed in a significance analysis of the genetic influence on the clinical outcomes. The viral genome length of hospitalized patients was significantly more extensive than that of asymptomatic patients. In contrast, the viral genome length of asymptomatic was considerably longer than that of ordinary patients with symptoms. A genome-level mutation scanning was performed to systematically evaluate the influence of mutations at each position on virulence. The results indicated that UTR deletion was the primary driving force in alternating virus virulence in the early evolution. In the end, we proposed a mathematical model to explain why this UTR deletion was not continuous.

A novel diG motif in ORF3a protein of SARS-Cov-2 for intracellular transport

The ongoing SARS-CoV-2/COVID-19 pandemic caused a global public health crisis. Yet, everyone's response to SARS-CoV-2 infection varies, and different viral variants confer diverse pathogenicity. Thus, it is imperative to understand how viral determinants contribute to COVID-19. Viral ORF3a protein is one of those viral determinants, as its functions are linked to induction of cell and tissues damages, disease severity and cytokine storm that is a major cause of COVID-19-related death. ORF3a is a membrane-associated protein. Upon synthesis, it is transported from endoplasmic reticulum, Golgi apparatus to plasma membrane and subcellular endomembranes including endosomes and lysosomes. However, how ORF3a is transported intracellularly remains elusive. The goal of this study was to carry out a systematic mutagenesis study to determine the structural relationship of ORF3a protein with its subcellular locations. Single amino acid (aa) and deletion mutations were generated in the putative function-relevant motifs and other regions of interest. Immunofluorescence and ImageJ analyses were used to determine and quantitate subcellular locations of ORF3a mutants in comparison with wildtype ORF3a. The wildtype ORF3a localizes predominantly (Pearson's coefficients about 0.8) on the membranes of endosomes and lysosomes. Consistent with earlier findings, deletion of the YXXΦ motif, which is required for protein export, retained ORF3a in the Golgi apparatus. Interestingly, mutations in a double glycine (diG) region (aa 187-188) displayed a similar phenotype to the YXXΦ deletion, implicating a similar role of the diG motif in intracellular transport. Indeed, interrupting any one of the two glycine residues such as deletion of a single (dG188), both (dG187/dG188) or substitution (G188Y) of these residues led to ORF3a retention in the Golgi apparatus (Pearson's coefficients ≥0.8). Structural analyses further suggest that the diG motif supports a type-II β-turn between the anti-parallel β4 and β5 sheets and connects to the YXXΦ motif via hydrogen bonds between two monomers. The diG- YXXΦ interaction forms a hand-in-hand configuration that could facilitate dimerization. Together, these observations suggest a functional role of the diG motif in intracellular transport of ORF3a.

SARS-CoV-2 ORF8: One protein, seemingly one structure, and many functions

SARS-CoV-2 is the virus responsible for the COVID-19 pandemic. The genome of SARS-CoV-2 encodes nine accessory proteins that are involved in host-pathogen interaction. ORF8 is unique among these accessory proteins. SARS-CoV-2 ORF8 shares a surprisingly low amino acid sequence similarity with SARS-COV ORF8 (30%), and it is presumed to have originated from bat. Studies have shown that ORF8 exerts multiple different functions that interfere with host immune responses, including the downregulation of MHC class I molecules. These functions may represent strategies of host immune evasion. The x-ray crystal structure of ORF8 revealed an immunoglobulin-like domain with several distinguishing features. To date, there are numerous unanswered questions about SARS-CoV-2 ORF8 protein and its structure-function relationship that we discuss in this mini-review. A better understanding of how ORF8 interacts with components of the immune system is needed for elucidating COVID-19 pathogenesis and to develop new avenues for the treatment of the disease.

Analysis of the mutation dynamics of SARS-CoV-2 genome in the samples from Georgia State of the United States

BACKGROUND

The COVID-19 is caused by a novel coronavirus SARS-CoV-2, which started from China. It spread rapidly throughout the world and was later declared a pandemic by the WHO. Over the course of time, SARS-CoV-2 has mutated for survival advantages, and this led to multiple variants. Multiple studies on mutations identification in SARS-CoV2 have been published covering extensive sample areas. The purpose of this study was to limit the sample area to the Georgia state in the U.S. and to analyze the genome sequences for mutation profiling across the genome and origin of variants.

METHODS

The genome sequences (n = 3,970) were obtained from the NCBI database as of June 12, 2021, with the filter of being complete sequenced genomes, homo-sapiens host, and only from Georgia State of the U.S. NextClade, an online tool was used for the analysis of the sequences using Wuhan-Hu-1/2019 as a reference genome. The algorithm was sequence alignment, translation, mutation calling, phylogenetic placement, clade assignment, and quality control (QC). Thirty-six samples with bad QC were removed from the mutational analysis.

RESULTS

A total 117,743 mutations in the nucleotides were identified (averaging 31.5 mutations per sample). The mutations A23403G, C3037T, C241T, and C14408T were detected in 98% of the samples. Also, a total of 75,517 mutations in the amino acid were identified (averaging 20.2 mutations per sample). The mutations D614G and P314L were identified in >97% samples whereas R203K, G204R, P681H, and N501Y were detected in >50% samples. Analysis also revealed 16 different clades with 20I (49.6%). Clades 20G (24.2%) and 20A (5.5%) being the most abundant, showed that SARS-CoV-2 in the Georgia State originated mainly from Southeast England, other parts of the U.S., and several countries in Western Europe.

CONCLUSION

Looking at the three most common variants in Georgia State of the U.S., we could determine the primary locations of transmission or origin for the virus, and our analyses indicates that majority of the cases originated from Southeast England (Clade 20I), the U.S. itself (Clade 20G), and from Western Europe (Clade 20C).

Clinical phenotypes and outcomes associated with SARS-CoV-2 variant Omicron in critically ill French patients with COVID-19

Infection with SARS-CoV-2 variant Omicron is considered to be less severe than infection with variant Delta, with rarer occurrence of severe disease requiring intensive care. Little information is available on comorbid factors, clinical conditions and specific viral mutational patterns associated with the severity of variant Omicron infection. In this multicenter prospective cohort study, patients consecutively admitted for severe COVID-19 in 20 intensive care units in France between December 7th 2021 and May 1st 2022 were included. Among 259 patients, we show that the clinical phenotype of patients infected with variant Omicron (n = 148) is different from that in those infected with variant Delta (n = 111). We observe no significant relationship between Delta and Omicron variant lineages/sublineages and 28-day mortality (adjusted odds ratio [95% confidence interval] = 0.68 [0.35–1.32]; p = 0.253). Among Omicron-infected patients, 43.2% are immunocompromised, most of whom have received two doses of vaccine or more (85.9%) but display a poor humoral response to vaccination. The mortality rate of immunocompromised patients infected with variant Omicron is significantly higher than that of non-immunocompromised patients (46.9% vs 26.2%; p = 0.009). In patients infected with variant Omicron, there is no association between specific sublineages (BA.1/BA.1.1 (n = 109) and BA.2 (n = 21)) or any viral genome polymorphisms/mutational profile and 28-day mortality.

SARS-CoV-2 variant Omicron has been suggested to cause less severe disease. This prospective study shows that the clinical phenotype in patients infected with Omicron differs from patients infected with Delta but no association between Delta and Omicron including sublineages and mortality was observed.

Bioinformatics pipeline unveils genetic variability to synthetic vaccine design for Indian SARS-CoV-2 genomes

In the worrisome scenarios of various waves of SARS-CoV-2 pandemic, a comprehensive bioinformatics pipeline is essential to analyse the virus genomes in order to understand its evolution, thereby identifying mutations as signature SNPs, conserved regions and subsequently to design epitope based synthetic vaccine. We have thus performed multiple sequence alignment of 4996 Indian SARS-CoV-2 genomes as a case study using MAFFT followed by phylogenetic analysis using Nextstrain to identify virus clades. Furthermore, based on the entropy of each genomic coordinate of the aligned sequences, conserved regions are identified. After refinement of the conserved regions, based on its length, one conserved region is identified for which the primers and probes are reported for virus detection. The refined conserved regions are also used to identify T-cell and B-cell epitopes along with their immunogenic and antigenic scores. Such scores are used for selecting the most immunogenic and antigenic epitopes. By executing this pipeline, 40 unique signature SNPs are identified resulting in 23 non-synonymous signature SNPs which provide 28 amino acid changes in protein. On the other hand, 12 conserved regions are selected based on refinement criteria out of which one is selected as the potential target for virus detection. Additionally, 22 MHC-I and 21 MHC-II restricted T-cell epitopes with 10 unique HLA alleles each and 17 B-cell epitopes are obtained for 12 conserved regions. All the results are validated both quantitatively and qualitatively which show that from genetic variability to synthetic vaccine design, the proposed pipeline can be used effectively to combat SARS-CoV-2.

Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival

Objectives: More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain. Methods: A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis. Results: A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins. Conclusions: This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.

A Comparative Study of the Plasma Chemokine Profile in COVID-19 Patients Infected with Different SARS-CoV-2 Variants

BACKGROUND

Infection caused by SARS-CoV-2 mostly affects the upper and lower respiratory tracts and causes symptoms ranging from the common cold to pneumonia with acute respiratory distress syndrome. Chemokines are deeply involved in the chemoattraction, proliferation, and activation of immune cells within inflammation. It is crucial to consider that mutations within the virion can potentially affect the clinical course of SARS-CoV-2 infection because disease severity and manifestation vary depending on the genetic variant. Our objective was to measure and assess the different concentrations of chemokines involved in COVID-19 caused by different variants of the virus.

METHODS

We used the blood plasma of patients infected with different variants of SARS-CoV-2, i.e., the ancestral Wuhan strain and the Alpha, Delta, and Omicron variants. We measured the concentrations of 11 chemokines in the samples: CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROα, CXCL8/IL-8, CXCL9/MIG, CXCL10/IP-10, and CX3CL1/Fractalkine.

RESULTS

We noted a statistically significant elevation in the concentrations of CCL2/MCP-1, CXCL8/IL-8, and CXCL1/IP-10 independently of the variant, and a drop in the CCL22/MDC concentrations.

CONCLUSIONS

The chemokine concentrations varied significantly depending on the viral variant, leading us to infer that mutations in viral proteins play a role in the cellular and molecular mechanisms of immune responses.

Multifaceted Assessment of Wastewater-Based Epidemiology for SARS-CoV-2 in Selected Urban Communities in Davao City, Philippines: A Pilot Study

Over 60 countries have integrated wastewater-based epidemiology (WBE) in their COVID-19 surveillance programs, focusing on wastewater treatment plants (WWTP). In this paper, we piloted the assessment of SARS-CoV-2 WBE as a complementary public health surveillance method in susceptible communities in a highly urbanized city without WWTP in the Philippines by exploring the extraction and detection methods, evaluating the contribution of physico-chemical–anthropogenic factors, and attempting whole-genome sequencing (WGS). Weekly wastewater samples were collected from sewer pipes or creeks in six communities with moderate-to-high risk of COVID-19 transmission, as categorized by the City Government of Davao from November to December 2020. Physico-chemical properties of the wastewater and anthropogenic conditions of the sites were noted. Samples were concentrated using a PEG-NaCl precipitation method and analyzed by RT-PCR to detect the SARS-CoV-2 N, RdRP, and E genes. A subset of nine samples were subjected to WGS using the Minion sequencing platform. SARS-CoV-2 RNA was detected in twenty-two samples (91.7%) regardless of the presence of new cases. Cycle threshold values correlated with RNA concentration and attack rate. The lack of a sewershed map in the sampled areas highlights the need to integrate this in the WBE planning. A combined analysis of wastewater physico-chemical parameters such as flow rate, surface water temperature, salinity, dissolved oxygen, and total dissolved solids provided insights on the ideal sampling location, time, and method for WBE, and their impact on RNA recovery. The contribution of fecal matter in the wastewater may also be assessed through the coliform count and in the context of anthropogenic conditions in the area. Finally, our attempt on WGS detected single-nucleotide polymorphisms (SNPs) in wastewater which included clinically reported and newly identified mutations in the Philippines. This exploratory report provides a contextualized framework for applying WBE surveillance in low-sanitation areas.

The First Geographic Identification by Country of Sustainable Mutations of SARS-COV2 Sequence Samples: Worldwide Natural Selection Trends

The high mutation rates of RNA viruses, coupled with short generation times and large population sizes, allow viruses to evolve rapidly and adapt to the host environment. The rapidity of viral mutation also causes problems in developing successful vaccines and antiviral drugs. With the spread of SARS-CoV-2 worldwide, thousands of mutations have been identified, some of which have relatively high incidences, but their potential impacts on virus characteristics remain unknown. The present study analyzed mutation patterns, SARS-CoV-2 AASs retrieved from the GISAID database containing 10,500,000 samples. Python 3.8.0 programming language was utilized to pre-process FASTA data, align to the reference sequence, and analyze the sequences. Upon completion, all mutations discovered were categorized based on geographical regions and dates. The most stable mutations were found in nsp1(8% S135R), nsp12(99.3% P323L), nsp16 (1.2% R216C), envelope (30.6% T9I), spike (97.6% D614G), and Orf8 (3.5% S24L), and were identified in the United States on April 3, 2020, and England, Gibraltar, and, New Zealand, on January 1, 2020, respectively. The study of mutations is the key to improving understanding of the function of the SARS-CoV-2, and recent information on mutations helps provide strategic planning for the prevention and treatment of this disease. Viral mutation studies could improve the development of vaccines, antiviral drugs, and diagnostic assays designed with high accuracy, specifically useful during pandemics. This knowledge helps to be one step ahead of new emergence variants.

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

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel virus that belongs to the Coronoviridae family, emerged in December 2019, causing the COVID-19 pandemic in March 2020. Unlike previous SARS and Middle East respiratory syndrome (MERS) outbreaks, this virus has a higher transmissibility rate, albeit a lower case fatality rate, which results in accumulation of a significant number of mutations and a faster evolution rate. Genomic studies on the mutation rate of the virus, as well as the identification of mutations that prevail and their impact on disease severity, are of great importance for pandemic surveillance and vaccine and drug development. Here, we aim to identify mutations on the SARS-CoV-2 viral genome and their effect on the proteins they are located in, in Greek patients infected in the first wave of the pandemic. To this end, we perform SARS-CoV-2 amplicon-based NGS sequencing on nasopharyngeal swab samples from Greek patients and bioinformatic analysis of the results. Although SARS-CoV-2 is considered genetically stable, we discover a variety of mutations on the viral genome. In detail, 18 mutations are detected in total on 10 SARS-CoV-2 isolates. The mutations are located on ORF1ab, S protein, M protein, ORF3a and ORF7a. Sixteen are also detected in patients from other regions around the world, and two are identified for the first time in the present study. Most of them result in amino acid substitutions. These substitutions are analyzed using computational tools, and the results indicate minor or major impact on the proteins’ structural stability, which could probably affect viral transmissibility and pathogenesis. The correlation of these variations with the viral load levels is examined, and their implication for disease severity and the biology of the virus are discussed.

SARS-CoV-2 Genomic Characteristics and Clinical Impact of SARS-CoV-2 Viral Diversity in Critically Ill COVID-19 Patients: A Prospective Multicenter Cohort Study

The SARS-CoV-2 variant of concern, α, spread worldwide at the beginning of 2021. It was suggested that this variant was associated with a higher risk of mortality than other variants. We aimed to characterize the genetic diversity of SARS-CoV-2 variants isolated from patients with severe COVID-19 and unravel the relationships between specific viral mutations/mutational patterns and clinical outcomes. This is a prospective multicenter observational cohort study. Patients aged ≥18 years admitted to 11 intensive care units (ICUs) in hospitals in the Greater Paris area for SARS-CoV-2 infection and acute respiratory failure between 1 October 2020 and 30 May 2021 were included. The primary clinical endpoint was day-28 mortality. Full-length SARS-CoV-2 genomes were sequenced by means of next-generation sequencing (Illumina COVIDSeq). In total, 413 patients were included, 183 (44.3%) were infected with pre-existing variants, 197 (47.7%) were infected with variant α, and 33 (8.0%) were infected with other variants. The patients infected with pre-existing variants were significantly older (64.9 ± 11.9 vs. 60.5 ± 11.8 years; p = 0.0005) and had more frequent COPD (11.5% vs. 4.1%; p = 0.009) and higher SOFA scores (4 [3–8] vs. 3 [2–4]; 0.0002). The day-28 mortality was no different between the patients infected with pre-existing, α, or other variants (31.1% vs. 26.2% vs. 30.3%; p = 0.550). There was no association between day-28 mortality and specific variants or the presence of specific mutations. At ICU admission, the patients infected with pre-existing variants had a different clinical presentation from those infected with variant α, but mortality did not differ between these groups. There was no association between specific variants or SARS-CoV-2 genome mutational pattern and day-28 mortality.

Possible intraindividual evolution of SARS-CoV-2 in nasopharyngeal and anal swab in an octogenarian: a case report

Introduction

COVID-19 is an emerging infectious disease that remains to be further investigated.

Case report

Here, we describe a case of COVID-19 in an octogenarian woman with comorbidities who slowly recovered during hospitalization, but died due to sudden cardiac death after 2 weeks of hospitalization. Her nasopharyngeal and anal swabs returned positive for SARS-CoV-2 by RT-PCR on day 7 of hospitalization. The NGS showed possible intraindividual evolution of virus. The sample from the nasopharyngeal swab yielded a B.1470 variant classified as clade GH. This variant showed mutation in the spike gene D614G; N gene; NS3 gene; NSP2 gene and NSP12 gene. The sample from the anal swab showed similar mutation but with additional point mutation in spike gene S12F and was classified as B.1.465 variant.

Conclusions

The possibility of the gastrointestinal tract that served as reservoir for virus mutation accumulation should also be considered and the potential impact of viral fecal transmission in the environment should be further investigated.

Increased Abundance of Achromobacter xylosoxidans and Bacillus cereus in Upper Airway Transcriptionally Active Microbiome of COVID-19 Mortality Patients Indicates Role of Co-Infections in Disease Severity and Outcome

The modulators of severe COVID-19 have emerged as the most intriguing features of SARS-CoV-2 pathogenesis. This is especially true as we are encountering variants of concern (VOC) with increased transmissibility and vaccination breakthroughs. Microbial co-infections are being investigated as one of the crucial factors for exacerbation of disease severity and complications of COVID-19. A key question remains whether early transcriptionally active microbial signature/s in COVID-19 patients can provide a window for future disease severity susceptibility and outcome? Using complementary metagenomics sequencing approaches, respiratory virus oligo panel (RVOP) and Holo-seq, our study highlights the possible functional role of nasopharyngeal early resident transcriptionally active microbes in modulating disease severity, within recovered patients with sub-phenotypes (mild, moderate, severe) and mortality. The integrative analysis combines patients' clinical parameters, SARS-CoV-2 phylogenetic analysis, microbial differential composition, and their functional role. The clinical sub-phenotypes analysis led to the identification of transcriptionally active bacterial species associated with disease severity. We found significant transcript abundance of Achromobacter xylosoxidans and Bacillus cereus in the mortality, Leptotrichia buccalis in the severe, Veillonella parvula in the moderate, and Actinomyces meyeri and Halomonas sp. in the mild COVID-19 patients. Additionally, the metabolic pathways, distinguishing the microbial functional signatures between the clinical sub-phenotypes, were also identified. We report a plausible mechanism wherein the increased transcriptionally active bacterial isolates might contribute to enhanced inflammatory response and co-infections that could modulate the disease severity in these groups. Current study provides an opportunity for potentially using these bacterial species for screening and identifying COVID-19 patient sub-groups with severe disease outcome and priority medical care. IMPORTANCE COVID-19 is invariably a disease of diverse clinical manifestation, with multiple facets involved in modulating the progression and outcome. In this regard, we investigated the role of transcriptionally active microbial co-infections as possible modulators of disease pathology in hospital admitted SARS-CoV-2 infected patients. Specifically, can there be early nasopharyngeal microbial signatures indicative of prospective disease severity? Based on disease severity symptoms, the patients were segregated into clinical sub-phenotypes: mild, moderate, severe (recovered), and mortality. We identified significant presence of transcriptionally active isolates, Achromobacter xylosoxidans and Bacillus cereus in the mortality patients. Importantly, the bacterial species might contribute toward enhancing the inflammatory responses as well as reported to be resistant to common antibiotic therapy, which together hold potential to alter the disease severity and outcome.

Contrasting Epidemiology and Population Genetics of COVID-19 Infections Defined by Multilocus Genotypes in SARS-CoV-2 Genomes Sampled Globally

Since its emergence in 2019, SARS-CoV-2 has spread and evolved globally, with newly emerged variants of concern (VOCs) accounting for more than 500 million COVID-19 cases and 6 million deaths. Continuous surveillance utilizing simple genetic tools is needed to measure the viral epidemiological diversity, risk of infection, and distribution among different demographics in different geographical regions. To help address this need, we developed a proof-of-concept multilocus genotyping tool and demonstrated its utility to monitor viral populations sampled in 2020 and 2021 across six continents. We sampled globally 22,164 SARS-CoV-2 genomes from GISAID (inclusion criteria: available clinical and demographic data). They comprised two study populations, “2020 genomes” (N = 5959) sampled from December 2019 to September 2020 and “2021 genomes” (N = 16,205) sampled from 15 January to 15 March 2021. All genomes were aligned to the SARS-CoV-2 reference genome and amino acid polymorphisms were called with quality filtering. Thereafter, 74 codons (loci) in 14 genes including orf1ab polygene (N = 9), orf3a, orf8, nucleocapsid (N), matrix (M), and spike (S) met the 0.01 minimum allele frequency criteria and were selected to construct multilocus genotypes (MLGs) for the genomes. At these loci, 137 mutant/variant amino acids (alleles) were detected with eight VOC-defining variant alleles, including N KR203&204, orf1ab (I265, F3606, and L4715), orf3a H57, orf8 S84, and S G614, being predominant globally with > 35% prevalence. Their persistence and selection were associated with peaks in the viral transmission and COVID-19 incidence between 2020 and 2021. Epidemiologically, older patients (≥20 years) compared to younger patients (<20 years) had a higher risk of being infected with these variants, but this association was dependent on the continent of origin. In the global population, the discriminant analysis of principal components (DAPC) showed contrasting patterns of genetic clustering with three (Africa, Asia, and North America) and two (North and South America) continental clusters being observed for the 2020 and 2021 global populations, respectively. Within each continent, the MLG repertoires (range 40−199) sampled in 2020 and 2021 were genetically differentiated, with ≤4 MLGs per repertoire accounting for the majority of genomes sampled. These data suggested that the majority of SARS-CoV-2 infections in 2020 and 2021 were caused by genetically distinct variants that likely adapted to local populations. Indeed, four GISAID clade-defined VOCs - GRY (Alpha), GH (Beta), GR (Gamma), and G/GK (Delta variant) were differentiated by their MLG signatures, demonstrating the versatility of the MLG tool for variant identification. Results from this proof-of-concept multilocus genotyping demonstrates its utility for SARS-CoV-2 genomic surveillance and for monitoring its spatiotemporal epidemiology and evolution, particularly in response to control interventions including COVID-19 vaccines and chemotherapies.

Severity of infection with the SARS-CoV-2 B.1.1.7 lineage among hospitalized COVID-19 patients in Belgium

Introduction

The pathogenesis of COVID-19 depends on the interplay between host characteristics, viral characteristics and contextual factors. Here, we compare COVID-19 disease severity between hospitalized patients in Belgium infected with the SARS-CoV-2 variant B.1.1.7 and those infected with previously circulating strains.

Methods

The study is conducted within a causal framework to study the severity of SARS-CoV-2 variants by merging surveillance registries in Belgium. Infection with SARS-CoV-2 B.1.1.7 (‘exposed’) was compared to infection with previously circulating strains (‘unexposed’) in terms of the manifestation of severe COVID-19, intensive care unit (ICU) admission, or in-hospital mortality. The exposed and unexposed group were matched based on the hospital and the mean ICU occupancy rate during the patient’s hospital stay. Other variables identified as confounders in a Directed Acyclic Graph (DAG) were adjusted for using regression analysis. Sensitivity analyses were performed to assess the influence of selection bias, vaccination rollout, and unmeasured confounding.

Results

We observed no difference between the exposed and unexposed group in severe COVID-19 disease or in-hospital mortality (RR = 1.15, 95% CI [0.93–1.38] and RR = 0.92, 95% CI [0.62–1.23], respectively). The estimated standardized risk to be admitted in ICU was significantly higher (RR = 1.36, 95% CI [1.03–1.68]) when infected with the B.1.1.7 variant. An age-stratified analysis showed that among the younger age group (≤65 years), the SARS-CoV-2 variant B.1.1.7 was significantly associated with both severe COVID-19 progression and ICU admission.

Conclusion

This matched observational cohort study did not find an overall increased risk of severe COVID-19 or death associated with B.1.1.7 infection among patients already hospitalized. There was a significant increased risk to be transferred to ICU when infected with the B.1.1.7 variant, especially among the younger age group. However, potential selection biases advocate for more systematic sequencing of samples from hospitalized COVID-19 patients.

Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method

SARS-CoV-2 shows great evolutionary capacity through a high frequency of genomic variation during transmission. Evolved SARS-CoV-2 often demonstrates resistance to previous vaccines and can cause poor clinical status in patients. Mutations in the SARS-CoV-2 genome involve mutations in structural and nonstructural proteins, and some of these proteins such as spike proteins have been shown to be directly associated with the clinical status of patients with severe COVID-19 pneumonia. In this study, we collected genome-wide mutation information of virulent strains and the severity of COVID-19 pneumonia in patients varying depending on their clinical status. Important protein mutations and untranslated region mutations were extracted using machine learning methods. First, through Boruta and four ranking algorithms (least absolute shrinkage and selection operator, light gradient boosting machine, max-relevance and min-redundancy, and Monte Carlo feature selection), mutations that were highly correlated with the clinical status of the patients were screened out and sorted in four feature lists. Some mutations such as D614G and V1176F were shown to be associated with viral infectivity. Moreover, previously unreported mutations such as A320V of nsp14 and I164ILV of nsp14 were also identified, which suggests their potential roles. We then applied the incremental feature selection method to each feature list to construct efficient classifiers, which can be directly used to distinguish the clinical status of COVID-19 patients. Meanwhile, four sets of quantitative rules were set up, which can help us to more intuitively understand the role of each mutation in differentiating the clinical status of COVID-19 patients. Identified key mutations linked to virologic properties will help better understand the mechanisms of infection and will aid in the development of antiviral treatments.

Viral Mimicry of Interleukin-17A by SARS-CoV-2 ORF8

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection triggers cytokine-mediated inflammation, leading to a myriad of clinical presentations in COVID-19. The SARS-CoV-2 open reading frame 8 (ORF8) is a secreted and rapidly evolving glycoprotein. Patients infected with SARS-CoV-2 variants with ORF8 deleted are associated with mild disease outcomes, but the molecular mechanism behind this is unknown. Here, we report that SARS-CoV-2 ORF8 is a viral cytokine that is similar to but distinct from interleukin 17A (IL-17A) as it induces stronger and broader human IL-17 receptor (hIL-17R) signaling than IL-17A. ORF8 primarily targeted blood monocytes and induced the heterodimerization of hIL-17RA and hIL-17RC, triggering a robust inflammatory response. Transcriptome analysis revealed that besides its activation of the hIL-17R pathway, ORF8 upregulated gene expression for fibrosis signaling and coagulation dysregulation. A naturally occurring ORF8 L84S variant that was highly associated with mild COVID-19 showed reduced hIL-17RA binding and attenuated inflammatory responses. This study reveals how SARS-CoV-2 ORF8 by a viral mimicry of the IL-17 cytokine contributes to COVID-19 severe inflammation. IMPORTANCE Patients infected with SARS-CoV-2 variants lacking open reading frame 8 (ORF8) have been associated with milder infection and disease outcome, but the molecular mechanism behind how this viral accessory protein mediates disease pathogenesis is not yet known. In our study, we revealed that secreted ORF8 protein mimics host IL-17 to activate IL-17 receptors A and C (IL-17RA/C) and induces a significantly stronger inflammatory response than host IL-17A, providing molecular insights into the role of ORF8 in COVID-19 pathogenesis and serving as a potential therapeutic target.

Unusual N Gene Dropout and Ct Value Shift in Commercial Multiplex PCR Assays Caused by Mutated SARS-CoV-2 Strain

Several SARS-CoV-2 variants have emerged and early detection for monitoring their prevalence is crucial. Many identification strategies have been implemented in cases where sequencing data for confirmation is pending or not available. The presence of B.1.1.318 among prevalent variants was indicated by an unusual amplification pattern in various RT-qPCR commercial assays. Positive samples for SARS-CoV-2, as determined using the Allplex SARS-CoV-2 Assay, the Viasure SARS-CoV-2 Real Time Detection Kit and the GeneFinder COVID-19 Plus RealAmp Kit, presented a delay or failure in the amplification of the N gene, which was further investigated. Whole-genome sequencing was used for variant characterization. The differences between the mean Ct values for amplification of the N gene vs. other genes were calculated for each detection system and found to be at least 14 cycles. Sequencing by WGS revealed that all the N gene dropout samples contained the B.1.1.318 variant. All the isolates harbored three non-synonymous mutations in the N gene, which resulted in four amino acid changes (R203K, G204R, A208G, Met234I). Although caution should be taken when the identification of SARS-CoV-2 variants is based on viral gene amplification failure, such patterns could serve as a basis for rapid and cost-effective screening, functioning as indicators of community circulation of specific variants, requiring subsequent verification via sequencing.

Pandemic trends in health care use: From the hospital bed to self-care with COVID-19

AIM

To explore whether the acute 30-day burden of COVID-19 on health care use has changed from February 2020 to February 2022.

METHODS

In all Norwegians (N = 493 520) who tested positive for SARS-CoV-2 in four pandemic waves (February 26th, 2020 -February 16th, 2021 (1st wave dominated by the Wuhan strain), February 17th-July 10th, 2021 (2nd wave dominated by the Alpha variant), July 11th-December 27th, 2021 (3rd wave dominated by the Delta variant), and December 28th, 2021 -January 14th, 2022 (4th wave dominated by the Omicron variant)), we studied the age- and sex-specific share of patients (by age groups 1-19, 20-67, and 68 or more) who had: 1) Relied on self-care, 2) used outpatient care (visiting general practitioners or emergency ward for COVID-19), and 3) used inpatient care (hospitalized ≥24 hours with COVID-19).

RESULTS

We find a remarkable decline in the use of health care services among COVID-19 patients for all age/sex groups throughout the pandemic. From 83% [95%CI = 83%-84%] visiting outpatient care in the first wave, to 80% [81%-81%], 69% [69%-69%], and 59% [59%-59%] in the second, third, and fourth wave. Similarly, from 4.9% [95%CI = 4.7%-5.0%] visiting inpatient care in the first wave, to 3.6% [3.4%-3.7%], 1.4% [1.3%-1.4%], and 0.5% [0.4%-0.5%]. Of persons testing positive for SARS-CoV-2, 41% [41%-41%] relied on self-care in the 30 days after testing positive in the fourth wave, compared to 16% [15%-16%] in the first wave.

CONCLUSION

From 2020 to 2022, the use of COVID-19 related outpatient care services decreased with 29%, whereas the use of COVID-19 related inpatient care services decreased with 80%.

Mutations in the genome of severe acute respiratory syndrome coronavirus 2: implications for COVID-19 severity and progression

Coronaviridae is a large family of enveloped, positive-strand RNA viruses that has plagued the world since it was discovered in humans in the 1960s. The recent severe acute respiratory syndrome coronavirus (SARS-CoV)-2 pandemic has already exceeded the number of combined cases and deaths witnessed during previous SARS-CoV and Middle East respiratory syndrome-CoV epidemics in the last two decades. This narrative review focuses on genomic mutations in SARS-CoV-2 and their impact on the severity and progression of COVID-19 in light of reported data in the literature. Notable SARS-CoV-2 mutations associated with open reading frames, the S glycoprotein, and nucleocapsid protein, currently circulating globally, are discussed along with emerging mutations such as those in the SARS-CoV-2 VUI 202012/01 variant in the UK and other European countries, the 484K.V2 and P.1 variants in Brazil, the B.1.617 variant in India, and South African variants 501Y.V2 and B.1.1.529 (omicron). These variants have the potential to influence the receptor binding domain, host-virus fusion, and SARS-CoV-2 replication. Correlating these mutations with disease dynamics could help us understand their pathogenicity and design appropriate therapeutics.

Phylogenetic analysis of 17271 Indian SARS-CoV-2 genomes to identify temporal and spatial hotspot mutations

The second wave of SARS-CoV-2 has hit India hard and though the vaccination drive has started, moderate number of COVID affected patients is still present in the country, thereby leading to the analysis of the evolving virus strains. In this regard, multiple sequence alignment of 17271 Indian SARS-CoV-2 sequences is performed using MAFFT followed by their phylogenetic analysis using Nextstrain. Subsequently, mutation points as SNPs are identified by Nextstrain. Thereafter, from the aligned sequences temporal and spatial analysis are carried out to identify top 10 hotspot mutations in the coding regions based on entropy. Finally, to judge the functional characteristics of all the non-synonymous hotspot mutations, their changes in proteins are evaluated as biological functions considering the sequences by using PolyPhen-2 while I-Mutant 2.0 evaluates their structural stability. For both temporal and spatial analysis, there are 21 non-synonymous hotspot mutations which are unstable and damaging.

An issue of concern: unique truncated ORF8 protein variants of SARS-CoV-2

Open reading frame 8 (ORF8) shows one of the highest levels of variability among accessory proteins in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus Disease 2019 (COVID-19). It was previously reported that the ORF8 protein inhibits the presentation of viral antigens by the major histocompatibility complex class I (MHC-I), which interacts with host factors involved in pulmonary inflammation. The ORF8 protein assists SARS-CoV-2 in evading immunity and plays a role in SARS-CoV-2 replication. Among many contributing mutations, Q27STOP, a mutation in the ORF8 protein, defines the B.1.1.7 lineage of SARS-CoV-2, engendering the second wave of COVID-19. In the present study, 47 unique truncated ORF8 proteins (T-ORF8) with the Q27STOP mutations were identified among 49,055 available B.1.1.7 SARS-CoV-2 sequences. The results show that only one of the 47 T-ORF8 variants spread to over 57 geo-locations in North America, and other continents, which include Africa, Asia, Europe and South America. Based on various quantitative features, such as amino acid homology, polar/non-polar sequence homology, Shannon entropy conservation, and other physicochemical properties of all specific 47 T-ORF8 protein variants, nine possible T-ORF8 unique variants were defined. The question as to whether T-ORF8 variants function similarly to the wild type ORF8 is yet to be investigated. A positive response to the question could exacerbate future COVID-19 waves, necessitating severe containment measures.