Recapping the Features of SARS-CoV-2 and Its Main Variants: Status and Future Paths

COVID-19 mutations: An overview

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) belongs to the genus Beta coronavirus and the family of Coronaviridae. It is a positive-sense, non-segmented single-strand RNA virus. Four common types of human coronaviruses circulate globally, particularly in the fall and winter seasons. They are responsible for 10%-30% of all mild upper respiratory tract infections in adults. These are 229E, NL63 of the Alfacoronaviridae family, OC43, and HKU1 of the Betacoronaviridae family. However, there are three highly pathogenic human coronaviruses: SARS-CoV-2, Middle East respiratory syndrome coronavirus, and the latest pandemic caused by the SARS-CoV-2 infection. All viruses, including SARS-CoV-2, have the inherent tendency to evolve. SARS-CoV-2 is still evolving in humans. Additionally, due to the development of herd immunity, prior infection, use of medication, vaccination, and antibodies, the viruses are facing immune pressure. During the replication process and due to immune pressure, the virus may undergo mutations. Several SARS-CoV-2 variants, including the variants of concern (VOCs), such as B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617/B.1.617.2 (Delta), P.1 (Gamma), and B.1.1.529 (Omicron) have been reported from various parts of the world. These VOCs contain several important mutations; some of them are on the spike proteins. These mutations may lead to enhanced infectivity, transmissibility, and decreased neutralization efficacy by monoclonal antibodies, convalescent sera, or vaccines. Mutations may also lead to a failure of detection by molecular diagnostic tests, leading to a delayed diagnosis, increased community spread, and delayed treatment. We searched PubMed, EMBASE, Covariant, the Stanford variant Database, and the CINAHL from December 2019 to February 2023 using the following search terms: VOC, SARS-CoV-2, Omicron, mutations in SARS-CoV-2, etc. This review discusses the various mutations and their impact on infectivity, transmissibility, and neutralization efficacy.

Analysis of SARS-CoV-2 genome evolutionary patterns

The spread of SARS-CoV-2 virus accompanied by public availability of abundant sequence data provides a window for the determination of viral evolutionary patterns. In this study, SARS-CoV-2 genome sequences were collected from seven countries in the period January 2020-December 2022. The sequences were classified into three phases, namely, pre-vaccination, post-vaccination, and recent period. Comparison was performed between these phases based on parameters like mutation rates, selection pressure (dN/dS ratio), and transition to transversion ratios (Ti/Tv). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t-test. The analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across all countries from the pre-vaccination sequences. Mutation rates were highest in NSP3, S, N, and NSP12b before and increased further after vaccination. NSP4 showed the largest change in mutation rates after vaccination. The dN/dS ratios showed purifying selection that shifted toward neutral selection after vaccination. N, ORF8, ORF3a, and ORF10 were under highest positive selection before vaccination. Shift toward neutral selection was driven by E, NSP3, and ORF7a in the after vaccination set. In recent sequences, the largest dN/dS change was observed in E, NSP1, and NSP13. The Ti/Tv ratios decreased with time. C→U and G→U were the most frequent transitions and transversions. However, U→G was the most frequent transversion in recent period. The Omicron variant had the highest genomic mutation rates, while Delta showed the highest dN/dS ratio. Protein-wise dN/dS ratio was also seen to vary across the different variants.IMPORTANCETo the best of our knowledge, there exists no other large-scale study of the genomic and protein-wise mutation patterns during the time course of evolution in different countries. Analyzing the SARS-CoV-2 evolutionary patterns in view of the varying spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.

SARS-CoV-2-specific antibody and T-cell immunity in convalescents after infection wave in Beijing in late 2022

OBJECTIVES

To evaluate SARS-CoV-2-specific antibody and T-cell responses in convalescents 5 months after infection wave in Beijing from December 2022 to January 2023 to prevent reinfection and severe disease.

METHODS

Convalescents and uninfected individuals vaccinated with different doses were enrolled to assess the IFNγ T-cell responses against SARS-CoV-2 prototype strain, BF.7, BQ.1, and XBB. Neutralizing antibodies against prototype strain, BF.7, BA.5, and XBB and immunoglobulin G antibody were further analyzed.

RESULTS

In convalescents, the IFNγ T-cell response was significantly higher than that of uninfected individuals (all P < 0.001), and the T-cell response against XBB had no significant difference from that of SARS-CoV-2 prototype strain and BF.7 and BQ.1 (all P > 0.05). The seropositive rates of IgG antibodies were 100% (303/303) with a median concentration of 90.52 (95% CI, 82.52-99.37). The neutralizing antibodies titers of convalescents against BF.7 and BA.5 were higher than that against the prototype strain (both P < 0.001), while XBB.1.5 was lower (P < 0.001). T-cell response, IgG and neutralizing antibodies had no significant difference in convalescents vaccinated with different doses (all P > 0.05).

CONCLUSIONS

The immunities may have some protective effect against possible future outbreaks and severe diseases of COVID-19.

Prognosis Predictive Markers in Patients with Chronic Obstructive Pulmonary Disease and COVID-19

Some studies have reported that chronic respiratory illnesses in patients with COVID-19 result in an increase in hospitalization and death rates, while other studies reported to the contrary. The present research aims to determine if a predictive model (developed by combing different clinical, imaging, or blood markers) could be established for patients with both chronic obstructive pulmonary disease (COPD) and COVID-19, in order to be able to foresee the outcomes of these patients. A prospective observational cohort of 165 patients with both diseases was analyzed in terms of clinical characteristics, blood tests, and chest computed tomography results. The beta-coefficients from the logistic regression were used to create a score based on the significant identified markers for poor outcomes (transfers to an intensive care unit (ICU) for mechanical ventilation, or death). The severity of COVID-19, renal failure, diabetes, smoking status (current or previous), the requirement for oxygen therapy upon admission, high lactate dehydrogenase (LDH) and C-reactive protein level (CRP readings), and low eosinophil and lymphocyte counts were all identified as being indicators of a poor prognosis. Higher mortality was linked to the occurrence of renal failure, the number of affected lobes, the need for oxygen therapy upon hospital admission, high LDH, and low lymphocyte levels. Patients had an 86.4% chance of dying if their mortality scores were -2.80 or lower, based on the predictive model. The factors that were linked to a poor prognosis in patients who had both COPD and COVID-19 were the same as those that were linked to a poor prognosis in patients who had only COVID-19.

Variable neutralizing antibody responses to 10 SARS-CoV-2 variants in natural infection with wild- type (B.1) virus, Kappa (B.1.617.1), and Delta (B.1.617.2) variants and COVISHIELD vaccine immunization in India: utility of the MSD platform

For the efficacy of COVID-19 vaccines, emergence of variants accumulating immune-escape mutations remains a major concern. We analyzed the anti-variant (n = 10) neutralization activity of sera from COVID-19 patients infected with Wuhan (B.1), Kappa, and Delta variants and COVISHIELD vaccine recipients with (prepositives) or without (prenegatives) prior antibody positivity using V- PLEX ACE2 Neutralization Kit from MSD. MSD and PRNT₅₀ correlated well (r = 0.76-0.83, p < 0.0001). Despite the least antibody positivity in Kappa patients, anti-variant neutralizing antibody (Nab) levels in the responders were comparable with Delta patients. Vaccinees sampled at 1 month (PD2-1) and 6 months (PD2-6) post-second dose showed the highest seropositivity and Nab levels against the Wuhan strain. At PD2-1, the responder rate was variant-dependent and 100% respectively in prenegatives and prepositives. Nab levels against B.1.135.1, B.1.620, B.1.1.7+E484K (both groups), AY.2 (prenegatives), and B.1.618 (prepositives) were lower than that of Wuhan. At PD2-6, positivity decreased to 15.6%-68.8% in the prenegatives; 3.5%-10.7% of prepositives turned negative for the same four variants. As against the decline in Nab levels in 9/10 variants (prenegatives), a further reduction was seen against the same four variants in the prepositives. These variants possess immune-evasion-associated mutations in the RBD/S region. In conclusion, our data show that the Nab response of patients to multiple variants depends on the infecting variant. We confirm superiority of hybrid immunity in neutralizing multiple variants. Depending on the infecting variant pre- or postvaccination, immune response to different vaccines in different populations will vary and impact protection against emerging variants. The MSD platform provides an excellent alternative to live virus/pseudovirus neutralization tests.

Recent Developments in Electrochemical-Impedimetric Biosensors for Virus Detection

Viruses, including influenza viruses, MERS-CoV (Middle East respiratory syndrome coronavirus), SARS-CoV (severe acute respiratory syndrome coronavirus), HAV (Hepatitis A virus), HBV (Hepatitis B virus), HCV (Hepatitis C virus), HIV (human immunodeficiency virus), EBOV (Ebola virus), ZIKV (Zika virus), and most recently SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), are responsible for many diseases that result in hundreds of thousands of deaths yearly. The ongoing outbreak of the COVID-19 disease has raised a global concern and intensified research on the detection of viruses and virus-related diseases. Novel methods for the sensitive, rapid, and on-site detection of pathogens, such as the recent SARS-CoV-2, are critical for diagnosing and treating infectious diseases before they spread and affect human health worldwide. In this sense, electrochemical impedimetric biosensors could be applied for virus detection on a large scale. This review focuses on the recent developments in electrochemical-impedimetric biosensors for the detection of viruses.

COVID-19 mRNA Vaccines: A Retrospective Observational Pharmacovigilance Study

Background and Objective

Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus has caused millions of deaths worldwide. The mRNA vaccines prevented the figure from being more severe. The objective of this retrospective study is to evaluate the safety of COVID-19 vaccines by analyzing the adverse events following immunization (AEFIs).

Methods

A retrospective observational pharmacovigilance study was conducted, based on the collection of reports of suspected AEFIs reported between 1 January 2021 and 31 December 2021 at the Naples 3 local health authority. AEFIs were stratified and described according to mRNA vaccine, demographics, clinical status, description of AEFI, and degree of severity. In 2021, local health authority Asl Naples 3 South received 1164 reports of suspected adverse events that occurred following the administration of mRNA vaccines.

Results

During the reporting period, 746 reports were related to the Comirnaty vaccine (64.1%), 281 to the Vaxzevria vaccine (24.1%), 107 to the Spikevax vaccine (9.2%), and 30 to the Jcovden vaccine (2.6%); 89.3% of the reports were classified as not serious (N = 1039 reports), the remaining 10.7% as serious (N = 125 reports).

Conclusions

This retrospective pharmacovigilance study demonstrates that COVID-19 mRNA vaccines are safe in all population groups.

Pharmacovigilance is an activity that ensures the safety of health care treatments. The COVID-19 pandemic has accelerated the administration of vaccines whose efficacy and safety is to be evaluated. In the year 2021, an analysis of all reported adverse events following immunization (AEFIs) to the vaccine was conducted on a sample of about 1 million people with the aim of understanding efficacy and safety. All adverse events were divided by age, sex, type of reaction, and severity. Serious reactions were divided into subcategories to report the most common critical issues. At the conclusion of the work, it can be seen that COVID-19 mRNA vaccines are safe but can give serious cardiovascular (12% of the total number of serious reports) and neurological (one serious case that led to the development of Guillain Barré syndrome) side effects that need to be monitored by medical personnel.