Polymorphism and Selection Pressure of SARS-CoV-2 Vaccine and Diagnostic Antigens: Implications for Immune Evasion and Serologic Diagnostic Performance.

The ongoing SARS-CoV-2 pandemic has triggered multiple efforts for serological tests and vaccine development. Most of these tests and vaccines are based on the Spike glycoprotein (S) or the Nucleocapsid (N) viral protein. Conservation of these antigens among viral strains is critical to ensure optimum diagnostic test performance and broad protective efficacy, respectively. We assessed N and S antigen diversity from 17,853 SARS-CoV-2 genome sequences and evaluated selection pressure. Up to 6-7 incipient phylogenetic clades were identified for both antigens, confirming early variants of the S antigen and identifying new ones. Significant diversifying selection was detected at multiple sites for both antigens. Some sequence variants have already spread in multiple regions, in spite of their low frequency. In conclusion, the N and S antigens of SARS-CoV-2 are well-conserved antigens, but new clades are emerging and may need to be included in future diagnostic and vaccine formulations.

Antigenic characterization of influenza and SARS-CoV-2 viruses.

Antigenic characterization of emerging and re-emerging viruses is necessary for the prevention of and response to outbreaks, evaluation of infection mechanisms, understanding of virus evolution, and selection of strains for vaccine development. Primary analytic methods, including enzyme-linked immunosorbent/lectin assays, hemagglutination inhibition, neuraminidase inhibition, micro-neutralization assays, and antigenic cartography, have been widely used in the field of influenza research. These techniques have been improved upon over time for increased analytical capacity, and some have been mobilized for the rapid characterization of the SARS-CoV-2 virus as well as its variants, facilitating the development of highly effective vaccines within 1 year of the initially reported outbreak. While great strides have been made for evaluating the antigenic properties of these viruses, multiple challenges prevent efficient vaccine strain selection and accurate assessment. For influenza, these barriers include the requirement for a large virus quantity to perform the assays, more than what can typically be provided by the clinical samples alone, cell- or egg-adapted mutations that can cause antigenic mismatch between the vaccine strain and circulating viruses, and up to a 6-month duration of vaccine development after vaccine strain selection, which allows viruses to continue evolving with potential for antigenic drift and, thus, antigenic mismatch between the vaccine strain and the emerging epidemic strain. SARS-CoV-2 characterization has faced similar challenges with the additional barrier of the need for facilities with high biosafety levels due to its infectious nature. In this study, we review the primary analytic methods used for antigenic characterization of influenza and SARS-CoV-2 and discuss the barriers of these methods and current developments for addressing these challenges.

Vaccine effectiveness against influenza A(H3N2)-associated hospitalized illness, United States, 2022.

BACKGROUND: The COVID-19 pandemic was associated with historically low influenza circulation during the 2020-2021 season, followed by increase in influenza circulation during the 2021-2022 US season. The 2a.2 subgroup of the influenza A(H3N2) 3C.2a1b subclade that predominated was antigenically different from the vaccine strain. METHODS: To understand the effectiveness of the 2021-2022 vaccine against hospitalized influenza illness, a multi-state sentinel surveillance network enrolled adults aged ≥18 years hospitalized with acute respiratory illness (ARI) and tested for influenza by a molecular assay. Using the test-negative design, vaccine effectiveness (VE) was measured by comparing the odds of current season influenza vaccination in influenza-positive case-patients and influenza-negative, SARS-CoV-2-negative controls, adjusting for confounders. A separate analysis was performed to illustrate bias introduced by including SARS-CoV-2 positive controls. RESULTS: A total of 2334 patients, including 295 influenza cases (47% vaccinated), 1175 influenza- and SARS-CoV-2 negative controls (53% vaccinated), and 864 influenza-negative and SARS-CoV-2 positive controls (49% vaccinated), were analyzed. Influenza VE was 26% (95%CI: -14 to 52%) among adults aged 18-64 years, -3% (95%CI: -54 to 31%) among adults aged ≥65 years, and 50% (95%CI: 15 to 71%) among adults 18-64 years without immunocompromising conditions. Estimated VE decreased with inclusion of SARS-CoV-2-positive controls. CONCLUSIONS: During a season where influenza A(H3N2) was antigenically different from the vaccine virus, vaccination was associated with a reduced risk of influenza hospitalization in younger immunocompetent adults. However, vaccination did not provide protection in adults ≥65 years of age. Improvements in vaccines, antivirals, and prevention strategies are warranted.

Genomic surveillance of SARS-CoV-2 in Kenya: March 2020-October 2021

Introduction/ Background: By end of October 2021, the Ministry of Health had confirmed over 250 thousand SARS-CoV-2 cases in Kenya following identification of the initial cases in March 2020. We setup a genome surveillance platform in Kenya to track introductions, local evolution and transmission of SARS-CoV-2 within the country and the region. Methods: Samples were collected from designated diagnostic centres across 47 Kenyan counties. Viral RNA was extracted from the Nasal and oropharyngeal swabs from RT-PCR confirmed cases followed by viral amplification of recovered cDNA using the ARTIC nCoV-2019 primer set and thereafter library preparation and sequencing using the Oxford Nanopore MinION platform. The raw signal files were base-called and processed to obtain consensus sequences followed by SARSCoV- 2 lineage assignment and phylogenetics analysis. Results: Phylogenetics and epidemiological analysis of 4,200 sequences provided insight on introduction of SARSCoV- 2 in Kenya. The first (March-September 2020), second (October 2020-February 2021) waves of infections were dominated by B-like lineages. The third wave (March-June 2021) coincided with introduction of Alpha and Beta variants (December 2020), merging into the fourth wave (June-October 2021), the Delta variant in April 2021. Ancestral reconstruction identified multiple introductions of the basal lineages (37<n<69) and Variants of Concern (Beta (n=14), Alpha (n=83), Delta (n=92)). We observed rapid replacement of ancestral lineages leading to dominance of the Delta variant that comprised the fourth wave of infections. Impact: Our genomic surveillance platform has improved monitoring of the diversity of circulating variants of concern (VOCs) and revealed transitions across the country in the dominance VOCs detected between late 2020 to October 2021. This output had fed into national decision-making through regular policy briefs. Conclusion: The Delta variant is the dominant variant of concern across the country. Genomic surveillance of SARSCoV- 2 should focus on identifying the emergence of local mutations with the potential to confer additional transmissibility and antigenic drift, particularly in the background of inadequate vaccine coverage and waning natural immunity.

Message in a bottle: mRNA vaccination for influenza.

Current influenza vaccines, while being the best method of managing viral outbreaks, have several major drawbacks that prevent them from being wholly-effective. They need to be updated regularly and require extensive resources to develop. When considering alternatives, the recent deployment of mRNA vaccines for SARS-CoV-2 has created a unique opportunity to evaluate a new platform for seasonal and pandemic influenza vaccines. The mRNA format has previously been examined for application to influenza and promising data suggest it may be a viable format for next-generation influenza vaccines. Here, we discuss the prospect of shifting global influenza vaccination efforts to an mRNA-based system that might allow better control over the product and immune responses and could aid in the development of a universal vaccine.

Relatively rapid evolution rates of SARS-CoV-2 spike gene at the primary stage of massive vaccination.

A series of stringent non-pharmacological and pharmacological interventions were implemented to contain the pandemic but the pandemic continues. Moreover, vaccination breakthrough infection and reinfection in convalescent coronavirus disease 2019 (COVID-19) cases have been reported. Further, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants emerged with mutations in spike (S) gene, the target of most current vaccines. Importantly, the mutations exhibit a trend of immune escape from the vaccination. Herein the scientific question that if the vaccination drives genetic or antigenic drifts of SARS-CoV-2 remains elusive. We performed correlation analyses to uncover the impacts of wide vaccination on epidemiological characteristics of COVID-19. In addition, we investigated the evolutionary dynamics and genetic diversity of SARS-CoV-2 under immune pressure by utilizing the Bayesian phylodynamic inferences and the lineage entropy calculation respectively. We found that vaccination coverage was negatively related to the infections, severe cases, and deaths of COVID-19 respectively. With the increasing vaccination coverage, the lineage diversity of SARS-CoV-2 dampened, but the rapid mutation rates of the S gene were identified, and the vaccination could be one of the explanations for driving mutations in S gene. Moreover, new epidemics resurged in several countries with high vaccination coverage, questioning their current pandemic control strategies. Hence, integrated vaccination and non-pharmacological interventions are critical to control the pandemic. Furthermore, novel vaccine preparation should enhance its capabilities to curb both disease severity and infection possibility.

Immune-evasion Conferring Mutations Associated with Cases of Breakthrough SARS-CoV-2 Infection among Walk-in Patients

Introduction: India recently faced a devastating second outbreak of COVID-19 infection, in which a majority of the viral sequences were found to be of the B.1.617.2 lineage. While India and the world focused on vaccination, reports of vaccine evasion by the virus, termed 'breakthrough cases', emerged worldwide. Materials and Methods: We analysed whole genome sequences of 150 SARS-CoV-2 viral samples isolated at our laboratory. We retrospectively found 9 cases of breakthrough infection, five of whom were fully, and four partially vaccinated. We followed-up these patients and can report that the variant lineages associated with these cases were B.1.617, B.1, and A. The mutations seen in these sequences in the Spike and ORF regions would have produced amino acid changes known to improve viral replication, confer drug resistance, influence host-cell interaction, and lead to antigenic drift. Increased virulence culminating in vaccine evasion may be inferred from these mutations. India, recently faced a devastating second outbreak of COVID-19 infection, in which a majority of the viral sequences were found to be of the B.1.617.2 lineage. While India and the world focused on vaccination, reports of vaccine evasion by the virus, termed 'breakthrough cases', emerged worldwide. We isolated mRNA from SARS-CoV-2 samples and outsourced them for whole genome sequencing. Results: We noticed that nine individuals had been fully (two doses of vaccine) or partially (one dose) vaccinated at least 14 days before infection. When we examined the sequences from these individuals, we found amino acid changes in the spike and NSP proteins, which were predicted to confer increased virulence upon the virus. We report the presence of three strains in the breakthrough cases;A, B.1, and B.1.617 (Nextstrain Clade G). We found one mutation, NSP6 T77A, that was present in both A and B.1 strains in the breakthrough cases, but not in other A and B.1 strains isolated, from patients of the same city. Additionally, we found multiple changes in the non-structural NSP proteins, which enable faster viral replication. Conclusion: It is clear from our case series that the strains A, B.1, and B.1.617 can attain increased virulence culminating in vaccine evasion.

Seasonal Variation of Influenza A Virus and Its Subtypes in Patients Attending Tertiary Care Hospital

Background:Influenza is an important respiratory infection, causing 250,000 to 500,000 deaths annually. Influenza virus A is the most virulent and associated with winter epidemics in temperate regions, more persistent transmission in the tropics, and occasional large-scale global pandemics. But, there is variability in the pattern, and the H1N1 pandemic of 2009-2010 was unusually with a large spike in spring and a sharp decline continuing throughout winter. Varying in pattern is due to antigenic shift and drift and reassortment of the virus. Methods:A prospective study was carried out in Advance Basic Sciences & Clinical Research Lab, Department of Micro- biology in SMS Medical College & Hospital, Jaipur for diagnosis of Influenza A virus as well as subtyping was done using RT-PCR technique over 1 year period (July 2019 to June 2020) and demographic data was noted. Results:Total of 7213 samples were tested, out of which 498 (6.90%) were positive for Influenza A which is less from the previous year’s 22.46%. Out of total positive cases Influenza a (H1N1) pdm09 was 24.9% and InfA H3N2 was 75.10%. InfA H3N2 was the prominent circulating strain in all months while Influenza a (H1N1) pdm09 was prominent strain pre- vious year. Majority of positive cases were found in March 2020 (43.17%), September 2019 (28.51%). Most of these cases 36.14% were from age group between 20 to 40 years. Conclusions: A decline in the positivity of influenza infection compared to last year is seen which could be in part due to circulation of SARS COV 2 and measures of prevention undertaken by community to prevent it. Demographic parame- ters and seasonal variation of Influenza A virus give ideas to create awareness and to improve control strategies to mini- mize the morbidity, mortality and spread of disease.

Insights on the mutational landscape of the SARS-CoV-2 Omicron variant receptor-binding domain.

The Omicron variant features enhanced transmissibility and antibody escape. Here, we describe the Omicron receptor-binding domain (RBD) mutational landscape using amino acid interaction (AAI) networks, which are well suited for interrogating constellations of mutations that function in an epistatic manner. Using AAI, we map Omicron mutations directly and indirectly driving increased escape breadth and depth in class 1-4 antibody epitopes. Further, we present epitope networks for authorized therapeutic antibodies and assess perturbations to each antibody's epitope. Since our initial modeling following the identification of Omicron, these predictions have been realized by experimental findings of Omicron neutralization escape from therapeutic antibodies ADG20, AZD8895, and AZD1061. Importantly, the AAI predicted escape resulting from indirect epitope perturbations was not captured by previous sequence or point mutation analyses. Finally, for several Omicron RBD mutations, we find evidence for a plausible role in enhanced transmissibility via disruption of RBD-down conformational stability at the RBDdown-RBDdown interface.

Adaptation of the endemic coronaviruses HCoV-OC43 and HCoV-229E to the human host.

Four coronaviruses (HCoV-OC43, HCoV-HKU1, HCoV-NL63, and HCoV-229E) are endemic in human populations. All these viruses are seasonal and generate short-term immunity. Like the highly pathogenic coronaviruses, the endemic coronaviruses have zoonotic origins. Thus, understanding the evolutionary dynamics of these human viruses might provide insight into the future trajectories of SARS-CoV-2 evolution. Because the zoonotic sources of HCoV-OC43 and HCoV-229E are known, we applied a population genetics-phylogenetic approach to investigate which selective events accompanied the divergence of these viruses from the animal ones. Results indicated that positive selection drove the evolution of some accessory proteins, as well as of the membrane proteins. However, the spike proteins of both viruses and the hemagglutinin-esterase (HE) of HCoV-OC43 represented the major selection targets. Specifically, for both viruses, most positively selected sites map to the receptor-binding domains (RBDs) and are polymorphic. Molecular dating for the HCoV-229E spike protein indicated that RBD Classes I, II, III, and IV emerged 3-9 years apart. However, since the appearance of Class V (with much higher binding affinity), around 25 years ago, limited genetic diversity accumulated in the RBD. These different time intervals are not fully consistent with the hypothesis that HCoV-229E spike evolution was driven by antigenic drift. An alternative, not mutually exclusive possibility is that strains with higher affinity for the cellular receptor have out-competed strains with lower affinity. The evolution of the HCoV-OC43 spike protein was also suggested to undergo antigenic drift. However, we also found abundant signals of positive selection in HE. Whereas such signals might result from antigenic drift, as well, previous data showing co-evolution of the spike protein with HE suggest that optimization for human cell infection also drove the evolution of this virus. These data provide insight into the possible trajectories of SARS-CoV-2 evolution, especially in case the virus should become endemic.

An Antigenic Space Framework for Understanding Antibody Escape of SARS-CoV-2 Variants.

The evolution of mutations in SARS-CoV-2 at antigenic sites that impact neutralizing antibody responses in humans poses a risk to immunity developed through vaccination and natural infection. The highly successful RNA-based vaccines have enabled rapid vaccine updates that incorporate mutations from current variants of concern (VOCs). It is therefore important to anticipate future antigenic mutations as the virus navigates the heterogeneous global landscape of host immunity. Toward this goal, we survey epitope-paratope interfaces of anti-SARS-CoV-2 antibodies to map an antigenic space that captures the role of each spike protein residue within the polyclonal antibody response directed against the ACE2-receptor binding domain (RBD) or the N-terminal domain (NTD). In particular, the antigenic space map builds on recently published epitope definitions by annotating epitope overlap and orthogonality at the residue level. We employ the antigenic space map as a framework to understand how mutations on nine major variants contribute to each variant's evasion of neutralizing antibodies. Further, we identify constellations of mutations that span the orthogonal epitope regions of the RBD and NTD on the variants with the greatest antibody escape. Finally, we apply the antigenic space map to predict which regions of antigenic space-should they mutate-may be most likely to complementarily augment antibody evasion for the most evasive and transmissible VOCs.

Cluster of Oseltamivir-Resistant and Hemagglutinin Antigenically Drifted Influenza A(H1N1)pdm09 Viruses, Texas, USA, January 2020.

Four cases of oseltamivir-resistant influenza A(H1N1)pdm09 virus infection were detected among inhabitants of a border detention center in Texas, USA. Hemagglutinin of these viruses belongs to 6B.1A5A-156K subclade, which may enable viral escape from preexisting immunity. Our finding highlights the necessity to monitor both drug resistance and antigenic drift of circulating viruses.

Antigenic sites in SARS-CoV-2 spike RBD show molecular similarity with pathogenic antigenic determinants and harbors peptides for vaccine development.

The spike protein of coronavirus is key target for drug development and other pharmacological interventions. In current study, we performed an integrative approach to predict antigenic sites in SARS-CoV-2 spike receptor binding domain and found nine potential antigenic sites. The predicted antigenic sites were then assessed for possible molecular similarity with other known antigens in different organisms. Out of nine sites, seven sites showed molecular similarity with 54 antigenic determinants found in twelve pathogenic bacterial species (Mycobacterium tuberculosis, Mycobacterium leprae, Bacillus anthracis, Borrelia burgdorferi, Clostridium perfringens, Clostridium tetani, Helicobacter Pylori, Listeria monocytogenes, Staphylococcus aureus, Streptococcus pyogenes, Vibrio cholera and Yersinia pestis), two malarial parasites (Plasmodium falciparum and Plasmodium knowlesi) and influenza virus A. Most of the bacterial antigens that displayed molecular similarity with antigenic sites in SARS-CoV-2 RBD (receptor binding domain) were toxins and virulent factors. Antigens from Mycobacterium that showed similarity were mainly involved in modulating host cell immune response and ensuring persistence and survival of pathogen in host cells. Presence of a large number of antigenic determinants, similar to those in highly pathogenic microorganisms, not merely accounts for complex etiology of the disease but also provides an explanation for observed pathophysiological complications, such as deregulated immune response, unleashed or dysregulated cytokine secretion (cytokine storm), multiple organ failure etc., that are more evident in aged and immune-compromised patients. Over-representation of antigenic determinants from Plasmodium and Mycobacterium in all antigenic sites suggests that anti-malarial and anti-TB drugs can prove to be clinical beneficial for COVID-19 treatment. Besides this, anti-leprosy, anti-lyme, anti-plague, anti-anthrax drugs/vaccine etc. are also expected to be beneficial in COVID-19 treatment. Moreover, individuals previously immunized/vaccinated or had previous history of malaria, tuberculosis or other disease caused by fifteen microorganisms are expected to display a considerable degree of resistance against SARS-CoV-2 infection. Out of the seven antigenic sites predicted in SARS-CoV-2, a part of two antigenic sites were also predicted as potent T-cell epitopes (KVGGNYNYL444-452 and SVLYNSASF366-374) against MHC class I and three (KRISNCVADYSVLYN356-370, DLCFTNVYADSFVI389-402, and YRVVVLSFELLHA508-520) against MHC class II. All epitopes possessed significantly lower predicted IC50 value which is a prerequisite for a preferred vaccine candidate for COVID-19.