Structural Analysis of the SARS-CoV-2 Omicron Variant Proteins

SARS-CoV-2 Omicron Variants Show Attenuated Neurovirulence Compared with the Wild-Type Strain in Elderly Human Brain Spheroids

Infection with severe acute respiratory syndrome coronavirus 2 Omicron variants still causes neurological complications in elderly individuals. However, whether and how aging brains are affected by Omicron variants in terms of neuroinvasiveness and neurovirulence are unknown. Here, we utilize resected paracarcinoma brain tissue from elderly individuals to generate primary brain spheroids (BSs) for investigating the replication capability of live wild-type (WT) strain and Omicron (BA.1/BA.2), as well as the mechanisms underlying their neurobiological effects. We find that both WT and Omicron BA.1/BA.2 are able to enter BSs but weakly replicate. There is no difference between Omicron BA.1/BA.2 and WT strains in neurotropism in aging BSs. However, Omicron BA.1/BA.2 exhibits ameliorating neurological damage. Transcriptional profiling indicates that Omicron BA.1/BA.2 induces a lower neuroinflammatory response than WT strain in elderly BSs, suggesting a mechanistic explanation for their attenuated neuropathogenicity. Moreover, we find that both Omicron BA.1/BA.2 and WT strain infections disrupt neural network activity associated with neurodegenerative disorders by causing neuron degeneration and amyloid-β deposition in elderly BSs. These results uncover Omicron-specific mechanisms and cellular immune responses associated with severe acute respiratory syndrome coronavirus 2-induced neurological complications.

Wide Real-Life Data Support Reduced Sensitivity of Antigen Tests for Omicron SARS-CoV-2 Infections

With the continuous spread of new SARS-CoV-2 variants of concern (VOCs), the monitoring of diagnostic test performances is mandatory. We evaluated the changes in antigen diagnostic tests' (ADTs) accuracy along the Delta to Omicron VOCs transition, exploring the N protein mutations possibly affecting ADT sensitivity and assessing the best sampling site for the diagnosis of Omicron infections. In total, 5175 subjects were enrolled from 1 October 2021 to 15 July 2022. The inclusion criteria were SARS-CoV-2 ADT combined with a same-day RT-PCR swab test. For the sampling site analysis, 61 patients were prospectively recruited during the Omicron period for nasal and oral swab analyses by RT-PCR. Next-Generation Sequencing data were obtained to evaluate the different sublineages. Using RT-PCR as a reference, 387 subjects resulted in becoming infected and the overall sensitivity of the ADT decreased from 63% in the Delta period to 33% in the Omicron period. This decrease was highly statistically significant (p < 0.001), and no decrease in viral load was detected at the RNA level. The nasal site presented a significantly higher viral load than the oral site during the Omicron wave. The reduced detection rate of Omicron infections by ADT should be considered in the global testing strategy to preserve accurate diagnoses across the changing SARS-CoV-2 variants.

AlphaFold2 Reveals Structural Patterns of Seasonal Haplotype Diversification in SARS-CoV-2 Spike Protein Variants

The slow experimental acquisition of high-quality atomic structures of the rapidly changing proteins of the COVID-19 virus challenges vaccine and therapeutic drug development efforts. Fortunately, deep learning tools such as AlphaFold2 can quickly generate reliable models of atomic structure at experimental resolution. Current modeling studies have focused solely on definitions of mutant constellations of Variants of Concern (VOCs), leaving out the impact of haplotypes on protein structure. Here, we conduct a thorough comparative structural analysis of S-proteins belonging to major VOCs and corresponding latitude-delimited haplotypes that affect viral seasonal behavior. Our approach identified molecular regions of importance as well as patterns of structural recruitment. The S1 subunit hosted the majority of structural changes, especially those involving the N-terminal domain (NTD) and the receptor-binding domain (RBD). In particular, structural changes in the NTD were much greater than just translations in three-dimensional space, altering the sub-structures to greater extents. We also revealed a notable pattern of structural recruitment with the early VOCs Alpha and Delta behaving antagonistically by suppressing regions of structural change introduced by their corresponding haplotypes, and the current VOC Omicron behaving synergistically by amplifying or collecting structural change. Remarkably, haplotypes altering the galectin-like structure of the NTD were major contributors to seasonal behavior, supporting its putative environmental-sensing role. Our results provide an extensive view of the evolutionary landscape of the S-protein across the COVID-19 pandemic. This view will help predict important regions of structural change in future variants and haplotypes for more efficient vaccine and drug development.

Hydroxypropyl-Beta Cyclodextrin Barrier Prevents Respiratory Viral Infections: A Preclinical Study

The emergence and mutation of pathogenic viruses have been occurring at an unprecedented rate in recent decades. The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has developed into a global public health crisis due to extensive viral transmission. In situ RNA mapping has revealed angiotensin-converting enzyme 2 (ACE2) expression to be highest in the nose and lower in the lung, pointing to nasal susceptibility as a predominant route for infection and the cause of subsequent pulmonary effects. By blocking viral attachment and entry at the nasal airway using a cyclodextrin-based formulation, a preventative therapy can be developed to reduce viral infection at the site of entry. Here, we assess the safety and antiviral efficacy of cyclodextrin-based formulations. From these studies, hydroxypropyl beta-cyclodextrin (HPBCD) and hydroxypropyl gamma-cyclodextrin (HPGCD) were then further evaluated for antiviral effects using SARS-CoV-2 pseudotypes. Efficacy findings were confirmed with SARS-CoV-2 Delta variant infection of Calu-3 cells and using a K18-hACE2 murine model. Intranasal pre-treatment with HPBCD-based formulations reduced viral load and inflammatory signaling in the lung. In vitro efficacy studies were further conducted using lentiviruses, murine hepatitis virus (MHV), and influenza A virus subtype H1N1. These findings suggest HPBCD may be used as an agnostic barrier against transmissible pathogens, including but not limited to SARS-CoV-2.

AlphaFold2 and its applications in the fields of biology and medicine

AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind that can predict three-dimensional (3D) structures of proteins from amino acid sequences with atomic-level accuracy. Protein structure prediction is one of the most challenging problems in computational biology and chemistry, and has puzzled scientists for 50 years. The advent of AF2 presents an unprecedented progress in protein structure prediction and has attracted much attention. Subsequent release of structures of more than 200 million proteins predicted by AF2 further aroused great enthusiasm in the science community, especially in the fields of biology and medicine. AF2 is thought to have a significant impact on structural biology and research areas that need protein structure information, such as drug discovery, protein design, prediction of protein function, et al. Though the time is not long since AF2 was developed, there are already quite a few application studies of AF2 in the fields of biology and medicine, with many of them having preliminarily proved the potential of AF2. To better understand AF2 and promote its applications, we will in this article summarize the principle and system architecture of AF2 as well as the recipe of its success, and particularly focus on reviewing its applications in the fields of biology and medicine. Limitations of current AF2 prediction will also be discussed.

SARS-CoV-2 Spike Protein Post-Translational Modification Landscape and Its Impact on Protein Structure and Function via Computational Prediction

To elucidate the role of post-translational modifications (PTMs) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein's structure and virulence, we generated a high-resolution map of 87 PTMs using liquid chromatography with tandem mass spectrometry data on the extracted spike protein from SARS-CoV-2 virions and then reconstituted its structure heterogeneity caused by PTMs. Nonetheless, Alphafold2, a high-accuracy artificial intelligence tool to perform protein structure prediction, relies solely on primary amino acid sequence, whereas the impact of PTM, which often modulates critical protein structure and function, is much ignored. To overcome this challenge, we proposed the mutagenesis approach-an in silico, site-directed amino acid substitution to mimic the influence of PTMs on protein structure due to altered physicochemical properties in the post-translationally modified amino acids-and then reconstituted the spike protein's structure from the substituted sequences by Alphafold2. For the first time, the proposed method revealed predicted protein structures resulting from PTMs, a problem that Alphafold2 has yet to address. As an example, we performed computational analyses of the interaction of the post-translationally modified spike protein with its host factors such as angiotensin-converting enzyme 2 to illuminate binding affinity. Mechanistically, this study suggested the structural analysis of post-translationally modified protein via mutagenesis and deep learning. To summarize, the reconstructed spike protein structures showed that specific PTMs can be used to modulate host factor binding, guide antibody design, and pave the way for new therapeutic targets. The code and Supplementary Materials are freely available at https://github.com/LTZHKUSTGZ/SARS-CoV-2-spike-protein-PTM.

Targeting viral proteins for restraining SARS-CoV-2: focusing lens on viral proteins beyond spike for discovering new drug targets

INTRODUCTION

Emergence of highly infectious SARS-CoV-2 variants are reducing protection provided by current vaccines, requiring constant updates in antiviral approaches. The virus encodes four structural and sixteen nonstructural proteins which play important roles in viral genome replication and transcription, virion assembly, release , entry into cells, and compromising host cellular defenses. As alien proteins to host cells, many viral proteins represent potential targets for combating the SARS-CoV-2.

AREAS COVERED

Based on literature from PubMed and Web of Science databases, the authors summarize the typical characteristics of SARS-CoV-2 from the whole viral particle to the individual viral proteins and their corresponding functions in virus life cycle. The authors also discuss the potential and emerging targeted interventions to curb virus replication and spread in detail to provide unique insights into SARS-CoV-2 infection and countermeasures against it.

EXPERT OPINION

Our comprehensive analysis highlights the rationale to focus on non-spike viral proteins that are less mutated but have important functions. Examples of this include: structural proteins (e.g. nucleocapsid protein, envelope protein) and extensively-concerned nonstructural proteins (e.g. NSP3, NSP5, NSP12) along with the ones with relatively less attention (e.g. NSP1, NSP10, NSP14 and NSP16), for developing novel drugs to overcome resistance of SARS-CoV-2 variants to preexisting vaccines and antibody-based treatments.

Comparison of Rapid Antigen Tests' Performance Between Delta and Omicron Variants of SARS-CoV-2 : A Secondary Analysis From a Serial Home Self-testing Study

BACKGROUND

It is important to document the performance of rapid antigen tests (Ag-RDTs) in detecting SARS-CoV-2 variants.

OBJECTIVE

To compare the performance of Ag-RDTs in detecting the Delta (B.1.617.2) and Omicron (B.1.1.529) variants of SARS-CoV-2.

DESIGN

Secondary analysis of a prospective cohort study that enrolled participants between 18 October 2021 and 24 January 2022. Participants did Ag-RDTs and collected samples for reverse transcriptase polymerase chain reaction (RT-PCR) testing every 48 hours for 15 days.

SETTING

The parent study enrolled participants throughout the mainland United States through a digital platform. All participants self-collected anterior nasal swabs for rapid antigen testing and RT-PCR testing. All Ag-RDTs were completed at home, whereas nasal swabs for RT-PCR were shipped to a central laboratory.

PARTICIPANTS

Of 7349 participants enrolled in the parent study, 5779 asymptomatic persons who tested negative for SARS-CoV-2 on day 1 of the study were eligible for this substudy.

MEASUREMENTS

Sensitivity of Ag-RDTs on the same day as the first positive (index) RT-PCR result and 48 hours after the first positive RT-PCR result.

RESULTS

A total of 207 participants were positive on RT-PCR (58 Delta, 149 Omicron). Differences in sensitivity between variants were not statistically significant (same day: Delta, 15.5% [95% CI, 6.2% to 24.8%] vs. Omicron, 22.1% [CI, 15.5% to 28.8%]; at 48 hours: Delta, 44.8% [CI, 32.0% to 57.6%] vs. Omicron, 49.7% [CI, 41.6% to 57.6%]). Among 109 participants who had RT-PCR-positive results for 48 hours, rapid antigen sensitivity did not differ significantly between Delta- and Omicron-infected participants (48-hour sensitivity: Delta, 81.5% [CI, 66.8% to 96.1%] vs. Omicron, 78.0% [CI, 69.1% to 87.0%]). Only 7.2% of the 69 participants with RT-PCR-positive results for shorter than 48 hours tested positive by Ag-RDT within 1 week; those with Delta infections remained consistently negative on Ag-RDTs.

LIMITATION

A testing frequency of 48 hours does not allow a finer temporal resolution of the analysis of test performance, and the results of Ag-RDTs are based on self-report.

CONCLUSION

The performance of Ag-RDTs in persons infected with the SARS-CoV-2 Omicron variant is not inferior to that in persons with Delta infections. Serial testing improved the sensitivity of Ag-RDTs for both variants. The performance of rapid antigen testing varies on the basis of duration of RT-PCR positivity.

PRIMARY FUNDING SOURCE

National Heart, Lung, and Blood Institute of the National Institutes of Health.

Rapidly identifying new coronavirus mutations of potential concern in the Omicron variant using an unsupervised learning strategy

Extensive mutations in the Omicron spike protein appear to accelerate the transmission of SARS-CoV-2, and rapid infections increase the odds that additional mutants will emerge. To build an investigative framework, we have applied an unsupervised machine learning approach to 4296 Omicron viral genomes collected and deposited to GISAID as of December 14, 2021, and have identified a core haplotype of 28 polymutants (A67V, T95I, G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, K796Y, N856K, Q954H, N69K, L981F) in the spike protein and a separate core haplotype of 17 polymutants in non-spike genes: (K38, A1892) in nsp3, T492 in nsp4, (P132, V247, T280, S284) in 3C-like proteinase, I189 in nsp6, P323 in RNA-dependent RNA polymerase, I42 in Exonuclease, T9 in envelope protein, (D3, Q19, A63) in membrane glycoprotein, and (P13, R203, G204) in nucleocapsid phosphoprotein. Using these core haplotypes as reference, we have identified four newly emerging polymutants (R346, A701, I1081, N1192) in the spike protein (p value = 9.37*10-4, 1.0*10-15, 4.76*10-7 and 1.56*10-4, respectively), and five additional polymutants in non-spike genes (D343G in nucleocapsid phosphoprotein, V1069I in nsp3, V94A in nsp4, F694Y in the RNA-dependent RNA polymerase and L106L/F of ORF3a) that exhibit significant increasing trajectories (all p values < 1.0*10-15). In the absence of relevant clinical data for these newly emerging mutations, it is important to monitor them closely. Two emerging mutations may be of particular concern: the N1192S mutation in spike protein locates in an extremely highly conserved region of all human coronaviruses that is integral to the viral fusion process, and the F694Y mutation in the RNA polymerase may induce conformational changes that could impact remdesivir binding.

Plaque-neutralizing antibody to BA.2.12.1, BA.4 and BA.5 in individuals with three doses of BioNTech or CoronaVac vaccines, natural infection and breakthrough infection

BACKGROUND

BA.2.12.1, BA.4 and BA.5 subvariants of SARS-CoV-2 variant-of-concern (VOC) Omicron (B.1.1.529) are spreading globally. They demonstrate higher transmissibility and immune escape.

OBJECTIVES

Determine BA.2.12.1, BA.4 and BA.5 virus plaque reduction neutralization test (PRNT) antibody titres in individuals recently vaccinated with BNT162b2 (n = 20) or CoronaVac (n = 20) vaccines or those convalescent from ancestral wild- type (WT) SARS-CoV-2 (n = 20) or BA.2 infections with (n = 17) or without (n = 7) prior vaccination.

RESULTS

Relative to neutralization of the WT virus, those vaccinated with BNT162b2 had 4.8, 3.4, 4.6, 11.3 and 15.5-fold reductions of geometric mean antibody titres (GMT) to BA.1, BA.2, BA.2.12.1, BA.4 and BA.5 viruses, respectively. Similarly, those vaccinated with CoronaVac had 8.0, 7.0, 11.8, 12.0 and 12.0 fold GMT reductions and those with two doses of CoronaVac boosted by BNT162b2 had 6.1, 6.7, 6,3, 13.0 and 21.2 fold GMT reductions to these viruses, respectively. Vaccinated individuals with BA.2 breakthrough infections had higher GMT antibody levels vs. BA.4 (36.9) and BA.5 (36.9) than unvaccinated individuals with BA.2 infections (BA.4 GMT 8.2; BA.5 GMT 11.0).

CONCLUSIONS

BA.4 and BA.5 subvariants were less susceptible to BNT162b2 or CoronaVac vaccine elicited antibody neutralization than subvariants BA.1, BA.2 and BA.2.12.1. Nevertheless, three doses BNT162b2 or booster of BNT162b2 following two doses of CoronaVac elicited detectable BA.4 and BA.5 neutralizing antibody responses while those vaccinated with three doses of CoronaVac largely fail to do so. BA.2 infections in vaccinated individuals led to higher levels of BA.4 or BA.5 neutralizing antibody compared to those who were vaccine-naive.

Comparative highlights on MERS-CoV, SARS-CoV-1, SARS-CoV-2, and NEO-CoV

The severe acute respiratory syndrome (SARS-CoV, now SARS-CoV-1), middle east respiratory syndrome (MERS-CoV), Neo-CoV, and 2019 novel coronavirus (SARS-CoV-2/COVID-19) are the most notable coronaviruses, infecting the number of people worldwide by targeting the respiratory system. All these viruses are of zoonotic origin, predominantly from bats which are one of the natural reservoir hosts for coronaviruses. Thus, the major goal of our review article is to compare and contrast the characteristics and attributes of these coronaviruses. The SARS-CoV-1, MERS-CoV, and COVID-19 have many viral similarities due to their classification, they are not genetically related. COVID-19 shares approximately 79 % of its genome with SARS-CoV-1 and about 50 % with MERS-CoV. The shared receptor protein, ACE2 exhibit the most striking genetic similarities between SARS-CoV-1 and SARS-CoV-2. SARS-CoV primarily replicates in the epithelial cells of the respiratory system, but it may also affect macrophages, monocytes, activated T cells, and dendritic cells. MERS-CoV not only infects and replicates inside the epithelial and immune cells, but it may lyse them too, which is one of the common reasons for MERS's higher mortality rate. The details of infections caused by SARS-CoV-2 and lytic replication mechanisms in host cells are currently mysterious. In this review article, we will discuss the comparative highlights of SARS-CoV-1, MERS-CoV, SARS-CoV-2, and Neo-CoV, concerning their structural features, morphological characteristics, sources of virus origin and their evolutionary transitions, infection mechanism, computational study approaches, pathogenesis and their severity towards several diseases, possible therapeutic approaches, and preventive measures.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and humoral responses against different variants of concern in domestic pet animals and stray cats from North-Eastern Spain

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the coronavirus disease 2019 (COVID-19) pandemic in humans, is able to infect several domestic, captive and wildlife animal species. Since reverse zoonotic transmission to pets has been demonstrated, it is crucial to determine their role in the epidemiology of the disease to prevent further spillover events and major spread of SARS-CoV-2. In the present study, we determined the presence of virus and the seroprevalence to SARS-CoV-2, as well as the levels of neutralizing antibodies (nAbs) against several variants of concern (VOCs) in pets (cats, dogs and ferrets) and stray cats from North-Eastern of Spain. We confirmed that cats and dogs can be infected by different VOCs of SARS-CoV-2 and, together with ferrets, are able to develop nAbs against the ancestral (B.1), Alpha (B.1.1.7), Beta (B.1.315), Delta (B.1.617.2) and Omicron (BA.1) variants, with lower titres against the latest in dogs and cats, but not in ferrets. Although the prevalence of active SARS-CoV-2 infection measured as direct viral RNA detection was low (0.3%), presence of nAbs in pets living in COVID-19-positive households was relatively high (close to 25% in cats, 10% in dogs and 40% in ferrets). It is essential to continue monitoring SARS-CoV-2 infections in these animals due to their frequent contact with human populations, and we cannot discard the probability of a higher animal susceptibility to new potential SARS-CoV-2 VOCs.

Deep learning-based molecular dynamics simulation for structure-based drug design against SARS-CoV-2

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), has led to a global pandemic. Deep learning (DL) technology and molecular dynamics (MD) simulation are two mainstream computational approaches to investigate the geometric, chemical and structural features of protein and guide the relevant drug design. Despite a large amount of research papers focusing on drug design for SARS-COV-2 using DL architectures, it remains unclear how the binding energy of the protein-protein/ligand complex dynamically evolves which is also vital for drug development. In addition, traditional deep neural networks usually have obvious deficiencies in predicting the interaction sites as protein conformation changes. In this review, we introduce the latest progresses of the DL and DL-based MD simulation approaches in structure-based drug design (SBDD) for SARS-CoV-2 which could address the problems of protein structure and binding prediction, drug virtual screening, molecular docking and complex evolution. Furthermore, the current challenges and future directions of DL-based MD simulation for SBDD are also discussed.

Decoding molecular factors shaping human angiotensin converting enzyme 2 receptor usage by spike glycoprotein in lineage B beta-coronaviruses

Acquiring the human ACE2 receptor usage trait enables the coronaviruses to spill over to humans. However, the origin of the ACE2 usage trait in coronaviruses is poorly understood. Using a multi-disciplinary approach combining evolutionary bioinformatics and molecular dynamics simulation, we decode the principal driving force behind human ACE2 receptor recognition in coronaviruses. Genomic content, evolutionary divergence, and codon usage bias analysis reveal that SARS-CoV2 is evolutionarily divergent from other human ACE2-user CoVs, indicating that SARS-CoV2 originates from a different lineage. Sequence analysis shows that all the human ACE2-user CoVs contain two insertions in the receptor-binding motif (RBM) that directly interact with ACE2. However, the insertion sequences in SARS-CoV2 are divergent from other ACE2-user CoVs, implicating their different recombination origins. The potential of mean force calculations reveals that the high binding affinity of SARS-CoV2 RBD to human ACE2 is primarily attributed to its ability to form a higher number of hydrogen bonds than the other ACE2-user CoVs. The adaptive branch-site random effects likelihood method identifies positive selection bias across the ACE2 user CoVs lineages. Recombination and selection forces shape the spike evolution in human ACE2-using beta-CoVs to optimize the interfacial hydrogen bonds between RBD and ACE2. However, these evolutionary forces work within the constraints of nucleotide composition, ensuring optimum codon adaptation of the spike (S) gene within the host cell.

SARS-CoV-2 Variants, Vaccines, and Host Immunity

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new beta coronavirus that emerged at the end of 2019 in the Hubei province of China. SARS-CoV-2 causes coronavirus disease 2019 (COVID-19) and was declared a pandemic by the World Health Organization (WHO) on 11 March 2020. Herd or community immunity has been proposed as a strategy to protect the vulnerable, and can be established through immunity from past infection or vaccination. Whether SARS-CoV-2 infection results in the development of a reservoir of resilient memory cells is under investigation. Vaccines have been developed at an unprecedented rate and 7 408 870 760 vaccine doses have been administered worldwide. Recently emerged SARS-CoV-2 variants are more transmissible with a reduced sensitivity to immune mechanisms. This is due to the presence of amino acid substitutions in the spike protein, which confer a selective advantage. The emergence of variants therefore poses a risk for vaccine effectiveness and long-term immunity, and it is crucial therefore to determine the effectiveness of vaccines against currently circulating variants. Here we review both SARS-CoV-2-induced host immune activation and vaccine-induced immune responses, highlighting the responses of immune memory cells that are key indicators of host immunity. We further discuss how variants emerge and the currently circulating variants of concern (VOC), with particular focus on implications for vaccine effectiveness. Finally, we describe new antibody treatments and future vaccine approaches that will be important as we navigate through the COVID-19 pandemic.

How to translate the knowledge of COVID-19 into the prevention of Omicron variants

Omicron variants are part of the "Coronavirus disease 2019 [COVID-19] Variants of Concerns" and has the potential to spread around the world rapidly and can harm human life. We can anticipate that the endemic state of COVID-19 will be characterized by the development of new strains with surges that will predominate in unvaccinated and immunodeficient populations. Thus, there will be an important role in promoting vaccinations, boosters and accessible testing to prevent disease transmission and to rapidly detect surges. There is an urgent need to explore the virology and biology of Omicron variants, define clinical phenomes and therapies, monitor dynamics of genetic changes, and translate the knowledge of COVID-19 into new variants. Clinical and translational medicine will be impactful in addressing these challenges by providing new insights for understanding and predicting new variants-associated transmissibility, disease severity, immune escape, diagnostic or therapeutic failure.