Molecular epidemiology and genetic diversity of canine coronavirus from domestic dogs in Chengdu, China from 2020 to 2021 using a multiplex RT-PCR.

Recent reports on identification of canine coronavirus (CCoV) in humans have emphasized the urgency to strengthen surveillance of animal CoVs. The fact that recombinations between CCoV with feline, porcine CoVs brought about new types of CoVs indicated that more attention should be paid to domestic animals like dogs, cats and pigs, and the CoVs they carried. However, there are about ten kinds of CoVs that infect above animals, and thus representative CoVs with zoonotic potentials were considered in this study. Multiplex RT-PCR against CCoV, Feline coronavirus (FCoV), porcine deltacoronavirus and porcine acute diarrhea syndrome coronavirus was developed to investigate the prevalence of CoVs from domestic dogs in Chengdu, Southwest China. Samples from a total of 117 dogs were collected from a veterinary hospital, and only CCoV (34.2%, 40/117) was detected. Therefore, this study focused on CCoV and its characteristics of S, E, M, N and ORF3abc genes. Compared with CoVs that are capable of infecting humans, CCoV strains showed highest nucleotide identity with the novel canine-feline recombinant detected from humans (CCoV-Hupn-2018). Phylogenetic analysis based on S gene, CCoV strains were not only clustered with CCoV-II strains, but also closely related to FCoV-II strains ZJU1617 and SMU-CD59/2018. As for assembled ORF3abc, E, M, N sequences, CCoV strains had the closest relationship with CCoV-II (B203_GZ_2019, B135_JS_2018 and JS2103). What's more, specific amino acid variations were found, especially in S and N proteins, and some mutations were consistent with FCoV, TGEV strains. Altogether, this study provided a novel insight into the identification, diversification and evolution of CoVs from domestic dogs. It is of top priority to recognize zoonotic potential of CoVs, and continued comprehensive surveillance will help better understand the emergence, spreading, and ecology of animal CoVs.

Balancing Functional Tradeoffs between Protein Stability and ACE2 Binding in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB Lineages: Dynamics-Based Network Models Reveal Epistatic Effects Modulating Compensatory Dynamic and Energetic Changes.

Evolutionary and functional studies suggested that the emergence of the Omicron variants can be determined by multiple fitness trade-offs including the immune escape, binding affinity for ACE2, conformational plasticity, protein stability and allosteric modulation. In this study, we systematically characterize conformational dynamics, structural stability and binding affinities of the SARS-CoV-2 Spike Omicron complexes with the host receptor ACE2 for BA.2, BA.2.75, XBB.1 and XBB.1.5 variants. We combined multiscale molecular simulations and dynamic analysis of allosteric interactions together with the ensemble-based mutational scanning of the protein residues and network modeling of epistatic interactions. This multifaceted computational study characterized molecular mechanisms and identified energetic hotspots that can mediate the predicted increased stability and the enhanced binding affinity of the BA.2.75 and XBB.1.5 complexes. The results suggested a mechanism driven by the stability hotspots and a spatially localized group of the Omicron binding affinity centers, while allowing for functionally beneficial neutral Omicron mutations in other binding interface positions. A network-based community model for the analysis of epistatic contributions in the Omicron complexes is proposed revealing the key role of the binding hotspots R498 and Y501 in mediating community-based epistatic couplings with other Omicron sites and allowing for compensatory dynamics and binding energetic changes. The results also showed that mutations in the convergent evolutionary hotspot F486 can modulate not only local interactions but also rewire the global network of local communities in this region allowing the F486P mutation to restore both the stability and binding affinity of the XBB.1.5 variant which may explain the growth advantages over the XBB.1 variant. The results of this study are consistent with a broad range of functional studies rationalizing functional roles of the Omicron mutation sites that form a coordinated network of hotspots enabling a balance of multiple fitness tradeoffs and shaping up a complex functional landscape of virus transmissibility.

Enhancing SARS-CoV-2 Surveillance through Regular Genomic Sequencing in Spain: The RELECOV Network.

Millions of SARS-CoV-2 whole genome sequences have been generated to date. However, good quality data and adequate surveillance systems are required to contribute to meaningful surveillance in public health. In this context, the network of Spanish laboratories for coronavirus (RELECOV) was created with the main goal of promoting actions to speed up the detection, analyses, and evaluation of SARS-CoV-2 at a national level, partially structured and financed by an ECDC-HERA-Incubator action (ECDC/GRANT/2021/024). A SARS-CoV-2 sequencing quality control assessment (QCA) was developed to evaluate the network's technical capacity. QCA full panel results showed a lower hit rate for lineage assignment compared to that obtained for variants. Genomic data comprising 48,578 viral genomes were studied and evaluated to monitor SARS-CoV-2. The developed network actions showed a 36% increase in sharing viral sequences. In addition, analysis of lineage/sublineage-defining mutations to track the virus showed characteristic mutation profiles for the Delta and Omicron variants. Further, phylogenetic analyses strongly correlated with different variant clusters, obtaining a robust reference tree. The RELECOV network has made it possible to improve and enhance the genomic surveillance of SARS-CoV-2 in Spain. It has provided and evaluated genomic tools for viral genome monitoring and characterization that make it possible to increase knowledge efficiently and quickly, promoting the genomic surveillance of SARS-CoV-2 in Spain.

Overall Survival with Osimertinib in Resected EGFR-Mutated NSCLC.

BACKGROUND: Among patients with resected, epidermal growth factor receptor (EGFR)-mutated, stage IB to IIIA non-small-cell lung cancer (NSCLC), adjuvant osimertinib therapy, with or without previous adjuvant chemotherapy, resulted in significantly longer disease-free survival than placebo in the ADAURA trial. We report the results of the planned final analysis of overall survival. METHODS: In this phase 3, double-blind trial, we randomly assigned eligible patients in a 1:1 ratio to receive osimertinib (80 mg once daily) or placebo until disease recurrence was observed, the trial regimen was completed (3 years), or a discontinuation criterion was met. The primary end point was investigator-assessed disease-free survival among patients with stage II to IIIA disease. Secondary end points included disease-free survival among patients with stage IB to IIIA disease, overall survival, and safety. RESULTS: Of 682 patients who underwent randomization, 339 received osimertinib and 343 received placebo. Among patients with stage II to IIIA disease, the 5-year overall survival was 85% in the osimertinib group and 73% in the placebo group (overall hazard ratio for death, 0.49; 95.03% confidence interval [CI], 0.33 to 0.73; P<0.001). In the overall population (patients with stage IB to IIIA disease), the 5-year overall survival was 88% in the osimertinib group and 78% in the placebo group (overall hazard ratio for death, 0.49; 95.03% CI, 0.34 to 0.70; P<0.001). One new serious adverse event, pneumonia related to coronavirus disease 2019, was reported after the previously published data-cutoff date (the event was not considered by the investigator to be related to the trial regimen, and the patient fully recovered). Adjuvant osimertinib had a safety profile consistent with that in the primary analysis. CONCLUSIONS: Adjuvant osimertinib provided a significant overall survival benefit among patients with completely resected, EGFR-mutated, stage IB to IIIA NSCLC. (Funded by AstraZeneca; ADAURA ClinicalTrials.gov number, NCT02511106.).

Molecular Epidemiology of SARS-CoV-2 during Five COVID-19 Waves and the Significance of Low-Frequency Lineages.

SARS-CoV-2 lineages and variants of concern (VOC) have gained more efficient transmission and immune evasion properties with time. We describe the circulation of VOCs in South Africa and the potential role of low-frequency lineages on the emergence of future lineages. Whole genome sequencing was performed on SARS-CoV-2 samples from South Africa. Sequences were analysed with Nextstrain pangolin tools and Stanford University Coronavirus Antiviral & Resistance Database. In 2020, 24 lineages were detected, with B.1 (3%; 8/278), B.1.1 (16%; 45/278), B.1.1.348 (3%; 8/278), B.1.1.52 (5%; 13/278), C.1 (13%; 37/278) and C.2 (2%; 6/278) circulating during the first wave. Beta emerged late in 2020, dominating the second wave of infection. B.1 and B.1.1 continued to circulate at low frequencies in 2021 and B.1.1 re-emerged in 2022. Beta was outcompeted by Delta in 2021, which was thereafter outcompeted by Omicron sub-lineages during the 4th and 5th waves in 2022. Several significant mutations identified in VOCs were also detected in low-frequency lineages, including S68F (E protein); I82T (M protein); P13L, R203K and G204R/K (N protein); R126S (ORF3a); P323L (RdRp); and N501Y, E484K, D614G, H655Y and N679K (S protein). Low-frequency variants, together with VOCs circulating, may lead to convergence and the emergence of future lineages that may increase transmissibility, infectivity and escape vaccine-induced or natural host immunity.

SARS-CoV-2 Omicron Specific Mutations Affecting Infectivity, Fusogenicity, and Partial TMPRSS2-Independency.

The COVID-19 pandemic resulted from the global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since its first appearance in 2019, new SARS-CoV-2 variants of concern (VOCs) have emerged frequently, changing the infection's dynamic. SARS-CoV-2 infects cells via two distinct entry routes; receptor-mediated endocytosis or membrane fusion, depending on the absence or presence of transmembrane serine protease 2 (TMPRSS2), respectively. In laboratory conditions, the Omicron SARS-CoV-2 strain inefficiently infects cells predominantly via endocytosis and is phenotypically characterized by decreased syncytia formation compared to the earlier Delta variant. Thus, it is important to characterize Omicron's unique mutations and their phenotypic manifestations. Here, by utilizing SARS-CoV-2 pseudovirions, we report that the specific Omicron Spike F375 residue decreases infectivity, and its conversion to the Delta S375 sequence significantly increases Omicron infectivity. Further, we identified that residue Y655 decreases Omicron's TMPRSS2 dependency and entry via membrane fusion. The Y655H, K764N, K856N and K969N Omicron revertant mutations, bearing the Delta variant sequence, increased the cytopathic effect of cell-cell fusion, suggesting these Omicron-specific residues reduced the severity of SARS-CoV-2. This study of the correlation of the mutational profile with the phenotypic outcome should sensitize our alertness towards emerging VOCs.

Spreading processes with mutations over multilayer networks.

A key scientific challenge during the outbreak of novel infectious diseases is to predict how the course of the epidemic changes under countermeasures that limit interaction in the population. Most epidemiological models do not consider the role of mutations and heterogeneity in the type of contact events. However, pathogens have the capacity to mutate in response to changing environments, especially caused by the increase in population immunity to existing strains, and the emergence of new pathogen strains poses a continued threat to public health. Further, in the light of differing transmission risks in different congregate settings (e.g., schools and offices), different mitigation strategies may need to be adopted to control the spread of infection. We analyze a multilayer multistrain model by simultaneously accounting for i) pathways for mutations in the pathogen leading to the emergence of new pathogen strains, and ii) differing transmission risks in different settings, modeled as network layers. Assuming complete cross-immunity among strains, namely, recovery from any infection prevents infection with any other (an assumption that will need to be relaxed to deal with COVID-19 or influenza), we derive the key epidemiological parameters for the multilayer multistrain framework. We demonstrate that reductions to existing models that discount heterogeneity in either the strain or the network layers may lead to incorrect predictions. Our results highlight that the impact of imposing/lifting mitigation measures concerning different contact network layers (e.g., school closures or work-from-home policies) should be evaluated in connection with their effect on the likelihood of the emergence of new strains.

Efflux-Related Carbapenem Resistance in Acinetobacter baumannii Is Associated with Two-Component Regulatory Efflux Systems' Alteration and Insertion of ΔAbaR25-Type Island Fragment.

The efflux pumps, beside the class D carbapenem-hydrolysing enzymes (CHLDs), are being increasingly investigated as a mechanism of carbapenem resistance in Acinetobacter baumannii. This study investigates the contribution of efflux mechanism to carbapenem resistance in 61 acquired blaCHDL-genes-carrying A. baumannii clinical strains isolated in Warsaw, Poland. Studies were conducted using phenotypic (susceptibility testing to carbapenems ± efflux pump inhibitors (EPIs)) and molecular (determining expression levels of efflux operon with regulatory-gene and whole genome sequencing (WGS)) methods. EPIs reduced carbapenem resistance of 14/61 isolates. Upregulation (5-67-fold) of adeB was observed together with mutations in the sequences of AdeRS local and of BaeS global regulators in all 15 selected isolates. Long-read WGS of isolate no. AB96 revealed the presence of AbaR25 resistance island and its two disrupted elements: the first contained a duplicate ISAba1-blaOXA-23, and the second was located between adeR and adeA in the efflux operon. This insert was flanked by two copies of ISAba1, and one of them provides a strong promoter for adeABC, elevating the adeB expression levels. Our study for the first time reports the involvement of the insertion of the ΔAbaR25-type resistance island fragment with ISAba1 element upstream the efflux operon in the carbapenem resistance of A. baumannii.

An optimized thermodynamics integration protocol for identifying beneficial mutations in antibody design.

Accurate identification of beneficial mutations is central to antibody design. Many knowledge-based (KB) computational approaches have been developed to predict beneficial mutations, but their accuracy leaves room for improvement. Thermodynamic integration (TI) is an alchemical free energy algorithm that offers an alternative technique for identifying beneficial mutations, but its performance has not been evaluated. In this study, we developed an efficient TI protocol with high accuracy for predicting binding free energy changes of antibody mutations. The improved TI method outperforms KB methods at identifying both beneficial and deleterious mutations. We observed that KB methods have higher accuracies in predicting deleterious mutations than beneficial mutations. A pipeline using KB methods to efficiently exclude deleterious mutations and TI to accurately identify beneficial mutations was developed for high-throughput mutation scanning. The pipeline was applied to optimize the binding affinity of a broadly sarbecovirus neutralizing antibody 10-40 against the circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant. Three identified beneficial mutations show strong synergy and improve both binding affinity and neutralization potency of antibody 10-40. Molecular dynamics simulation revealed that the three mutations improve the binding affinity of antibody 10-40 through the stabilization of an altered binding mode with increased polar and hydrophobic interactions. Above all, this study presents an accurate and efficient TI-based approach for optimizing antibodies and other biomolecules.

CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning.

BACKGROUND: Literature about SARS-CoV-2 widely discusses the effects of variations that have spread in the past 3 years. Such information is dispersed in the texts of several research articles, hindering the possibility of practically integrating it with related datasets (e.g., millions of SARS-CoV-2 sequences available to the community). We aim to fill this gap, by mining literature abstracts to extract-for each variant/mutation-its related effects (in epidemiological, immunological, clinical, or viral kinetics terms) with labeled higher/lower levels in relation to the nonmutated virus. RESULTS: The proposed framework comprises (i) the provisioning of abstracts from a COVID-19-related big data corpus (CORD-19) and (ii) the identification of mutation/variant effects in abstracts using a GPT2-based prediction model. The above techniques enable the prediction of mutations/variants with their effects and levels in 2 distinct scenarios: (i) the batch annotation of the most relevant CORD-19 abstracts and (ii) the on-demand annotation of any user-selected CORD-19 abstract through the CoVEffect web application (http://gmql.eu/coveffect), which assists expert users with semiautomated data labeling. On the interface, users can inspect the predictions and correct them; user inputs can then extend the training dataset used by the prediction model. Our prototype model was trained through a carefully designed process, using a minimal and highly diversified pool of samples. CONCLUSIONS: The CoVEffect interface serves for the assisted annotation of abstracts, allowing the download of curated datasets for further use in data integration or analysis pipelines. The overall framework can be adapted to resolve similar unstructured-to-structured text translation tasks, which are typical of biomedical domains.

Identification of Evolutionary Trajectories Shared across Human Betacoronaviruses.

Comparing the evolution of distantly related viruses can provide insights into common adaptive processes related to shared ecological niches. Phylogenetic approaches, coupled with other molecular evolution tools, can help identify mutations informative on adaptation, although the structural contextualization of these to functional sites of proteins may help gain insight into their biological properties. Two zoonotic betacoronaviruses capable of sustained human-to-human transmission have caused pandemics in recent times (SARS-CoV-1 and SARS-CoV-2), although a third virus (MERS-CoV) is responsible for sporadic outbreaks linked to animal infections. Moreover, two other betacoronaviruses have circulated endemically in humans for decades (HKU1 and OC43). To search for evidence of adaptive convergence between established and emerging betacoronaviruses capable of sustained human-to-human transmission (HKU1, OC43, SARS-CoV-1, and SARS-CoV-2), we developed a methodological pipeline to classify shared nonsynonymous mutations as putatively denoting homoplasy (repeated mutations that do not share direct common ancestry) or stepwise evolution (sequential mutations leading towards a novel genotype). In parallel, we look for evidence of positive selection and draw upon protein structure data to identify potential biological implications. We find 30 candidate mutations, from which 4 (codon sites 18121 [nsp14/residue 28], 21623 [spike/21], 21635 [spike/25], and 23948 [spike/796]; SARS-CoV-2 genome numbering) further display evolution under positive selection and proximity to functional protein regions. Our findings shed light on potential mechanisms underlying betacoronavirus adaptation to the human host and pinpoint common mutational pathways that may occur during establishment of human endemicity.

In Silico Evaluation of SARS-CoV-2 K417N, L452R, and E484K Detection Assays Against Omicron Variants.

The study's objective was to assess whether the performance of the DIAGNOVITAL SARS-CoV-2 Mutation Detection Assays is affected by Omicron mutations. In silico evaluation of 67,717 Variant of Concern, Variant of Interest sequences and 6,612 sequences of the Omicron variants involving BA1., BA2., BA3 sub-lineages downloaded from the GISAID database by 17 December 2021, were performed. The sequences were aligned according to the reference genome MN908947.3 using MAFFT multiple sequence alignment software version 7. Our findings showed that among 6,612 Omicron, 41 Spike gene mutations with a frequency of ≥70% were identified. Some of the Omicron mutations (R408S, N440K, G446S, Q493S, Q498R) could affect the diagnostic performance of K417N, L452R, and E484K assays against the Omicron sub-lineages. However, L452R and K417N mutation tests allow differentiation of the Delta and Omicron variants mutation profile. The COVID-19 pandemic lasted longer than expected, and the rapid modification of diagnostic kits seems necessary to combat the pandemic.

The Mutational Landscape of SARS-CoV-2.

Mutation research is crucial for detecting and treating SARS-CoV-2 and developing vaccines. Using over 5,300,000 sequences from SARS-CoV-2 genomes and custom Python programs, we analyzed the mutational landscape of SARS-CoV-2. Although almost every nucleotide in the SARS-CoV-2 genome has mutated at some time, the substantial differences in the frequency and regularity of mutations warrant further examination. C>U mutations are the most common. They are found in the largest number of variants, pangolin lineages, and countries, which indicates that they are a driving force behind the evolution of SARS-CoV-2. Not all SARS-CoV-2 genes have mutated in the same way. Fewer non-synonymous single nucleotide variations are found in genes that encode proteins with a critical role in virus replication than in genes with ancillary roles. Some genes, such as spike (S) and nucleocapsid (N), show more non-synonymous mutations than others. Although the prevalence of mutations in the target regions of COVID-19 diagnostic RT-qPCR tests is generally low, in some cases, such as for some primers that bind to the N gene, it is significant. Therefore, ongoing monitoring of SARS-CoV-2 mutations is crucial. The SARS-CoV-2 Mutation Portal provides access to a database of SARS-CoV-2 mutations.

Generation of SARS-CoV-2 escape mutations by monoclonal antibody therapy.

COVID-19 patients at risk of severe disease may be treated with neutralising monoclonal antibodies (mAbs). To minimise virus escape from neutralisation these are administered as combinations e.g. casirivimab+imdevimab or, for antibodies targeting relatively conserved regions, individually e.g. sotrovimab. Unprecedented genomic surveillance of SARS-CoV-2 in the UK has enabled a genome-first approach to detect emerging drug resistance in Delta and Omicron cases treated with casirivimab+imdevimab and sotrovimab respectively. Mutations occur within the antibody epitopes and for casirivimab+imdevimab multiple mutations are present on contiguous raw reads, simultaneously affecting both components. Using surface plasmon resonance and pseudoviral neutralisation assays we demonstrate these mutations reduce or completely abrogate antibody affinity and neutralising activity, suggesting they are driven by immune evasion. In addition, we show that some mutations also reduce the neutralising activity of vaccine-induced serum.

Pathogenesis and Management of Acute Necrotizing Encephalopathy.

INTRODUCTION: During the COVID-19 pandemic, many cases of acute necrotizing encephalopathy (ANE) secondary to COVID-19 have been reported. ANE is characterized by a rapid onset, a fulminant course, and low morbidity and fatality rates. Therefore, clinicians need to be vigilant for such disorders, especially during the influenza virus and COVID-19 epidemics. AREAS COVERED: The authors summarize the most recent studies on the clinical spectrum and treatment essentials of ANE to provide references for prompt diagnosis and improved treatment of this rare but fatal disease. EXPERT OPINION: ANE is a type of necrotizing lesion of the brain parenchyma. There are two major types of reported cases. One is isolated and sporadic ANE, which is primarily caused by viral infections, particularly influenza and HHV-6 virus. The other type is familial recurrent ANE, which is caused by RANBP2 gene mutations. ANE patients have rapid progression and a very poor prognosis, with acute brain dysfunction occurring within days of viral infection and requiring admission to the intensive care unit. Clinicians still need to investigate and find solutions for the problems of early detection and treatment of ANE.

Frequent Emergence of Resistance Mutations Following Complex Intra-Host Genomic Dynamics in SARS-CoV-2 Patients Receiving Sotrovimab.

The emergence of the Omicron variant of SARS-CoV-2 represented a challenge to the treatment of COVID-19 using monoclonal antibodies. Only Sotrovimab maintained partial activity, allowing it to be used in high-risk patients infected with the Omicron variant. However, reports of resistance mutations to Sotrovimab demand efforts to better understand the intra-patient emergence of Sotrovimab resistance. A retrospective genomic analysis was conducted on respiratory samples from immunocompromised patients infected with SARS-CoV-2 who received Sotrovimab at our hospital between December 2021 and August 2022. The study involved 95 sequential specimens from 22 patients (1 to 12 samples/patient; 3 to 107 days post-infusion; threshold cycle [CT] ≤ 32). Resistance mutations (in P337, E340, K356, and R346) were detected in 68% of cases; the shortest time to detection of a resistance mutation was 5 days after Sotrovimab infusion. The dynamics of resistance acquisition were highly complex, with up to 11 distinct amino acid changes in specimens from the same patient. In two patients, the mutation distribution was compartmentalized in respiratory samples from different sources. This is the first study to examine the acquisition of Sotrovimab resistance in the BA.5 lineage, enabling us to determine the lack of genomic or clinical differences between Sotrovimab resistance in BA.5 relative to that in BA.1/2. Across all Omicron lineages, the acquisition of resistance delayed SARS-CoV-2 clearance (40.67 versus 19.5 days). Close, real-time genomic surveillance of patients receiving Sotrovimab should be mandatory to facilitate early therapeutic interventions.

Allosteric communication between ACE2 active site and binding interface with SARS-CoV-2.

SARS-CoV-2, the virus causing COVID-19, initiates cell invasion by deploying a receptor binding domain (RBD) to recognize the host transmembrane peptidase angiotensin-converting enzyme 2 (ACE2). Numerous experimental and theoretical studies have adopted high-throughput and structure-guided approaches to (i) understand how the RBD recognizes ACE2, (ii) rationalize, and (iii) predict the effect of viral mutations on the binding affinity. Here, we investigate the allosteric signal triggered by the dissociation of the ACE2-RBD complex. To this end, we construct an Elastic Network Model (ENM), and we use the Structural Perturbation Method (SPM). Our key result is that complex dissociation opens the ACE2 substrate-binding cleft located away from the interface and that fluctuations of the ACE2 binding cleft are facilitated by RBD binding. These and other observations provide a structural and dynamical basis for the influence of SARS-CoV-2 on ACE2 enzymatic activity. In addition, we identify a conserved glycine (G502 in SARS-CoV-2) as a key participant in complex disassembly.

Evaluation of Analytical and Clinical Performance and Usefulness in a Real-Life Hospital Setting of Two in-House Real-Time RT-PCR Assays to Track SARS-CoV-2 Variants of Concern.

Since the end of 2020, multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) have emerged and spread worldwide. Tracking their evolution has been a challenge due to the huge number of positive samples and limited capacities of whole-genome sequencing. Two in-house variant-screening RT-PCR assays were successively designed in our laboratory in order to detect specific known mutations in the spike region and to rapidly detect successively emerging VOCs. The first one (RT-PCR#1) targeted the 69-70 deletion and the N501Y substitution simultaneously, whereas the second one (RT-PCR#2) targeted the E484K, E484Q, and L452R substitutions simultaneously. To evaluate the analytical performance of these two RT-PCRs, 90 negative and 30 positive thawed nasopharyngeal swabs were retrospectively analyzed, and no discordant results were observed. Concerning the sensitivity, for RT-PCR#1, serial dilutions of the WHO international standard SARS-CoV-2 RNA, corresponding to the genome of an Alpha variant, were all detected up to 500 IU/mL. For RT-PCR#2, dilutions of a sample harboring the E484K substitution and of a sample harboring the L452R and E484Q substitutions were all detected up to 1000 IU/mL and 2000 IU/mL, respectively. To evaluate the performance in a real-life hospital setting, 1308 and 915 profiles of mutations, obtained with RT-PCR#1 and RT-PCR#2, respectively, were prospectively compared to next-generation sequencing (NGS) data. The two RT-PCR assays showed an excellent concordance with the NGS data, with 99.8% for RT-PCR#1 and 99.2% for RT-PCR#2. Finally, for each mutation targeted, the clinical sensitivity, the clinical specificity and the positive and negative predictive values showed excellent clinical performance. Since the beginning of the SARS-CoV-2 pandemic, the emergence of variants-impacting the disease's severity and the efficacy of vaccines and therapies-has forced medical analysis laboratories to constantly adapt to the strong demand for screening them. Our data showed that in-house RT-PCRs are useful and adaptable tools for monitoring such rapid evolution and spread of SARS-CoV-2 VOCs.

Quantitative Mutation Analysis of Genes and Proteins of Major SARS-CoV-2 Variants of Concern and Interest.

Of various SARS-CoV-2 variants, some have drawn special concern or interest because of their heightened disease threat. The mutability of individual SARS-CoV-2 genes/proteins presumably varies. The present study quantified gene/protein mutations in 13 major SARS-CoV-2 variants of concern/interest, and analyzed viral protein antigenicity using bioinformatics. The results from 187 carefully perused genome clones showed significantly higher mean percent mutations in the spike, ORF8, nucleocapsid, and NSP6 than in other viral proteins. The ORF8 and spike proteins also tolerated higher maximal percent mutations. The omicron variant presented more percent mutations in the NSP6 and structural proteins, whereas the delta featured more in the ORF7a. Omicron subvariant BA.2 exhibited more mutations in ORF6, and omicron BA.4 had more in NSP1, ORF6, and ORF7b, relative to omicron BA.1. Delta subvariants AY.4 and AY.5 bore more mutations in ORF7b and ORF8 than delta B.1.617.2. Predicted antigen ratios of SARS-CoV-2 proteins significantly vary (range: 38-88%). To overcome SARS-CoV-2 immune evasion, the relatively conserved, potentially immunogenic NSP4, NSP13, NSP14, membrane, and ORF3a viral proteins may serve as more suitable targets for molecular vaccines or therapeutics than the mutation-prone NSP6, spike, ORF8, or nucleocapsid protein. Further investigation into distinct mutations of the variants/subvariants may help understand SARS-CoV-2 pathogenesis.