The scale and duration of neutralizing antibody responses targeting SARS-CoV-2 viral variants represents a critically important serological parameter that predicts protective immunity for COVID-19. In this study, we describe the development and employment of a new functional assay that measures neutralizing antibodies for SARS-CoV-2 and present longitudinal data illustrating the impact of age, sex and comorbidities on the kinetics and strength of vaccine-induced antibody responses for key variants in an Asian volunteer cohort. We also present an accurate quantitation of serological responses for SARS-CoV-2 that exploits a unique set of in-house, recombinant human monoclonal antibodies targeting the viral Spike and nucleocapsid proteins and demonstrate a reduction in neutralizing antibody titres across all groups six months post-vaccination. We also observe a marked reduction in the serological binding activity and neutralizing responses targeting recently newly emerged Omicron variants including XBB 1.5 and highlight a significant increase in cross-protective neutralizing antibody responses following a third dose (boost) of vaccine. These data illustrate how key virological factors such as immune escape mutations combined with host demographic factors such as age and sex of the vaccinated individual influence the strength and duration of cross-protective serological immunity for COVID-19.

The emergence of numerous variants of SARS-CoV-2 has presented challenges to the global efforts to control the COVID-19 pandemic. The major mutation is in the SARS-CoV-2 viral envelope spike protein that is responsible for virus attachment to the host, and is the main target for host antibodies. It is critically important to study the biological effects of the mutations to understand the mechanisms of how mutations alter viral functions. Here, we propose a protein co-conservation weighted network (PCCN) model only based on the protein sequence to characterize the mutation sites by topological features and to investigate the mutation effects on the spike protein from a network view. Frist, we found that the mutation sites on the spike protein had significantly larger centrality than the non-mutation sites. Second, the stability changes and binding free energy changes in the mutation sites were positively significantly correlated with their neighbors’ degree and the shortest path length separately. The results indicate that our PCCN model provides new insights into mutations on spike proteins and reflects the mutation effects on protein function alternations.

The strain that dominated in Greece during the first pandemic wave was primarily imported from a group of returning travelers in February 2020, while molecular and clinical data suggest that the origin of the transmission was Egypt. The observed molecular transmission clusters reflect the transmission dynamics of this particular strain bearing the D614G mutation while highlighting the necessity of their use as a surveillance tool for the prioritization of nonpharmaceutical interventions and combating present and future outbreaks.

The Alpha (B.1.1.7) and Omicron (B.1.1.529, BA.1, BA.4 and BA.5) variants of concern (VOC) share several mutations in their spike gene, including mutations resulting in the deletion of two amino acids at position 69 and 70 (del 69–70) in the Spike protein. Del 69–70 causes failure to detect the S gene target on a widely used, commercial test, the TaqPath SARS-CoV-2 RT-PCR (Thermo Fisher). The S gene target failure (SGTF) signature has been used to preliminarily infer the presence of Alpha and Omicron VOC. We evaluated the accuracy of the SGTF signature in identifying these two variants through analysis of all positive SARS-CoV-2 samples tested on the TaqPath RT-PCR and sequenced by next generation sequencing between December 2020 to July 2022. 2324 samples were successfully sequenced including 914 SGTF positive samples. The sensitivity and specificity of the SGTF signature was 99.6% (95% CI 96.1–99.9%) and 98.6% (95% CI 99.2–99.8%) for the Alpha variant and 99.6% (95% CI 98.9–99.9%) and 99.8% (95% CI 99.4–99.9%) for the Omicron variant. At the peak of their corresponding wave, the positive predictive value of the SGTF was 98% for Alpha and 100% for Omicron. The accuracy of the SGTF signature was high, making this genomic signature a rapid and accurate proxy for identification of these variants in real-world laboratory settings.

SARS-CoV-2 variants of concern (VOCs) represent an alarming threat as they show altered biological behavior and may escape vaccination effectiveness. Broad-spectrum antivirals could play an important role to control infections. The activity of Echinacea purpurea (Echinaforce^® extract, EF) against (i) VOCs B1.1.7 (alpha), B.1.351.1 (beta), P.1 (gamma), B1.617.2 (delta), AV.1 (Scottish), B1.525 (eta), and B.1.1.529.BA1 (omicron); (ii) SARS-CoV-2 spike (S) protein-pseudotyped viral particles and reference strain OC43 as well as (iii) wild type SARS-CoV-2 (Hu-1) was analyzed. Molecular dynamics (MD) were applied to study the interaction of Echinacea’s phytochemical markers with known pharmacological viral and host cell targets. EF extract broadly inhibited the propagation of all investigated SARS-CoV-2 VOCs as well as the entry of SARS-CoV-2 pseudoparticles at EC_50′s ranging from 3.62 to 12.03 µg/mL. The preventive addition of 25 µg/mL EF to epithelial cells significantly reduced sequential infection with SARS-CoV-2 (Hu-1) and OC43. MD analyses showed constant binding affinities to VOC-typical S protein variants for alkylamides, caftaric acid, and feruloyl-tartaric acid in EF extract and interactions with serine protease TMPRSS-2. EF extract demonstrated stable virucidal activity across seven tested VOCs, likely due to the constant affinity of the contained phytochemical substances to all spike variants. A possible interaction of EF with TMPRSS-2 partially would explain the cell protective benefits of the extract by the inhibition of membrane fusion and cell entry. EF may therefore offer a supportive addition to vaccination endeavors in the control of existing and future SARS-CoV-2 virus mutations.

Intro The number of studies on SARS-CoV-2 published on a daily basis is constantly increasing, in an attempt to understand and address the challenges posed by the pandemic in a better way. Most of these studies also include a phylogeny of SARS-CoV-2 as background context, always taking into consideration the latest data in order to construct an updated tree. However, some of these studies have also revealed the difficulties of inferring a reliable phylogeny. [13] have shown that reliable phylogeny is an inherently complex task due to the large number of highly similar sequences, given the relatively low number of mutations evident in each sequence. Motivation From this viewpoint, there is indeed a challenge and an opportunity in identifying the evolutionary history of the SARS-CoV-2 virus, in order to assist the phylogenetic analysis process as well as support researchers in keeping track of the virus and the course of its characteristic mutations, and in finding patterns of the emerging mutations themselves and the interactions between them. The research question is formulated as follows: Detecting new patterns of co-occurring mutations beyond the strain-specific / strain-defining ones, in SARS-CoV-2 data, through the application of ML methods. Aim Going beyond the traditional phylogenetic approaches, we will be designing and implementing a clustering method that will effectively create a dendrogram of the involved sequences, based on a feature space defined on the present mutations, rather than the entire sequence. Ultimately, this ML method is tested out in sequences retrieved from public databases and validated using the available metadata as labels. The main goal of the project is to design, implement and evaluate a software that will automatically detect and cluster relevant mutations, that could potentially be used to identify trends in emerging variants. Contact tasos1109{at}gmail.com

La enfermedad por coronavirus 2019 (COVID-19) ha generado un impacto a gran escala en la salud pública mundial debido a su rápida propagación y a su alta capacidad de contagio, adaptación y evolución. En esta revisión se describen las diferencias entre mutaciones, variantes, linajes y cepas de Coronavirus del Síndrome Respiratorio Agudo Severo 2 (SARS-CoV-2); se listan las principales mutaciones presentes en las variantes de interés (VOI por sus siglas en inglés) y variantes de preocupación (VOC por sus siglas en inglés) de SARS-CoV-2 y su distribución geográfica; y finalmente, se analiza la implicación que tienen las nuevas variantes sobre la efectividad de las vacunas, evidenciando la importancia de la vigilancia genómica de SARS-CoV-2 en la era post vacunación.

Several variants of concern (VOCs) explain most of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic waves in Europe. We aimed to dissect the spread of the SARS-CoV-2 VOCs in the Canary Islands (Spain) between December 2020 and September 2021 at a micro-geographical level. We sequenced the viral genome of 8,224 respiratory samples collected in the archipelago. We observed that Alpha (B.1.1.7) and Delta (B.1.617.2 and sublineages) were ubiquitously present in the islands, while Beta (B.1.351) and Gamma (P.1/P.1.1) had a heterogeneous distribution and were responsible for fewer and more controlled outbreaks. This work represents the largest effort for viral genomic surveillance in the Canary Islands so far, helping the public health bodies in decision-making throughout the pandemic.

Unlike the ancestral SARS-CoV-2 strain, the Beta (B.1.351) variant of concern has been reported to replicate to some extent in WT mice (C57BL/6 and BALB/c). We demonstrate here that infection of SCID mice with the Beta variant resulted in high viral loads in the lungs on day 3 postinfection.

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

In Poland, the first case of SARS-CoV-2 infection was confirmed in March 2020. Since then, many circulating virus lineages fueled rapid pandemic waves which inflicted a severe burden on the Polish healthcare system. Some of these lineages were associated with increased transmissibility and immune escape. Mutations in the viral spike protein, which is responsible for host cell recognition and serves as the primary target for neutralizing antibodies, are of particular importance. We investigated the molecular epidemiology of the SARS-CoV-2 clades circulating in Southern Poland from February 2021 to August 2021. The 921 whole-genome sequences were used for variant identification, spike mutation, and phylogenetic analyses. The Pango B.1.1.7 was the dominant variant (n = 730, 89.68%) from March 2021 to July 2021. In July 2021, the B.1.1.7 was displaced by the B.1.617.2 lineage with 66.66% in July 2021 and 92.3% in August 2021 frequencies, respectively. Moreover, our results were compared with the sequencing available on the GISAID platform for other regions of Poland, the Czech Republic, and Slovakia. The analysis showed that the dominant variant in the analyzed period was B.1.1.7 in all countries and Southern Poland (Silesia). Interestingly, B.1.1.7 was replaced by B.1.617.2 earlier in Southern Poland than in the rest of the country. Moreover, in the Czech Republic and Slovakia, AY lineages were predominant at that time, contrary to the Silesia region.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic and public health crisis since the beginning of 2020. First recognized for the induction of severe disease, the virus also causes asymptomatic infections or infections with mild symptoms that can resemble common colds. To provide better understanding of these mild SARS-CoV-2 infections and to monitor the development of symptoms over time, we performed a detailed analysis of self-reported symptoms of SARS-CoV-2 positive and SARS-CoV-2 negative individuals. In an online-based survey, a total of 2117 individuals provided information on symptoms associated with an acute respiratory infection, 1925 of the participants had tested positive for SARS-CoV-2 infection, and 192 had tested negative. The symptoms reported most frequently during the early phases of the pandemic by SARS-CoV-2 infected individuals were tiredness, headache, impairment of smell or taste and dry cough. With the spread of the alpha and delta variants, the frequency of nose symptoms such as blocked or runny nose and sneezing increased to being reported by almost 60% of infected individuals. Interestingly, the spread of the omicron variant brought a sharp decrease in the incidence of impaired sense of smell or taste, which was reported by only 24% in this phase of the pandemic. The constellation of symptoms should be monitored closely in the months ahead, since future SARS-CoV-2 variants are likely to bring about more changes.

Background: Convalescent plasma (CP) has been widely used to treat COVID-19 and is under study. However, the variability in the current clinical trials has averted its wide use in the current pandemic. We aimed to evaluate the safety and efficacy of CP in severe coronavirus disease 2019 (COVID-19) in the early stages of the disease. Methods: A randomized controlled clinical study was conducted on 101 patients admitted to the hospital with confirmed severe COVID-19. Most participants had less than 14 days from symptoms onset and less than seven days from hospitalization. Fifty patients were assigned to receive CP plus standard therapy (ST), and 51 were assigned to receive ST alone. Participants in the CP arm received two doses of 250 mL each, transfused 24 h apart. All transfused plasma was obtained from "super donors" that fulfilled the following criteria: titers of anti-SARS-CoV-2 S1 IgG ≥ 1:3200 and IgA ≥ 1:800 antibodies. The effect of transfused anti-IFN antibodies and the SARS-CoV-2 variants at the entry of the study on the overall CP efficacy was evaluated. The primary outcomes were the reduction in viral load and the increase in IgG and IgA antibodies at 28 days of follow-up. The per-protocol analysis included 91 patients. Results: An early but transient increase in IgG anti-S1-SARS-CoV-2 antibody levels at day 4 post-transfusion was observed (Estimated difference [ED], − 1.36; 95% CI, − 2.33 to − 0.39; P = 0.04). However, CP was not associated with viral load reduction in any of the points evaluated. Analysis of secondary outcomes revealed that those patients in the CP arm disclosed a shorter time to discharge (ED adjusted for mortality, 3.1 days; 95% CI, 0.20 to 5.94; P = 0.0361) or a reduction of 2 points on the WHO scale when compared with the ST group (HR adjusted for mortality, 1.6; 95% CI, 1.03 to 2.5; P = 0.0376). There were no benefits from CP on the rates of intensive care unit admission (HR, 0.82; 95% CI, 0.35 to 1.9; P = 0.6399), mechanical ventilation (HR, 0.66; 95% CI, 0.25 to 1.7; P = 0.4039), or mortality (HR, 3.2; 95% CI, 0.64 to 16; P = 0.1584). Anti-IFN antibodies and SARS-CoV-2 variants did not influence these results. Conclusion: CP was not associated with viral load reduction, despite the early increase in IgG anti-SARS-CoV-2 antibodies. However, CP is safe and could be a therapeutic option to reduce the hospital length of stay. Trial registration NCT04332835

Background: A global pandemic has been declared for coronavirus disease 2019 (COVID-19), which has serious impacts on human health and healthcare systems in the affected areas, including Vietnam. None of the previous studies have a framework to provide summary statistics of the virus variants and assess the severity associated with virus proteins and host cells in COVID-19 patients in Vietnam. Method: In this paper, we comprehensively investigated SARS-CoV-2 variants and immune responses in COVID-19 patients. We provided summary statistics of target sequences of SARS-CoV-2 in Vietnam and other countries for data scientists to use in downstream analysis for therapeutic targets. For host cells, we proposed a predictive model of the severity of COVID-19 based on public datasets of hospitalization status in Vietnam, incorporating a polygenic risk score. This score uses immunogenic SNP biomarkers as indicators of COVID-19 severity. Result: We identified that the Delta variant of SARS-CoV-2 is most prevalent in southern areas of Vietnam and it is different from other areas in the world using various data sources. Our predictive models of COVID-19 severity had high accuracy (Random Forest AUC = 0.81, Elastic Net AUC = 0.7, and SVM AUC = 0.69) and showed that the use of polygenic risk scores increased the models’ predictive capabilities. Conclusion: We provided a comprehensive analysis for COVID-19 severity in Vietnam. This investigation is not only helpful for COVID-19 treatment in therapeutic target studies, but also could influence further research on the disease progression and personalized clinical outcomes.

Introduction: A global surge in SARS-CoV-2 cases is occurring due to the emergence of new disease variants, and requires continuous adjustment of public health measures. This study aims to continuously monitor and mitigate the impact of SARS-CoV-2 through genomic surveillance, to determine the emergence of variants and their impact on public health. Methods: Data were collected from 50 full-genome sequences of SARS-CoV-2 isolates from Makassar, South Sulawesi, Indonesia. Mutation and phylogenetic analysis was performed of SARS-CoV-2 from Makassar, South Sulawesi, Indonesia. Results: Phylogenetic analysis showed that two samples (4%) were of the B.1.319 lineage, while the others (96%) were of the B.1.466.2 lineage. Mutation analysis of the spike (S) protein region showed that the most common mutation was D614G (found in 100% of the sequenced isolates), followed by N439K (98%) and P681R (76%). Several mutations were also identified in other genomes with a high frequency, including P323L (nsp12), Q57H (ns3-orf3a), and T205I (nucleoprotein). Conclusion: Our findings highlight the importance of continuous genomic surveillance to identify new viral mutations and variants with possible impacts on public health.

Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have been reported in immune-compromised individuals and people undergoing immune-modulatory treatments. Although intrahost evolution has been documented, to our knowledge, no direct evidence of subsequent transmission and stepwise adaptation is available.Here we describe sequential persistent SARS-CoV-2 infections in three individuals that led to the emergence, forward transmission, and continued evolution of a new Omicron sublineage, BA.1.23, over an eight-month period. The initially transmitted BA.1.23 variant encoded seven additional amino acid substitutions within the spike protein (E96D, R346T, L455W, K458M, A484V, H681R, A688V), and displayed substantial resistance to neutralization by sera from boosted and/or Omicron BA.1-infected study participants. Subsequent continued BA.1.23 replication resulted in additional substitutions in the spike protein (S254F, N448S, F456L, M458K, F981L, S982L) as well as in five other virus proteins.Our findings demonstrate that the Omicron BA.1 lineage can diverge further from its already exceptionally mutated genome during persistent infection in more than one host, and also document ongoing transmission of these novel variants. There is an urgent need to implement strategies to prevent prolonged SARS-CoV-2 replication and to limit the spread of newly emerging, neutralization-resistant variants in vulnerable patients.

Background: Due to rapid spread, the Omicron variant has become the dominant SARS-CoV-2 variant responsible for infections worldwide. We present the first detection of the Omicron variant in Croatia which resulted in rapid cross-border spreading. Methods: Whole-genome sequencing was performed using the Illumina MiniSeq sequencing system. SARS-CoV-2 lineages were identified using the PANGOLIN and GISAID databases. Results: The first case of the Omicron variant (BA.1.17) emerged in Croatia after a workshop held in Zagreb in November 2021. The patient reported a history of previous COVID-19 and received two doses of an mRNA vaccine. Three additional cases were detected among Croatian participants of the workshop. At the beginning of December, SARS-CoV-2 infection was confirmed in one participant from Montenegro and her husband. Phylogenetic analysis showed that the detected Omicron variants were closely related to the first Croatian case, confirming the connection with the workshop outbreak and rapid cross-border spreading. Subsequent analyses of SARS-CoV-2 positive samples in Croatia showed the rapid introduction of the Omicron variant and depletion of the Delta variant resulting in the fifth pandemic wave. Conclusions: Genomic monitoring and early detection of novel SARS-CoV-2 variants are essential to implement timely epidemiological interventions and reduce further transmission in the population.

Background The rapid spread of SARS-CoV-2 worldwide has led to the emergence of new variants due to the presence of mutations that alter viral characteristics, but there have been few studies on trends in viral lineages in Japan, an island country. We hypothesized that changes in cycle threshold (Ct) values on reverse transcription polymerase chain reaction (RT-PCR) reflect the prevalent variants during a given period. Methods We performed next-generation sequencing of positive samples to identify the viral lineages in Japan in 2021 and compared variant prevalence with the average Ct values on routine RT-PCR using 4 primer sets. Results Based on 3 sequencing runs, the highly transmissible Alpha variant, which prevailed over other lineages, such as R.1, from April 2021, was dominated by the even stronger Delta variant between July and August 2021 in Japan. The decrease in our routine RT-PCR Ct values with 4 primer sets correlated with these fluctuations in lineage prevalence over time. Conclusions We confirmed that our RT-PCR protocol reflects the trends in SARS-CoV-2 variant prevalence over time regardless of sequence mutation. This may aid in the tracking of new variants in the population.

Several variants of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging all over the world. Variant surveillance from genome sequencing has become crucial to determine if mutations in these variants are rendering the virus more infectious, potent, or resistant to existing vaccines and therapeutics. Meanwhile, analyzing many raw sequencing data repeatedly with currently available code-based bioinformatics tools is tremendously challenging to be implemented in this unprecedented pandemic time due to the fact of limited experts and computational resources. Therefore, in order to hasten variant surveillance efforts, we developed an installation-free cloud workflow for robust mutation profiling of SARS-CoV-2 variants from multiple Illumina sequencing data. Herein, 55 raw sequencing data representing four early SARS-CoV-2 variants of concern (Alpha, Beta, Gamma, and Delta) from an open-access database were used to test our workflow performance. As a result, our workflow could automatically identify mutated sites of the variants along with reliable annotation of the protein-coding genes at cost-effective and timely manner for all by harnessing parallel cloud computing in one execution under resource-limitation settings. In addition, our workflow can also generate a consensus genome sequence which can be shared with others in public data repositories to support global variant surveillance efforts.

Tracing the appearance and evolution of virus variants is essential in the management of the COVID-19 pandemic. Here, we focus on SARS-CoV-2 spread in Italian patients by using viral sequences deposited in public databases and a tracing procedure which is used to monitor the evolution of the pandemic and detect the spreading, within the infected population of emergent sub-clades with a potential positive selection. Analyses of a collection of monthly samples focused on Italy highlighted the appearance and evolution of all the main viral sub-trees emerging at the end of the first year of the pandemic. It also identified additional expanding subpopulations which spread during the second year (i.e., 2021). Three-dimensional (3D) modelling of the main amino acid changes in mutated viral proteins, including ORF1ab (nsp3, nsp4, 2’-o-ribose methyltransferase, nsp6, helicase, nsp12 [RdRp]), N, ORF3a, ORF8, and spike proteins, shows the potential of the analysed structural variations to result in epistatic modulation and positive/negative selection pressure. These analyzes will be of importance to the early identification of emerging clades, which can develop into new “variants of concern” (i.e., VOC). These analyses and settings will also help SARS-CoV-2 coronet genomic centers in other countries to trace emerging worldwide variants.

Summary: The scale and duration of neutralizing antibody responses targeting SARS-CoV-2 viral variants represents a critically important serological parameter that predicts protective immunity for COVID-19. In this study, we present longitudinal data illustrating the impact of age, sex and comorbidities on the kinetics and strength of vaccine-induced neutralizing antibody responses for key variants in an Asian volunteer cohort. We demonstrate a reduction in neutralizing antibody titres across all groups six months post-vaccination and show a marked reduction in the serological binding and neutralizing response targeting Omicron compared to other viral variants. We also highlight the increase in cross-protective neutralizing antibody responses against Omicron induced by a third dose (booster) of vaccine. These data illustrate how key virological factors such as immune escape mutation combined with host factors such as age and sex of the vaccinated individuals influence the strength and duration of cross-protective serological immunity for COVID-19.

The genetic association of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) with different clinical conditions remains unclear and needs further investigation. In this study, we characterized 57 complete SARS-CoV-2 genomes from patients in Mexico with distinct disease severity outcomes: mild disease or ambulatory care, severe disease or hospitalized, and deceased.

Low complexity regions (LCRs) are protein sequences formed by a set of compositionally biased residues. LCRs are extremely abundant in cellular proteins and have also been reported in viruses, where they may partake in evasion of the host immune system. Analyses of 28,231 SARS-CoV-2 whole proteomes and of 261,051 spike protein sequences revealed the presence of four extremely conserved LCRs in the spike protein of several SARS-CoV-2 variants. With the exception of Iota, where it is absent, the Spike LCR-1 is present in the signal peptide of 80.57% of the Delta variant sequences, and in other variants of concern and interest. The Spike LCR-2 is highly prevalent (79.87%) in Iota. Two distinctive LCRs are present in the Delta spike protein. The Delta Spike LCR-3 is present in 99.19% of the analyzed sequences, and the Delta Spike LCR-4 in 98.3% of the same set of proteins. These two LCRs are located in the furin cleavage site and HR1 domain, respectively, and may be considered hallmark traits of the Delta variant. The presence of the medically-important point mutations P681R and D950N in these LCRs, combined with the ubiquity of these regions in the highly contagious Delta variant opens the possibility that they may play a role in its rapid spread.

Establishing vaccine-based population immunity has been the key factor in attaining herd protection. Thanks to expedited worldwide research efforts, the potency of mRNA vaccines against the coronavirus disease 2019 (COVID-19) is now incontestable.

Genomics is fundamentally changing epidemiological research. However, systematically exploring hypotheses in pathogen evolution requires new modeling tools. Models intertwining pathogen epidemiology and genomic evolution can help understand processes such as the emergence of novel pathogen genotypes with higher transmissibility or resistance to treatment. In this work, we present Opqua, a flexible simulation framework that explicitly links epidemiology to sequence evolution and selection. We use Opqua to study determinants of evolution across fitness valleys. We confirm that competition can limit evolution in high transmission environments and find that low transmission, host mobility, and complex pathogen life cycles facilitate reaching new adaptive peaks through population bottlenecks and decoupling of selective pressures. The results show the potential of genomic epidemiological modeling as a tool in infectious disease research.

Background: Being able to efficiently call variants from the increasing amount of sequencing data daily produced from multiple viral strains is of the utmost importance, as demonstrated during the COVID-19 pandemic, in order to track the spread of the viral strains across the globe. Results: We present , an easy-to-install and easy-to-use application that assists users in multiple tasks required for the analysis of a viral population, such as the SARS-CoV-2. allows to: (1) construct a variant catalog consisting in a set of variations (SNPs/indels) from the population sequences, (2) efficiently genotype and annotate variants of the catalog supported by a read sample, and (3) when the considered viral species is the SARS-CoV-2, assign the input sample to the most likely Pango lineages using the genotyped variations. Conclusions: Tests on Illumina and Nanopore samples proved the efficiency and the effectiveness of in analyzing SARS-CoV-2 strain samples with respect to publicly available data provided by NCBI and the more complete dataset provided by GISAID. A comparison with state-of-the-art tools showed that is always more precise and often have a better recall.

As the pandemic of COVID-19 caused by the coronavirus SARS-CoV-2 continues, the selection of genomic variants which can influence how the pandemic progresses is of growing concern. Of particular concern, are those variants that carry mutations/amino acid changes conferring higher transmission, more severe disease, re-infection, and immune escape. These can broadly be classified as Variants of Concern (VOCs). VOCs have been reported from several parts of the world- UK (lineage B.1.1.7), South Africa (lineage B.1.351) and, Brazil (lineage P.1/B.1.1.28). The conditions that contribute to the emergence of VOCs are not well understood. International travel remains an important means of spread. To track importation, spread, and the emergence of variants locally; we sequenced whole genomes of SARS-CoV-2 from international travellers (n=75) entering Karnataka, a state in South India, between Dec 22, 2020- Jan 31, 2021, and from positive cases in the city of Bengaluru (n=108), between Nov 22, 2020- Jan 22, 2021. The resulting 176 SARS-CoV-2 genomes could be classified into 34 lineages, that were either imported (73/176) or circulating (103/176) in this time period. The lineage B.1.1.7 (a.k.a the UK variant) was the major lineage imported into the state (24/73, 32.9%), followed by B.1.36 (20/73, 27.4%) and B.1 (14/73, 19.2%). We identified B.1.36 (45/103; 43.7%), B.1 (26/103; 25.2%), B.1.1.74 (5/103; 4.9%) and B.1.468 (4/103; 3.9%) as the major variants circulating in Bengaluru city. A distinct clade within the B.1.36 lineage was associated with a local outbreak. Analysis of the complete genomes predicted multiple amino acid replacements in the Spike protein. In total, we identified nine amino acid changes (singly or in pairs) in the Receptor Binding Domain of the Spike protein. Of these, the amino acid replacement N440K was found in 37/65 (56.92%) sequences in the B.1.36 lineage. The E484K amino acid change which is present in both VOCs, B.1.351 and P.1/B.1.1.28, was found in a single circulating virus in the B.1.36 lineage. This study highlights the introduction of VOCs by travel and the local circulation of viruses with amino acid replacements in the Spike protein. These were spread across lineages, suggesting that multiple paths can lead to the emergence of VOCs, this, in turn, highlights the need to sequence and limit outbreaks of SARS-CoV-2 locally. Our data support the use of concentrated and continued genomic surveillance of SARS-CoV-2 to direct public health measures, suggest revisions to vaccines, and serve as an early warning system to prepare for a surge in COVID-19 cases.