Mapping genome variation of SARS-CoV-2 worldwide highlights the impact of COVID-19 super-spreaders

Dispersion of SARS-CoV-2 lineage BA.5.1.25 and its descendants in Peru during two COVID-19 waves in 2022

During the third year of the pandemic in Peru, the persistent transmission of SARS-CoV-2 led to the appearance of more transmissible and immune-evasive Omicron sublineages; in that context, the National Genomic Surveillance of SARS-CoV-2 performed by the Peruvian National Institute of Health detected spike mutations in the circulating Omicron BA.5.1.25 sublineage which was later designated as DJ.1 and increased during the fourth COVID-19 wave, this eventually branched into new sublineages. The introduction, emergence, and timing of the most recent common ancestor (tMRCA) of BA.5.1.25 and its descendants (DJ.1, DJ.1.1, DJ.1.2, and DJ.1.3) were investigated in this paper as well as the time lags between their emergence and identification by the Peruvian National Institute of Health. Our findings show that ongoing genomic surveillance of SARS-CoV-2 is critical for understanding its phylogenetic evolution and the emergence of novel variations.

Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Wholesale Seafood Market, the site with the most reported wildlife vendors in the city of Wuhan, China. Here, we analyze publicly available qPCR and sequencing data from environmental samples collected in the Huanan market in early 2020. We demonstrate that the SARS-CoV-2 genetic diversity linked to this market is consistent with market emergence, and find increased SARS-CoV-2 positivity near and within a particular wildlife stall. We identify wildlife DNA in all SARS-CoV-2 positive samples from this stall. This includes species such as civets, bamboo rats, porcupines, hedgehogs, and one species, raccoon dogs, known to be capable of SARS-CoV-2 transmission. We also detect other animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them to those from other markets. This analysis provides the genetic basis for a short list of potential intermediate hosts of SARS-CoV-2 to prioritize for retrospective serological testing and viral sampling.

Genome analysis of SARS-CoV-2 isolates from a population reveals the rapid selective sweep of a haplotype carrying many pre-existing and new mutations

To understand the mechanism underlying the evolution of SARS-CoV-2 in a population, we sequenced 92 viral genomes from Assam, India. Analysis of these and database sequences revealed a complete selective sweep of a haplotype in Assam carrying 13 pre-existing variants, including a high leap in frequency of a variant on ORF8, which is involved in immune evasion. A comparative study between sequences of same lineage and similar time frames in and outside Assam showed that 10 of the 13 pre-existing variants had a frequency ranging from 96 to 99%, and the remaining 3 had a low frequency outside Assam. Using a phylogenetic approach to infer sequential occurrences of variants we found that the variant Phe120del on ORF8, which had a low frequency (1.75%) outside Assam, is at the base of the phylogenetic tree of variants and became totally fixed (100%) in Assam population. Based on this observation, we inferred that the variant on ORF8 had a selective advantage, so it carried the haplotype to reach the100% frequency. The haplotype also carried 32 pre-existing variants at a frequency from 1.00 to 80.00% outside Assam. Those of these variants that are more closely linked to the S-protein locus, which often carries advantageous mutations and is tightly linked to the ORF8 locus, retained higher frequencies, while the less tightly linked variants showed lower frequencies, likely due to recombination among co- circulating variants in Assam. The ratios of non-synonymous substitutions to synonymous substitutions suggested that some genes such as those coding for the S-protein and non-structural proteins underwent positive selection while others were subject to purifying selection during their evolution in Assam. Furthermore, we observed negative correlation of the Ct value of qRT-PCR of the patients with abundant ORF6 transcripts, suggesting that ORF6 can be used as a marker for estimating viral titer. In conclusion, our in-depth analysis of SARS-CoV-2 genomes in a regional population reveals the mechanism and dynamics of viral evolution.

Evolutionary implications of SARS-CoV-2 vaccination for the future design of vaccination strategies

Once the first SARS-CoV-2 vaccine became available, mass vaccination was the main pillar of the public health response to the COVID-19 pandemic. It was very effective in reducing hospitalizations and deaths. Here, we discuss the possibility that mass vaccination might accelerate SARS-CoV-2 evolution in antibody-binding regions compared to natural infection at the population level. Using the evidence of strong genetic variation in antibody-binding regions and taking advantage of the similarity between the envelope proteins of SARS-CoV-2 and influenza, we assume that immune selection pressure acting on these regions of the two viruses is similar. We discuss the consequences of this assumption for SARS-CoV-2 evolution in light of mathematical models developed previously for influenza. We further outline the implications of this phenomenon, if our assumptions are confirmed, for the future design of SARS-CoV-2 vaccination strategies.

Emergence, spread and characterisation of the SARS-CoV-2 variant B.1.640 circulating in France, October 2021 to February 2022

BackgroundSuccessive epidemic waves of COVID-19 illustrated the potential of SARS-CoV-2 variants to reshape the pandemic. Detecting and characterising emerging variants is essential to evaluate their public health impact and guide implementation of adapted control measures.AimTo describe the detection of emerging variant, B.1.640, in France through genomic surveillance and present investigations performed to inform public health decisions.MethodsIdentification and monitoring of SARS-CoV-2 variant B.1.640 was achieved through the French genomic surveillance system, producing 1,009 sequences. Additional investigation of 272 B.1.640-infected cases was performed between October 2021 and January 2022 using a standardised questionnaire and comparing with Omicron variant-infected cases.ResultsB.1.640 was identified in early October 2021 in a school cluster in Bretagne, later spreading throughout France. B.1.640 was detected at low levels at the end of SARS-CoV-2 Delta variant's dominance and progressively disappeared after the emergence of the Omicron (BA.1) variant. A high proportion of investigated B.1.640 cases were children aged under 14 (14%) and people over 60 (27%) years, because of large clusters in these age groups. B.1.640 cases reported previous SARS-CoV-2 infection (4%), anosmia (32%) and ageusia (34%), consistent with data on pre-Omicron SARS-CoV-2 variants. Eight percent of investigated B.1.640 cases were hospitalised, with an overrepresentation of individuals aged over 60 years and with risk factors.ConclusionEven though B.1.640 did not outcompete the Delta variant, its importation and continuous low-level spread raised concerns regarding its public health impact. The investigations informed public health decisions during the time that B.1.640 was circulating.

Positive feedback loops exacerbate the influence of superspreaders in disease transmission

Superspreaders are recognized as being important drivers of disease spread. However, models to date have assumed random occurrence of superspreaders, irrespective of whom they were infected by. Evidence suggests though that those individuals infected by superspreaders may be more likely to become superspreaders themselves. Here, we begin to explore, theoretically, the effects of such a positive feedback loop on (1) the final epidemic size, (2) the herd immunity threshold, (3) the basic reproduction number, R₀, and (4) the peak prevalence of superspreaders, using a generic model for a hypothetical acute viral infection and illustrative parameter values. We show that positive feedback loops can have a profound effect on our chosen epidemic outcomes, even when the transmission advantage of superspreaders is moderate, and despite peak prevalence of superspreaders remaining low. We argue that positive superspreader feedback loops in different infectious diseases, including SARS-CoV-2, should be investigated further, both theoretically and empirically.

Cancer survival in the Faroe Islands over the last 50 years compared to the other Nordic countries

As sustained development in cancer treatment protocols have led to improved survival in most areas of the world, surveillance is needed to ensure that small populations follow suit. Our study reports age-standardized relative cancer survival in the Faroe Islands compared to the other Nordic countries. We present 1- and 5-year survival estimates and corresponding 95% confidence intervals for the Faroe Islands and compare them with estimates for the Nordic countries. The data for this article has been obtained through the NORDCAN collaboration (2019 data). Age-standardized relative survival was estimated using shared R codes on individual-level data within each country. Ten-year calendar inclusion periods were used in addition to the usual 5-year calendar periods to include cancer sites with few cases, which is especially beneficial to the smaller populations. The primary findings were that 1- and 5-year survival were consistently lower in the Faroes for the summary group all sites but non-melanoma skin cancer for both women and men. Further, 5-year survival was lower for women with ovarian cancer and men with lung cancer than in other Nordic countries. Previously, breast cancer survival was low in the Faroes but has improved to a comparable level over the last few years. Colorectal cancer survival was relatively high for both sexes. The reported estimates in this article call for further research to investigate the cancers with lower survival and should call for actions to improve the survival of Faroese cancer patients.

The P323L substitution in the SARS-CoV-2 polymerase (NSP12) confers a selective advantage during infection

BACKGROUND

The mutational landscape of SARS-CoV-2 varies at the dominant viral genome sequence and minor genomic variant population. During the COVID-19 pandemic, an early substitution in the genome was the D614G change in the spike protein, associated with an increase in transmissibility. Genomes with D614G are accompanied by a P323L substitution in the viral polymerase (NSP12). However, P323L is not thought to be under strong selective pressure.

RESULTS

Investigation of P323L/D614G substitutions in the population shows rapid emergence during the containment phase and early surge phase during the first wave. These substitutions emerge from minor genomic variants which become dominant viral genome sequence. This is investigated in vivo and in vitro using SARS-CoV-2 with P323 and D614 in the dominant genome sequence and L323 and G614 in the minor variant population. During infection, there is rapid selection of L323 into the dominant viral genome sequence but not G614. Reverse genetics is used to create two viruses (either P323 or L323) with the same genetic background. L323 shows greater abundance of viral RNA and proteins and a smaller plaque morphology than P323.

CONCLUSIONS

These data suggest that P323L is an important contribution in the emergence of variants with transmission advantages. Sequence analysis of viral populations suggests it may be possible to predict the emergence of a new variant based on tracking the frequency of minor variant genomes. The ability to predict an emerging variant of SARS-CoV-2 in the global landscape may aid in the evaluation of medical countermeasures and non-pharmaceutical interventions.

Rooting and Dating Large SARS-CoV-2 Trees by Modeling Evolutionary Rate as a Function of Time

Almost all published rooting and dating studies on SARS-CoV-2 assumed that (1) evolutionary rate does not change over time although different lineages can have different evolutionary rates (uncorrelated relaxed clock), and (2) a zoonotic transmission occurred in Wuhan and the culprit was immediately captured, so that only the SARS-CoV-2 genomes obtained in 2019 and the first few months of 2020 (resulting from the first wave of the global expansion from Wuhan) are sufficient for dating the common ancestor. Empirical data contradict the first assumption. The second assumption is not warranted because mounting evidence suggests the presence of early SARS-CoV-2 lineages cocirculating with the Wuhan strains. Large trees with SARS-CoV-2 genomes beyond the first few months are needed to increase the likelihood of finding SARS-CoV-2 lineages that might have originated at the same time as (or even before) those early Wuhan strains. I extended a previously published rapid rooting method to model evolutionary rate as a linear function instead of a constant. This substantially improves the dating of the common ancestor of sampled SARS-CoV-2 genomes. Based on two large trees with 83,688 and 970,777 high-quality and full-length SARS-CoV-2 genomes that contain complete sample collection dates, the common ancestor was dated to 12 June 2019 and 7 July 2019 with the two trees, respectively. The two data sets would give dramatically different or even absurd estimates if the rate was treated as a constant. The large trees were also crucial for overcoming the high rate-heterogeneity among different viral lineages. The improved method was implemented in the software TRAD.

A Timeframe for SARS-CoV-2 Genomes: A Proof of Concept for Postmortem Interval Estimations

Establishing the timeframe when a particular virus was circulating in a population could be useful in several areas of biomedical research, including microbiology and legal medicine. Using simulations, we demonstrate that the circulation timeframe of an unknown SARS-CoV-2 genome in a population (hereafter, estimated time of a queried genome [QG]; tE-QG) can be easily predicted using a phylogenetic model based on a robust reference genome database of the virus, and information on their sampling dates. We evaluate several phylogeny-based approaches, including modeling evolutionary (substitution) rates of the SARS-CoV-2 genome (~10-3 substitutions/nucleotide/year) and the mutational (substitutions) differences separating the QGs from the reference genomes (RGs) in the database. Owing to the mutational characteristics of the virus, the present Viral Molecular Clock Dating (VMCD) method covers timeframes going backwards from about a month in the past. The method has very low errors associated to the tE-QG estimates and narrow intervals of tE-QG, both ranging from a few days to a few weeks regardless of the mathematical model used. The SARS-CoV-2 model represents a proof of concept that can be extrapolated to any other microorganism, provided that a robust genome sequence database is available. Besides obvious applications in epidemiology and microbiology investigations, there are several contexts in forensic casework where estimating tE-QG could be useful, including estimation of the postmortem intervals (PMI) and the dating of samples stored in hospital settings.

Variation analysis of SARS-CoV-2 complete sequences from Iran

Aim: SARS-CoV-2 is an emerging coronavirus that was discovered in China and rapidly spread throughout the world. The authors looked at nucleotide and amino acid variations in SARS-CoV-2 genomes, as well as phylogenetic and evolutionary events in viral genomes, in Iran. Materials & methods: All SARS-CoV-2 sequences that were publicly released between the start of the pandemic and 15 October 2021 were included. Results: The majority of mutations were found in vaccine target proteins, Spike and Nucleocapsid proteins, and nonstructural proteins. The majority of the viruses that circulated in the early stages of the pandemic belonged to the B.4 lineage. Conclusion: We discovered the prevalence of viral populations in Iran. As a result, tracking the virus’s variation in Iran and comparing it with a variety of nearby neighborhoods may reveal a pattern for future variant introductions.

Evaluation of Variant-Specific Peptides for Detection of SARS-CoV-2 Variants of Concern

The SARS-CoV-2 omicron variant presented significant challenges to the global effort to counter the pandemic. SARS-CoV-2 is predicted to remain prevalent for the foreseeable future, making the ability to identify SARS-CoV-2 variants imperative in understanding and controlling the pandemic. The predominant variant discovery method, genome sequencing, is time-consuming, insensitive, and expensive. Ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) offers an exciting alternative detection modality provided that variant-containing peptide markers are sufficiently detectable from their tandem mass spectra (MS/MS). We have synthesized model tryptic peptides of SARS-CoV-2 variants alpha, beta, gamma, delta, and omicron and evaluated their signal intensity, HCD spectra, and reverse phase retention time. Detection limits of 781, 781, 65, and 65 amol are obtained for the molecular ions of the proteotypic peptides, beta (QIAPGQTGNIADYNYK), gamma (TQLPSAYTNSFTR), delta (VGGNYNYR), and omicron (TLVKQLSSK), from neat solutions. These detection limits are on par with the detection limits of a previously reported proteotypic peptide from the SARS-CoV-2 spike protein, HTPINLVR. This study demonstrates the potential to differentiate SARS-CoV-2 variants through their proteotypic peptides with an approach that is broadly applicable across a wide range of pathogens.

Modeling the change in European and US COVID-19 death rates

Motivated by several possible differences in Covid-19 virus strains, age demographics, and face mask wearing between continents and countries, we focussed on changes in Covid death rates in 2020. We have extended our Covid-19 multicompartment model (Khan et al., 2020) to fit cumulative case and death data for 49 European countries and 52 US states and territories during the recent pandemic, and found that the case mortality rate had decreased by at least 80% in most of the US and at least 90% in most of Europe. We found that death rate decreases do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as population density, GDP, and median age. Almost all the decreases occurred between mid-April and mid-June 2020, which corresponds to the time when many state and national lockdowns were relaxed resulting in surges of new cases. We examine here several plausible causes for this drop—improvements in treatment, face mask wearing, new virus strains, testing, potentially changing demographics of infected patients, and changes in data collection and reporting—but none of their effects are as significant as the death rate changes suggest. In conclusion, this work shows that a two death rate model is effective in quantifying the reported drop in death rates.

A review of pathophysiological mechanism, diagnosis, and treatment of thrombosis risk associated with COVID-19 infection

Severe coronavirus (COVID-19) infection has been reportedly associated with a high risk of thromboembolism. Developing macrovascular thrombotic complications, including myocardial injury/infarction, venous thromboembolism, and stroke have been observed in one-third of severe COVID-19 hospitalized patients, leading to an increase in mortality and morbidity. The diagnosis of COVID-19 associated coagulopathy may be challenging because there are close similarities between pulmonary embolism and severe COVID-19 disease. Therefore, a critical step in improving the clinical outcome of patients with hospitalized COVID-19 is the recognition of coagulation abnormalities and the identification of patients with poor prognoses, prophylactic guidance, or antithrombotic therapy. Prescribing anticoagulants in all patients hospitalized with COVID-19 and 2-6 weeks post-hospital discharge in the absence of contraindications is recommended by most consensus documents published on behalf of professional societies. However, a decision on some variable factors such as intensity and duration of anticoagulation may be made based on an individual case and needs future randomized trial studies. Regarding little information on this subject, this study aims to review how inflammation and thrombosis are related to COVID-19 patients, discuss the types of thrombosis in these patients, and summarize the diagnosis and treatment of thrombosis in COVID19 patients.

A multi-tissue study of immune gene expression profiling highlights the key role of the nasal epithelium in COVID-19 severity

Coronavirus Disease-19 (COVID-19) symptoms range from mild to severe illness; the cause for this differential response to infection remains unknown. Unravelling the immune mechanisms acting at different levels of the colonization process might be key to understand these differences. We carried out a multi-tissue (nasal, buccal and blood; n = 156) gene expression analysis of immune-related genes from patients affected by different COVID-19 severities, and healthy controls through the nCounter technology. Mild and asymptomatic cases showed a powerful innate antiviral response in nasal epithelium, characterized by activation of interferon (IFN) pathway and downstream cascades, successfully controlling the infection at local level. In contrast, weak macrophage/monocyte driven innate antiviral response and lack of IFN signalling activity were present in severe cases. Consequently, oral mucosa from severe patients showed signals of viral activity, cell arresting and viral dissemination to the lower respiratory tract, which ultimately could explain the exacerbated innate immune response and impaired adaptative immune responses observed at systemic level. Results from saliva transcriptome suggest that the buccal cavity might play a key role in SARS-CoV-2 infection and dissemination in patients with worse prognosis. Co-expression network analysis adds further support to these findings, by detecting modules specifically correlated with severity involved in the abovementioned biological routes; this analysis also provides new candidate genes that might be tested as biomarkers in future studies. We also found tissue specific severity-related signatures mainly represented by genes involved in the innate immune system and cytokine/chemokine signalling. Local immune response could be key to determine the course of the systemic response and thus COVID-19 severity. Our findings provide a framework to investigate severity host gene biomarkers and pathways that might be relevant to diagnosis, prognosis, and therapy.

First report on genome wide association study in western Indian population reveals host genetic factors for COVID-19 severity and outcome

Different human races across the globe responded in a different way to the SARS-CoV-2 infection leading to different disease severity. Therefore, it is anticipated that host genetic factors have a straight association with the COVID-19. We identified a total 6, 7, and 6 genomic loci for deceased-recovered, asymptomatic-recovered, and deceased-asymptomatic group comparison, respectively. Unfavourable alleles of the markers nearby the genes which are associated with lung and heart diseases such as Tumor necrosis factor superfamily (TNFSF4&18), showed noteworthy association with the disease severity and outcome for the COVID-19 patients in the western Indian population. The markers found with significant association with disease prognosis or recovery are of value in determining the individual's response to SARS-CoV-2 infection and can be used for the risk prediction in COVID-19. Besides, GWAS study in other populations from India may help to strengthen the outcome of this study.

Identifying SARS-CoV-2 regional introductions and transmission clusters in real time

The unprecedented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) global sequencing effort has suffered from an analytical bottleneck. Many existing methods for phylogenetic analysis are designed for sparse, static datasets and are too computationally expensive to apply to densely sampled, rapidly expanding datasets when results are needed immediately to inform public health action. For example, public health is often concerned with identifying clusters of closely related samples, but the sheer scale of the data prevents manual inspection and the current computational models are often too expensive in time and resources. Even when results are available, intuitive data exploration tools are of critical importance to effective public health interpretation and action. To help address this need, we present a phylogenetic heuristic that quickly and efficiently identifies newly introduced strains in a region, resulting in clusters of infected individuals, and their putative geographic origins. We show that this approach performs well on simulated data and yields results largely congruent with more sophisticated Bayesian phylogeographic modeling approaches. We also introduce Cluster-Tracker (https://clustertracker.gi.ucsc.edu/), a novel interactive web-based tool to facilitate effective and intuitive SARS-CoV-2 geographic data exploration and visualization across the USA. Cluster-Tracker is updated daily and automatically identifies and highlights groups of closely related SARS-CoV-2 infections resulting from the transmission of the virus between two geographic areas by travelers, streamlining public health tracking of local viral diversity and emerging infection clusters. The site is open-source and designed to be easily configured to analyze any chosen region, making it a useful resource globally. The combination of these open-source tools will empower detailed investigations of the geographic origins and spread of SARS-CoV-2 and other densely sampled pathogens.

Reconstruction of the Evolutionary Origin, Phylodynamics, and Phylogeography of the Porcine Circovirus Type 3

Porcine circovirus type 3 (PCV3) is a newly identified virus associated with porcine dermatitis and nephropathy syndrome (PDNS) and multisystemic inflammatory responses in pigs. Recent studies suggests that PCV3 originated from bat circoviruses; however, the origin time, mode of spread, and geographic distribution of PCV3 remain unclear. In this study, the evolutionary origin, phylodynamics, and phylogeography of PCV3 were reconstructed based on the available complete genome sequences. PCV3 showed a closer relationship with bird circovirus than with bat circovirus, but their common ancestor was bat circovirus, indicating that birds may be intermediate hosts for the spread of circoviruses in pigs. Using the BEAST and phylogenetic analyses, three different clades of PCV3 (PCV3a, PCV3b, and PCV3c) were identified, with PCV3a being the most prevalent PCV3 clade. Further studies indicated that the earliest origin of PCV3 can be traced back to 1907.53–1923.44, with a substitution rate of 3.104 × 10^–4 to 6.8524 × 10^–4 substitution/site/year. A phylogeographic analysis highlighted Malaysia as the earliest location of the original PCV3, which migrated to Asia, America, and Europe. Overall, this study provides novel insights into the evolutionary origin, spread mode, and geographic distribution of PCV3, which will facilitate the prevention and control of PCV3 epidemics in the future.

The Evolution, Genomic Epidemiology, and Transmission Dynamics of Tembusu Virus

Tembusu virus (TMUV) can induce severe egg drop syndrome in ducks, causing significant economic losses. In this study, the possible origin, genomic epidemiology, and transmission dynamics of TMUV were determined. The time to the most recent common ancestor of TMUV was found to be 1924, earlier than that previously reported. The effective population size of TMUV increased rapidly from 2010 to 2013 and was associated with the diversification of different TMUV clusters. TMUV was classified into three clusters (clusters 1, 2, and 3) based on the envelope (E) protein. Subcluster 2.2, within cluster 2, is the most prevalent, and the occurrence of these mutations is accompanied by changes in the virulence and infectivity of the virus. Two positive selections on codons located in the NS3 and NS5 genes (591 of NS3 and 883 of NS5) were identified, which might have caused changes in the ability of the virus to replicate. Based on phylogeographic analysis, Malaysia was the most likely country of origin for TMUV, while Shandong Province was the earliest province of origin in China. This study has important implications for understanding TMUV and provides suggestions for its prevention and control.

A Novel Human Neutralizing mAb Recognizes Delta, Gamma and Omicron Variants of SARS-CoV-2 and Can Be Used in Combination with Sotrovimab

The dramatic experience with SARS-CoV-2 has alerted the scientific community to be ready to face new epidemics/pandemics caused by new variants. Among the therapies against the pandemic SARS-CoV-2 virus, monoclonal Antibodies (mAbs) targeting the Spike glycoprotein have represented good drugs to interfere in the Spike/ Angiotensin Converting Enzyme-2 (ACE-2) interaction, preventing virus cell entry and subsequent infection, especially in patients with a defective immune system. We obtained, by an innovative phage display selection strategy, specific binders recognizing different epitopes of Spike. The novel human antibodies specifically bind to Spike-Receptor Binding Domain (RBD) in a nanomolar range and interfere in the interaction of Spike with the ACE-2 receptor. We report here that one of these mAbs, named D3, shows neutralizing activity for virus infection in cell cultures by different SARS-CoV-2 variants and retains the ability to recognize the Omicron-derived recombinant RBD differently from the antibodies Casirivimab or Imdevimab. Since anti-Spike mAbs, used individually, might be unable to block the virus cell entry especially in the case of resistant variants, we investigated the possibility to combine D3 with the antibody in clinical use Sotrovimab, and we found that they recognize distinct epitopes and show additive inhibitory effects on the interaction of Omicron-RBD with ACE-2 receptor. Thus, we propose to exploit these mAbs in combinatorial treatments to enhance their potential for both diagnostic and therapeutic applications in the current and future pandemic waves of coronavirus.

Histopathological and Immunohistochemical Characterization of Skin Biopsies From 41 SARS-CoV-2 (+) Patients: Experience in a Mexican Concentration Institute: A Case Series and Literature Review

ABSTRACT

The SARS-CoV-2 pandemic brought countless clinical and pathophysiological questions. Although mucocutaneous infections are the most visible, they are among the least studied. This article provides relevant information to characterize morphologically and immunohistochemically the dermatoses from patients with COVID-19, during the first year of the pandemic. Immunohistochemistry reactions against the spike protein were performed in 48 skin biopsies, and the positive cases were classified according to their histomorphology; at the end, 41 biopsies led us to identify 12 morphological patterns that mimic other skin pathologies, among which pityriasiform patterns predominate. For the literature review, we selected cases of SARS-CoV-2 dermatoses that included complete histopathological information and that were published during the same interval of time; after careful evaluation, 205 biopsies were selected and then classified into 8 groups according to previously published proposals. Dermatoses associated with SARS-CoV-2 are as diverse in their clinical expression as in their histopathology, mimicking entities totally unrelated to COVID-19. Furthermore, some of these groups are characteristically associated with an aggressive course of the disease. Undoubtedly, it is necessary to delve into the possibility that these findings are translatable into prognostic and therapeutic factors.

Evaluation of BNT162b2 Vaccine Effectiveness in Galicia, Northwest Spain

Investigating vaccine effectiveness (VE) in real-world conditions is crucial, especially its variation across different settings and populations. We undertook a test-negative control study in Galicia (Northwest Spain) to assess BNT162b2 effectiveness against acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection as well as COVID-19 associated hospitalization, intensive care unit (ICU) admission and mortality. A total of 44,401 positive and 817,025 negative SARS-CoV-2 test results belonging to adults were included. Adjusted odds ratios of vaccination and their 95% confidence interval (CI) were estimated using multivariate logistic-regression models. BNT162b2 showed high effectiveness in reducing SARS-CoV-2 infections in all age categories, reaching maximum VE ≥ 14 days after administering the second dose [18-64 years: VE = 92.9% (95%CI: 90.2-95.1); 65-79 years: VE = 85.8% (95%CI: 77.3-91.9), and ≥80 years: VE = 91.4% (95%CI: 87.9-94.1)]. BNT162b2 also demonstrated effectiveness in preventing COVID-19 hospitalization for all age categories, with VE more pronounced for those aged ≥80 years [VE = 60.0% (95%CI: 49.4-68.3)]. Moreover, there was a considerable reduction in ICU admission [VE = 88.0% (95%CI: 74.6-95.8)] and mortality [VE = 38.0% (95%CI: 15.9-55.4)] in the overall population. BNT162b2 showed substantial protection against SARS-CoV-2 infections and COVID-19 severity. Our findings would prove useful for systematic reviews and meta-analysis on COVID-19 VE.

CovidPhy: A tool for phylogeographic analysis of SARS-CoV-2 variation

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease 2019 (COVID-19) pandemic. SARS-CoV-2 genomes have been sequenced massively and worldwide and are now available in different public genome repositories. There is much interest in generating bioinformatic tools capable to analyze and interpret SARS-CoV-2 variation. We have designed CovidPhy (http://covidphy.eu), a web interface that can process SARS-CoV-2 genome sequences in plain fasta text format or provided through identity codes from the Global Initiative on Sharing Avian Influenza Data (GISAID) or GenBank. CovidPhy aggregates information available on the large GISAID database (>1.49 M genomes). Sequences are first aligned against the reference sequence and the interface provides different sources of information, including automatic classification of genomes into a pre-computed phylogeny and phylogeographic information, haplogroup/lineage frequencies, and sequencing variation, indicating also if the genome contains known variants of concern (VOC). Additionally, CovidPhy allows searching for variants and haplotypes introduced by the user and includes a list of genomes that are good candidates for being responsible for large outbreaks worldwide, most likely mediated by important superspreading events, indicating their possible geographic epicenters and their relative impact as recorded in the GISAID database.

Periodically aperiodic pattern of SARS-CoV-2 mutations underpins the uncertainty of its origin and evolution

Various lineages of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have contributed to prolongation of the Coronavirus Disease 2019 (COVID-19) pandemic. Several non-synonymous mutations in SARS-CoV-2 proteins have generated multiple SARS-CoV-2 variants. In our previous report, we have shown that an evenly uneven distribution of unique protein variants of SARS-CoV-2 is geo-location or demography-specific. However, the correlation between the demographic transmutability of the SARS-CoV-2 infection and mutations in various proteins remains unknown due to hidden symmetry/asymmetry in the occurrence of mutations. This study tracked how these mutations are emerging in SARS-CoV-2 proteins in six model countries and globally. In a geo-location, considering the mutations having a frequency of detection of at least 500 in each SARS-CoV-2 protein, we studied the country-wise percentage of invariant residues. Our data revealed that since October 2020, highly frequent mutations in SARS-CoV-2 have been observed mostly in the Open Reading Frame (ORF) 7b and ORF8, worldwide. No such highly frequent mutations in any of the SARS-CoV-2 proteins were found in the UK, India, and Brazil, which does not correlate with the degree of transmissibility of the virus in India and Brazil. However, we have found a signature that SARS-CoV-2 proteins were evolving at a higher rate, and considering global data, mutations are detected in the majority of the available amino acid locations. Fractal analysis of each protein's normalized factor time series showed a periodically aperiodic emergence of dominant variants for SARS-CoV-2 protein mutations across different countries. It was noticed that certain high-frequency variants have emerged in the last couple of months, and thus the emerging SARS-CoV-2 strains are expected to contain prevalent mutations in the ORF3a, membrane, and ORF8 proteins. In contrast to other beta-coronaviruses, SARS-CoV-2 variants have rapidly emerged based on demographically dependent mutations. Characterization of the periodically aperiodic nature of the demographic spread of SARS-CoV-2 variants in various countries can contribute to the identification of the origin of SARS-CoV-2.

Evolutionary dynamics of the severe acute respiratory syndrome coronavirus 2 genomes

The coronavirus disease 2019 (COVID-19) pandemic has caused immense losses in human lives and the global economy and posed significant challenges for global public health. As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, has evolved, thousands of single nucleotide variants (SNVs) have been identified across the viral genome. The roles of individual SNVs in the zoonotic origin, evolution, and transmission of SARS-CoV-2 have become the focus of many studies. This review summarizes recent comparative genomic analyses of SARS-CoV-2 and related coronaviruses (SC2r-CoVs) found in non-human animals, including delineation of SARS-CoV-2 lineages based on characteristic SNVs. We also discuss the current understanding of receptor-binding domain (RBD) evolution and characteristic mutations in variants of concern (VOCs) of SARS-CoV-2, as well as possible co-evolution between RBD and its receptor, angiotensin-converting enzyme 2 (ACE2). We propose that the interplay between SARS-CoV-2 and host RNA editing mechanisms might have partially resulted in the bias in nucleotide changes during SARS-CoV-2 evolution. Finally, we outline some current challenges, including difficulty in deciphering the complicated relationship between viral pathogenicity and infectivity of different variants, and monitoring transmission of SARS-CoV-2 between humans and animals as the pandemic progresses.

Characteristics of SARS-CoV-2 transmission in a medium-sized city with traditional communities during the early COVID-19 epidemic in China

The nationwide COVID-19 epidemic ended in 2020, a few months after its outbreak in Wuhan, China at the end of 2019. Most COVID-19 cases occurred in Hubei Province, with a few local outbreaks in other provinces of China. A few studies have reported the early SARS-CoV-2 epidemics in several large cities or provinces of China. However, information regarding the early epidemics in small and medium-sized cities, where there are still traditionally large families and community culture is more strongly maintained and thus, transmission profiles may differ, is limited. In this study, we characterized 60 newly sequenced SARS-CoV-2 genomes from Anyang as a representative of small and medium-sized Chinese cities, compared them with more than 400 reference genomes from the early outbreak, and studied the SARS-CoV-2 transmission profiles. Genomic epidemiology revealed multiple SARS-CoV-2 introductions in Anyang and a large-scale expansion of the epidemic because of the large family size. Moreover, our study revealed two transmission patterns in a single outbreak, which were attributed to different social activities. We observed the complete dynamic process of single-nucleotide polymorphism development during community transmission and found that intrahost variant analysis was an effective approach to studying cluster infections. In summary, our study provided new SARS-CoV-2 transmission profiles representative of small and medium-sized Chinese cities as well as information on the evolution of SARS-CoV-2 strains during the early COVID-19 epidemic in China.

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The SARS-CoV-2 strains from multiple regions and multiple lineages together caused the outbreak of COVID-19 in Anyang.

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The traditional family/community facilitates the widespread of SARS-CoV-2 in small and medium-sized Chinese cities.

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The iSNV analysis is an effective approach to studying cluster infections and reconstructing the transmission chain.

The Genomic Physics of COVID-19 Pathogenesis and Spread

Coronavirus disease (COVID-19) spreads mainly through close contact of infected persons, but the molecular mechanisms underlying its pathogenesis and transmission remain unknown. Here, we propose a statistical physics model to coalesce all molecular entities into a cohesive network in which the roadmap of how each entity mediates the disease can be characterized. We argue that the process of how a transmitter transforms the virus into a recipient constitutes a triad unit that propagates COVID-19 along reticulate paths. Intrinsically, person-to-person transmissibility may be mediated by how genes interact transversely across transmitter, recipient, and viral genomes. We integrate quantitative genetic theory into hypergraph theory to code the main effects of the three genomes as nodes, pairwise cross-genome epistasis as edges, and high-order cross-genome epistasis as hyperedges in a series of mobile hypergraphs. Charting a genome-wide atlas of horizontally epistatic hypergraphs can facilitate the systematic characterization of the community genetic mechanisms underlying COVID-19 spread. This atlas can typically help design effective containment and mitigation strategies and screen and triage those more susceptible persons and those asymptomatic carriers who are incubation virus transmitters.

Case Report: Genomic Characteristics of the First Known Case of SARS-CoV-2 Imported From Spain to Sichuan, China

The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been basically under control in China since March 2020, but the import of domestic SARS-CoV-2 has begun to increase. This study reported the first case of asymptomatic SARS-CoV-2 infection imported from Spain into Sichuan Province, China, on March 11, 2020. The infected male had a body temperature of 37.5°C, normal blood oxygen saturation levels, and a computed tomography (CT) examination showed that his lungs had no shadows. However, a throat swab from the subject tested positive for SARS-CoV-2 using qPCR assay. In this study, we conducted transcriptome sequencing on respiratory throat swabs from the subject and found that the dominant SARS-CoV-2 sequence (Gene Bank ID: MW301121) was a spike protein D614G mutant strain, which is currently popular throughout world. We downloaded and analyzed SARS-CoV-2 sequences collected from cases in China and Spain for comparison and tracing purposes. After March 11, 2020, the Chinese domestic clade was naturally divided into the imported SARS-CoV-2 D614G mutant strain and evolutionarily-related similar sequences and that of sequences collected in the original Wuhan area. The sequence reported in this study was located on a small branch, far from the evolution of Wuhan sequences. As expected, the identified sequence was closely related to the evolution of the SARS-CoV-2 D614G mutant strain circulating in Spain.

Predicting COVID-19 Transmission to Inform the Management of Mass Events: Model-Based Approach

BACKGROUND

Modelling COVID-19 transmission at live events and public gatherings is essential to controlling the probability of subsequent outbreaks and communicating to participants their personalized risk. Yet, despite the fast-growing body of literature on COVID-19 transmission dynamics, current risk models either neglect contextual information including vaccination rates or disease prevalence or do not attempt to quantitatively model transmission.

OBJECTIVE

This paper attempted to bridge this gap by providing informative risk metrics for live public events, along with a measure of their uncertainty.

METHODS

Building upon existing models, our approach ties together 3 main components: (1) reliable modelling of the number of infectious cases at the time of the event, (2) evaluation of the efficiency of pre-event screening, and (3) modelling of the event's transmission dynamics and their uncertainty using Monte Carlo simulations.

RESULTS

We illustrated the application of our pipeline for a concert at the Royal Albert Hall and highlighted the risk's dependency on factors such as prevalence, mask wearing, and event duration. We demonstrate how this event held on 3 different dates (August 20, 2020; January 20, 2021; and March 20, 2021) would likely lead to transmission events that are similar to community transmission rates (0.06 vs 0.07, 2.38 vs 2.39, and 0.67 vs 0.60, respectively). However, differences between event and background transmissions substantially widened in the upper tails of the distribution of the number of infections (as denoted by their respective 99th quantiles: 1 vs 1, 19 vs 8, and 6 vs 3, respectively, for our 3 dates), further demonstrating that sole reliance on vaccination and antigen testing to gain entry would likely significantly underestimate the tail risk of the event.

CONCLUSIONS

Despite the unknowns surrounding COVID-19 transmission, our estimation pipeline opens the discussion on contextualized risk assessment by combining the best tools at hand to assess the order of magnitude of the risk. Our model can be applied to any future event and is presented in a user-friendly RShiny interface. Finally, we discussed our model's limitations as well as avenues for model evaluation and improvement.

Evolutionary analysis and lineage designation of SARS-CoV-2 genomes

The pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19), has caused immense global disruption. With the rapid accumulation of SARS-CoV-2 genome sequences, however, thousands of genomic variants of SARS-CoV-2 are now publicly available. To improve the tracing of the viral genomes' evolution during the development of the pandemic, we analyzed single nucleotide variants (SNVs) in 121,618 high-quality SARS-CoV-2 genomes. We divided these viral genomes into two major lineages (L and S) based on variants at sites 8782 and 28144, and further divided the L lineage into two major sublineages (L1 and L2) using SNVs at sites 3037, 14408, and 23403. Subsequently, we categorized them into 130 sublineages (37 in S, 35 in L1, and 58 in L2) based on marker SNVs at 201 additional genomic sites. This lineage/sublineage designation system has a hierarchical structure and reflects the relatedness among the subclades of the major lineages. We also provide a companion website (www.covid19evolution.net) that allows users to visualize sublineage information and upload their own SARS-CoV-2 genomes for sublineage classification. Finally, we discussed the possible roles of compensatory mutations and natural selection during SARS-CoV-2's evolution. These efforts will improve our understanding of the temporal and spatial dynamics of SARS-CoV-2's genome evolution.

Emergence of B.1.524(G) SARS-CoV-2 in Malaysia during the third COVID-19 epidemic wave

The COVID-19 pandemic first emerged in Malaysia in Jan 2020. As of 12th Sept 2021, 1,979,698 COVID-19 cases that occurred over three major epidemic waves were confirmed. The virus contributing to the three epidemic waves has not been well-studied. We sequenced the genome of 22 SARS-CoV-2 strains detected in Malaysia during the second and the ongoing third wave of the COVID-19 epidemic. Detailed phylogenetic and genetic variation analyses of the SARS-CoV-2 isolate genomes were performed using these newly determined sequences and all other available sequences. Results from the analyses suggested multiple independent introductions of SARS-CoV-2 into Malaysia. A new B.1.524(G) lineage with S-D614G mutation was detected in Sabah, East Malaysia and Selangor, Peninsular Malaysia on 7th October 2020 and 14th October 2020, respectively. This new B.1.524(G) group was not the direct descendant of any of the previously detected lineages. The new B.1.524(G) carried a set of genetic variations, including A701V (position variant frequency = 0.0007) in Spike protein and a novel G114T mutation at the 5’UTR. The biological importance of the specific mutations remained unknown. The sequential appearance of the mutations, however, suggests that the spread of the new B.1.524(G) lineages likely begun in Sabah and then spread to Selangor. The findings presented here support the importance of SARS-CoV-2 full genome sequencing as a tool to establish an epidemiological link between cases or clusters of COVID-19 worldwide.

TIPICO XI: report of the first series and podcast on infectious diseases and vaccines (aTIPICO)

TIPiCO is an annual expert meeting and workshop on infectious diseases and vaccination. The edition of 2020 changed its name and format to aTIPiCO, the first series and podcasts on infectious diseases and vaccines. A total of 13 prestigious experts from different countries participated in this edition launched on the 26 November 2020. The state of the art of coronavirus disease-2019 (COVID-19) and the responsible pathogen, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and the options to tackle the pandemic situation were discussed in light of the knowledge in November 2020. Despite COVID-19, the status of other infectious diseases, including influenza infections, respiratory syncytial virus disease, human papillomavirus infection, measles, pertussis, tuberculosis, meningococcal disease, and pneumococcal disease, were also addressed. The essential lessons that can be learned from these diseases and their vaccines to use in the COVID-19 pandemic were also commented with the experts.

SARS-CoV-2 and approaches for a testing and diagnostic strategy

The COVID-19 pandemic has led to an unprecedented global health challenge, creating sudden, massive demands for diagnostic testing, treatment, therapies, and vaccines. In particular, the development of diagnostic assays for SARS-CoV-2 has been pursued as they are needed for quarantine, disease surveillance, and patient treatment. One of the major lessons the pandemic highlighted was the need for fast, cheap, scalable and reliable diagnostic methods, such as paper-based assays. Furthermore, it has previously been suggested that paper-based tests may be more suitable for settings with lower resource availability and may help alleviate some supply chain challenges which arose during the COVID-19 pandemic. Therefore, we explore how such devices may fit in a comprehensive diagnostic strategy and how some of the challenges to the technology, e.g. low sensitivity, may be addressed. We discuss the properties of the SARS-CoV-2 virus itself, the COVID-19 disease pathway, and the immune response. We then describe the different diagnostic strategies that have been pursued, focusing on molecular strategies for viral genetic material, antigen tests, and serological assays, and innovations for improving the diagnostic sensitivity and capabilities. Finally, we discuss pressing issues for the future, and what needs to be addressed for the ongoing pandemic and future outbreaks.

The impact of the hypoxia-VEGF-vascular permeability on COVID-19-infected patients

Effective treatment of patients with severe COVID-19 to reduce mortality remains one of the most challenging medical issues in controlling unpredictable emergencies caused by the global pandemics. Unfortunately, such effective therapies are not available at this time of writing. In this article, I discuss the possibility of repurposing clinically available anti-VEGF (vascular endothelial growth factor) drugs that are routinely used in oncology and ophthalmology areas for effective treatment of patients with severe and critical COVID-19. Our preliminary findings from a clinical trial support the therapeutic concept of using anti-VEGF for treating patients with severe COVID-19 to reduce mortality. The aim of this article is to further provide mechanistic insights into the role of VEGF in causing pathological changes during COVID-19 infection.

Superspreading in the emergence of COVID-19 variants

Superspreading and variants of concern (VOC) of the human pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are the main catalyzers of the coronavirus disease 2019 (COVID-19) pandemic. However, measuring their individual impact is challenging. By examining the largest database of SARS-CoV-2 genomes The Global Initiative on Sharing Avian Influenza Data [GISAID; n >1.2 million high-quality (HQ) sequences], we present evidence suggesting that superspreading has had a key role in the epidemiological predominance of VOC. There are clear signatures in the database compatible with large superspreading events (SSEs) coinciding chronologically with the worst epidemiological scenarios triggered by VOC. The data suggest that, without the randomness effect of the genetic drift facilitated by superspreading, new VOC of SARS-CoV-2 would have had more limited chance of success.

Dating the Common Ancestor from an NCBI Tree of 83688 High-Quality and Full-Length SARS-CoV-2 Genomes

All dating studies involving SARS-CoV-2 are problematic. Previous studies have dated the most recent common ancestor (MRCA) between SARS-CoV-2 and its close relatives from bats and pangolins. However, the evolutionary rate thus derived is expected to differ from the rate estimated from sequence divergence of SARS-CoV-2 lineages. Here, I present dating results for the first time from a large phylogenetic tree with 86,582 high-quality full-length SARS-CoV-2 genomes. The tree contains 83,688 genomes with full specification of collection time. Such a large tree spanning a period of about 1.5 years offers an excellent opportunity for dating the MRCA of the sampled SARS-CoV-2 genomes. The MRCA is dated 16 August 2019, with the evolutionary rate estimated to be 0.05526 mutations/genome/day. The Pearson correlation coefficient (r) between the root-to-tip distance (D) and the collection time (T) is 0.86295. The NCBI tree also includes 10 SARS-CoV-2 genomes isolated from cats, collected over roughly the same time span as human COVID-19 infection. The MRCA from these cat-derived SARS-CoV-2 is dated 30 July 2019, with r = 0.98464. While the dating method is well known, I have included detailed illustrations so that anyone can repeat the analysis and obtain the same dating results. With 16 August 2019 as the date of the MRCA of sampled SARS-CoV-2 genomes, archived samples from respiratory or digestive tracts collected around or before 16 August 2019, or those that are not descendants of the existing SARS-CoV-2 lineages, should be particularly valuable for tracing the origin of SARS-CoV-2.

Entropy based analysis of SARS-CoV-2 spread in India using informative subtype markers

India became one of the most COVID-19 affected countries with more than 4 million infected cases and 71,000 deaths by September 2020. We studied the temporal dynamics and geographic distribution of SARS-CoV-2 subtypes in India. Moreover, we analysed the RGD motif and D614G mutation in the spike protein of SARS-CoV-2. We used a previously proposed viral subtyping method based upon informative subtype markers (ISMs). The ISMs were identified on the basis of information entropy using 94,515 genome sequences of SARS-CoV-2 available publicly at the Global Initiative on Sharing All Influenza Data (GISAID). We identified 11 distinct positions in the SARS-CoV-2 genomes for defining ISMs resulting in 798 unique ISMs. The most abundant ISM in India was transferred from European countries. In contrast, the second most abundant ISM in India was found to be transferred via Australia. Moreover, the eastern regions in India were infected by the ISM most abundant in China due to geographical linkage. Our analysis confirmed higher rates of new cases in the countries abundant with S-G614 strain compared to countries with abundant S-D614 strain. In India, overall S-G614 was most prevalent compared to S-D614, except a few regions including New Delhi, Bihar, and Rajasthan.

One year into the pandemic: Short-term evolution of SARS-CoV-2 and emergence of new lineages

The COVID-19 pandemic was officially declared on March 11th, 2020. Since the very beginning, the spread of the virus has been tracked nearly in real-time by worldwide genome sequencing efforts. As of March 2021, more than 830,000 SARS-CoV-2 genomes have been uploaded in GISAID and this wealth of data allowed researchers to study the evolution of SARS-CoV-2 during this first pandemic year. In parallel, nomenclatures systems, often with poor consistency among each other, have been developed to designate emerging viral lineages. Despite general fears that the virus might mutate to become more virulent or transmissible, SARS-CoV-2 genetic diversity has remained relatively low during the first ~ 8 months of sustained human-to-human transmission. At the end of 2020/beginning of 2021, though, some alarming events started to raise concerns of possible changes in the evolutionary trajectory of the virus. Specifically, three new viral variants associated with extensive transmission have been described as variants of concern (VOC). These variants were first reported in the UK (B.1.1.7), South Africa (B.1.351) and Brazil (P.1). Their designation as VOCs was determined by an increase of local cases and by the high number of amino acid substitutions harboured by these lineages. This latter feature is reminiscent of viral sequences isolated from immunocompromised patients with long-term infection, suggesting a possible causal link. Here we review the events that led to the identification of these lineages, as well as emerging data concerning their possible implications for viral phenotypes, reinfection risk, vaccine efficiency and epidemic potential. Most of the available evidence is, to date, provisional, but still represents a starting point to uncover the potential threat posed by the VOCs. We also stress that genomic surveillance must be strengthened, especially in the wake of the vaccination campaigns.

Molecular Phylogenesis and Spatiotemporal Spread of SARS-CoV-2 in Southeast Asia

Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed an unprecedented challenge to public health in Southeast Asia, a tropical region with limited resources. This study aimed to investigate the evolutionary dynamics and spatiotemporal patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the region. Materials and Methods: A total of 1491 complete SARS-CoV-2 genome sequences from 10 Southeast Asian countries were downloaded from the Global Initiative on Sharing Avian Influenza Data (GISAID) database on November 17, 2020. The evolutionary relationships were assessed using maximum likelihood (ML) and time-scaled Bayesian phylogenetic analyses, and the phylogenetic clustering was tested using principal component analysis (PCA). The spatial patterns of SARS-CoV-2 spread within Southeast Asia were inferred using the Bayesian stochastic search variable selection (BSSVS) model. The effective population size (Ne) trajectory was inferred using the Bayesian Skygrid model. Results: Four major clades (including one potentially endemic) were identified based on the maximum clade credibility (MCC) tree. Similar clustering was yielded by PCA; the first three PCs explained 46.9% of the total genomic variations among the samples. The time to the most recent common ancestor (tMRCA) and the evolutionary rate of SARS-CoV-2 circulating in Southeast Asia were estimated to be November 28, 2019 (September 7, 2019 to January 4, 2020) and 1.446 × 10-3 (1.292 × 10-3 to 1.613 × 10-3) substitutions per site per year, respectively. Singapore and Thailand were the two most probable root positions, with posterior probabilities of 0.549 and 0.413, respectively. There were high-support transmission links (Bayes factors exceeding 1,000) in Singapore, Malaysia, and Indonesia; Malaysia involved the highest number (7) of inferred transmission links within the region. A twice-accelerated viral population expansion, followed by a temporary setback, was inferred during the early stages of the pandemic in Southeast Asia. Conclusions: With available genomic data, we illustrate the phylogeography and phylodynamics of SARS-CoV-2 circulating in Southeast Asia. Continuous genomic surveillance and enhanced strategic collaboration should be listed as priorities to curb the pandemic, especially for regional communities dominated by developing countries.

An Evolutionary Portrait of the Progenitor SARS-CoV-2 and Its Dominant Offshoots in COVID-19 Pandemic

Global sequencing of genomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to reveal new genetic variants that are the key to unraveling its early evolutionary history and tracking its global spread over time. Here we present the heretofore cryptic mutational history and spatiotemporal dynamics of SARS-CoV-2 from an analysis of thousands of high-quality genomes. We report the likely most recent common ancestor of SARS-CoV-2, reconstructed through a novel application and advancement of computational methods initially developed to infer the mutational history of tumor cells in a patient. This progenitor genome differs from genomes of the first coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the United States harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide months before and after the first reported cases of COVID-19 in China. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains that have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic in 2020. There have been multiple replacements of predominant coronavirus strains in Europe and Asia as well as continued presence of multiple high-frequency strains in Asia and North America. We have developed a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).

Evolutionary Tracking of SARS-CoV-2 Genetic Variants Highlights an Intricate Balance of Stabilizing and Destabilizing Mutations

The currently ongoing COVID-19 pandemic caused by SARS-CoV-2 has accounted for millions of infections and deaths across the globe. Genome sequences of SARS-CoV-2 are being published daily in public databases and the availability of these genome data sets has allowed unprecedented access to the mutational patterns of SARS-CoV-2 evolution. We made use of the same genomic information for conducting phylogenetic analysis and identifying lineage-specific mutations. The catalogued lineage-defining mutations were analyzed for their stabilizing or destabilizing impact on viral proteins. We recorded persistence of D614G, S477N, A222V, and V1176F variants and a global expansion of the PANGOLIN variant B.1. In addition, a retention of Q57H (B.1.X), R203K/G204R (B.1.1.X), T85I (B.1.2-B.1.3), G15S+T428I (C.X), and I120F (D.X) variations was observed. Overall, we recorded a striking balance between stabilizing and destabilizing mutations, therefore leading to well-maintained protein structures. With selection pressures in the form of newly developed vaccines and therapeutics to mount in the coming months, the task of mapping viral mutations and recording their impact on key viral proteins should be crucial to preemptively catch any escape mechanism for which SARS-CoV-2 may evolve.

Novel and emerging mutations of SARS-CoV-2: Biomedical implications

Coronavirus disease-19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The SARS-CoV-2 virus strains has geographical diversity associated with diverse severity, mortality rate, and response to treatment that were characterized using phylogenetic network analysis of SARS-CoV-2 genomes. Although, there is no explicit and integrative explanation for these variations, the genetic arrangement, and stability of SARS-CoV-2 are basic contributing factors to its virulence and pathogenesis. Hence, understanding these features can be used to predict the future transmission dynamics of SARS-CoV-2 infection, drug development, and vaccine. In this review, we discuss the most recent findings on the mutations in the SARS-CoV-2, which provide valuable information on the genetic diversity of SARS-CoV-2, especially for DNA-based diagnosis, antivirals, and vaccine development for COVID-19.

Modeling the heterogeneity in COVID-19's reproductive number and its impact on predictive scenarios

The correct evaluation of the reproductive number R for COVID-19 is central in the quantification of the potential scope of the pandemic and the selection of an appropriate course of action. In most models, R is modeled as a constant - effectively averaging out the inherent variability of the transmission process due to varying individual contact rates, population densities, or temporal factors amongst many. Yet, due to the exponential nature of epidemic growth, the error due to this simplification can be rapidly amplified, and its extent remains unknown. How can this intrinsic variability be percolated into epidemic models, and its impact, better quantified? We study this question here through a Bayesian perspective that captures at scale the heterogeneity of a population and environmental conditions, creating a bridge between the traditional agent-based and compartmental approaches. We use our model to simulate the spread as well as the impact of different social distancing strategies on real COVID-19 data, and highlight the significant impact of the heterogeneity. We emphasize that the contribution of this paper focuses on discussing the importance of the impact of R's heterogeneity on uncertainty quantification from a statistical viewpoint, rather than developing new predictive models.

Prevalence of the SNP rs10774671 of the OAS1 gene in Mexico as a possible predisposing factor for RNA virus disease

The COVID-19 pandemic has revealed the susceptibility of certain populations to RNA virus infection. This variety of agents is currently the cause of severe respiratory diseases (SARS-CoV2 and Influenza), Hepatitis C, measles and of high prevalence tropical diseases that are detected throughout the year (Dengue and Zika). The rs10774671 polymorphism is a base change from G to A in the last nucleotide of intron-5 of the OAS1 gene. This change modifies a splicing site and generates isoforms of the OAS1 protein with a higher molecular weight and a demonstrated lower enzymatic activity. The low activity of these OAS1 isoforms makes the innate immune response against RNA virus infections less efficient, representing a previously unattended risk factor for certain populations.

OBJECTIVE

Determine the distribution of rs10774671 in the open population of Mexico.

METHODS

In 98 healthy volunteers, allelic and genotypic frequencies were determined by qPCR using allele specific labeled probes, and the Hardy-Weinberg equilibrium was determined.

RESULTS

The A-allele turned out to be the most prevalent in the analyzed population.

CONCLUSIONS

Our population is genetically susceptible to RNA virus disease due to the predominant presence of the A allele of rs10774671 in the OAS1 gene.

Field and Molecular Epidemiology: How Viral Sequencing Changed Transmission Inferences in the First Portuguese SARS-CoV-2 Infection Cluster

Field epidemiology and viral sequencing provide a comprehensive characterization of transmission chains and allow a better identification of superspreading events. However, very few examples have been presented to date during the COVID-19 pandemic. We studied the first COVID-19 cluster detected in Portugal (59 individuals involved amongst extended family and work environments), following the return of four related individuals from work trips to Italy. The first patient to introduce the virus would be misidentified following the traditional field inquiry alone, as shown by the viral sequencing in isolates from 23 individuals. The results also pointed out family, and not work environment, as the primary mode of transmission.

Characterization of SARS-CoV-2 different variants and related morbidity and mortality: a systematic review

INTRODUCTION

Coronavirus Disease-2019 (SARS-CoV-2) started its devastating trajectory into a global pandemic in Wuhan, China, in December 2019. Ever since, several variants of SARS-CoV-2 have been identified. In the present review, we aimed to characterize the different variants of SARS-CoV-2 and explore the related morbidity and mortality.

METHODS

A systematic review including the current evidence related to different variants of SARS-CoV-2 and the related morbidity and mortality was conducted through a systematic search utilizing the keywords in the online databases including Scopus, PubMed, Web of Science, and Science Direct; we retrieved all related papers and reports published in English from December 2019 to September 2020.

RESULTS

A review of identified articles has shown three main genomic variants, including type A, type B, and type C. we also identified three clades including S, V, and G. Studies have demonstrated that the C14408T and A23403G alterations in the Nsp12 and S proteins are the most prominent alterations in the world, leading to life-threatening mutations.The spike D614G amino acid change has become the most common variant since December 2019. From missense mutations found from Gujarat SARS-CoV-2 genomes, C28854T, deleterious mutation in the nucleocapsid (N) gene was significantly associated with patients' mortality. The other significant deleterious variant (G25563T) is found in patients located in Orf3a and has a potential role in viral pathogenesis.

CONCLUSION

Overall, researchers identified several SARS-CoV-2 variants changing clinical manifestations and increasing the transmissibility, morbidity, and mortality of COVID-19. This should be considered in current practice and interventions to combat the pandemic and prevent related morbidity and mortality.

Severe Acute Respiratory Syndrome Coronavirus 2: The Emergence of Important Genetic Variants and Testing Options for Clinical Laboratories

Monitoring the spread of emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants relies on rapid genetic testing of the viral genome. The sequencing method commonly called next-generation sequencing can identify virus variants. At times, for target-specific mutation detection, reverse transcriptase polymerase chain reaction is used to identify specific variants. The Centers for Disease Control and Prevention's national SARS-CoV-2 Strain Surveillance Program is a comprehensive, population-based U.S. surveillance system to monitor SARS-CoV-2 genes, identifying emerging SARS-CoV-2 variants to determine implications for coronavirus disease 2019 (COVID-19) diagnostics, therapy, and vaccines. This review describes the main viral variants of concern and their potential impacts and briefly describes testing strategies.

Comparative Genomics Reveals Early Emergence and Biased Spatiotemporal Distribution of SARS-CoV-2

Effective systems for the analysis of molecular data are fundamental for monitoring the spread of infectious diseases and studying pathogen evolution. The rapid identification of emerging viral strains, and/or genetic variants potentially associated with novel phenotypic features is one of the most important objectives of genomic surveillance of human pathogens and represents one of the first lines of defense for the control of their spread. During the COVID 19 pandemic, several taxonomic frameworks have been proposed for the classification of SARS-Cov-2 isolates. These systems, which are typically based on phylogenetic approaches, represent essential tools for epidemiological studies as well as contributing to the study of the origin of the outbreak. Here, we propose an alternative, reproducible, and transparent phenetic method to study changes in SARS-CoV-2 genomic diversity over time. We suggest that our approach can complement other systems and facilitate the identification of biologically relevant variants in the viral genome. To demonstrate the validity of our approach, we present comparative genomic analyses of more than 175,000 genomes. Our method delineates 22 distinct SARS-CoV-2 haplogroups, which, based on the distribution of high-frequency genetic variants, fall into four major macrohaplogroups. We highlight biased spatiotemporal distributions of SARS-CoV-2 genetic profiles and show that seven of the 22 haplogroups (and of all of the four haplogroup clusters) showed a broad geographic distribution within China by the time the outbreak was widely recognized—suggesting early emergence and widespread cryptic circulation of the virus well before its isolation in January 2020. General patterns of genomic variability are remarkably similar within all major SARS-CoV-2 haplogroups, with UTRs consistently exhibiting the greatest variability, with s2m, a conserved secondary structure element of unknown function in the 3′-UTR of the viral genome showing evidence of a functional shift. Although several polymorphic sites that are specific to one or more haplogroups were predicted to be under positive or negative selection, overall our analyses suggest that the emergence of novel types is unlikely to be driven by convergent evolution and independent fixation of advantageous substitutions, or by selection of recombined strains. In the absence of extensive clinical metadata for most available genome sequences, and in the context of extensive geographic and temporal biases in the sampling, many questions regarding the evolution and clinical characteristics of SARS-CoV-2 isolates remain open. However, our data indicate that the approach outlined here can be usefully employed in the identification of candidate SARS-CoV-2 genetic variants of clinical and epidemiological importance.