Comprehensive evolution and molecular characteristics of a large number of SARS-CoV-2 genomes reveal its epidemic trends

Evolutionary and Phylogenetic Dynamics of SARS-CoV-2 Variants: A Genetic Comparative Study of Taiyuan and Wuhan Cities of China

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-sense, single-stranded RNA genome-containing virus which has infected millions of people all over the world. The virus has been mutating rapidly enough, resulting in the emergence of new variants and sub-variants which have reportedly been spread from Wuhan city in China, the epicenter of the virus, to the rest of China and all over the world. The occurrence of mutations in the viral genome, especially in the viral spike protein region, has resulted in the evolution of multiple variants and sub-variants which gives the virus the benefit of host immune evasion and thus renders modern-day vaccines and therapeutics ineffective. Therefore, there is a continuous need to study the genetic characteristics and evolutionary dynamics of the SARS-CoV-2 variants. Hence, in this study, a total of 832 complete genomes of SARS-CoV-2 variants from the cities of Taiyuan and Wuhan in China was genetically characterized and their phylogenetic and evolutionary dynamics studied using phylogenetics, genetic similarity, and phylogenetic network analyses. This study shows that the four most prevalent lineages in Taiyuan and Wuhan are as follows: the Omicron lineages EG.5.1.1, followed by HK.3, FY.3, and XBB.1.16 (Pangolin classification), and clades 23F (EG.5.1), followed by 23H (HK.3), 22F (XBB), and 23D (XBB.1.9) (Nextclade classification), and lineage B followed by the Omicron FY.3, lineage A, and Omicron FL.2.3 (Pangolin classification), and the clades 19A, followed by 22F (XBB), 23F (EG.5.1), and 23H (HK.3) (Nextclade classification), respectively. Furthermore, our genetic similarity analysis show that the SARS-CoV-2 clade 19A-B.4 from Wuhan (name starting with 412981) has the least genetic similarity of about 95.5% in the spike region of the genome as compared to the query sequence of Omicron XBB.2.3.2 from Taiyuan (name starting with 18495234), followed by the Omicron FR.1.4 from Taiyuan (name starting with 18495199) with ~97.2% similarity and Omicron DY.3 (name starting with 17485740) with ~97.9% similarity. The rest of the variants showed ≥98% similarity with the query sequence of Omicron XBB.2.3.2 from Taiyuan (name starting with 18495234). In addition, our recombination analysis results show that the SARS-CoV-2 variants have three statistically significant recombinant events which could have possibly resulted in the emergence of Omicron XBB.1.16 (recombination event 3), FY.3 (recombination event 5), and FL.2.4 (recombination event 7), suggesting some very important information regarding viral evolution. Also, our phylogenetic tree and network analyses show that there are a total of 14 clusters and more than 10,000 mutations which may have probably resulted in the emergence of cluster-I, followed by 47 mutations resulting in the emergence of cluster-II and so on. The clustering of the viral variants of both cities reveals significant information regarding the phylodynamics of the virus among them. The results of our temporal phylogenetic analysis suggest that the variants of Taiyuan have likely emerged as independent variants separate from the variants of Wuhan. This study, to the best of our knowledge, is the first ever genetic comparative study between Taiyuan and Wuhan cities in China. This study will help us better understand the virus and cope with the emergence and spread of new variants at a local as well as an international level, and keep the public health authorities informed for them to make better decisions in designing new viral vaccines and therapeutics. It will also help the outbreak investigators to better examine any future outbreak.

Emergence of SARS and COVID-19 and preparedness for the next emerging disease X

Severe acute respiratory syndrome (SARS) and Coronavirus disease 2019 (COVID-19) are two human Coronavirus diseases emerging in this century, posing tremendous threats to public health and causing great loss to lives and economy. In this review, we retrospect the studies tracing the molecular evolution of SARS-CoV, and we sort out current research findings about the potential ancestor of SARS-CoV-2. Updated knowledge about SARS-CoV-2-like viruses found in wildlife, the animal susceptibility to SARS-CoV-2, as well as the interspecies transmission risk of SARS-related coronaviruses (SARSr-CoVs) are gathered here. Finally, we discuss the strategies of how to be prepared against future outbreaks of emerging or re-emerging coronaviruses.

The most exposed regions of SARS-CoV-2 structural proteins are subject to strong positive selection and gene overlap may locally modify this behavior

The SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic that emerged in 2019 has been an unprecedented event in international science, as it has been possible to sequence millions of genomes, tracking their evolution very closely. This has enabled various types of secondary analyses of these genomes, including the measurement of their sequence selection pressure. In this work, we have been able to measure the selective pressure of all the described SARS-CoV-2 genes, even analyzed by sequence regions, and we show how this type of analysis allows us to separate the genes between those subject to positive selection (usually those that code for surface proteins or those exposed to the host immune system) and those subject to negative selection because they require greater conservation of their structure and function. We have also seen that when another gene with an overlapping reading frame appears within a gene sequence, the overlapping sequence between the two genes evolves under a stronger purifying selection than the average of the non-overlapping regions of the main gene. We propose this type of analysis as a useful tool for locating and analyzing all the genes of a viral genome when an adequate number of sequences are available.IMPORTANCEWe have analyzed the selection pressure of all severe acute respiratory syndrome coronavirus 2 genes by means of the nonsynonymous (Ka) to synonymous (Ks) substitution rate. We found that protein-coding genes are exposed to strong positive selection, especially in the regions of interaction with other molecules (host receptor and genome of the virus itself). However, overlapping coding regions are more protected and show negative selection. This suggests that this measure could be used to study viral gene function as well as overlapping genes.

SARS-CoV-2 within-host diversity of human hosts and its implications for viral immune evasion

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving, bringing great challenges to the control of the virus. In the present study, we investigated the characteristics of SARS-CoV-2 within-host diversity of human hosts and its implications for immune evasion using about 2,00,000 high-depth next-generation genome sequencing data of SARS-CoV-2. A total of 44% of the samples showed within-host variations (iSNVs), and the average number of iSNVs in the samples with iSNV was 1.90. C-to-U is the dominant substitution pattern for iSNVs. C-to-U/G-to-A and A-to-G/U-to-C preferentially occur in 5'-CG-3' and 5'-AU-3' motifs, respectively. In addition, we found that SARS-CoV-2 within-host variations are under negative selection. About 15.6% iSNVs had an impact on the content of the CpG dinucleotide (CpG) in SARS-CoV-2 genomes. We detected signatures of faster loss of CpG-gaining iSNVs, possibly resulting from zinc-finger antiviral protein-mediated antiviral activities targeting CpG, which could be the major reason for CpG depletion in SARS-CoV-2 consensus genomes. The non-synonymous iSNVs in the S gene can largely alter the S protein's antigenic features, and many of these iSNVs are distributed in the amino-terminal domain (NTD) and receptor-binding domain (RBD). These results suggest that SARS-CoV-2 interacts actively with human hosts and attempts to take different evolutionary strategies to escape human innate and adaptive immunity. These new findings further deepen and widen our understanding of the within-host evolutionary features of SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of the coronavirus disease 2019, has evolved rapidly since it was discovered. Recent studies have pointed out that some mutations in the SARS-CoV-2 S protein could confer SARS-CoV-2 the ability to evade the human adaptive immune system. In addition, it is observed that the content of the CpG dinucleotide in SARS-CoV-2 genome sequences has decreased over time, reflecting the adaptation to the human host. The significance of our research is revealing the characteristics of SARS-CoV-2 within-host diversity of human hosts, identifying the causes of CpG depletion in SARS-CoV-2 consensus genomes, and exploring the potential impacts of non-synonymous within-host variations in the S gene on immune escape, which could further deepen and widen our understanding of the evolutionary features of SARS-CoV-2.

Structural, genomic information and computational analysis of emerging coronavirus (SARS-CoV-2)

Background

The emerging viral pandemic worldwide is associated with a novel coronavirus, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). This virus is said to emerge from its epidemic center in Wuhan, China, in 2019. Coronaviruses (CoVs) are single-stranded, giant, enveloped RNA viruses that come under the family of coronaviridae and order Nidovirales which are the crucial pathogens for humans and other vertebrates.

Main body

Coronaviruses are divided into several subfamilies and genera based on the genomic structure and phylogenetic relationship. The name corona is raised due to the presence of spike protein on the envelope of the virus. The structural and genomic study revealed that the total genome size of SARS-CoV-2 is from 29.8 kb to 29.9 kb. The spike protein (S) is a glycoprotein that attaches to the receptor of host cells for entry into the host cell, followed by the attachment of virus RNA to the host ribosome for translation. The phylogenetic analysis of SARS-CoV-2 revealed the similarity (75-88%) with bat SARS-like coronavirus.

Conclusion

The sign and symptoms of novel severe acute respiratory syndrome coronavirus 2 are also discussed in this paper. The worldwide outbreak and prevention from severe acute respiratory syndrome coronavirus 2 are overviewed in the present article. The latest variant of coronavirus and the status of vaccines are also overviewed in the present article.

SARS-CoV-2 Mutant Spectra at Different Depth Levels Reveal an Overwhelming Abundance of Low Frequency Mutations

Populations of RNA viruses are composed of complex and dynamic mixtures of variant genomes that are termed mutant spectra or mutant clouds. This applies also to SARS-CoV-2, and mutations that are detected at low frequency in an infected individual can be dominant (represented in the consensus sequence) in subsequent variants of interest or variants of concern. Here we briefly review the main conclusions of our work on mutant spectrum characterization of hepatitis C virus (HCV) and SARS-CoV-2 at the nucleotide and amino acid levels and address the following two new questions derived from previous results: (i) how is the SARS-CoV-2 mutant and deletion spectrum composition in diagnostic samples, when examined at progressively lower cut-off mutant frequency values in ultra-deep sequencing; (ii) how the frequency distribution of minority amino acid substitutions in SARS-CoV-2 compares with that of HCV sampled also from infected patients. The main conclusions are the following: (i) the number of different mutations found at low frequency in SARS-CoV-2 mutant spectra increases dramatically (50- to 100-fold) as the cut-off frequency for mutation detection is lowered from 0.5% to 0.1%, and (ii) that, contrary to HCV, SARS-CoV-2 mutant spectra exhibit a deficit of intermediate frequency amino acid substitutions. The possible origin and implications of mutant spectrum differences among RNA viruses are discussed.

Molecular evolution and structural analyses of the spike glycoprotein from Brazilian SARS-CoV-2 genomes: the impact of selected mutations

The COVID-19 pandemic caused by SARS-CoV-2 has reached by February 2022 more than 380 million cases and 5.5 million deaths worldwide since its beginning in late 2019, leading to enhanced concern in the scientific community and the general population. One of the most important pieces of this host-pathogen interaction is the spike protein, which binds to the hACE2 cell receptor, mediates the membrane fusion and is the major target of neutralizing antibodies against SARS-CoV-2. The multiple amino acid substitutions observed in this region, specially in RBD have enhanced the hACE2 binding affinity and led to several modifications in the mechanisms of SARS-CoV-2 pathogenesis, improving the viral fitness and/or promoting immune evasion, with potential impact in the vaccine development. In this work, we identified 48 sites under selective pressures, 17 of them with the strongest evidence by the HyPhy tests, including VOC related mutation sites 138, 142, 222, 262, 484, 681, and 845, among others. The coevolutionary analysis identified 28 sites found not to be conditionally independent, such as E484K-N501Y. The molecular dynamics and free energy estimates showed the structural stabilizing effect and the higher impact of E484K for enhanced binding affinity between the spike RBD and hACE2 in P.1 and P.2 lineages (specially with L452V). Structural changes were also identified in the hACE molecule when interacting with B.1.1.7 RDB. Despite some destabilizing substitutions, a stabilizing effect was identified for the majority of the positively selected mutations.Communicated by Ramaswamy H. Sarma.

SARS-CoV-2 Point Mutation and Deletion Spectra and Their Association with Different Disease Outcomes

Mutant spectra of RNA viruses are important to understand viral pathogenesis and response to selective pressures. There is a need to characterize the complexity of mutant spectra in coronaviruses sampled from infected patients. In particular, the possible relationship between SARS-CoV-2 mutant spectrum complexity and disease associations has not been established. In the present study, we report an ultradeep sequencing (UDS) analysis of the mutant spectrum of amplicons from the nsp12 (polymerase)- and spike (S)-coding regions of 30 nasopharyngeal isolates (diagnostic samples) of SARS-CoV-2 of the first COVID-19 pandemic wave (Madrid, Spain, April 2020) classified according to the severity of ensuing COVID-19. Low-frequency mutations and deletions, counted relative to the consensus sequence of the corresponding isolate, were overwhelmingly abundant. We show that the average number of different point mutations, mutations per haplotype, and several diversity indices was significantly higher in SARS-CoV-2 isolated from patients who developed mild disease than in those associated with moderate or severe disease (exitus). No such bias was observed with RNA deletions. Location of amino acid substitutions in the three-dimensional structures of nsp12 (polymerase) and S suggest significant structural or functional effects. Thus, patients who develop mild symptoms may be a richer source of genetic variants of SARS-CoV-2 than patients with moderate or severe COVID-19. IMPORTANCE The study shows that mutant spectra of SARS-CoV-2 from diagnostic samples differ in point mutation abundance and complexity and that significantly larger values were observed in virus from patients who developed mild COVID-19 symptoms. Mutant spectrum complexity is not a uniform trait among isolates. The nature and location of low-frequency amino acid substitutions present in mutant spectra anticipate great potential for phenotypic diversification of SARS-CoV-2.

An evolutionary insight into Severe Acute Respiratory Syndrome Coronavirus 2 Omicron variant of concern

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel virus that belongs to the family Coronaviridae. This virus produces a respiratory illness known as coronavirus disease 2019 (COVID-19) and is to blame for the pandemic of COVID-19. Due to its massive circulation around the world and the capacity of mutation of this virus, genomic studies are much needed in to order to reveal new variants of concern (VOCs). On November 26th, 2021, the WHO announced that a new SARS-CoV-2 VOC, named Omicron, had emerged. In order to get insight into the emergence, spread and evolution of Omicron SARS-CoV-2 variants, a comprehensive phylogenetic study was performed. The results of these studies revealed significant differences in codon usage among the S genes of SARS-CoV-2 VOCs Alfa, Beta, Gamma, Delta and Omicron, which can be linked to SARS-CoV-2 genotypes. Omicron variant did not evolve out of one of the early VOCs, but instead it belongs to a complete different genetic lineage from previous ones. Strains classified as Omicron variants evolved from ancestors that existed around May 15th, 2020, suggesting that this VOC may have been circulating undetected for a period of time until its emergence was observed in South Africa. A rate of evolution of 5.61 × 10⁻⁴ substitutions/site/year was found for Omicron strains enrolled in these analyses. The results of these studies demonstrate that S genes have suitable genetic information for clear assignment of emerging VOCs to its specific genotypes.

Analyses of Long-Term Epidemic Trends and Evolution Characteristics of Haplotype Subtypes Reveal the Dynamic Selection on SARS-CoV-2

The scale of SARS-CoV-2 infection and death is so enormous that further study of the molecular and evolutionary characteristics of SARS-CoV-2 will help us better understand and respond to SARS-CoV-2 outbreaks. The present study analyzed the epidemic and evolutionary characteristics of haplotype subtypes or regions based on 1.8 million high-quality SARS-CoV-2 genomic data. The estimated ratio of the rates of non-synonymous to synonymous changes (Ka/Ks) in North America and the United States were always more than 1.0, while the Ka/Ks in other continents and countries showed a sharp decline, then a slow increase to 1.0, and a dramatic increase over time. H1 (B.1) with the highest substitution rate has become the most dominant haplotype subtype since March 2020 and has evolved into multiple haplotype subtypes with smaller substitution rates. Many evolutionary characteristics of early SARS-CoV-2, such as H3 being the only early haplotype subtype that existed for the shortest time, the global prevalence of H1 and H1-5 (B.1.1) within a month after being detected, and many high divergent genome sequences early in February 2020, indicate the missing of early SARS-CoV-2 genomic data. SARS-CoV-2 experienced dynamic selection from December 2019 to August 2021 and has been under strong positive selection since May 2021. Its transmissibility and the ability of immune escape may be greatly enhanced over time. This will bring greater challenges to the control of the pandemic.

An entropy-based study on mutational trajectory of SARS-CoV-2 in India

The pandemic of COVID-19 has been haunting us for almost the past two years. Although, the vaccination drive is in full swing throughout the world, different mutations of the SARS-CoV-2 virus are making it very difficult to put an end to the pandemic. The second wave in India, one of the worst sufferers of this pandemic, can be mainly attributed to the Delta variant i.e. B.1.617.2. Thus, it is very important to analyse and understand the mutational trajectory of SARS-CoV-2 through the study of the 26 virus proteins. In this regard, more than 17,000 protein sequences of Indian SARS-CoV-2 genomes are analysed using entropy-based approach in order to find the monthly mutational trajectory. Furthermore, Hellinger distance is also used to show the difference of the mutation events between the consecutive months for each of the 26 SARS-CoV-2 protein. The results show that the mutation rates and the mutation events of the viral proteins though changing in the initial months, start stabilizing later on for mainly the four structural proteins while the non-structural proteins mostly exhibit a more constant trend. As a consequence, it can be inferred that the evolution of the new mutative configurations will eventually reduce.

Advances, challenges and opportunities of phylogenetic and social network analysis using COVID-19 data

Coronavirus disease 2019 (COVID-19) has attracted research interests from all fields. Phylogenetic and social network analyses based on connectivity between either COVID-19 patients or geographic regions and similarity between syndrome coronavirus 2 (SARS-CoV-2) sequences provide unique angles to answer public health and pharmaco-biological questions such as relationships between various SARS-CoV-2 mutants, the transmission pathways in a community and the effectiveness of prevention policies. This paper serves as a systematic review of current phylogenetic and social network analyses with applications in COVID-19 research. Challenges in current phylogenetic network analysis on SARS-CoV-2 such as unreliable inferences, sampling bias and batch effects are discussed as well as potential solutions. Social network analysis combined with epidemiology models helps to identify key transmission characteristics and measure the effectiveness of prevention and control strategies. Finally, future new directions of network analysis motivated by COVID-19 data are summarized.

Causes and Consequences of Purifying Selection on SARS-CoV-2

Owing to a lag between a deleterious mutation's appearance and its selective removal, gold-standard methods for mutation rate estimation assume no meaningful loss of mutations between parents and offspring. Indeed, from analysis of closely related lineages, in SARS-CoV-2, the Ka/Ks ratio was previously estimated as 1.008, suggesting no within-host selection. By contrast, we find a higher number of observed SNPs at 4-fold degenerate sites than elsewhere and, allowing for the virus's complex mutational and compositional biases, estimate that the mutation rate is at least 49-67% higher than would be estimated based on the rate of appearance of variants in sampled genomes. Given the high Ka/Ks one might assume that the majority of such intrahost selection is the purging of nonsense mutations. However, we estimate that selection against nonsense mutations accounts for only ∼10% of all the "missing" mutations. Instead, classical protein-level selective filters (against chemically disparate amino acids and those predicted to disrupt protein functionality) account for many missing mutations. It is less obvious why for an intracellular parasite, amino acid cost parameters, notably amino acid decay rate, is also significant. Perhaps most surprisingly, we also find evidence for real-time selection against synonymous mutations that move codon usage away from that of humans. We conclude that there is common intrahost selection on SARS-CoV-2 that acts on nonsense, missense, and possibly synonymous mutations. This has implications for methods of mutation rate estimation, for determining times to common ancestry and the potential for intrahost evolution including vaccine escape.

AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus

In our previous work, we developed an automated tool, AutoVEM, for real-time monitoring the candidate key mutations and epidemic trends of SARS-CoV-2. In this research, we further developed AutoVEM into AutoVEM2. AutoVEM2 is composed of three modules, including call module, analysis module, and plot module, which can be used modularly or as a whole for any virus, as long as the corresponding reference genome is provided. Therefore, it's much more flexible than AutoVEM. Here, we analyzed three existing viruses by AutoVEM2, including SARS-CoV-2, HBV and HPV-16, to show the functions, effectiveness and flexibility of AutoVEM2. We found that the N501Y locus was almost completely linked to the other 16 loci in SARS-CoV-2 genomes from the UK and Europe. Among the 17 loci, 5 loci were on the S protein and all of the five mutations cause amino acid changes, which may influence the epidemic traits of SARS-CoV-2. And some candidate key mutations of HBV and HPV-16, including T350G of HPV-16 and C659T of HBV, were detected. In brief, we developed a flexible automated tool to analyze candidate key mutations and epidemic trends for any virus, which would become a standard process for virus analysis based on genome sequences in the future.

Molecular characterization of SARS-CoV-2 from Bangladesh: implications in genetic diversity, possible origin of the virus, and functional significance of the mutations

In a try to understand the pathogenesis, evolution and epidemiology of the SARS-CoV-2 virus, scientists from all over the world are tracking its genomic changes in real-time. Genomic studies can be helpful in understanding the disease dynamics. We have downloaded 324 complete and near complete SARS-CoV-2 genomes submitted in GISAID database from Bangladesh which were isolated between 30 March to 7 September, 2020. We then compared these genomes with Wuhan reference sequence and found 4160 mutation events including 2253 missense single nucleotide variations, 38 deletions and 10 insertions. The C>T nucleotide change was most prevalent (41% of all mutations) possibly due to selective mutation pressure to reduce CpG sites to evade CpG targeted host immune response. The most frequent mutation that occurred in 98% isolates was 3037C>T which is a synonymous change that usually accompanied 3 other mutations that include 241C>T, 14408C>T (P323L in RdRp) and 23403A>G (D614G in spike protein). The P323L was reported to increase mutation rate and D614G is associated with increased viral replication and currently most prevalent variant circulating all over the world. We identified multiple missense mutations in B-cell and T-cell predicted epitope regions and/or PCR target regions (including R203K and G204R that occurred in 86% of the isolates) that may impact immunogenicity and/or RT-PCR based diagnosis. Our analysis revealed 5 large deletion events in ORF7a and ORF8 gene products that may be associated with less severity of the disease and increased viral clearance. Our phylogeny analysis identified most of the isolates belonged to the Nextstrain clade 20B (86%) and GISAID clade GR (88%). Most of our isolates shared common ancestors either directly with European countries or jointly with middle eastern countries as well as Australia and India. Interestingly, the 19B clade (GISAID S clade) was unique to Chittagong, which was originally prevalent in China. This reveals possible multiple introductions of the virus in Bangladesh via different routes. Hence, more genome sequencing and analysis with related clinical data is needed to interpret functional significance and better predict the disease dynamics that may be helpful for policy makers to control the COVID-19 pandemic.

Relevant SARS-CoV-2 Genome Variation through Six Months of Worldwide Monitoring

Real-time genome monitoring of the SARS-CoV-2 pandemic outbreak is of utmost importance for designing diagnostic tools, guiding antiviral treatment and vaccination strategies. In this study, we present an accurate method for temporal and geographical comparison of mutational events based on GISAID database genome sequencing. Among 42523 SARS-CoV-2 genomes analyzed, we found 23202 variants compared to the reference genome. The Ti/Tv (transition/transversion) ratio was used to filter out possible false-positive errors. Transition mutations generally occurred more frequently than transversions. Our clustering analysis revealed remarkable hotspot mutation patterns for SARS-CoV-2. Mutations were clustered based on how their frequencies changed over time according to each geographical location. We observed some clusters showing a clear variation in mutation frequency and continuously evolving in the world. However, many mutations appeared in specific periods without a clear pattern over time. Various important nonsynonymous mutations were observed, mainly in Oceania and Asia. More than half of these mutations were observed only once. Four hotspot mutations were found in all geographical locations at least once: T265I (NSP2), P314L (NSP12), D614G (S), and Q57H (ORF3a). The current analysis of SARS-CoV-2 genomes provides valuable information on the geographical and temporal mutational evolution of SARS-CoV-2.

Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences

We present an approach to discriminate SARS-CoV-2 virus types based on their RNA sequence descriptions avoiding a sequence alignment. For that purpose, sequences are preprocessed by feature extraction and the resulting feature vectors are analyzed by prototype-based classification to remain interpretable. In particular, we propose to use variants of learning vector quantization (LVQ) based on dissimilarity measures for RNA sequence data. The respective matrix LVQ provides additional knowledge about the classification decisions like discriminant feature correlations and, additionally, can be equipped with easy to realize reject options for uncertain data. Those options provide self-controlled evidence, i.e., the model refuses to make a classification decision if the model evidence for the presented data is not sufficient. This model is first trained using a GISAID dataset with given virus types detected according to the molecular differences in coronavirus populations by phylogenetic tree clustering. In a second step, we apply the trained model to another but unlabeled SARS-CoV-2 virus dataset. For these data, we can either assign a virus type to the sequences or reject atypical samples. Those rejected sequences allow to speculate about new virus types with respect to nucleotide base mutations in the viral sequences. Moreover, this rejection analysis improves model robustness. Last but not least, the presented approach has lower computational complexity compared to methods based on (multiple) sequence alignment.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00521-021-06018-2.

AutoVEM: An automated tool to real-time monitor epidemic trends and key mutations in SARS-CoV-2 evolution

With the global epidemic of SARS-CoV-2, it is important to effectively monitor the variation, haplotype subgroup epidemic trends and key mutations of SARS-CoV-2 over time. This is of great significance to the development of new vaccines, the update of therapeutic drugs, and the improvement of detection methods. The AutoVEM tool developed in the present study could complete all mutations detections, haplotypes classification, haplotype subgroup epidemic trends and candidate key mutations analysis for 131,576 SARS-CoV-2 genome sequences in 18 h on a 1 core CPU and 2 GB RAM computer. Through haplotype subgroup epidemic trends analysis of 131,576 genome sequences, the great significance of the previous 4 specific sites (C241T, C3037T, C14408T and A23403G) was further revealed, and 6 new mutation sites of highly linked (T445C, C6286T, C22227T, G25563T, C26801G and G29645T) were discovered for the first time that might be related to the infectivity, pathogenicity or host adaptability of SARS-CoV-2. In brief, we proposed an integrative method and developed an efficient automated tool to monitor haplotype subgroup epidemic trends and screen for the candidate key mutations in the evolution of SARS-CoV-2 over time for the first time, and all data could be updated quickly to track the prevalence of previous key mutations and new candidate key mutations because of high efficiency of the tool. In addition, the idea of combinatorial analysis in the present study can also provide a reference for the mutation monitoring of other viruses.

UMAP-assisted K-means clustering of large-scale SARS-CoV-2 mutation datasets

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a worldwide devastating effect. Understanding the evolution and transmission of SARS-CoV-2 is of paramount importance for controlling, combating and preventing COVID-19. Due to the rapid growth in both the number of SARS-CoV-2 genome sequences and the number of unique mutations, the phylogenetic analysis of SARS-CoV-2 genome isolates faces an emergent large-data challenge. We introduce a dimension-reduced K-means clustering strategy to tackle this challenge. We examine the performance and effectiveness of three dimension-reduction algorithms: principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and uniform manifold approximation and projection (UMAP). By using four benchmark datasets, we found that UMAP is the best-suited technique due to its stable, reliable, and efficient performance, its ability to improve clustering accuracy, especially for large Jaccard distanced-based datasets, and its superior clustering visualization. The UMAP-assisted K-means clustering enables us to shed light on increasingly large datasets from SARS-CoV-2 genome isolates.

SARS-CoV-2 Molecular Transmission Clusters and Containment Measures in Ten European Regions during the First Pandemic Wave

Background: The spatiotemporal profiling of molecular transmission clusters (MTCs) using viral genomic data can effectively identify transmission networks in order to inform public health actions targeting SARS-CoV-2 spread. Methods: We used whole genome SARS-CoV-2 sequences derived from ten European regions belonging to eight countries to perform phylogenetic and phylodynamic analysis. We developed dedicated bioinformatics pipelines to identify regional MTCs and to assess demographic factors potentially associated with their formation. Results: The total number and the scale of MTCs varied from small household clusters identified in all regions, to a super-spreading event found in Uusimaa-FI. Specific age groups were more likely to belong to MTCs in different regions. The clustered sequences referring to the age groups 50–100 years old (y.o.) were increased in all regions two weeks after the establishment of the lockdown, while those referring to the age group 0–19 y.o. decreased only in those regions where schools’ closure was combined with a lockdown. Conclusions: The spatiotemporal profiling of the SARS-CoV-2 MTCs can be a useful tool to monitor the effectiveness of the interventions and to reveal cryptic transmissions that have not been identified through contact tracing.

Evolutionary study of COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as an emerging coronavirus: Phylogenetic analysis and literature review

Since emerging coronaviruses have always become a human health concern globally especially severe acute respiratory syndrome coronavirus 2 (SARS-CoV) and Middle East respiratory syndrome coronavirus and a novel coronavirus was introduced in Wuhan, China, in December 2019 (called SARS-CoV-2), many researchers focused on its epidemics, virological and clinical features. SARS-CoV-2 is classified as Betacoronaviruses genus and Sarbecovirus subgenus (lineage B). The virus shows a great similarity with SARS-CoV and bat SARS-like coronaviruses. In this study, we evaluate SARS-CoV-2 virus phylogeny and evolution by using current virus and related sequences.

COVID-19 Crisis Creates Opportunity towards Global Monitoring & Surveillance

The spectrum of emerging new diseases as well as re-emerging old diseases is broadening as infectious agents evolve, adapt, and spread at enormous speeds in response to changing ecosystems. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a recent phenomenon and may take a while to understand its transmission routes from less traveled territories, ranging from fomite exposure routes to wastewater transmission. The critical challenge is how to negotiate with such catastrophic pandemics in high-income countries (HICs ~20% of the global population) and low-and middle-income countries (LMICs ~ 80% of the global population) with a total global population size of approximately eight billion, where practical mass testing and tracing is only a remote possibility, particularly in low-and middle-income countries (LMICs). Keeping in mind the population distribution disparities of high-income countries (HICs) and LMICs and urbanisation trends over recent years, traditional wastewater-based surveillance such as that used to combat polio may help in addressing this challenge. The COVID-19 era differs from any previous pandemics or global health challenges in the sense that there is a great deal of curiosity within the global community to find out everything about this virus, ranging from diagnostics, potential vaccines/therapeutics, and possible routes of transmission. In this regard, the fact that the gut is the common niche for both poliovirus and SARS-CoV-2, and due to the shedding of the virus through faecal material into sewerage systems, the need for long-term wastewater surveillance and developing early warning systems for better preparedness at local and global levels is increasingly apparent. This paper aims to provide an insight into the ongoing COVID-19 crisis, how it can be managed, and what measures are required to deal with a current global international public health concern. Additionally, it shed light on the importance of using wastewater surveillance strategy as an early warning practical tool suitable for massive passive screening, as well as the urgent need for microfluidic technology as a rapid and cost-effective approach tracking SARS-CoV-2 in wastewater.

Isolation and characterization of an early SARS-CoV-2 isolate from the 2020 epidemic in Medellín, Colombia

Introduction: SARS-CoV-2 has been identified as the new coronavirus causing an outbreak of acute respiratory disease in China in December, 2019. This disease, currently named COVID-19, has been declared as a pandemic by the World Health Organization (WHO). The first case of COVID-19 in Colombia was reported on March 6, 2020. Here we characterize an early SARS-CoV-2 isolate from the pandemic recovered in April, 2020. Objective: To describe the isolation and characterization of an early SARS-CoV-2 isolate from the epidemic in Colombia. Materials and methods: A nasopharyngeal specimen from a COVID-19 positive patient was inoculated on different cell lines. To confirm the presence of SARS-CoV-2 on cultures we used qRT-PCR, indirect immunofluorescence assay, transmission and scanning electron microscopy, and next-generation sequencing. Results: We determined the isolation of SARS-CoV-2 in Vero-E6 cells by the appearance of the cytopathic effect three days post-infection and confirmed it by the positive results in the qRT-PCR and the immunofluorescence with convalescent serum. Transmission and scanning electron microscopy images obtained from infected cells showed the presence of structures compatible with SARS-CoV-2. Finally, a complete genome sequence obtained by next-generation sequencing allowed classifying the isolate as B.1.5 lineage. Conclusion: The evidence presented in this article confirms the first isolation of SARSCoV-2 in Colombia. In addition, it shows that this strain behaves in cell culture in a similar way to that reported in the literature for other isolates and that its genetic composition is consistent with the predominant variant in the world. Finally, points out the importance of viral isolation for the detection of neutralizing antibodies, for the genotypic and phenotypic characterization of the strain and for testing compounds with antiviral potential.

Prediction and evolution of B cell epitopes of surface protein in SARS-CoV-2

BACKGROUND

In order to obtain antibodies that recognize natural proteins, it is possible to predict the antigenic determinants of natural proteins, which are eventually embodied as polypeptides. The polypeptides can be coupled with corresponding vectors to stimulate the immune system to produce corresponding antibodies, which is also a simple and effective vaccine development method. The discovery of epitopes is helpful to the development of SARS-CoV-2 vaccine.

METHODS

The analyses were related to epitopes on 3 proteins, including spike (S), envelope (E) and membrane (M) proteins, which are located on the lipid envelope of the SARS-CoV-2. Based on the NCBI Reference Sequence: NC_045512.2, the conformational and linear B cell epitopes of the surface protein were predicted separately by various prediction methods. Furthermore, the conservation of the epitopes, the adaptability and other evolutionary characteristics were also analyzed, the sequences of the whole genome of SARS-CoV-2 were obtained from the GISAID.

RESULTS

7 epitopes were predicted, including 6 linear epitopes and 1 conformational epitope. One of the linear and one of the conformational consist of identical sequence, but represent different forms of epitopes. It is worth mentioning that all 6 identified epitopes were conserved in nearly 3500 SARS-CoV-2 genomes, showing that it is helpful to obtain stable and long-acting epitopes under the condition of high frequency of amino acid mutation, which deserved further study at the experiment level.

CONCLUSION

The findings would facilitate the vaccine development, had the potential to be directly applied on the prevention in this disease, but also have the potential to prevent the possible threats caused by other types of coronavirus.

Molecular Epidemiology Analysis of SARS-CoV-2 Strains Circulating in Romania during the First Months of the Pandemic

BACKGROUND

The spread of SARS-CoV-2 generated an unprecedented global public health crisis. Soon after Asia, Europe was seriously affected. Many countries, including Romania, adopted lockdown measures to limit the outbreak.

AIM

We performed a molecular epidemiology analysis of SARS-CoV-2 viral strains circulating in Romania during the first two months of the epidemic in order to detect mutation profiles and phylogenetic relatedness.

METHODS

Respiratory samples were directly used for shotgun sequencing.

RESULTS

All Romanian sequences belonged to lineage B, with a different subtype distribution between northern and southern regions (subtype B.1.5 and B.1.1). Phylogenetic analysis suggested that the Romanian epidemic started with multiple introduction events from other European countries followed by local transmission. Phylogenetic links between northern Romania and Spain, Austria, Scotland and Russia were observed, as well as between southern Romania and Switzerland, Italy, France and Turkey. One viral strain presented a previously unreported mutation in the Nsp2 gene, namely K489E. Epidemiologically-defined clusters displayed specific mutations, suggesting molecular signatures for strains coming from areas that were isolated during the lockdown.

CONCLUSIONS

Romanian epidemic was initiated by multiple introductions from European countries followed by local transmissions. Different subtype distribution between northern and southern Romania was observed after two months of the pandemic.