Genetic Spectrum and Distinct Evolution Patterns of SARS-CoV-2

Integrated approach for detection of SARS-CoV-2 and its variant by utilizing LAMP and ARMS-PCR

Global impact of COVID-19 pandemic has heightened the urgency for efficient virus detection and identification of variants such as the Q57H mutation. Early and efficient detection of SARS-CoV-2 among densely populated developing countries is paramount objective. Although RT-PCR assays offer accuracy, however, dependence on expansive kits and availability of allied health resources pose an immense challenge for developing countries. In the current study, RT-LAMP based detection of SARS-Cov-2 with subsequent confirmation of Q57H variant through ARMS-PCR was performed. Among the 212 collected samples, 134 yielded positive results, while 78 tested negative using RT-LAMP. Oropharyngeal swabs of suspected individuals were collected and processed for viral RNA isolation. Isolated viral RNA was processed further by using either commercially available WarmStart Master Mix or our in house developed LAMP master mix separately. Subsequently, the end results of each specimen were evaluated by colorimetry. For LAMP assays, primers targeting three genes (ORF1ab, N and S) were designed using PrimerExplorer software. Interestingly, pooling of these three genes in single reaction tube increased sensitivity (95.5%) and specificity (93.5%) of LAMP assay. SARS-CoV-2 positive specimens were screened further for Q57H mutation using ARMS-PCR. Based on amplicon size variation, later confirmed by sequencing, our data showed 18.5% samples positive for Q57H mutation. Hence, these findings strongly advocate use of RT-LAMP-based assay for SARS-CoV-2 screening within suspected general population. Furthermore, ARMS-PCR also provides an efficient mean to detect prevalent mutations against SARS-Cov-2.

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

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

A vigorous study of fractional order mathematical model for SARS-CoV-2 epidemic with Mittag-Leffler kernel

SARS-CoV-2 and its variants have been investigated using a variety of mathematical models. In contrast to multi-strain models, SARS-CoV-2 models exhibit a memory effect that is often overlooked and more realistic. Atangana-Baleanu’s fractional-order operator is discussed in this manuscript for the analysis of the transmission dynamics of SARS-CoV-2. We investigated the transmission mechanism of the SARS-CoV-2 virus using the non-local Atangana-Baleanu fractional-order approach taking into account the different phases of infection and transmission routes. Using conventional ordinary derivative operators, our first step will be to develop a model for the proposed study. As part of the extension, we will incorporate fractional order derivatives into the model where the used operator is the fractional order operator of order Ψ1. Additionally, some basic aspects of the proposed model are examined in addition to calculating the reproduction number and determining the possible equilibrium. Stability analysis of the model is conducted to determine the necessary equilibrium conditions as they are also required in developing a numerical setup. Utilizing the theory of nonlinear functional analysis, for the model, Ulam-Hyers’ stability is established. We present a numerical scheme based on Newton’s polynomial in order to set up an iterative algorithm for the proposed ABC system. The application of this scheme to a variety of values of Φ1 indicates that there is a relationship between infection dynamics and the derivative’s order. We present further simulations which demonstrate the importance and cruciality of different parameters, as well as their effect on the dynamics and administer the disease. Furthermore, this study will provide a better understanding of the mechanisms underlying contagious diseases, thus supporting the development of policies to control them.

Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk

Infectious diseases still threaten global human health, and host genetic factors have been indicated as determining risk factors for observed variations in disease susceptibility, severity, and outcome. We performed a genome-wide meta-analysis on 4624 subjects from the 10,001 Dalmatians cohort, with 14 infection-related traits. Despite a rather small number of cases in some instances, we detected 29 infection-related genetic associations, mostly belonging to rare variants. Notably, the list included the genes CD28, INPP5D, ITPKB, MACROD2, and RSF1, all of which have known roles in the immune response. Expanding our knowledge on rare variants could contribute to the development of genetic panels that could assist in predicting an individual's life-long susceptibility to major infectious diseases. In addition, longitudinal biobanks are an interesting source of information for identifying the host genetic variants involved in infectious disease susceptibility and severity. Since infectious diseases continue to act as a selective pressure on our genomes, there is a constant need for a large consortium of biobanks with access to genetic and environmental data to further elucidate the complex mechanisms behind host-pathogen interactions and infectious disease susceptibility.

Modeling and numerical analysis of a fractional order model for dual variants of SARS-CoV-2☆

This paper considers the novel fractional-order operator developed by Atangana-Baleanu for transmission dynamics of the SARS-CoV-2 epidemic. Assuming the importance of the non-local Atangana-Baleanu fractional-order approach, the transmission mechanism of SARS-CoV-2 has been investigated while taking into account different phases of infection and various transmission routes of the disease. To conduct the proposed study, first of all, we shall formulate the model by using the classical operator of ordinary derivatives. We utilize the fractional order derivative and the model will be extended to a model containing fractional order derivatives. The operator being used is the fractional differential operator and has fractional order Φ1. The model is analyzed further and some basic aspects of the model are investigated besides calculating the basic reproduction number and the possible equilibria of the proposed model. The equilibria of the model are examined for stability purposes and necessary conditions for stability are obtained. Stability is also necessary in terms of numerical setup. The theory of non-linear functional analysis is employed and Ulam-Hyers’s stability of the model is presented. The approach of newton’s polynomial is considered and a new numerical scheme is developed which helped in presenting an iterative process for the proposed ABC system. Based on this scheme, sample curves are obtained for various values of Φ1 and a pattern is derived between the dynamics of the infection and the order of the derivative. Further simulations are presented which show the cruciality and importance of various parameters and the impact of such parameters on the dynamics and control of the disease is presented. The findings of this study will also provide strong conceptual insights into the mechanisms of contagious diseases, assisting global professionals in developing control policies.

Global asymptotic stability, extinction and ergodic stationary distribution in a stochastic model for dual variants of SARS-CoV-2

Several mathematical models have been developed to investigate the dynamics SARS-CoV-2 and its different variants. Most of the multi-strain SARS-CoV-2 models do not capture an important and more realistic feature of such models known as randomness. As the dynamical behavior of most epidemics, especially SARS-CoV-2, is unarguably influenced by several random factors, it is appropriate to consider a stochastic vaccination co-infection model for two strains of SARS-CoV-2. In this work, a new stochastic model for two variants of SARS-CoV-2 is presented. The conditions of existence and the uniqueness of a unique global solution of the stochastic model are derived. Constructing an appropriate Lyapunov function, the conditions for the stochastic system to fluctuate around endemic equilibrium of the deterministic system are derived. Stationary distribution and ergodicity for the new co-infection model are also studied. Numerical simulations are carried out to validate theoretical results. It is observed that when the white noise intensities are larger than certain thresholds and the associated stochastic reproduction numbers are less than unity, both strains die out and go into extinction with unit probability. More-over, it is observed that, for weak white noise intensities, the solution of the stochastic system fluctuates around the endemic equilibrium (EE) of the deterministic model. Frequency distributions are also studied to show random fluctuations due to stochastic white noise intensities. The results presented herein also reveal the impact of vaccination in reducing the co-circulation of SARS-CoV-2 variants within a given population.

Effective Approaches to Study the Genetic Variability of SARS-CoV-2

Significant efforts are being made in many countries around the world to respond to the COVID-19 pandemic by developing diagnostic reagent kits, identifying infected people, determining treatment methods, and finally producing effective vaccines. However, novel coronavirus variants may potentially reduce the effectiveness of all these efforts, demonstrating increased transmissibility and abated response to therapy or vaccines, as well as the possibility of false negative results in diagnostic procedures based on nucleic acid amplification methods. Since the end of 2020, several variants of concern have been discovered around the world. When information about a new, potentially more dangerous strain of pathogen appears, it is crucial to determine the moment of its emergence in a region. Eventually, that permits taking timely measures and minimizing new risks associated with the spreading of the virus. Therefore, numerous nations have made tremendous efforts to identify and trace these virus variants, which necessitates serious technological processes to sequence a large number of viral genomes. Here, we report on our experience as one of the primary laboratories involved in monitoring SARS-CoV-2 variants in Russia. We discuss the various approaches used, describe effective protocols, and outline a potential technique combining several methods to increase the ability to trace genetic variants while minimizing financial and labor costs.

SARS-CoV-2 Amino Acid Mutations Detection in Greek Patients Infected in the First Wave of the Pandemic

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

Advanced Functions Embedded in the Second Version of Database, Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2

The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2 (GESS v2 https://shiny.ph.iu.edu/GESS_v2/) is an updated version of GESS, which has offered a handy query platform to analyze single-nucleotide variants (SNVs) on millions of high coverages and high-quality severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) complete genomes provided by the Global Initiative on Sharing Avian Influenza Data (GISAID). Including the tools in the first version, the GESS v2 is embedded with new functions, which allow users to search SNVs, given the viral nucleotide or amino acid sequence. The GESS v2 helps users to identify SNVs or SARS-CoV-2 lineages enriched in countries of user's interest and show the migration path of a selected lineage on a world map during specific time periods chosen by the users. In addition, the GESS v2 can recognize the dynamic variations of newly emerging SNVs in each month to help users monitor SNVs, which will potentially become dominant soon. More importantly, multiple sets of analyzed results about SNVs can be downloaded directly from the GESS v2 by which users can conduct their own independent research. With these significant updates, the GESS v2 will continue to serve as a public open platform for researchers to explore SARS-CoV-2 evolutionary patterns from the perspectives of the prevalence and impact of SNVs.

Viral surface geometry shapes influenza and coronavirus spike evolution through antibody pressure

The evolution of circulating viruses is shaped by their need to evade antibody response, which mainly targets the viral spike. Because of the high density of spikes on the viral surface, not all antigenic sites are targeted equally by antibodies. We offer here a geometry-based approach to predict and rank the probability of surface residues of SARS spike (S protein) and influenza H1N1 spike (hemagglutinin) to acquire antibody-escaping mutations utilizing in-silico models of viral structure. We used coarse-grained MD simulations to estimate the on-rate (targeting) of an antibody model to surface residues of the spike protein. Analyzing publicly available sequences, we found that spike surface sequence diversity of the pre-pandemic seasonal influenza H1N1 and the sarbecovirus subgenus highly correlates with our model prediction of antibody targeting. In particular, we identified an antibody-targeting gradient, which matches a mutability gradient along the main axis of the spike. This identifies the role of viral surface geometry in shaping the evolution of circulating viruses. For the 2009 H1N1 and SARS-CoV-2 pandemics, a mutability gradient along the main axis of the spike was not observed. Our model further allowed us to identify key residues of the SARS-CoV-2 spike at which antibody escape mutations have now occurred. Therefore, it can inform of the likely functional role of observed mutations and predict at which residues antibody-escaping mutation might arise.

A survey on computational methods in discovering protein inhibitors of SARS-CoV-2

The outbreak of acute respiratory disease in 2019, namely Coronavirus Disease-2019 (COVID-19), has become an unprecedented healthcare crisis. To mitigate the pandemic, there are a lot of collective and multidisciplinary efforts in facilitating the rapid discovery of protein inhibitors or drugs against COVID-19. Although many computational methods to predict protein inhibitors have been developed [ 1– 5], few systematic reviews on these methods have been published. Here, we provide a comprehensive overview of the existing methods to discover potential inhibitors of COVID-19 virus, so-called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). First, we briefly categorize and describe computational approaches by the basic algorithms involved in. Then we review the related biological datasets used in such predictions. Furthermore, we emphatically discuss current knowledge on SARS-CoV-2 inhibitors with the latest findings and development of computational methods in uncovering protein inhibitors against COVID-19.

Case report: change of dominant strain during dual SARS-CoV-2 infection

BACKGROUND

The dual infection with SARS-CoV-2 is poorly described and is currently under discussion. We present a study of two strains of SARS-CoV-2 detected in the same patient during the same disease presentation.

CASE PRESENTATION

A patient in their 90 s was hospitalised with fever. Oropharyngeal swab obtained on the next day (sample 1) tested positive for SARS-CoV-2. Five days later, the patient was transferred to the ICU (intensive care unit) of the hospital specialising in the treatment of COVID-19 patients, where the patient's condition progressively worsened and continuous oxygen insufflation was required. Repeated oropharyngeal swab (sample 2), which was taken eight days after the first one, also tested positive for SARS-CoV-2. After 5 days of ICU treatment, the patient died. The cause of death was a coronavirus infection, which progressed unfavourably due to premorbid status. We have performed sequencing of full SARS-CoV-2 genomes from oropharyngeal swabs obtained eight days apart. Genomic analysis revealed the presence of two genetically distant SARS-CoV-2 strains in both swabs. Detected strains belong to different phylogenetic clades (GH and GR) and differ in seven nucleotide positions. The relative abundance of strains was 70% (GH) and 30% (GR) in the first swab, and 3% (GH) and 97% (GR) in the second swab.

CONCLUSIONS

Our findings suggest that the patient was infected by two genetically distinct SARS-CoV-2 strains at the same time. One of the possible explanations is that the second infection was hospital-acquired. Change of the dominant strain ratio during disease manifestation could be explained by the advantage or higher virulence of the GR clade strain.

Different Strategies for the Identification of SARS-CoV-2 Variants in the Laboratory Practice

A considerable effort has been devoted in all countries to react to the COVID-19 pandemic by tracing infected individuals, containing the spread of the disease, identifying therapies, and producing and distributing vaccines. Currently, a significant concern is the appearance of variants of the virus that may frustrate these efforts by showing increased transmissibility, increased disease severity, reduced response to therapy or vaccines, and ability to escape diagnosis. All countries have therefore devoted a massive attempt to the identification and tracking of these variants, which requires a vast technological effort to sequence a large number of viral genomes. In this paper, we report our experience as one of the Italian laboratories involved in SARS-CoV-2 variant tracing. We summarize the different approaches used, and outline a potential model combining several techniques to increase tracing ability while at the same time minimizing costs.

Viral Load and Patterns of SARS-CoV-2 Dissemination to the Lungs, Mediastinal Lymph Nodes, and Spleen of Patients with COVID-19 Associated Lymphopenia

Lymphopenia is a frequent hematological manifestation, associated with a severe course of COVID-19, with an insufficiently understood pathogenesis. We present molecular genetic immunohistochemical, and electron microscopic data on SARS-CoV-2 dissemination and viral load (VL) in lungs, mediastinum lymph nodes, and the spleen of 36 patients who died from COVID-19. Lymphopenia <1 × 109/L was observed in 23 of 36 (63.8%) patients. In 12 of 36 cases (33%) SARS-CoV-2 was found in lung tissues only with a median VL of 239 copies (range 18-1952) SARS-CoV-2 cDNA per 100 copies of ABL1. Histomorphological changes corresponding to bronchopneumonia and the proliferative phase of DAD were observed in these cases. SARS-CoV-2 dissemination into the lungs, lymph nodes, and spleen was detected in 23 of 36 patients (58.4%) and was associated with the exudative phase of DAD in most of these cases. The median VL in the lungs was 12,116 copies (range 810-250281), lymph nodes-832 copies (range 96-11586), and spleen-71.5 copies (range 0-2899). SARS-CoV-2 in all cases belonged to the 19A strain. A immunohistochemical study revealed SARS-CoV-2 proteins in pneumocytes, alveolar macrophages, and bronchiolar epithelial cells in lung tissue, sinus histiocytes of lymph nodes, as well as cells of the Billroth pulp cords and spleen capsule. SARS-CoV-2 particles were detected by transmission electron microscopy in the cytoplasm of the endothelial cell, macrophages, and lymphocytes. The infection of lymphocytes with SARS-CoV-2 that we discovered for the first time may indicate a possible link between lymphopenia and SARS-CoV-2-mediated cytotoxic effect.

Updated SARS-CoV-2 single nucleotide variants and mortality association

By analyzing newly collected SARS‐CoV‐2 genomes and comparing them with our previous study about SARS‐CoV‐2 single nucleotide variants (SNVs) before June 2020, we found that the SNV clustering had changed remarkably since June 2020. Apart from that the group of SNVs became dominant, which is represented by two nonsynonymous mutations A23403G (S:D614G) and C14408T (ORF1ab:P4715L), a few emerging groups of SNVs were recognized with sharply increased monthly incidence ratios of up to 70% in November 2020. Further investigation revealed sets of SNVs specific to patients' ages and/or gender, or strongly associated with mortality. Our logistic regression model explored features contributing to mortality status, including three critical SNVs, G25088T(S:V1176F), T27484C (ORF7a:L31L), and T25A (upstream of ORF1ab), ages above 40 years old, and the male gender. The protein structure analysis indicated that the emerging subgroups of nonsynonymous SNVs and the mortality‐related ones were located on the protein surface area. The clashes in protein structure introduced by these mutations might in turn affect the viral pathogenesis through the alteration of protein conformation, leading to a difference in transmission and virulence. Particularly, we explored the fact that nonsynonymous SNVs tended to occur in intrinsic disordered regions of Spike and ORF1ab to significantly increase hydrophobicity, suggesting a potential role in the change of protein folding related to immune evasion.

There has been a considerable temporal change of the SARS‐CoV‐2 single nucleotide variants (SNVs) clustering since June 2020. Apart from one group of SNVs that became dominant, a few emerging groups of SNVs were recognized with sharply increased monthly occurrence ratios in November 2020. All of these individual SNVs could be traced back to February or March of 2020 when they were identified for the first time, suggesting a potential incubation period of the collectivity of special groups of SNVs.

114 age‐specific SNVs were identified in one or across multiple age groups.

42 SNVs showed significantly high rates in either males or females.

41 and 30 SNVs were observed with at least twofold higher incidence rates in the death and the nondeath group, respectively.

A logistic regression model demonstrated that three critical SNVs, G25088T(S:V1176F), T27484C (ORF7a:L31L), and T25A (upstream of ORF1ab), ages above 40 years old, and the male group contribute to a relatively higher mortality.

The emerging subgroups of nonsynonymous SNVs and the mortality‐related ones were located on the protein surface area. Nonsynonymous SNVs tended to occur in intrinsically disordered regions of Spike and ORF1ab.

Introduction and Characteristics of SARS-CoV-2 in North-East of Romania During the First COVID-19 Outbreak

Romania officially declared its first Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) case on February 26, 2020. The first and largest coronavirus disease 2019 (COVID-19) outbreak in Romania was recorded in Suceava, North-East region of the country, and originated at the Suceava regional county hospital. Following sheltering-in-place measures, infection rates decreased, only to rise again after relaxation of measures. This study describes the spread of SARS-CoV-2 in Suceava and other parts of Romania and analyses the mutations and their association with clinical manifestation of the disease during the period of COVID-19 outbreak. Sixty-two samples were sequenced via high-throughput platform and screened for variants. For selected mutations, putative biological significance was assessed, and their effects on disease severity. Phylogenetic analysis was conducted on Romanian genomes (n = 112) and on sequences originating from Europe, United Kingdom, Africa, Asia, South, and North America (n = 876). The results indicated multiple introduction events for SARS-CoV-2 in Suceava, mainly from Italy, Spain, United Kingdom, and Russia although some sequences were also related to those from the Czechia, Belgium, and France. Most Suceava genomes contained mutations common to European lineages, such as A20268G, however, approximately 10% of samples were missing such mutations, indicating a possible different arrival route. While overall genome regions ORF1ab, S, and ORF7 were subject to most mutations, several recurring mutations such as A105V were identified, and these were mainly present in severe forms of the disease. Non-synonymous mutations, such as T987N (Thr987Asn in NSP3a domain), associated with changes in a protein responsible for decreasing viral tethering in human host were also present. Patients with diabetes and hypertension exhibited higher risk ratios (RR) of acquiring severe forms of the disease and these were mainly related to A105V mutation. This study identified the arrival routes of SARS-CoV-2 in Romania and revealed potential associations between the SARS-CoV-2 genomic organization circulating in the country and the clinical manifestation of COVID-19 disease.

Association of CXCR6 with COVID-19 severity: delineating the host genetic factors in transcriptomic regulation

The coronavirus disease 2019 (COVID-19) is an infectious disease that mainly affects the host respiratory system with ~ 80% asymptomatic or mild cases and ~ 5% severe cases. Recent genome-wide association studies (GWAS) have identified several genetic loci associated with the severe COVID-19 symptoms. Delineating the genetic variants and genes is important for better understanding its biological mechanisms. We implemented integrative approaches, including transcriptome-wide association studies (TWAS), colocalization analysis, and functional element prediction analysis, to interpret the genetic risks using two independent GWAS datasets in lung and immune cells. To understand the context-specific molecular alteration, we further performed deep learning-based single-cell transcriptomic analyses on a bronchoalveolar lavage fluid (BALF) dataset from moderate and severe COVID-19 patients. We discovered and replicated the genetically regulated expression of CXCR6 and CCR9 genes. These two genes have a protective effect on lung, and a risk effect on whole blood, respectively. The colocalization analysis of GWAS and cis-expression quantitative trait loci highlighted the regulatory effect on CXCR6 expression in lung and immune cells. In the lung-resident memory CD8⁺ T (T_RM) cells, we found a 2.24-fold decrease of cell proportion among CD8⁺ T cells and lower expression of CXCR6 in the severe patients than moderate patients. Pro-inflammatory transcriptional programs were highlighted in the T_RM cellular trajectory from moderate to severe patients. CXCR6 from the 3p21.31 locus is associated with severe COVID-19. CXCR6 tends to have a lower expression in lung T_RM cells of severe patients, which aligns with the protective effect of CXCR6 from TWAS analysis.

The First Molecular Characterization of Serbian SARS-CoV-2 Isolates From a Unique Early Second Wave in Europe

March 6, 2020 is considered as the official date of the beginning of the COVID-19 epidemic in Serbia. In late spring and early summer 2020, Europe recorded a decline in the rate of SARS-CoV-2 infection and subsiding of the first wave. This trend lasted until the fall, when the second wave of the epidemic began to appear. Unlike the rest of Europe, Serbia was hit by the second wave of the epidemic a few months earlier. Already in June 2020, newly confirmed cases had risen exponentially. As the COVID-19 pandemic is the first pandemic in which there has been instant sharing of genomic information on isolates around the world, the aim of this study was to analyze whole SARS-CoV-2 viral genomes from Serbia, to identify circulating variants/clade/lineages, and to explore site-specific mutational patterns in the unique early second wave of the European epidemic. This analysis of Serbian isolates represents the first publication from Balkan countries, which demonstrates the importance of specificities of local transmission especially when preventive measures differ among countries. One hundred forty-eight different genome variants among 41 Serbian isolates were detected in this study. One unique and seven extremely rare mutations were identified, with locally specific continuous dominance of the 20D clade. At the same time, amino acid substitutions of newly identified variants of concern were found in our isolates from October 2020. Future research should be focused on functional characterization of novel mutations in order to understand the exact role of these variations.

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.

V483A: an emerging mutation hotspot of SARS-CoV-2

One of the many mutations that have occurred in the viral genome is the V483A mutation, which is a part of the receptor-binding motif present in the S1 domain of the spike protein. V483A mutant virus is popular in North America with 36 cases so far and frequently occurring in recent days. This review compares the wild-type and the V483A mutants to analyze certain factors like the interaction between the virus and host-cell interface, binding affinity, stability, partition energy, hydrophobicity, occurrence rate and transmissibility. This information can be of monumental importance in vaccine and drug development since the mutants can become resistant to the vaccines and monoclonal antibodies.

Investigating Cellular Trajectories in the Severity of COVID-19 and Their Transcriptional Programs Using Machine Learning Approaches

Single-cell RNA sequencing of the bronchoalveolar lavage fluid (BALF) samples from COVID-19 patients has enabled us to examine gene expression changes of human tissue in response to the SARS-CoV-2 virus infection. However, the underlying mechanisms of COVID-19 pathogenesis at single-cell resolution, its transcriptional drivers, and dynamics require further investigation. In this study, we applied machine learning algorithms to infer the trajectories of cellular changes and identify their transcriptional programs. Our study generated cellular trajectories that show the COVID-19 pathogenesis of healthy-to-moderate and healthy-to-severe on macrophages and T cells, and we observed more diverse trajectories in macrophages compared to T cells. Furthermore, our deep-learning algorithm DrivAER identified several pathways (e.g., xenobiotic pathway and complement pathway) and transcription factors (e.g., MITF and GATA3) that could be potential drivers of the transcriptomic changes for COVID-19 pathogenesis and the markers of the COVID-19 severity. Moreover, macrophages-related functions corresponded more to the disease severity compared to T cells-related functions. Our findings more proficiently dissected the transcriptomic changes leading to the severity of a COVID-19 infection.

Genomic Characterization and Phylogenetic Analysis of SARS-CoV-2 in Libya

The COVID-19 epidemic started in Libya in March 2020 and rapidly spread. To shed some light on the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) strains circulating in Libya, viruses isolated from 10 patients in this country were sequenced, characterized at the genomic level, and compared to genomes isolated in other parts of the world. As nine genomes out of 10 belonged to the SS1 cluster and one to SS4, three datasets were built. One included only African strains and the other two contained internationally representative SS1 and SS4 genomes. Genomic analysis showed that the Libyan strains have some peculiar features in addition to those reported in other world regions. Considering the countries in which the strains are genetically more similar to the Libyan strains, SARS-CoV-2 could have entered Libya from a North African country (possibly Egypt), sub-Saharan Africa (e.g., Ghana, Mali, Nigeria), the Middle East (e.g., Saudi Arabia), or Asia (India, Bangladesh).

Association of CXCR6 with COVID-19 severity: Delineating the host genetic factors in transcriptomic regulation

Background:

The coronavirus disease 2019 (COVID-19) is an infectious disease that mainly affects the host respiratory system with ~80% asymptomatic or mild cases and ~5% severe cases. Recent genome-wide association studies (GWAS) have identified several genetic loci associated with the severe COVID-19 symptoms. Delineating the genetic variants and genes is important for better understanding its biological mechanisms.

Methods:

We implemented integrative approaches, including transcriptome-wide association studies (TWAS), colocalization analysis and functional element prediction analysis, to interpret the genetic risks using two independent GWAS datasets in lung and immune cells. To understand the context-specific molecular alteration, we further performed deep learning-based single cell transcriptomic analyses on a bronchoalveolar lavage fluid (BALF) dataset from moderate and severe COVID-19 patients.

Results:

We discovered and replicated the genetically regulated expression of CXCR6 and CCR9 genes. These two genes have a protective effect on the lung and a risk effect on whole blood, respectively. The colocalization analysis of GWAS and cis-expression quantitative trait loci highlighted the regulatory effect on CXCR6 expression in lung and immune cells. In the lung resident memory CD8⁺ T (T_RM) cells, we found a 3.32-fold decrease of cell proportion and lower expression of CXCR6 in the severe than moderate patients using the BALF transcriptomic dataset. Pro-inflammatory transcriptional programs were highlighted in T_RM cells trajectory from moderate to severe patients.

Conclusions:

CXCR6 from the 3p21.31 locus is associated with severe COVID-19. CXCR6 tends to have a lower expression in lung T_RM cells of severe patients, which aligns with the protective effect of CXCR6 from TWAS analysis. We illustrate one potential mechanism of host genetic factor impacting the severity of COVID-19 through regulating the expression of CXCR6 and T_RM cell proportion and stability. Our results shed light on potential therapeutic targets for severe COVID-19.

SARS-CoV-2 genomic surveillance in Rondônia, Brazilian Western Amazon

SARS-CoV-2 has spread rapidly around the world, with Brazil currently considered an epicenter of the pandemic. The Northern region has the second highest incidence coefficient, as well as the third highest mortality rate in the country. This study aimed to investigate information about the evolutionary history of epidemic spread and genetic aspects of strains isolated on the Western Amazon, in the State of Rondônia, Brazil. It was possible to detect a total of 22 mutations. Some of these alterations may possibly be related to effects on transmissibility, the fidelity of RNA replication, the ability of cancer patients to respond to infection, beyond a mutation that emerged after the introduction of SARS-CoV-2 in Rondônia. At least two events of introduction were detected, corresponding to the B.1 and B.1.1 European lineages. An introduction was observed possibly through Argentina, where strains originated that circulated in the Minas Gerais and Ceará Brazilian states, prior to Rondônia (B.1.), as well as through the Minas Gerais state and the Federal District, which gave rise to strains that spread to Rondônia, from the capital to more rural parts of the state (B.1.1.). The findings show the need to monitor the genetic epidemiology of COVID-19, in order to surveil the virus’s evolution, dispersion and diversity.

Early Diffusion of SARS-CoV-2 Infection in the Inner Area of the Italian Sardinia Island

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been responsible for the coronavirus disease 2019 (COVID-19) pandemic, which started as a severe pneumonia outbreak in Wuhan, China, in December 2019. Italy has been the first European country affected by the pandemic, registering a total of 300,363 cases and 35,741 deaths until September 24, 2020. The geographical distribution of SARS-CoV-2 in Italy during early 2020 has not been homogeneous, including regions severely affected as well as administrative areas being only slightly interested by the infection. Among the latter, Sardinia represents one of the lowest incidence areas likely due to its insular nature.

METHODS

Next-generation sequencing of a small number of complete viral genomes from clinical samples and their virologic and phylogenetic characterization was performed.

RESULTS

We provide a first overview of the SARS-CoV-2 genomic diversity in Sardinia in the early phase of the March-May 2020 pandemic based on viral genomes isolated in the most inner regional hospital of the island. Our analysis revealed a remarkable genetic diversity in local SARS-CoV-2 viral genomes, showing the presence of at least four different clusters that can be distinguished by specific amino acid substitutions. Based on epidemiological information, these sequences can be linked to at least eight different clusters of infection, four of which likely originates from imported cases. In addition, the presence of amino acid substitutions that were not previously reported in Italian patients has been observed, asking for further investigations in a wider population to assess their prevalence and dynamics of emergence during the pandemic.

CONCLUSION

The present study provides a snapshot of the initial phases of the SARS-CoV-2 infection in inner area of the Sardinia Island, showing an unexpected genomic diversity.

A Comprehensive Summary of the Knowledge on COVID-19 Treatment

Currently, the world is challenged by the coronavirus disease 2019 (COVID-19) pandemic. Epidemiologists and researchers worldwide are invariably trying to understand and combat this precarious new disease. Scrutinizing available drug options and developing potential new drugs are urgent needs to subdue this pandemic. Several intervention strategies are being considered and handled worldwide with limited success, and many drug candidates are yet in the trial phase. Despite these limitations, the development of COVID-19 treatment strategies has been accelerated to improve the clinical outcome of patients with COVID-19, and some countries have efficiently kept it under control. Recently, the use of natural and traditional medicine has also set the trend in coronavirus treatment. This review aimed to discuss the prevailing COVID-19 treatment strategies available globally by examining their efficacy, potential mechanisms, limitations, and challenges in predicting a future potential treatment candidate and bridging them with the effective traditional Chinese medicine (TCM). The findings might enrich the knowledge on traditional alternative medication and its complementary role with Western medicine in managing the COVID-19 epidemic.

GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences

The COVID-19 outbreak has become a global emergency since December 2019. Analysis of SARS-CoV-2 sequences can uncover single nucleotide variants (SNVs) and corresponding evolution patterns. The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences (GESS, https://wan-bioinfo.shinyapps.io/GESS/) is a resource to provide comprehensive analysis results based on tens of thousands of high-coverage and high-quality SARS-CoV-2 complete genomes. The database allows user to browse, search and download SNVs at any individual or multiple SARS-CoV-2 genomic positions, or within a chosen genomic region or protein, or in certain country/area of interest. GESS reveals geographical distributions of SNVs around the world and across the states of USA, while exhibiting time-dependent patterns for SNV occurrences which reflect development of SARS-CoV-2 genomes. For each month, the top 100 SNVs that were firstly identified world-widely can be retrieved. GESS also explores SNVs occurring simultaneously with specific SNVs of user's interests. Furthermore, the database can be of great help to calibrate mutation rates and identify conserved genome regions. Taken together, GESS is a powerful resource and tool to monitor SARS-CoV-2 migration and evolution according to featured genomic variations. It provides potential directive information for prevalence prediction, related public health policy making, and vaccine designs.