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

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.

Phylogenetic Analysis of SARS-CoV-2 Data Is Difficult

Numerous studies covering some aspects of SARS-CoV-2 data analyses are being published on a daily basis, including a regularly updated phylogeny on nextstrain.org. Here, we review the difficulties of inferring reliable phylogenies by example of a data snapshot comprising a quality-filtered subset of 8,736 out of all 16,453 virus sequences available on May 5, 2020 from gisaid.org. We find that it is difficult to infer a reliable phylogeny on these data due to the large number of sequences in conjunction with the low number of mutations. We further find that rooting the inferred phylogeny with some degree of confidence either via the bat and pangolin outgroups or by applying novel computational methods on the ingroup phylogeny does not appear to be credible. Finally, an automatic classification of the current sequences into subclasses using the mPTP tool for molecular species delimitation is also, as might be expected, not possible, as the sequences are too closely related. We conclude that, although the application of phylogenetic methods to disentangle the evolution and spread of COVID-19 provides some insight, results of phylogenetic analyses, in particular those conducted under the default settings of current phylogenetic inference tools, as well as downstream analyses on the inferred phylogenies, should be considered and interpreted with extreme caution.

Pharmacological Modulators of Autophagy as a Potential Strategy for the Treatment of COVID-19

The family of coronaviruses (CoVs) uses the autophagy machinery of host cells to promote their growth and replication; thus, this process stands out as a potential target to combat COVID-19. Considering the different roles of autophagy during viral infection, including SARS-CoV-2 infection, in this review, we discuss several clinically used drugs that have effects at different stages of autophagy. Among them, we mention (1) lysosomotropic agents, which can prevent CoVs infection by alkalinizing the acid pH in the endolysosomal system, such as chloroquine and hydroxychloroquine, azithromycin, artemisinins, two-pore channel modulators and imatinib; (2) protease inhibitors that can inhibit the proteolytic cleavage of the spike CoVs protein, which is necessary for viral entry into host cells, such as camostat mesylate, lopinavir, umifenovir and teicoplanin and (3) modulators of PI3K/AKT/mTOR signaling pathways, such as rapamycin, heparin, glucocorticoids, angiotensin-converting enzyme inhibitors (IECAs) and cannabidiol. Thus, this review aims to highlight and discuss autophagy-related drugs for COVID-19, from in vitro to in vivo studies. We identified specific compounds that may modulate autophagy and exhibit antiviral properties. We hope that research initiatives and efforts will identify novel or "off-label" drugs that can be used to effectively treat patients infected with SARS-CoV-2, reducing the risk of mortality.

Genomic Analysis and Lineage Identification of SARS-CoV-2 Strains in Migrants Accessing Europe Through the Libyan Route

Many African countries, representing the origin of the majority of refugees, asylum-seekers, and other migrants, toward regions bordering on the Mediterranean area, are experiencing sustained local transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Sicily is one of the main entry gates of migrants crossing into Europe. We conducted a pilot study, based on the full-genome sequencing of SARS-CoV-2 strains isolated from migrants coming to Sicily by crossing the Mediterranean Sea, with the aim to investigate the viral genome polymorphism and to describe their genetic variations and the phylogenetic relationships. On June 21, a nongovernmental organization vessel rescued 210 migrants crossing the Mediterranean Sea from Libya to Sicily. Of them, 13.4% tested positive for SARS-CoV-2. Eighteen whole genome sequences were obtained to explore viral genetic variability. All but one of the sequences clustered with other viral African strains within the lineage A, whereas only one intermixed among B.1 lineage genomes. Our findings documented that most of the investigated migrants acquired SARS-CoV-2 infection before landing in Sicily. However, SARS-CoV-2 transmission during travel or in overcrowded Libyan immigrant camps and/or illegal transport boats could not be ruled out. SARS-CoV-2 molecular surveillance on migrants arriving in Europe through the Sicilian gate may improve the knowledge of global SARS-CoV-2 transmission dynamic also in light of the emergence of new variants.

The variant gambit: COVID-19's next move

More than a year after its emergence, COVID-19, the disease caused by SARS-CoV-2, continues to plague the world and dominate our daily lives. Even with the development of effective vaccines, this coronavirus pandemic continues to cause a fervor with the identification of major new variants hailing from the United Kingdom, South Africa, Brazil, and California. Coupled with worries over a distinct mink strain that has caused human infections and potential for further mutations, SARS-CoV-2 variants bring concerns for increased spread and escape from both vaccine and natural infection immunity. Here, we outline factors driving SARS-CoV-2 variant evolution, explore the potential impact of specific mutations, examine the risk of further mutations, and consider the experimental studies needed to understand the threat these variants pose. In this review, Plante et al. examine SARS-CoV-2 variants including B.1.1.7 (UK), B.1.351 (RSA), P.1 (Brazil), and B.1.429 (California). They focus on what factors contribute to variant emergence, mutations in and outside the spike protein, and studies needed to understand the impact of variants on infection, transmission, and vaccine efficacy.

Assessing Uncertainty in the Rooting of the SARS-CoV-2 Phylogeny

The rooting of the SARS-CoV-2 phylogeny is important for understanding the origin and early spread of the virus. Previously published phylogenies have used different rootings that do not always provide consistent results. We investigate several different strategies for rooting the SARS-CoV-2 tree and provide measures of statistical uncertainty for all methods. We show that methods based on the molecular clock tend to place the root in the B clade, whereas methods based on outgroup rooting tend to place the root in the A clade. The results from the two approaches are statistically incompatible, possibly as a consequence of deviations from a molecular clock or excess back-mutations. We also show that none of the methods provide strong statistical support for the placement of the root in any particular edge of the tree. These results suggest that phylogenetic evidence alone is unlikely to identify the origin of the SARS-CoV-2 virus and we caution against strong inferences regarding the early spread of the virus based solely on such evidence.

Genetic Diversity of SARS-CoV-2 over a One-Year Period of the COVID-19 Pandemic: A Global Perspective

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of coronavirus disease in 2019 (COVID-19). Genome surveillance is a key method to track the spread of SARS-CoV-2 variants. Genetic diversity and evolution of SARS-CoV-2 were analyzed based on 260,673 whole-genome sequences, which were sampled from 62 countries between 24 December 2019 and 12 January 2021. We found that amino acid (AA) substitutions were observed in all SARS-CoV-2 proteins, and the top six proteins with the highest substitution rates were ORF10, nucleocapsid, ORF3a, spike glycoprotein, RNA-dependent RNA polymerase, and ORF8. Among 25,629 amino acid substitutions at 8484 polymorphic sites across the coding region of the SARS-CoV-2 genome, the D614G (93.88%) variant in spike and the P323L (93.74%) variant in RNA-dependent RNA polymerase were the dominant variants on six continents. As of January 2021, the genomic sequences of SARS-CoV-2 could be divided into at least 12 different clades. Distributions of SARS-CoV-2 clades were featured with temporal and geographical dynamics on six continents. Overall, this large-scale analysis provides a detailed mapping of SARS-CoV-2 variants in different geographic areas at different time points, highlighting the importance of evaluating highly prevalent variants in the development of SARS-CoV-2 antiviral drugs and vaccines.

Perfect Match Genomic Landscape strategy: Refinement and customization of reference genomes

The accuracy of the nucleotide sequence of genomes is of utmost importance. The Perfect Match Genomic Landscape (PMGL) is a precise, sensitive, and nonstatistical strategy to detect genome variation. We used this strategy to refine reference genomes from microorganisms belonging to the three domains of life. Our studies show as well that the PMGL can be useful to detect variants in pathogen agents during a pandemic, and to isolate mutations generated during any desired stage of experimental evolution studies. We propose that the PMGL strategy could be the final step in the refinement of any haploid genome, independently of the methodology and algorithms used for its assembly.

When addressing a genomic question, having a reliable and adequate reference genome is of utmost importance. This drives the necessity to refine and customize reference genomes (RGs). Our laboratory has recently developed a strategy, the Perfect Match Genomic Landscape (PMGL), to detect variation between genomes [K. Palacios-Flores et al.. Genetics 208, 1631–1641 (2018)]. The PMGL is precise and sensitive and, in contrast to most currently used algorithms, is nonstatistical in nature. Here we demonstrate the power of PMGL to refine and customize RGs. As a proof-of-concept, we refined different versions of the Saccharomyces cerevisiae RG. We applied the automatic PMGL pipeline to refine the genomes of microorganisms belonging to the three domains of life: the archaea Methanococcus maripaludis and Pyrococcus furiosus; the bacteria Escherichia coli, Staphylococcus aureus, and Bacillus subtilis; and the eukarya Schizosaccharomyces pombe, Aspergillus oryzae, and several strains of Saccharomyces paradoxus. We analyzed the reference genome of the virus SARS-CoV-2 and previously published viral genomes from patients’ samples with COVID-19. We performed a mutation-accumulation experiment in E. coli and show that the PMGL strategy can detect specific mutations generated at any desired step of the whole procedure. We propose that PMGL can be used as a final step for the refinement and customization of any haploid genome, independently of the strategies and algorithms used in its assembly.

Diverse SARS-CoV-2 variants preceded the initial COVID-19 outbreak in Croatia

We developed a next-generation SARS-CoV-2 sequencing platform and obtained the first SARS-CoV-2 sequences from patients in Croatia at the beginning of the COVID-19 outbreak in the spring of 2020. Integrating the sequencing and the epidemiological data, we show that patients were infected with different SARS-CoV-2 variants belonging to different clades (mostly G and GH). This result confirms that there was widespread virus transmission early in 2020. Interestingly, we identified a unique mutation resulting in a V13I substitution in Nsp5A, the main viral protease, in a patient who had not received antiviral therapy.

VERSO: A comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples

We introduce VERSO, a two-step framework for the characterization of viral evolution from sequencing data of viral genomes, which is an improvement on phylogenomic approaches for consensus sequences. VERSO exploits an efficient algorithmic strategy to return robust phylogenies from clonal variant profiles, also in conditions of sampling limitations. It then leverages variant frequency patterns to characterize the intra-host genomic diversity of samples, revealing undetected infection chains and pinpointing variants likely involved in homoplasies. On simulations, VERSO outperforms state-of-the-art tools for phylogenetic inference. Notably, the application to 6,726 amplicon and RNA sequencing samples refines the estimation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution, while co-occurrence patterns of minor variants unveil undetected infection paths, which are validated with contact tracing data. Finally, the analysis of SARS-CoV-2 mutational landscape uncovers a temporal increase of overall genomic diversity and highlights variants transiting from minor to clonal state and homoplastic variants, some of which fall on the spike gene. Available at: https://github.com/BIMIB-DISCo/VERSO.

Comprehensive analysis of genomic diversity of SARS-CoV-2 in different geographic regions of India: an endeavour to classify Indian SARS-CoV-2 strains on the basis of co-existing mutations

Accumulation of mutations within the genome is the primary driving force in viral evolution within an endemic setting. This inherent feature often leads to altered virulence, infectivity and transmissibility, and antigenic shifts to escape host immunity, which might compromise the efficacy of vaccines and antiviral drugs. Therefore, we carried out a genome-wide analysis of circulating SARS-CoV-2 strains to detect the emergence of novel co-existing mutations and trace their geographical distribution within India. Comprehensive analysis of whole genome sequences of 837 Indian SARS-CoV-2 strains revealed the occurrence of 33 different mutations, 18 of which were unique to India. Novel mutations were observed in the S glycoprotein (6/33), NSP3 (5/33), RdRp/NSP12 (4/33), NSP2 (2/33), and N (1/33). Non-synonymous mutations were found to be 3.07 times more prevalent than synonymous mutations. We classified the Indian isolates into 22 groups based on their co-existing mutations. Phylogenetic analysis revealed that the representative strains of each group were divided into various sub-clades within their respective clades, based on the presence of unique co-existing mutations. The A2a clade was found to be dominant in India (71.34%), followed by A3 (23.29%) and B (5.36%), but a heterogeneous distribution was observed among various geographical regions. The A2a clade was highly predominant in East India, Western India, and Central India, whereas the A2a and A3 clades were nearly equal in prevalence in South and North India. This study highlights the divergent evolution of SARS-CoV-2 strains and co-circulation of multiple clades in India. Monitoring of the emerging mutations will pave the way for vaccine formulation and the design of antiviral drugs.

A Journey From SARS-CoV-2 to COVID-19 and Beyond: A Comprehensive Insight of Epidemiology, Diagnosis, Pathogenesis, and Overview of the Progress into Its Therapeutic Management

The 2019 novel coronavirus (2019-nCoV), commonly known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or coronavirus disease 2019 (COVID-19), was first revealed in late 2019 in Wuhan city, Hubei province, China. It was subsequently spread globally and thereby declared as a pandemic by WHO in March 2020. The disease causes severe acute respiratory illness and is highly contagious due to the fast-onward transmission. As of the mid of November 2020, the disease has affected 220 countries with more than 16 million active cases and 1.3 million deaths worldwide. Males, pregnant women, the elderly, immunosuppressed patients, and those with underlying medical conditions are more vulnerable to the disease than the general healthy population. Unfortunately, no definite treatment is available. Although remdesivir as an antiviral had been approved for use in those above 12 years of age and 40 kg weight group, it has been observed to be ineffective in large-scale SOLIDARITY trials by WHO. Moreover, dexamethasone has been found to increase the recovery rate of ventilated patients; oxygen and inhaled nitric oxide as a vasodilator have been given emergency expanded access. In addition, more than 57 clinical trials are being conducted for the development of the vaccines on various platforms. Two vaccines were found to be significantly promising in phase III results. It is concluded that till the approval of a specific treatment or development of a vaccine against this deadly disease, the preventive measures should be followed strictly to reduce the spread of the disease.

World-wide tracking of major SARS-CoV-2 genome haplotypes in sequences of June 1 to November 15, 2020 and discovery of rapid expansion of a new haplotype

Earlier, 13 haplotype groups defined by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome sequence variations were identified in 2790 sequences available in March 2020. Also, 23403A>G that causes p. Asp614Gly in the spike protein and is one of the defining variations of the haplotype group H1, was becoming increasingly prevalent. As a follow-up, 74922 SARS-CoV-2 sequences retrieved from individuals infected in June 1 to November 15 were analyzed. Consistent with the reports on 23403A>G, H1 haplotype frequency increased world-wide; among August to November sequences, only 0.3% were associated with non-H1 haplotypes. This finding prompted assessment of H1 sub-haplotypes among the sequences of the later stage of the coronavirus disease 2019 pandemic. The distribution of the sub-haplotypes differed in different regions, but 98.4% of the sequences were associated with five H1 sub-haplotypes. One of these had not been previously observed and had emerged in Europe by June 2020. The most important finding of the present study is identification of this new sub-haplotype (H1r) and finding evidence that suggest it may have a high potential for expansion. Its frequency had reached 10%-90% in various countries/territories of Europe by the end of September. The new sub-haplotype is defined by seven sequence variations, one of which causes Ala222Val in the spike protein.

Variant analysis of SARS-CoV-2 genomes in the Middle East

Background

Coronavirus (COVID-19) was introduced into society in late 2019 and has now reached over 88 million cases and 1.9 million deaths. The Middle East has a death toll of ~80,000 and over 35000 of these are in Iran, which has over 1.2 million confirmed cases. We expect that Iranian cases caused outbreaks in the neighbouring countries and that variant mapping and phylogenetic analysis can be used to prove this. We also aim to analyse the variants of severe acute respiratory syndrome coronavirus-2 (SARS -CoV-2) to characterise the common genome variants and provide useful data in the global effort to prevent further spread of COVID-19.

Methods

The approach uses bioinformatics approaches including multiple sequence alignment, variant calling and annotation and phylogenetic analysis to identify the genomic variants found in the region. The approach uses 122 samples from the 13 countries of the Middle East sourced from the Global Initiative on Sharing All Influenza Data (GISAID).

Findings

We identified 2200 distinct genome variants including 129 downstream gene variants, 298 frame shift variants, 789 missense variants, 1 start lost, 13 start gained, 1 stop lost, 249 synonymous variants and 720 upstream gene variants. The most common, high impact variants were 10818delTinsG, 2772delCinsC, 14159delCinsC and 2789delAinsA. These high impact variant ultimately results in 36 number of mutations on spike glycoprotein. Variant alignment and phylogenetic tree generation indicates that samples from Iran likely introduced COVID-19 to the rest of the Middle East.

Interpretation

The phylogenetic and variant analysis provides unique insight into mutation types in genomes. Initial introduction of COVID-19 was most likely due to Iranian transmission. Some countries show evidence of novel mutations and unique strains. Increased time in small populations is likely to contribute to more unique genomes. This study provides more in depth analysis of the variants affecting in the region than any other study.

Dynamics of a Dual SARS-CoV-2 Lineage Co-Infection on a Prolonged Viral Shedding COVID-19 Case: Insights into Clinical Severity and Disease Duration

A few molecularly proven severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases of symptomatic reinfection are currently known worldwide, with a resolved first infection followed by a second infection after a 48 to 142-day intervening period. We report a multiple-component study of a clinically severe and prolonged viral shedding coronavirus disease 2019 (COVID-19) case in a 17-year-old Portuguese female. She had two hospitalizations, a total of 19 RT-PCR tests, mostly positive, and criteria for releasing from home isolation at the end of 97 days. The viral genome was sequenced in seven serial samples and in the diagnostic sample from her infected mother. A human genome-wide array (>900 K) was screened on the seven samples, and in vitro culture was conducted on isolates from three late samples. The patient had co-infection by two SARS-CoV-2 lineages, which were affiliated in distinct clades and diverging by six variants. The 20A lineage was absolute at the diagnosis (shared with the patient’s mother), but nine days later, the 20B lineage had 3% frequency, and two months later, the 20B lineage had 100% frequency. The 900 K profiles confirmed the identity of the patient in the serial samples, and they allowed us to infer that she had polygenic risk scores for hospitalization and severe respiratory disease within the normal distributions for a Portuguese population cohort. The early-on dynamic co-infection may have contributed to the severity of COVID-19 in this otherwise healthy young patient, and to her prolonged SARS-CoV-2 shedding profile.

Epidemiology and Clinical Course of First Wave Coronavirus Disease Cases, Faroe Islands

The Faroe Islands was one of the first countries in the Western Hemisphere to eliminate coronavirus disease (COVID-19). During the first epidemic wave in the country, 187 cases were reported between March 3 and April 22, 2020. Large-scale testing and thorough contact tracing were implemented early on, along with lockdown measures. Transmission chains were mapped through patient history and knowledge of contact with prior cases. The most common reported COVID-19 symptoms were fever, headache, and cough, but 11.2% of cases were asymptomatic. Among 187 cases, 8 patients were admitted to hospitals but none were admitted to intensive care units and no deaths occurred. Superspreading was evident during the epidemic because most secondary cases were attributed to just 3 infectors. Even with the high incidence rate in early March, the Faroe Islands successfully eliminated the first wave of COVID-19 through the early use of contact tracing, quarantine, social distancing, and large-scale testing.

Pitfalls of barcodes in the study of worldwide SARS-CoV-2 variation and phylodynamics

Analysis of SARS-CoV-2 genome variation using a minimal number of selected informative sites conforming a genetic barcode presents several drawbacks. We show that purely mathematical procedures for site selection should be supervised by known phylogeny (i) to ensure that solid tree branches are represented instead of mutational hotspots with poor phylogeographic proprieties, and (ii) to avoid phylogenetic redundancy. We propose a procedure that prevents information redundancy in site selection by considering the cumulative informativeness of previously selected sites (as a proxy for phylogenetic-based criteria). This procedure demonstrates that, for short barcodes (e.g., 11 sites), there are thousands of informative site combinations that improve previous proposals. We also show that barcodes based on worldwide databases inevitably prioritize variants located at the basal nodes of the phylogeny, such that most representative genomes in these ancestral nodes are no longer in circulation. Consequently, coronavirus phylodynamics cannot be properly captured by universal genomic barcodes because most SARS-CoV-2 variation is generated in geographically restricted areas by the continuous introduction of domestic variants.

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

We report the likely most recent common ancestor of SARS-CoV-2 - the coronavirus that causes COVID-19. This progenitor SARS-CoV-2 genome was recovered through a novel application and advancement of computational methods initially developed to reconstruct the mutational history of tumor cells in a patient. The progenitor differs from the earliest 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 USA harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide as soon as weeks after the first reported cases of COVID-19. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains, which 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. There have been multiple replacements of predominant coronavirus strains in Europe and Asia and the continued presence of multiple high-frequency strains in Asia and North America. We provide a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).

Pitfalls of barcodes in the study of worldwide SARS-CoV-2 variation and phylodynamics

Analysis of SARS-CoV-2 genome variation using a minimal number of selected informative sites conforming a genetic barcode presents several drawbacks. We show that purely mathematical procedures for site selection should be supervised by known phylogeny (i) to ensure that solid tree branches are represented instead of mutational hotspots with poor phylogeographic proprieties, and (ii) to avoid phylogenetic redundancy. We propose a procedure that prevents information redundancy in site selection by considering the cumulative informativeness of previously selected sites (as a proxy for phylogenetic-based criteria). This procedure demonstrates that, for short barcodes (e.g., 11 sites), there are thousands of informative site combinations that improve previous proposals. We also show that barcodes based on worldwide databases inevitably prioritize variants located at the basal nodes of the phylogeny, such that most representative genomes in these ancestral nodes are no longer in circulation. Consequently, coronavirus phylodynamics cannot be properly captured by universal genomic barcodes because most SARS-CoV-2 variation is generated in geographically restricted areas by the continuous introduction of domestic variants.

Clinical Evaluation of a COVID-19 Antibody Lateral Flow Assay using Point of Care Samples

Introduction

The ongoing SARS-CoV-2 pandemic has spurred the development of numerous point of care (PoC) immunoassays. Assessments of performance of available kits are necessary to determine their clinical utility. Previous studies have mostly performed these assessments in a laboratory setting, which raises concerns of translating findings for PoC use. The aim of this study was to assess the performance of a lateral flow immunoassay for the detection of SARS-CoV-2 antibodies using samples collected at PoC.

Method

One lateral flow immunoassay (Humasis® COVID-19 IgG/IgM) was tested. In total, 50 PCR RT-PCR positive and 52 RT-PCR negative samples were collected at PoC. Fifty serum specimens from Dec 2018 to Feb 2019 were used as controls for specificity. Serum samples collected between Dec 2019 to Feb 2020 were used as additional comparators. Clinical data including symptom onset date was collected from patient history and the medical record.

Results

The overall sensitivity for the kit was 74% (95% CI: 59.7% - 85.4%). The sensitivity for IgM and IgG detection >14 days after date of onset was 88% (95% CI: 68.8% - 97.5%) and 84% (95% CI: 63.9% - 95.5%), with a negative predictive value (NPV) of 94% for IgM (95% CI: 83.5% - 98.8%) and 93% for IgG (95% CI: 81.8% - 97.9%). The overall specificity was 94% (95% CI: 83.5% - 98.8%). The Immunoglobulin specific specificity was 94% for IgM (95% CI: 83.5% - 98.8%) and 98% for IgG (95% CI: 89.4% - 100.0%), with a positive predictive value (PPV) of 88% for IgM (95% CI: 68.8% - 97.5%) and 95% for IgG (95% CI: 77.2% - 99.9%) respectively for samples collected from patients >14 days after date of onset. Specimen collected during early phase of COVID-19 pandemic (Dec 2019 to Feb 2020) showed 11.8% antibody positivity, and 11.3% of PCR-negative patients demonstrated antibody positivity.

Discussion

Humasis® COVID-19 IgG/IgM LFA demonstrates greater than 90% PPV and NPV for samples collected 14 days after the onset of symptoms using samples collected at PoC. While not practical for the diagnosis of acute infection, the use of the lateral flow assays with high specificity may have utility for determining seroprevalence or seroconversion in longitudinal studies.

Phylogeography of SARS-CoV-2 pandemic in Spain: a story of multiple introductions, micro-geographic stratification, founder effects, and super-spreaders

Spain has been one of the main global pandemic epicenters for coronavirus disease 2019 (COVID-19). Here, we analyzed >41 000 genomes (including >26 000 high-quality (HQ) genomes) downloaded from the GISAID repository, including 1 245 (922 HQ) sampled in Spain. The aim of this study was to investigate genome variation of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and reconstruct phylogeographic and transmission patterns in Spain. Phylogeographic analysis suggested at least 34 independent introductions of SARS-CoV-2 to Spain at the beginning of the outbreak. Six lineages spread very successfully in the country, probably favored by super-spreaders, namely, A2a4 (7.8%), A2a5 (38.4%), A2a10 (2.8%), B3a (30.1%), and B9 (8.7%), which accounted for 87.9% of all genomes in the Spanish database. One distinct feature of the Spanish SARS-CoV-2 genomes was the higher frequency of B lineages (39.3%, mainly B3a+B9) than found in any other European country. While B3a, B9, (and an important sub-lineage of A2a5, namely, A2a5c) most likely originated in Spain, the other three haplogroups were imported from other European locations. The B3a strain may have originated in the Basque Country from a B3 ancestor of uncertain geographic origin, whereas B9 likely emerged in Madrid. The time of the most recent common ancestor (TMRCA) of SARS-CoV-2 suggested that the first coronavirus entered the country around 11 February 2020, as estimated from the TMRCA of B3a, the first lineage detected in the country. Moreover, earlier claims that the D614G mutation is associated to higher transmissibility is not consistent with the very high prevalence of COVID-19 in Spain when compared to other countries with lower disease incidence but much higher frequency of this mutation (56.4% in Spain vs. 82.4% in rest of Europe). Instead, the data support a major role of genetic drift in modeling the micro-geographic stratification of virus strains across the country as well as the role of SARS-CoV-2 super-spreaders.

Phylogeography of SARS-CoV-2 pandemic in Spain: a story of multiple introductions, micro-geographic stratification, founder effects, and super-spreaders

Spain has been one of the main global pandemic epicenters for coronavirus disease 2019 (COVID-19). Here, we analyzed >41 000 genomes (including >26 000 high-quality (HQ) genomes) downloaded from the GISAID repository, including 1 245 (922 HQ) sampled in Spain. The aim of this study was to investigate genome variation of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and reconstruct phylogeographic and transmission patterns in Spain. Phylogeographic analysis suggested at least 34 independent introductions of SARS-CoV-2 to Spain at the beginning of the outbreak. Six lineages spread very successfully in the country, probably favored by super-spreaders, namely, A2a4 (7.8%), A2a5 (38.4%), A2a10 (2.8%), B3a (30.1%), and B9 (8.7%), which accounted for 87.9% of all genomes in the Spanish database. One distinct feature of the Spanish SARS-CoV-2 genomes was the higher frequency of B lineages (39.3%, mainly B3a+B9) than found in any other European country. While B3a, B9, (and an important sub-lineage of A2a5, namely, A2a5c) most likely originated in Spain, the other three haplogroups were imported from other European locations. The B3a strain may have originated in the Basque Country from a B3 ancestor of uncertain geographic origin, whereas B9 likely emerged in Madrid. The time of the most recent common ancestor (TMRCA) of SARS-CoV-2 suggested that the first coronavirus entered the country around 11 February 2020, as estimated from the TMRCA of B3a, the first lineage detected in the country. Moreover, earlier claims that the D614G mutation is associated to higher transmissibility is not consistent with the very high prevalence of COVID-19 in Spain when compared to other countries with lower disease incidence but much higher frequency of this mutation (56.4% in Spain vs. 82.4% in rest of Europe). Instead, the data support a major role of genetic drift in modeling the micro-geographic stratification of virus strains across the country as well as the role of SARS-CoV-2 super-spreaders.

Phylogeography of 27,000 SARS-CoV-2 Genomes: Europe as the Major Source of the COVID-19 Pandemic

The novel coronavirus SARS-CoV-2 emerged from a zoonotic transmission in China towards the end of 2019, rapidly leading to a global pandemic on a scale not seen for a century. In order to cast fresh light on the spread of the virus and on the effectiveness of the containment measures adopted globally, we used 26,869 SARS-CoV-2 genomes to build a phylogeny with 20,247 mutation events and adopted a phylogeographic approach. We confirmed that the phylogeny pinpoints China as the origin of the pandemic with major founders worldwide, mainly during January 2020. However, a single specific East Asian founder underwent massive radiation in Europe and became the main actor of the subsequent spread worldwide during March 2020. This lineage accounts for the great majority of cases detected globally and even spread back to the source in East Asia. Despite an East Asian source, therefore, the global pandemic was mainly fueled by its expansion across and out of Europe. It seems likely that travel bans established throughout the world in the second half of March helped to decrease the number of intercontinental exchanges, particularly from mainland China, but were less effective between Europe and North America where exchanges in both directions are visible up to April, long after bans were imposed.

HOW GENETICISTS CONTRIBUTE TO UNDERSTANDING OF COVID-19 DISEASE PATHOGENICITY

Human populations are faced to the COVID-19 pandemic due to the emerging SARS-CoV-2 coronavirus originating from Wuhan (China) and with dramatic Public Health consequences. Despite periods of panic, the scientific community demonstrated an incredible innovation potential and energy ending up in one year with new vaccines to be used in population. Researchers are interrogating on how individual genetic differences contribute to the diversity of clinical manifestations or ethnic and geographic disparities of COVID-19. While efforts were spent to understand mechanistically the infectious potential of the virus, recent progresses in molecular genetics and bioinformatics allowed the characterization of viral sequence and construction of phylogeographical maps of viral dispersion worldwide. These data will help understanding epidemiological disparities among continents and ethnic populations. Much effort was also spent in analyzing host genetics by studying individual genes involved in innate and immune responses or explaining pathogenesis of comorbidities that complicate the fate of elderly patients. Several international consortia launched already Genome wide Association Studies (GWAS) and whole genome sequencing strategies to identify genetic markers with immediate application in patients at risk of respiratory failure. These new genetic data are important not only for understanding susceptibility factors for COVID-19 but they also contain an important message of hope for mankind warranting our survival and health.