SARS-CoV-2 variant evolution in the United States: High accumulation of viral mutations over time likely through serial Founder Events and mutational bursts

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don't yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

Enzyme Fragment Complementation Driven by Nucleic Acid Hybridization

A modified protein fragment complementation assay has been designed and validated as a gain-of-signal biosensor for nucleic acid:nucleic acid interactions. The assay uses fragments of NanoBiT, the split luciferase reporter enzyme, that are esterified at their C-termini to steramers, sterol-modified oligodeoxynucleotides. The Drosophila hedgehog autoprocessing domain, DHhC, served as a self-cleaving catalyst for these bioconjugations. In the presence of ssDNA or RNA with segments complementary to the steramers and adjacent to one another, the two NanoBiT fragments productively associate, reconstituting NanoBiT enzyme activity. NanoBiT luminescence in samples containing nM ssDNA or RNA template exceeded background by 30-fold and as high as 120-fold depending on assay conditions. A unique feature of this detection system is the absence of a self-labeling domain in the NanoBiT bioconjugates. Eliminating that extraneous bulk broadens the detection range from short oligos to full-length mRNA.

Differential RNA editing landscapes in host cell versus the SARS-CoV-2 genome

The SARS-CoV-2 pandemic was defined by the emergence of new variants formed through virus mutation originating from random errors not corrected by viral proofreading and/or the host antiviral response introducing mutations into the viral genome. While sequencing information hints at cellular RNA editing pathways playing a role in viral evolution, here, we use an in vitro human cell infection model to assess RNA mutation types in two SARS-CoV-2 strains representing the original and the alpha variants. The variants showed both different cellular responses and mutation patterns with alpha showing higher mutation frequency with most substitutions observed being C-U, indicating an important role for apolipoprotein B mRNA editing catalytic polypeptide-like editing. Knockdown of select APOBEC3s through RNAi increased virus production in the original virus, but not in alpha. Overall, these data suggest a deaminase-independent anti-viral function of APOBECs in SARS-CoV-2 while the C-U editing itself might function to enhance genetic diversity enabling evolutionary adaptation.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Seasonal effects decouple SARS-CoV-2 haplotypes worldwide

Background: Variants of concern (VOCs) have been replacing each other during the still rampant COVID-19 pandemic. As a result, SARS-CoV-2 populations have evolved increasingly intricate constellations of mutations that often enhance transmissibility, disease severity, and other epidemiological characteristics. The origin and evolution of these constellations remain puzzling. Methods: Here we study the evolution of VOCs at the proteome level by analyzing about 12 million genomic sequences retrieved from GISAID on July 23, 2022. A total 183,276 mutations were identified and filtered with a relevancy heuristic. The prevalence of haplotypes and free-standing mutations was then tracked monthly in various latitude corridors of the world. Results: A chronology of 22 haplotypes defined three phases driven by protein flexibility-rigidity, environmental sensing, and immune escape. A network of haplotypes illustrated the recruitment and coalescence of mutations into major VOC constellations and seasonal effects of decoupling and loss. Protein interaction networks mediated by haplotypes predicted communications impacting the structure and function of proteins, showing the increasingly central role of molecular interactions involving the spike (S), nucleocapsid (N), and membrane (M) proteins. Haplotype markers either affected fusogenic regions while spreading along the sequence of the S-protein or clustered around binding domains. Modeling of protein structure with AlphaFold2 showed that VOC Omicron and one of its haplotypes were major contributors to the distortion of the M-protein endodomain, which behaves as a receptor of other structural proteins during virion assembly. Remarkably, VOC constellations acted cooperatively to balance the more extreme effects of individual haplotypes. Conclusions: Our study uncovers seasonal patterns of emergence and diversification occurring amid a highly dynamic evolutionary landscape of bursts and waves. The mapping of genetically-linked mutations to structures that sense environmental change with powerful ab initio modeling tools demonstrates the potential of deep-learning for COVID-19 predictive intelligence and therapeutic intervention.

Predicting COVID-19 disease severity from SARS-CoV-2 spike protein sequence by mixed effects machine learning

Epidemiological studies show that COVID-19 variants-of-concern, like Delta and Omicron, pose different risks for severe disease, but they typically lack sequence-level information for the virus. Studies which do obtain viral genome sequences are generally limited in time, location, and population scope. Retrospective meta-analyses require time-consuming data extraction from heterogeneous formats and are limited to publicly available reports. Fortuitously, a subset of GISAID, the global SARS-CoV-2 sequence repository, includes "patient status" metadata that can indicate whether a sequence record is associated with mild or severe disease. While GISAID lacks data on comorbidities relevant to severity, such as obesity and chronic disease, it does include metadata for age and sex to use as additional attributes in modeling. With these caveats, previous efforts have demonstrated that genotype-patient status models can be fit to GISAID data, particularly when country-of-origin is used as an additional feature. But are these models robust and biologically meaningful? This paper shows that, in fact, temporal and geographic biases in sequences submitted to GISAID, as well as the evolving pandemic response, particularly reduction in severe disease due to vaccination, create complex issues for model development and interpretation. This paper poses a potential solution: efficient mixed effects machine learning using GPBoost, treating country as a random effect group. Training and validation using temporally split GISAID data and emerging Omicron variants demonstrates that GPBoost models are more predictive of the impact of spike protein mutations on patient outcomes than fixed effect XGBoost, LightGBM, random forests, and elastic net logistic regression models.

The roles of APOBEC-mediated RNA editing in SARS-CoV-2 mutations, replication and fitness

During COVID-19 pandemic, mutations of SARS-CoV-2 produce new strains that can be more infectious or evade vaccines. Viral RNA mutations can arise from misincorporation by RNA-polymerases and modification by host factors. Analysis of SARS-CoV-2 sequence from patients showed a strong bias toward C-to-U mutation, suggesting a potential mutational role by host APOBEC cytosine deaminases that possess broad anti-viral activity. We report the first experimental evidence demonstrating that APOBEC3A, APOBEC1, and APOBEC3G can edit on specific sites of SARS-CoV-2 RNA to produce C-to-U mutations. However, SARS-CoV-2 replication and viral progeny production in Caco-2 cells are not inhibited by the expression of these APOBECs. Instead, expression of wild-type APOBEC3 greatly promotes viral replication/propagation, suggesting that SARS-CoV-2 utilizes the APOBEC-mediated mutations for fitness and evolution. Unlike the random mutations, this study suggests the predictability of all possible viral genome mutations by these APOBECs based on the UC/AC motifs and the viral genomic RNA structure.

Population genetic models for the spatial spread of adaptive variants: A review in light of SARS-CoV-2 evolution

Theoretical population genetics has long studied the arrival and geographic spread of adaptive variants through the analysis of mathematical models of dispersal and natural selection. These models take on a renewed interest in the context of the COVID-19 pandemic, especially given the consequences that novel adaptive variants have had on the course of the pandemic as they have spread through global populations. Here, we review theoretical models for the spatial spread of adaptive variants and identify areas to be improved in future work, toward a better understanding of variants of concern in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) evolution and other contemporary applications. As we describe, characteristics of pandemics such as COVID-19-such as the impact of long-distance travel patterns and the overdispersion of lineages due to superspreading events-suggest new directions for improving upon existing population genetic models.

An Electrostatically-steered Conformational Selection Mechanism Promotes SARS-CoV-2 Spike Protein Variation

After two years since the outbreak, the COVID-19 pandemic remains a global public health emergency. SARS-CoV-2 variants with substitutions on the spike (S) protein emerge increasing the risk of immune evasion and cross-species transmission. Here, we analyzed the evolution of the S protein as recorded in 276,712 samples collected before the start of vaccination efforts. Our analysis shows that most variants destabilize the S protein trimer, increase its conformational heterogeneity and improve the odds of the recognition by the host cell receptor. Most frequent substitutions promote overall hydrophobicity by replacing charged amino acids, reducing stabilizing local interactions in the unbound S protein trimer. Moreover, our results identify "forbidden" regions that rarely show any sequence variation, and which are related to conformational changes occurring upon fusion. These results are significant for understanding the structure and function of SARS-CoV-2 related proteins which is a critical step in vaccine development and epidemiological surveillance.

From Alpha to Delta-Genetic Epidemiology of SARS-CoV-2 (hCoV-19) in Southern Poland

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

Identifying Markers of Emerging SARS-CoV-2 Variants in Patients With Secondary Immunodeficiency

Since the end of 2019, the world has been challenged by the coronavirus disease 2019 (COVID-19) pandemic. With COVID-19 cases rising globally, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve, resulting in the emergence of variants of interest (VOI) and of concern (VOC). Of the hundreds of millions infected, immunodeficient patients are one of the vulnerable cohorts that are most susceptible to this virus. These individuals include those with preexisting health conditions and/or those undergoing immunosuppressive treatment (secondary immunodeficiency). In these cases, several researchers have reported chronic infections in the presence of anti-COVID-19 treatments that may potentially lead to the evolution of the virus within the host. Such variations occurred in a variety of viral proteins, including key structural ones involved in pathogenesis such as spike proteins. Tracking and comparing such mutations with those arisen in the general population may provide information about functional sites within the SARS-CoV-2 genome. In this study, we reviewed the current literature regarding the specific features of SARS-CoV-2 evolution in immunocompromised patients and identified recurrent de novo amino acid changes in virus isolates of these patients that can potentially play an important role in SARS-CoV-2 pathogenesis and evolution.

The first three waves of the Covid-19 pandemic hint at a limited genetic repertoire for SARS-CoV-2

The genomic diversity of SARS-CoV-2 is the result of a relatively low level of spontaneous mutations introduced during viral replication. With millions of SARS-CoV-2 genome sequences now available, we can begin to assess the overall genetic repertoire of this virus. We find that during 2020, there was a global wave of one variant that went largely unnoticed, possibly because its members were divided over several sublineages (B.1.177 and sublineages B.1.177.XX). We collectively call this Janus, and it was eventually replaced by the Alpha (B.1.1.7) variant of concern (VoC), next replaced by Delta (B.1.617.2), which itself might soon be replaced by a fourth pandemic wave consisting of Omicron (B.1.1.529). We observe that splitting up and redefining variant lineages over time, as was the case with Janus and is now happening with Alpha, Delta and Omicron, is not helpful to describe the epidemic waves spreading globally. Only ∼5% of the 30 000 nucleotides of the SARS-CoV-2 genome are found to be variable. We conclude that a fourth wave of the pandemic with the Omicron variant might not be that different from other VoCs, and that we may already have the tools in hand to effectively deal with this new VoC.

Microbial ecology and evolution is key to pandemics: using the coronavirus model to mitigate future public health challenges

Pandemics are global challenges that lead to total disruption of human activities. From the inception of human existence, all pandemics have resulted in loss of human lives. The coronavirus disease caused by SAR-CoV-2 began in China and is now at the global scale with an increase in mortality and morbidity. Numerous anthropogenic activities have been implicated in the emergence and severity of pandemics, including COVID-19. These activities cause changes in microbial ecology, leading to evolution due to mutation and recombination. This review hypothesized that an understanding of these anthropogenic activities would explain the dynamics of pandemics. The recent coronavirus model was used to study issues leading to microbial evolution, towards preventing future pandemics. Our review highlighted anthropogenic activities, including deforestation, mining activities, waste treatment, burning of fossil fuel, as well as international travels as drivers of microbial evolution leading to pandemics. Furthermore, human-animal interaction has also been implicated in pandemic incidents. Our study recommends substantial control of such anthropogenic activities as having been highlighted as ways to reduce the frequency of mutation, reduce pathogenic reservoirs, and the emergence of infectious diseases.

Mapping Data to Deep Understanding: Making the Most of the Deluge of SARS-CoV-2 Genome Sequences

Next-generation sequencing has been essential to the global response to the COVID-19 pandemic. As of January 2022, nearly 7 million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences are available to researchers in public databases. Sequence databases are an abundant resource from which to extract biologically relevant and clinically actionable information. As the pandemic has gone on, SARS-CoV-2 has rapidly evolved, involving complex genomic changes that challenge current approaches to classifying SARS-CoV-2 variants. Deep sequence learning could be a potentially powerful way to build complex sequence-to-phenotype models. Unfortunately, while they can be predictive, deep learning typically produces "black box" models that cannot directly provide biological and clinical insight. Researchers should therefore consider implementing emerging methods for visualizing and interpreting deep sequence models. Finally, researchers should address important data limitations, including (i) global sequencing disparities, (ii) insufficient sequence metadata, and (iii) screening artifacts due to poor sequence quality control.

Microfluidic point-of-care device for detection of early strains and B.1.1.7 variant of SARS-CoV-2 virus

Since the beginning of the COVID-19 pandemic, several mutations of the SARS-CoV-2 virus have emerged. Current gold standard detection methods for detecting the virus and its variants are based on PCR-based diagnostics using complex laboratory protocols and time-consuming steps, such as RNA isolation and purification, and thermal cycling. These steps limit the translation of technology to the point-of-care and limit accessibility to under-resourced regions. While PCR-based assays currently offer the possibility of multiplexed gene detection, and commercial products of single gene PCR and isothermal LAMP at point-of-care are also now available, reports of isothermal assays at the point-of-care with detection of multiple genes are lacking. Here, we present a microfluidic assay and device to detect and differentiate the Alpha variant (B.1.1.7) from the SARS-CoV-2 virus early strains in saliva samples. The detection assay, which is based on isothermal RT-LAMP amplification, takes advantage of the S-gene target failure (SGTF) to differentiate the Alpha variant from the SARS-CoV-2 virus early strains using a binary detection system based on spatial separation of the primers specific to the N- and S-genes. We use additively manufactured plastic cartridges in a low-cost optical reader system to successfully detect the SARS-CoV-2 virus from saliva samples (positive amplification is detected with concentration ≥10 copies per μL) within 30 min. We demonstrate that our platform can discriminate the B.1.1.7 variant (USA/CA_CDC_5574/2020 isolate) from SARS-CoV-2 negative samples, but also from the SARS-CoV-2 USA-WA1/2020 isolate. The reliability of the developed point-of-care device was confirmed by testing 38 clinical saliva samples, including 20 samples positive for Alpha variant (sensitivity > 90%, specificity = 100%). This study highlights the current relevance of binary-based testing, as the new Omicron variant also exhibits S-gene target failure and could be tested by adapting the approach presented here.

Can the SARS-CoV-2 Omicron Variant Confer Natural Immunity against COVID-19?

The coronavirus disease 2019 (COVID-19) pandemic is still ongoing, with no signs of abatement in sight. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of this pandemic and has claimed over 5 million lives, is still mutating, resulting in numerous variants. One of the newest variants is Omicron, which shows an increase in its transmissibility, but also reportedly reduces hospitalization rates and shows milder symptoms, such as in those who have been vaccinated. As a result, many believe that Omicron provides a natural vaccination, which is the first step toward ending the COVID-19 pandemic. Based on published research and scientific evidence, we review and discuss how the end of this pandemic is predicted to occur as a result of Omicron variants being surpassed in the community. In light of the findings of our research, we believe that it is most likely true that the Omicron variant is a natural way of vaccinating the masses and slowing the spread of this deadly pandemic. While the mutation that causes the Omicron variant is encouraging, subsequent mutations do not guarantee that the disease it causes will be less severe. As the virus continues to evolve, humans must constantly adapt by increasing their immunity through vaccination.

Commentary on “Poor evidence for host-dependent regular RNA editing in the transcriptome of SARS-CoV-2”

Analysis of the SARS-CoV-2 transcriptome has revealed a background of low-frequency intra-host genetic changes with a strong bias towards transitions. A similar pattern is also observed when inter-host variability is considered. We and others have shown that the cellular RNA editing machinery based on ADAR and APOBEC host-deaminases could be involved in the onset of SARS-CoV-2 genetic variability. Our hypothesis is based both on similarities with other known forms of viral genome editing and on the excess of transition changes, which is difficult to explain with errors during viral replication. Zong et al. criticize our analysis on both conceptual and technical grounds. While ultimate proof of an involvement of host deaminases in viral RNA editing will depend on experimental validation, here, we address the criticism to suggest that viral RNA editing is the most reasonable explanation for the observed intra- and inter-host variability.

Detection of A-to-I RNA Editing in SARS-COV-2

ADAR1-mediated deamination of adenosines in long double-stranded RNAs plays an important role in modulating the innate immune response. However, recent investigations based on metatranscriptomic samples of COVID-19 patients and SARS-COV-2-infected Vero cells have recovered contrasting findings. Using RNAseq data from time course experiments of infected human cell lines and transcriptome data from Vero cells and clinical samples, we prove that A-to-G changes observed in SARS-COV-2 genomes represent genuine RNA editing events, likely mediated by ADAR1. While the A-to-I editing rate is generally low, changes are distributed along the entire viral genome, are overrepresented in exonic regions, and are (in the majority of cases) nonsynonymous. The impact of RNA editing on virus-host interactions could be relevant to identify potential targets for therapeutic interventions.

The Roles of APOBEC-mediated RNA Editing in SARS-CoV-2 Mutations, Replication and Fitness.. [PMID: 34981048 PMCID: PMC8722585 DOI: 10.1101/2021.12.18.473309]

During COVID-19 pandemic, mutations of SARS-CoV-2 produce new strains that can be more infectious or evade vaccines. Viral RNA mutations can arise from misincorporation by RNA-polymerases and modification by host factors. Analysis of SARS-CoV-2 sequence from patients showed a strong bias toward C-to-U mutation, suggesting a potential mutational role by host APOBEC cytosine deaminases that possess broad anti-viral activity. We report the first experimental evidence demonstrating that APOBEC3A, APOBEC1, and APOBEC3G can edit on specific sites of SARS-CoV-2 RNA to produce C-to-U mutations. However, SARS-CoV-2 replication and viral progeny production in Caco-2 cells are not inhibited by the expression of these APOBECs. Instead, expression of wild-type APOBEC3 greatly promotes viral replication/propagation, suggesting that SARS-CoV-2 utilizes the APOBEC-mediated mutations for fitness and evolution. Unlike the random mutations, this study suggests the predictability of all possible viral genome mutations by these APOBECs based on the UC/AC motifs and the viral genomic RNA structure.

Efficient Editing of SARS-CoV-2 genomic RNA by Host APOBEC deaminases and Its Potential Impacts on the Viral Replication and Emergence of New Strains in COVID-19 Pandemic

Progress in the Diagnosis and Treatment of COVID-19 in Children: A Review

Coronavirus disease 2019 (COVID-19) has been circulating in many countries around the world, characterized by long incubation period, strong infectivity, strong variability, high population susceptibility and diversified transmission methods. Its causative agent is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Compared with adult patients, the clinical manifestations of COVID-19 in children are often dominated by mild or asymptomatic infections, but children are also important virus carriers and play an important role in the transmission of the virus. In addition, some children will show excessive inflammatory response and experience serious complications such as multisystem inflammatory syndrome in children (MIS-C). At present, the research on COVID-19 in children is still imperfect. This article will review epidemiological characteristics, the mechanism of action, variant characteristics, clinical manifestations, auxiliary examinations and treatment of children with COVID-19, in order to provide help for the diagnosis, treatment and research of children with COVID-19.

The seasonal behaviour of COVID-19 and its galectin-like culprit of the viral spike

Seasonal behaviour is an attribute of many viral diseases. Like other 'winter' RNA viruses, infections caused by the causative agent of COVID-19, SARS-CoV-2, appear to exhibit significant seasonal changes. Here we discuss the seasonal behaviour of COVID-19, emerging viral phenotypes, viral evolution, and how the mutational landscape of the virus affects the seasonal attributes of the disease. We propose that the multiple seasonal drivers behind infectious disease spread (and the spread of COVID-19 specifically) are in 'trade-off' relationships and can be better described within a framework of a 'triangle of viral persistence' modulated by the environment, physiology, and behaviour. This 'trade-off' exists as one trait cannot increase without a decrease in another. We also propose that molecular components of the virus can act as sensors of environment and physiology, and could represent molecular culprits of seasonality. We searched for flexible protein structures capable of being modulated by the environment and identified a galectin-like fold within the N-terminal domain of the spike protein of SARS-CoV-2 as a potential candidate. Tracking the prevalence of mutations in this structure resulted in the identification of a hemisphere-dependent seasonal pattern driven by mutational bursts. We propose that the galectin-like structure is a frequent target of mutations because it helps the virus evade or modulate the physiological responses of the host to further its spread and survival. The flexible regions of the N-terminal domain should now become a focus for mitigation through vaccines and therapeutics and for prediction and informed public health decision making.

Genomic diversity of SARS-CoV-2 in Oxford during United Kingdom's first national lockdown

Epidemiological efforts to model the spread of SARS-CoV-2, the virus that causes COVID-19, are crucial to understanding and containing current and future outbreaks and to inform public health responses. Mutations that occur in viral genomes can alter virulence during outbreaks by increasing infection rates and helping the virus evade the host immune system. To understand the changes in viral genomic diversity and molecular epidemiology in Oxford during the first wave of infections in the United Kingdom, we analyzed 563 clinical SARS-CoV-2 samples via whole-genome sequencing using Nanopore MinION sequencing. Large-scale surveillance efforts during viral epidemics are likely to be confounded by the number of independent introductions of the viral strains into a region. To avoid such issues and better understand the selection-based changes occurring in the SARS-CoV-2 genome, we utilized local isolates collected during the UK's first national lockdown whereby personal interactions, international and national travel were considerably restricted and controlled. We were able to track the short-term evolution of the virus, detect the emergence of several mutations of concern or interest, and capture the viral diversity of the region. Overall, these results demonstrate genomic pathogen surveillance efforts have considerable utility in controlling the local spread of the virus.