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1.
Sci Rep ; 12(1): 11735, 2022 07 19.
Article in English | MEDLINE | ID: covidwho-1947493

ABSTRACT

Whole genome sequencing of SARS-CoV-2 has occurred at an unprecedented scale, and can be exploited for characterising outbreak risks at the fine-scale needed to inform control strategies. One setting at continued risk of COVID-19 outbreaks are higher education institutions, associated with student movements at the start of term, close living conditions within residential halls, and high social contact rates. Here we analysed SARS-CoV-2 whole genome sequences in combination with epidemiological data to investigate a large cluster of student cases associated with University of Glasgow accommodation in autumn 2020, Scotland. We identified 519 student cases of SARS-CoV-2 infection associated with this large cluster through contact tracing data, with 30% sequencing coverage for further analysis. We estimated at least 11 independent introductions of SARS-CoV-2 into the student population, with four comprising the majority of detected cases and consistent with separate outbreaks. These four outbreaks were curtailed within a week following implementation of control measures. The impact of student infections on the local community was short-term despite an underlying increase in community infections. Our study highlights the need for context-specific information in the formation of public health policy for higher educational settings.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Disease Outbreaks , Genomics , Health Planning , Humans , SARS-CoV-2/genetics , United States , Universities
4.
J Infect ; 83(1): 96-103, 2021 07.
Article in English | MEDLINE | ID: covidwho-1198895

ABSTRACT

OBJECTIVES: Patients requiring haemodialysis are at increased risk of serious illness with SARS-CoV-2 infection. To improve the understanding of transmission risks in six Scottish renal dialysis units, we utilised the rapid whole-genome sequencing data generated by the COG-UK consortium. METHODS: We combined geographical, temporal and genomic sequence data from the community and hospital to estimate the probability of infection originating from within the dialysis unit, the hospital or the community using Bayesian statistical modelling and compared these results to the details of epidemiological investigations. RESULTS: Of 671 patients, 60 (8.9%) became infected with SARS-CoV-2, of whom 16 (27%) died. Within-unit and community transmission were both evident and an instance of transmission from the wider hospital setting was also demonstrated. CONCLUSIONS: Near-real-time SARS-CoV-2 sequencing data can facilitate tailored infection prevention and control measures, which can be targeted at reducing risk in these settings.


Subject(s)
COVID-19 , SARS-CoV-2 , Bayes Theorem , Hospitals , Humans , Molecular Epidemiology , Renal Dialysis/adverse effects
5.
PLoS Biol ; 19(2): e3001091, 2021 02.
Article in English | MEDLINE | ID: covidwho-1102372

ABSTRACT

The recent emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the underlying cause of Coronavirus Disease 2019 (COVID-19), has led to a worldwide pandemic causing substantial morbidity, mortality, and economic devastation. In response, many laboratories have redirected attention to SARS-CoV-2, meaning there is an urgent need for tools that can be used in laboratories unaccustomed to working with coronaviruses. Here we report a range of tools for SARS-CoV-2 research. First, we describe a facile single plasmid SARS-CoV-2 reverse genetics system that is simple to genetically manipulate and can be used to rescue infectious virus through transient transfection (without in vitro transcription or additional expression plasmids). The rescue system is accompanied by our panel of SARS-CoV-2 antibodies (against nearly every viral protein), SARS-CoV-2 clinical isolates, and SARS-CoV-2 permissive cell lines, which are all openly available to the scientific community. Using these tools, we demonstrate here that the controversial ORF10 protein is expressed in infected cells. Furthermore, we show that the promising repurposed antiviral activity of apilimod is dependent on TMPRSS2 expression. Altogether, our SARS-CoV-2 toolkit, which can be directly accessed via our website at https://mrcppu-covid.bio/, constitutes a resource with considerable potential to advance COVID-19 vaccine design, drug testing, and discovery science.


Subject(s)
COVID-19 Vaccines , COVID-19/diagnosis , COVID-19/virology , Reverse Genetics , SARS-CoV-2/genetics , A549 Cells , Angiotensin-Converting Enzyme 2/metabolism , Animals , Chlorocebus aethiops , Codon , Humans , Hydrazones/pharmacology , Mice , Morpholines/pharmacology , Open Reading Frames , Plasmids/genetics , Pyrimidines/pharmacology , Serine Endopeptidases/metabolism , Vero Cells , Viral Proteins/metabolism
6.
Cell ; 184(5): 1171-1187.e20, 2021 03 04.
Article in English | MEDLINE | ID: covidwho-1051523

ABSTRACT

SARS-CoV-2 can mutate and evade immunity, with consequences for efficacy of emerging vaccines and antibody therapeutics. Here, we demonstrate that the immunodominant SARS-CoV-2 spike (S) receptor binding motif (RBM) is a highly variable region of S and provide epidemiological, clinical, and molecular characterization of a prevalent, sentinel RBM mutation, N439K. We demonstrate N439K S protein has enhanced binding affinity to the hACE2 receptor, and N439K viruses have similar in vitro replication fitness and cause infections with similar clinical outcomes as compared to wild type. We show the N439K mutation confers resistance against several neutralizing monoclonal antibodies, including one authorized for emergency use by the US Food and Drug Administration (FDA), and reduces the activity of some polyclonal sera from persons recovered from infection. Immune evasion mutations that maintain virulence and fitness such as N439K can emerge within SARS-CoV-2 S, highlighting the need for ongoing molecular surveillance to guide development and usage of vaccines and therapeutics.


Subject(s)
COVID-19/immunology , Genetic Fitness , Immune Evasion , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/genetics , Angiotensin-Converting Enzyme 2/chemistry , Antibodies, Neutralizing/genetics , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , COVID-19/virology , Humans , Mutation , Phylogeny , SARS-CoV-2/chemistry , SARS-CoV-2/pathogenicity , Spike Glycoprotein, Coronavirus/chemistry , Virulence
7.
Nat Microbiol ; 6(1): 112-122, 2021 01.
Article in English | MEDLINE | ID: covidwho-989837

ABSTRACT

Coronavirus disease 2019 (COVID-19) was first diagnosed in Scotland on 1 March 2020. During the first month of the outbreak, 2,641 cases of COVID-19 led to 1,832 hospital admissions, 207 intensive care admissions and 126 deaths. We aimed to identify the source and number of introductions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into Scotland using a combined phylogenetic and epidemiological approach. Sequencing of 1,314 SARS-CoV-2 viral genomes from available patient samples enabled us to estimate that SARS-CoV-2 was introduced to Scotland on at least 283 occasions during February and March 2020. Epidemiological analysis confirmed that early introductions of SARS-CoV-2 originated from mainland Europe (the majority from Italy and Spain). We identified subsequent early outbreaks in the community, within healthcare facilities and at an international conference. Community transmission occurred after 2 March, 3 weeks before control measures were introduced. Earlier travel restrictions or quarantine measures, both locally and internationally, would have reduced the number of COVID-19 cases in Scotland. The risk of multiple reintroduction events in future waves of infection remains high in the absence of population immunity.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , SARS-CoV-2/genetics , Adult , Aged , Europe/epidemiology , Genome, Viral , High-Throughput Nucleotide Sequencing , Humans , Male , Middle Aged , Molecular Epidemiology , Phylogeny , SARS-CoV-2/isolation & purification , Spain/epidemiology , Travel/statistics & numerical data
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