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3.
Brief Bioinform ; 22(2): 642-663, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1343629

ABSTRACT

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de.


Subject(s)
COVID-19/prevention & control , Computational Biology , SARS-CoV-2/isolation & purification , Biomedical Research , COVID-19/epidemiology , COVID-19/virology , Genome, Viral , Humans , Pandemics , SARS-CoV-2/genetics
4.
Elife ; 102021 06 29.
Article in English | MEDLINE | ID: covidwho-1287004

ABSTRACT

Background: Rapid identification and investigation of healthcare-associated infections (HCAIs) is important for suppression of SARS-CoV-2, but the infection source for hospital onset COVID-19 infections (HOCIs) cannot always be readily identified based only on epidemiological data. Viral sequencing data provides additional information regarding potential transmission clusters, but the low mutation rate of SARS-CoV-2 can make interpretation using standard phylogenetic methods difficult. Methods: We developed a novel statistical method and sequence reporting tool (SRT) that combines epidemiological and sequence data in order to provide a rapid assessment of the probability of HCAI among HOCI cases (defined as first positive test >48 hr following admission) and to identify infections that could plausibly constitute outbreak events. The method is designed for prospective use, but was validated using retrospective datasets from hospitals in Glasgow and Sheffield collected February-May 2020. Results: We analysed data from 326 HOCIs. Among HOCIs with time from admission ≥8 days, the SRT algorithm identified close sequence matches from the same ward for 160/244 (65.6%) and in the remainder 68/84 (81.0%) had at least one similar sequence elsewhere in the hospital, resulting in high estimated probabilities of within-ward and within-hospital transmission. For HOCIs with time from admission 3-7 days, the SRT probability of healthcare acquisition was >0.5 in 33/82 (40.2%). Conclusions: The methodology developed can provide rapid feedback on HOCIs that could be useful for infection prevention and control teams, and warrants further prospective evaluation. The integration of epidemiological and sequence data is important given the low mutation rate of SARS-CoV-2 and its variable incubation period. Funding: COG-UK HOCI funded by COG-UK consortium, supported by funding from UK Research and Innovation, National Institute of Health Research and Wellcome Sanger Institute.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Cross Infection/diagnosis , Cross Infection/epidemiology , Disease Outbreaks/statistics & numerical data , Population Surveillance/methods , SARS-CoV-2/genetics , Genome, Viral , Hospitals/statistics & numerical data , Humans , Probability , Retrospective Studies , United Kingdom/epidemiology , Whole Genome Sequencing
5.
PLoS Biol ; 19(3): e3001115, 2021 03.
Article in English | MEDLINE | ID: covidwho-1133664

ABSTRACT

Virus host shifts are generally associated with novel adaptations to exploit the cells of the new host species optimally. Surprisingly, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has apparently required little to no significant adaptation to humans since the start of the Coronavirus Disease 2019 (COVID-19) pandemic and to October 2020. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus the early SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses. In contrast, our analysis detects evidence for significant positive episodic diversifying selection acting at the base of the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in these ancestral bat hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor about 1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. While an undiscovered "facilitating" intermediate species cannot be discounted, collectively, our results support the progenitor of SARS-CoV-2 being capable of efficient human-human transmission as a consequence of its adaptive evolutionary history in bats, not humans, which created a relatively generalist virus.


Subject(s)
COVID-19/virology , Chiroptera/virology , SARS-CoV-2/genetics , Viral Zoonoses/virology , Animals , COVID-19/epidemiology , COVID-19/transmission , Evolution, Molecular , Genome, Viral , Host Specificity , Humans , Pandemics , Phylogeny , Receptors, Virus/genetics , SARS-CoV-2/pathogenicity , Selection, Genetic , Viral Zoonoses/genetics , Viral Zoonoses/transmission
8.
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
9.
Virus Evol ; 6(1): veaa034, 2020 Jan.
Article in English | MEDLINE | ID: covidwho-143933

ABSTRACT

A recent study by Tang et al. claimed that two major types of severe acute respiratory syndrome-coronavirus-2 (CoV-2) had evolved in the ongoing CoV disease-2019 pandemic and that one of these types was more 'aggressive' than the other. Given the repercussions of these claims and the intense media coverage of these types of articles, we have examined in detail the data presented by Tang et al., and show that the major conclusions of that paper cannot be substantiated. Using examples from other viral outbreaks, we discuss the difficulty in demonstrating the existence or nature of a functional effect of a viral mutation, and we advise against overinterpretation of genomic data during the pandemic.

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