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

  1. Andrei Lobiuc
  2. Mihai Dimian
  3. Roxana Gheorghita
  4. Olga Adriana Caliman Sturdza
  5. Mihai Covasa

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Abstract

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.

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  1. Version published to 10.3389/fmicb.2021.654417
  2. ScreenIT

    SciScore for 10.1101/2020.12.22.20248741: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: Patients signed informed consent for data access and the study was approved by the University of Suceava Research Ethics Committee.
    IRB: Patients signed informed consent for data access and the study was approved by the University of Suceava Research Ethics Committee.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Sample preparation and sequencing: RNA extraction was performed using Bioneer
    Bioneer
    suggested: None
    Sequence processing and data availability: Sequences were assembled using the Iterative Refinement Meta Assembler (IRMA), after which variants were called with Torrent VariantCaller plugin, referenced to the Wuhan SARS-CoV-2 sequence and annotated using SnpEff plugin.
    SnpEff
    suggested: (SnpEff, RRID:SCR_005191)
    Prior to phylogenetic analyses, all samples were aligned using MAFFT algorithm, then trimmed at ends, to remove unnecessary artifacts caused by sequencing in those areas.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Bayesian time dated phylogenetic analysis of the data set was performed using BEAST 2.6.3, with Beagle library enabled.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)
    Beagle
    suggested: (BEAGLE, RRID:SCR_001789)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on pages 34 and 35. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.12.22.20248741v1 on medRxiv