Genomics of postvaccination SARS‐CoV‐2 infections during the Delta dominated second wave of COVID‐19 pandemic, from Mumbai Metropolitan Region (MMR), India

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Abstract

The present study was initiated to understand the proportion of predominant variants of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) in postvaccination infections during the Delta dominated second wave of coronavirus disease 2019 (COVID‐19) in the Mumbai Metropolitan Region (MMR) in India and to understand any mutations selected in the postvaccination infections or showing association with any patient demographics. Samples were collected ( n  = 166) from severe/moderate/mild COVID‐19 patients who were either vaccinated (COVISHIELD/COVAXIN—partial/fully vaccinated) or unvaccinated, from a city hospital and from home isolation patients in MMR. A total of 150 viral genomes were sequenced by Oxford Nanopore sequencing and the data of 136 viral genomes were analyzed for clade/lineage and for identifying mutations. The sequences belonged to three clades (21A, 21I, and 21J) and their lineage was identified as either Delta (B.1.617.2) or Delta+ (B.1.617.2 + K417N) or sub‐lineages of Delta variant (AY.120/AY.38/AY.99). A total of 620 mutations were identified of which 10 mutations showed an increase in trend with time (May–October 2021). Associations of six mutations (two in spike, three in orf1a, and one in nucleocapsid) were shown with milder forms of the disease and one mutation (in orf1a) with partial vaccination status. The results indicate a trend toward reduction in disease severity as the wave progressed.

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  1. SciScore for 10.1101/2022.02.26.22271546: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Ethical clearance for the study was obtained from the Institutional Ethics Committees at FMR (FMR/IREC/C19/01/2021 and FMR/IREC/C19/02/2021) and BCH (P6/2021).
    Consent: Written informed consent was obtained from all the patients during recruitment regarding the collection of swab samples and patient metadata (Table 1).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The RT-PCR was carried out in the Bio-Rad CFX96 (Bio-Rad Laboratories, California, USA), real-time PCR Detection System, and SARS-CoV-2 specific genes (N and ORF1) were detected using the COVIpath™ COVID-19 RT-PCR kit (Applied Biosystems-Invitrogen Bioservices India Pvt. Ltd.) as per the manufacturer’s protocol. cDNA Synthesis and Multiplex PCR: Subsequent to RT-PCR, RNA samples with Ct < 33 (150/166) were subjected to reverse transcriptase PCR to convert the SARS-CoV-2 RNA into cDNA for sequencing, using LunaScript RT SuperMix Kit (Cat no: E3010, NEB, Ipswich, USA) as per manufacturer’s protocol.
    SARS-CoV-2
    suggested: (Active Motif Cat# 91351, RRID:AB_2847848)
    DNA libraries were sequenced using the SpotON flow cell (FLO-MIN106, Oxford Nanopore Technologies, UK) in a MinION MK1B sequencer using MinKNOW operating software for primary data acquisition (Oxford Nanopore Technologies, UK).
    MinION
    suggested: (MinION, RRID:SCR_017985)
    MinKNOW
    suggested: None
    Reads were aligned using Minimap2 (v2.17) [17] to the reference genome (MN908947.3).
    Minimap2
    suggested: (Minimap2, RRID:SCR_018550)
    Variants were called using Medaka (v.1.5.0) [18] from the aligned reads and consensus FASTA were created using samtools (v1.14) [19].
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    SnpEff (version latest core) was used to annotate the discovered variants with reference strain NC_045512.
    SnpEff
    suggested: (SnpEff, RRID:SCR_005191)
    Phylogenetic Analysis: The consensus FASTA files from the SARS-CoV-2 were aligned using MAFFT (v7.489) [22] and clustered using Augur (v13.0.0) [23].
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Maximum likelihood trees were constructed with default parameters using IQ-TREE (v2.1.3) [24] and visualised with Auspice (v2.32.1) [25].
    IQ-TREE
    suggested: (IQ-TREE, RRID:SCR_017254)
    Mutation Association Analysis: The association of each mutation (including lineage defining mutations) with clinical parameters such as disease severity (severe/moderate/mild), vaccination status (vaccinated/unvaccinated), vaccine type (COVISHIELD/COVAXIN) and vaccination dose (partially/fully vaccinated) were analyzed using the Chi-square test in GraphPad Prism 6.
    Mutation Association Analysis
    suggested: None
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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: We detected the following sentences addressing limitations in the study:
    However, the limitation of the meagre number of partially vaccinated patients (n=23) in this study should be noted before drawing any conclusion. The third mutation in orf1a (T3255I) is present in the nsp4 protein, whose function is to produce double-membrane vesicles required to form a replication-transcription complex [33]. This mutation may play a role in reducing the formation of active replication-transcription complexes in the host cell, in turn reducing the viral load and explaining its association with the milder disease form. In contrast, another mutation in the nucleocapsid protein (N: R203M) was observed to associate with the milder form of the disease (Fig. 5). It has already been reported that the N: R203M mutation leads to increased packaging of the viral RNA genome producing a 50-fold higher viral load [34]. The association of the N: R203M mutation with milder disease could possibly explain the increase in viral load due to an increase in variant transmission fitness, leading to a tradeoff with disease severity. The increase in the frequency of the mutations orf1a (T3255I) (leading to a potential decrease in viral load) and N: R203M (leading to a possible increase in viral load) in the recent Delta variants and their association with milder disease indicates their significant role in determining the transmission fitness of the newer variants and tradeoff with disease severity. A continued global effort towards ever expanding viral genome sequencing will help to...

    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: We did not find any issues relating to colormaps.


    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.

    Results from scite Reference Check: We found no unreliable references.


    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.