ABSTRACT
We announce the coding-complete genome sequences of 23 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron strains obtained from Bangladeshi individuals. The Oxford Nanopore Technologies sequencing platform was utilized to generate the genomic data, deploying ARTIC Network-based amplicon sequencing.
ANNOUNCEMENT
A novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (family Coronaviridae, genus Betacoronavirus) variant, known as the Omicron variant (B.1.1.529), was initially reported to the World Health Organization (WHO) on 24 November 2021 (1). Now this variant of concern (VOC) includes more than 100 sublineages (2). Omicron BA.2 sublineage BA.2.75 was first identified in India, and findings showed that BA.2.75 replicates more efficiently in the lungs than does BA.2 or BA.5 (3).
As part of a nationwide coronavirus disease 2019 (COVID-19) surveillance program (Institute of Epidemiology, Disease Control, and Research [IEDCR] protocol IEDCR/IRB/2020/11), nasopharyngeal swab specimens were obtained from routine diagnostic samples from patients across Bangladesh. Reverse transcription (Real-time)-PCR was performed using a commercially available novel coronavirus (2019-nCoV) nucleic acid diagnostic kit (Sansure Biotech, China). A total of 48 SARS-CoV-2 RT-PCR-positive samples were subjected to sequencing. Viral RNA was extracted from nasopharyngeal swab samples using the QIAamp viral RNA minikit (Qiagen). ARTIC v3 primer-based multiplex PCR amplicons were generated and used as the sequencing libraries (4, 5). Libraries were barcoded using the Oxford Nanopore Technologies native barcoding system (EXP-NBD104 and EXP-NBD114), pooled, and sequenced with a FLO-MIN106D flow cell (R9.4.1) for 6 h. Raw reads were base called and demultiplexed with MinKNOW v21.02.1. Processed reads were assembled with the ARTIC guppyplex code script with Medaka v1.4, using the ARTIC EPI2ME v3.3.0 SARS-CoV-2 pipeline (FastQC plus ARTIC plus NextClade) (https://artic.network/ncov-2019/ncov2019-bioinformatics-sop.html). To summarize, 3,723,478 reads were generated (range, 95,728 to 645,221 reads per sample; average length, 503 bp; read depth, 1,200× to 4,000×). A nearly complete genome was obtained for each sample, and the genomic information is provided in Table 1. SARS-CoV-2 lineages were assigned according to the proposed nomenclature of pangolin lineage assignment software v2.0.7 (https://github.com/cov-lineages/pangolin), followed by visual inspection using CLC Genomics Workbench v21.0 (Qiagen). In comparison with the reference genome (Wuhan Hu-1 [GenBank accession number NC_045512.2]), the spike protein-based signature amino acid variations assigned 22 of the sequences as sublineage BA.5 and 1 as BA.2.75. Genome sequencing has been playing a critical role in COVID-19 responses, because new variants are constantly evolving. Therefore, rapid sequencing and data sharing can contribute to the implementation of quick and informed public health decisions to mitigate COVID-19 consequences.
TABLE 1.
Data for Bangladesh SARS-CoV-2 Omicron strains
| Sample | Date of sample collection (day/mo/yr) | Patient age (yr) | Sexa | Symptomsb | Vaccination type | Booster dose completed | Pangolin lineage | GC content (%) | SRA accession no. | GenBank accession no. |
|---|---|---|---|---|---|---|---|---|---|---|
| TND-04-1538 | 29/5/2022 | 53 | F | + | Oxford/AstraZeneca | No | BA.5.1 | 40.03 | SRR20936503 | OP164783 |
| TND-04-1566 | 4/6/2022 | 26 | M | + | Moderna | No | BA.5.1 | 40.36 | SRR20936502 | OP164784 |
| TND-01-0668 | 8/6/2022 | 44 | F | + | Oxford/AstraZeneca | Yes (Pfizer-BioNTech) | BA.5.3.1 | 39.77 | SRR20936520 | OP164786 |
| IR-2986 | 13/6/2022 | 39 | M | − | Oxford/AstraZeneca | No | BA.5.3.1 | 40.19 | SRR20936521 | OP164777 |
| IR-2989 | 13/6/2022 | 77 | M | + | Oxford/AstraZeneca | Yes (Moderna) | BA.5.3.1 | 41.02 | SRR20936510 | OP164778 |
| TND-04-1606 | 13/6/2022 | 33 | F | + | Not vaccinated | No | BA.5.2 | 39.95 | SRR20936501 | OP164785 |
| IR-2991 | 14/6/2022 | 35 | M | + | Oxford/AstraZeneca | Yes (Moderna) | BA.5.3.1 | 39.79 | SRR20936507 | OP164779 |
| TND-07-1525 | 14/6/2022 | 55 | M | + | Oxford/AstraZeneca | Yes (Moderna) | BA.5.3.1 | 39.59 | SRR20936522 | OP164776 |
| TND-06-0758 | 14/6/2022 | 25 | M | + | Pfizer-BioNTech | Yes (Moderna) | BA.5.3.1 | 40 | SRR20936519 | OP164787 |
| TND-04-1610 | 14/6/2022 | 27 | F | + | Oxford/AstraZeneca | No | BA.5.3.1 | 40.37 | SRR20936518 | OP164792 |
| TND-04-1611 | 14/6/2022 | 69 | M | + | Oxford/AstraZeneca | No | BA.5.3.1 | 40.56 | SRR20936517 | OP164793 |
| TND-04-1612 | 14/6/2022 | 42 | M | + | Sinopharm | No | BA.5.3.1 | 40.95 | SRR20936516 | OP164794 |
| IR-2993 | 15/6/2022 | 35 | F | + | Oxford/AstraZeneca | No | BA.5.3.1 | 40.17 | SRR20936506 | OP164780 |
| TND-05-0773 | 15/6/2022 | 19 | M | + | Pfizer-BioNTech | No | BA.5.2 | 40.89 | SRR20936515 | OP164795 |
| TND-04-1623 | 16/6/2022 | 22 | M | + | Sinopharm | No | BA.5 | 40.15 | SRR20936514 | OP164788 |
| TND-04-1625 | 16/6/2022 | 37 | M | + | Oxford/AstraZeneca | No | BA.5.3.1 | 40.92 | SRR20936513 | OP164796 |
| TND-04-1628 | 16/6/2022 | 26 | M | + | Sinopharm | No | BA.5.3.1 | 40.83 | SRR20936512 | OP164797 |
| IR-2995 | 17/6/2022 | 29 | F | + | Oxford/AstraZeneca | Yes (Moderna) | BA.5.2 | 39.95 | SRR20936505 | OP164781 |
| IR-2998 | 18/6/2022 | 73 | M | + | Oxford/AstraZeneca | Yes (Pfizer-BioNTech) | BA.5.3.1 | 40.04 | SRR20936504 | OP164782 |
| TND-06-0768 | 18/6/2022 | 60 | F | + | Sinopharm | No | BA.5.3.1 | 40.03 | SRR20936511 | OP164789 |
| TND-06-0770 | 18/6/2022 | 66 | F | + | Sinopharm | No | BA.5 | 40.76 | SRR20936509 | OP164790 |
| TND-09-0721 | 18/6/2022 | 36 | M | + | Not vaccinated | No | BA.5.3.1 | 39.87 | SRR20936508 | OP164791 |
| TND-04-2046 | 8/7/2022 | 41 | M | + | Sinopharm | No | BA.2.75 | 40.38 | SRR21484218 | OP390081 |
F, female; M, male.
+, present (fever, cough, and/or mild weakness); −, absent.
Data availability.
The data from this study can be found under GISAID accession numbers EPI_ISL_13439470, EPI_ISL_13439471, EPI_ISL_13439472, EPI_ISL_13439473, EPI_ISL_13439474, EPI_ISL_13439475, EPI_ISL_13439476, EPI_ISL_13439477, EPI_ISL_13439478, EPI_ISL_13439479, EPI_ISL_13439480, EPI_ISL_13439481, EPI_ISL_13574266, EPI_ISL_13574267, EPI_ISL_13574268, EPI_ISL_13574269, EPI_ISL_13439482, EPI_ISL_13574270, EPI_ISL_13574271, EPI_ISL_13439484, EPI_ISL_13439485, EPI_ISL_13439486, and EPI_ISL_14859273. The GenBank accession numbers are listed in Table 1.
ACKNOWLEDGMENTS
This work was supported by the Wellcome Trust (grant UNS124908). We would also like to acknowledge the Fogarty International Center and NIAID Training Grant (D43 TW005572). The International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) is grateful to the governments of Bangladesh, Canada, Sweden, and the United Kingdom for providing core/unrestricted support.
We acknowledge physicians and diagnostic testing staff members at the IEDCR and the Institute for Developing Science and Health Initiatives (ideSHi) who provided initial diagnostic testing of the SARS-CoV-2 samples.
Contributor Information
Firdausi Qadri, Email: fqadri@icddrb.org.
Simon Roux, DOE Joint Genome Institute.
REFERENCES
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data from this study can be found under GISAID accession numbers EPI_ISL_13439470, EPI_ISL_13439471, EPI_ISL_13439472, EPI_ISL_13439473, EPI_ISL_13439474, EPI_ISL_13439475, EPI_ISL_13439476, EPI_ISL_13439477, EPI_ISL_13439478, EPI_ISL_13439479, EPI_ISL_13439480, EPI_ISL_13439481, EPI_ISL_13574266, EPI_ISL_13574267, EPI_ISL_13574268, EPI_ISL_13574269, EPI_ISL_13439482, EPI_ISL_13574270, EPI_ISL_13574271, EPI_ISL_13439484, EPI_ISL_13439485, EPI_ISL_13439486, and EPI_ISL_14859273. The GenBank accession numbers are listed in Table 1.