Genomic characterization of the dominating Beta, V2 variant carrying vaccinated (Oxford−AstraZeneca) and nonvaccinated COVID‐19 patient samples in Bangladesh: A metagenomics and whole‐genome approach

Abstract

Bangladesh is experiencing a second wave of COVID-19 since March 2021, despite the nationwide vaccination drive with ChAdOx1 (Oxford−AstraZeneca) vaccine from early February 2021. Here, we characterized 19 nasopharyngeal swab (NPS) samples from COVID-19 suspect patients using genomic and metagenomic approaches. Screening for SARS-CoV-2 by reverse transcriptase polymerase chain reaction and metagenomic sequencing revealed 17 samples of COVID-19 positive (vaccinated = 10, nonvaccinated = 7) and 2 samples of COVID-19 negative. We did not find any significant correlation between associated factors including vaccination status, age or sex of the patients, diversity or abundance of the coinfected organisms/pathogens, and the abundance of SARS-CoV-2. Though the first wave of the pandemic was dominated by clade 20B, Beta, V2 (South African variant) dominated the second wave (January 2021 to May 2021), while the third wave (May 2021 to September 2021) was responsible for Delta variants of the epidemic in Bangladesh including both vaccinated and unvaccinated infections. Noteworthily, the receptor binding domain (RBD) region of S protein of all the isolates harbored similar substitutions including K417N, E484K, and N501Y that signify the Beta, while D614G, D215G, D80A, A67V, L18F, and A701V substitutions were commonly found in the non-RBD region of Spike proteins. ORF7b and ORF3a genes underwent a positive selection (dN/dS ratio 1.77 and 1.24, respectively), while the overall S protein of the Bangladeshi SARS-CoV-2 isolates underwent negative selection pressure (dN/dS = 0.621). Furthermore, we found different bacterial coinfections like Streptococcus agalactiae, Neisseria meningitidis, Elizabethkingia anophelis, Stenotrophomonas maltophilia, Klebsiella pneumoniae, and Pseudomonas plecoglossicida, expressing a number of antibiotic resistance genes such as tetA and tetM. Overall, this approach provides

Dispersal patterns and influence of air travel during the global expansion of SARS-CoV-2 variants of concern

“…We infer that Asia was a net source of Beta along with Africa, with exports peaking after April 2021 for Asia ( Figure S1 B), which is plausible given sizable Beta waves in some countries in Asia during that time (e.g., Bangladesh and Cambodia). 19 We again observe a multi-stage process of Beta spread: during the earliest stages between late 2020 and early 2021, Beta was primarily exported from southern Africa into North America, Europe, and Asia. Later, dispersal from Asia occurred mostly to Europe and North America, with minimal introductions to South America ( Figure 1 ).…”

Global Expansion of SARS-CoV-2 Variants of Concern: Dispersal Patterns and Influence of Air Travel

“…We infer that Asia was a net source of Beta along with Africa, with exports peaking after April 2021 (Figure S2), which is plausible given sizable Beta waves in some countries in Asia during that time (e.g. Bangladesh and Cambodia) 19 . We again observe a multi-stage process of Beta spread: during the earliest stages between late 2020 and early 2021, Beta was primarily exported from southern Africa into North America, Europe and Asia.…”

Metabuli: sensitive and specific metagenomic classification via joint analysis of amino-acid and DNA

“…Two sets of RNA sequencing data from COVID-19 patients were used as query reads. One set was prepared from three patients infected by the beta variant (25), and the other from three patients infected by the omicron variant (26).…”