Both simulation and sequencing data reveal coinfections with multiple SARS-CoV-2 variants in the COVID-19 pandemic

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Zhengtu Li
  • Yonghan Yu
  • Yen Kaow Ng
  • Feng Ye
  • Bairong Shen

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)1389-1401
Journal / PublicationComputational and Structural Biotechnology Journal
Volume20
Online published18 Mar 2022
Publication statusPublished - 2022

Link(s)

Abstract

SARS-CoV-2 is a single-stranded RNA betacoronavirus with a high mutation rate. The rapidly emerging SARS-CoV-2 variants could increase transmissibility and diminish vaccine protection. However, whether coinfection with multiple SARS-CoV-2 variants exists remains controversial. This study collected 12,986 and 4,113 SARS-CoV-2 genomes from the GISAID database on May 11, 2020 (GISAID20May11), and Apr 1, 2021 (GISAID21Apr1), respectively. With single-nucleotide variant (SNV) and network clique analyses, we constructed single-nucleotide polymorphism (SNP) coexistence networks and discovered maximal SNP cliques of sizes 16 and 34 in the GISAID20May11 and GISAID21Apr1 datasets, respectively. Simulating the transmission routes and SNV accumulations, we discovered a linear relationship between the size of the maximal clique and the number of coinfected variants. We deduced that the COVID-19 cases in GISAID20May11 and GISAID21Apr1 were coinfections with 3.20 and 3.42 variants on average, respectively. Additionally, we performed Nanopore sequencing on 42 COVID-19 patients and discovered recurrent heterozygous SNPs in twenty of the patients, including loci 8,782 and 28,144, which were crucial for SARS-CoV-2 lineage divergence. In conclusion, our findings reported SARS-CoV-2 variants coinfection in COVID-19 patients and demonstrated the increasing number of coinfected variants.

Research Area(s)

  • Coinfection index, Heterozygous single-nucleotide polymorphisms, SARS-CoV-2 variant coinfection, Viral transmission simulation

Citation Format(s)

Both simulation and sequencing data reveal coinfections with multiple SARS-CoV-2 variants in the COVID-19 pandemic. / Li, Yinhu; Jiang, Yiqi; Li, Zhengtu; Yu, Yonghan; Chen, Jiaxing; Jia, Wenlong; Kaow Ng, Yen; Ye, Feng; Cheng Li, Shuai; Shen, Bairong.

In: Computational and Structural Biotechnology Journal, Vol. 20, 2022, p. 1389-1401.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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