Population Bottlenecks and Intra-host Evolution during Human-to-Human Transmission of SARS-CoV-2

Abstract The emergence of the novel human coronavirus, SARS-CoV-2, causes a global COVID-19 (coronavirus disease 2019) pandemic. Here, we have characterized and compared viral populations of SARS-CoV-2 among COVID-19 patients within and across households. Our work showed an active viral replication activity in the human respiratory tract and the co-existence of genetically distinct viruses within the same host. The inter-host comparison among viral populations further revealed a narrow transmission bottleneck between patients from the same households, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions.Author summary In this study, we compared SARS-CoV-2 populations of 13 Chinese COVID-19 patients. Those viral populations contained a considerable proportion of viral sub-genomic messenger RNAs (sgmRNA), reflecting an active viral replication activity in the respiratory tract tissues. The comparison of 66 identified intra-host variants further showed a low viral genetic distance between intra-household patients and a narrow transmission bottleneck size. Despite the co-existence of genetically distinct viruses within the same host, most intra-host minor variants were not shared between transmission pairs, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions. Furthermore, the narrow bottleneck and active viral activity in the respiratory tract show that the passage of a small number of virions can cause infection. Our data have therefore delivered a key genomic resource for the SARS-CoV-2 transmission research and enhanced our understanding of the evolutionary dynamics of SARS-CoV-2..

Medienart:

Preprint

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

bioRxiv.org - (2021) vom: 15. Dez. Zur Gesamtaufnahme - year:2021

Sprache:

Englisch

Beteiligte Personen:

Wang, Daxi [VerfasserIn]
Wang, Yanqun [VerfasserIn]
Sun, Wanying [VerfasserIn]
Zhang, Lu [VerfasserIn]
Ji, Jingkai [VerfasserIn]
Zhang, Zhaoyong [VerfasserIn]
Cheng, Xinyi [VerfasserIn]
Li, Yimin [VerfasserIn]
Xiao, Fei [VerfasserIn]
Zhu, Airu [VerfasserIn]
Zhong, Bei [VerfasserIn]
Ruan, Shicong [VerfasserIn]
Li, Jiandong [VerfasserIn]
Ren, Peidi [VerfasserIn]
Ou, Zhihua [VerfasserIn]
Xiao, Minfeng [VerfasserIn]
Li, Min [VerfasserIn]
Deng, Ziqing [VerfasserIn]
Zhong, Huanzi [VerfasserIn]
Li, Fuqiang [VerfasserIn]
Wang, Wen-jing [VerfasserIn]
Zhang, Yongwei [VerfasserIn]
Chen, Weijun [VerfasserIn]
Zhu, Shida [VerfasserIn]
Xu, Xun [VerfasserIn]
Jin, Xin [VerfasserIn]
Zhao, Jingxian [VerfasserIn]
Zhong, Nanshan [VerfasserIn]
Zhang, Wenwei [VerfasserIn]
Zhao, Jincun [VerfasserIn]
Li, Junhua [VerfasserIn]
Xu, Yonghao [VerfasserIn]

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doi:

10.1101/2020.06.26.173203

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI018233910