Discovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing

ABSTRACT Coronaviruses (CoVs) of bat origin have caused two pandemics in this century. Severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV both originated from bats, and it is highly likely that bat coronaviruses will cause future outbreaks. Active surveillan...

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Autores principales: Bei Li, Hao-Rui Si, Yan Zhu, Xing-Lou Yang, Danielle E. Anderson, Zheng-Li Shi, Lin-Fa Wang, Peng Zhou
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Publicado: American Society for Microbiology 2020
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spelling oai:doaj.org-article:14bff36f21f44e15b7332378423353f42021-11-15T15:27:52ZDiscovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing10.1128/mSphere.00807-192379-5042https://doaj.org/article/14bff36f21f44e15b7332378423353f42020-02-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSphere.00807-19https://doaj.org/toc/2379-5042ABSTRACT Coronaviruses (CoVs) of bat origin have caused two pandemics in this century. Severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV both originated from bats, and it is highly likely that bat coronaviruses will cause future outbreaks. Active surveillance is both urgent and essential to predict and mitigate the emergence of these viruses in humans. Next-generation sequencing (NGS) is currently the preferred methodology for virus discovery to ensure unbiased sequencing of bat CoVs, considering their high genetic diversity. However, unbiased NGS is an expensive methodology and is prone to missing low-abundance CoV sequences due to the high background level of nonviral sequences present in surveillance field samples. Here, we employ a capture-based NGS approach using baits targeting most of the CoV species. Using this technology, we effectively reduced sequencing costs by increasing the sensitivity of detection. We discovered nine full genomes of bat CoVs in this study and revealed great genetic diversity for eight of them. IMPORTANCE Active surveillance is both urgent and essential to predict and mitigate the emergence of bat-origin CoV in humans and livestock. However, great genetic diversity increases the chance of homologous recombination among CoVs. Performing targeted PCR, a common practice for many surveillance studies, would not reflect this diversity. NGS, on the other hand, is an expensive methodology and is prone to missing low-abundance CoV sequences. Here, we employ a capture-based NGS approach using baits targeting all CoVs. Our work demonstrates that targeted, cost-effective, large-scale, genome-level surveillance of bat CoVs is now highly feasible.Bei LiHao-Rui SiYan ZhuXing-Lou YangDanielle E. AndersonZheng-Li ShiLin-Fa WangPeng ZhouAmerican Society for Microbiologyarticlebatcoronavirusgenomeenrichmentnext-generation sequencingMicrobiologyQR1-502ENmSphere, Vol 5, Iss 1 (2020)
institution DOAJ
collection DOAJ
language EN
topic bat
coronavirus
genome
enrichment
next-generation sequencing
Microbiology
QR1-502
spellingShingle bat
coronavirus
genome
enrichment
next-generation sequencing
Microbiology
QR1-502
Bei Li
Hao-Rui Si
Yan Zhu
Xing-Lou Yang
Danielle E. Anderson
Zheng-Li Shi
Lin-Fa Wang
Peng Zhou
Discovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing
description ABSTRACT Coronaviruses (CoVs) of bat origin have caused two pandemics in this century. Severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV both originated from bats, and it is highly likely that bat coronaviruses will cause future outbreaks. Active surveillance is both urgent and essential to predict and mitigate the emergence of these viruses in humans. Next-generation sequencing (NGS) is currently the preferred methodology for virus discovery to ensure unbiased sequencing of bat CoVs, considering their high genetic diversity. However, unbiased NGS is an expensive methodology and is prone to missing low-abundance CoV sequences due to the high background level of nonviral sequences present in surveillance field samples. Here, we employ a capture-based NGS approach using baits targeting most of the CoV species. Using this technology, we effectively reduced sequencing costs by increasing the sensitivity of detection. We discovered nine full genomes of bat CoVs in this study and revealed great genetic diversity for eight of them. IMPORTANCE Active surveillance is both urgent and essential to predict and mitigate the emergence of bat-origin CoV in humans and livestock. However, great genetic diversity increases the chance of homologous recombination among CoVs. Performing targeted PCR, a common practice for many surveillance studies, would not reflect this diversity. NGS, on the other hand, is an expensive methodology and is prone to missing low-abundance CoV sequences. Here, we employ a capture-based NGS approach using baits targeting all CoVs. Our work demonstrates that targeted, cost-effective, large-scale, genome-level surveillance of bat CoVs is now highly feasible.
format article
author Bei Li
Hao-Rui Si
Yan Zhu
Xing-Lou Yang
Danielle E. Anderson
Zheng-Li Shi
Lin-Fa Wang
Peng Zhou
author_facet Bei Li
Hao-Rui Si
Yan Zhu
Xing-Lou Yang
Danielle E. Anderson
Zheng-Li Shi
Lin-Fa Wang
Peng Zhou
author_sort Bei Li
title Discovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing
title_short Discovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing
title_full Discovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing
title_fullStr Discovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing
title_full_unstemmed Discovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing
title_sort discovery of bat coronaviruses through surveillance and probe capture-based next-generation sequencing
publisher American Society for Microbiology
publishDate 2020
url https://doaj.org/article/14bff36f21f44e15b7332378423353f4
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