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通过监测和基于探针捕获的下一代测序发现蝙蝠冠状病毒。

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

机构信息

CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China.

University of Chinese Academy of Sciences, Beijing, China.

出版信息

mSphere. 2020 Jan 29;5(1):e00807-19. doi: 10.1128/mSphere.00807-19.

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. 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.

摘要

蝙蝠源性冠状病毒在本世纪引发了两次大流行。严重急性呼吸综合征(SARS)-CoV 和中东呼吸综合征(MERS)-CoV 均源自蝙蝠,而且极有可能蝙蝠冠状病毒将导致未来的爆发。主动监测对于预测和减轻这些病毒在人类中的出现是紧急且必要的。下一代测序(NGS)目前是病毒发现的首选方法,以确保对蝙蝠 CoV 进行无偏测序,考虑到它们的高度遗传多样性。然而,无偏 NGS 是一种昂贵的方法,由于监测野外样本中存在大量非病毒序列,因此容易错过低丰度 CoV 序列。在这里,我们采用基于捕获的 NGS 方法,使用针对大多数 CoV 物种的探针。使用这项技术,我们通过提高检测灵敏度有效地降低了测序成本。在本研究中,我们发现了九种蝙蝠 CoV 的完整基因组,并揭示了其中八种的巨大遗传多样性。主动监测对于预测和减轻人类和家畜中蝙蝠源性 CoV 的出现是紧急且必要的。然而,巨大的遗传多样性增加了 CoV 之间同源重组的机会。进行针对许多监测研究的常见实践的靶向 PCR 不会反映这种多样性。另一方面,NGS 是一种昂贵的方法,并且容易错过低丰度 CoV 序列。在这里,我们采用基于捕获的 NGS 方法,使用针对所有 CoV 的探针。我们的工作表明,现在可以高度可行地针对蝙蝠 CoV 进行靶向、经济高效、大规模、基因组水平的监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f7e/6992374/0db0ee311314/mSphere.00807-19-f0001.jpg

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