Predicting mammalian hosts in which novel coronaviruses can be generated

Predicting mammalian hosts in which novel coronaviruses can be generated
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预测可产生新型冠状病毒的哺乳动物宿主

DOI:
10.1101/2020.06.15.151845
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发表时间:
2020
期刊:
--
影响因子:
--
通讯作者:
Wardeh M
Wardeh M
中科院分区:
--
文献类型:
--
作者:
Wardeh M

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新型致病性冠状病毒,如SARS-CoV,可能还有SARS-CoV-2,是由在单个细胞中共同感染的病毒之间的同源重组产生的。因此,确定新型冠状病毒的可能来源需要确定多种冠状病毒的宿主;然而,大多数冠状病毒与宿主的相互作用仍然未知。在这里,通过从三个互补的角度(病毒、哺乳动物和网络)部署相似性学习器的元集合,我们预测哪些哺乳动物是多种冠状病毒的宿主。我们预测,在平均概率截止点(>0.9821)下,与迄今为止观察到的结果相比,冠状病毒与宿主的关联增加了11.5倍,潜在的SARS-CoV-2重组宿主增加了30倍以上,具有四种或更多不同冠状病毒亚属的宿主物种增加了40倍以上。我们的研究结果表明,人们对野生和家养动物中新型冠状病毒的潜在繁殖规模存在严重低估。我们确定高危物种进行冠状病毒监测。
Novel pathogenic coronaviruses – such as SARS-CoV and probably SARS-CoV-2 – arise by homologous recombination between co-infecting viruses in a single cell. Identifying possible sources of novel coronaviruses therefore requires identifying hosts of multiple coronaviruses; however, most coronavirus-host interactions remain unknown. Here, by deploying a meta-ensemble of similarity learners from three complementary perspectives (viral, mammalian and network), we predict which mammals are hosts of multiple coronaviruses. We predict that there are 11.5-fold more coronavirus-host associations, over 30-fold more potential SARS-CoV-2 recombination hosts, and over 40-fold more host species with four or more different subgenera of coronaviruses than have been observed to date at >0.5 mean probability cut-off (2.4-, 4.25- and 9-fold, respectively, at >0.9821). Our results demonstrate the large underappreciation of the potential scale of novel coronavirus generation in wild and domesticated animals. We identify high-risk species for coronavirus surveillance.
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