Eng Christine L P, Tong Joo Chuan, Tan Tin Wee
Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Institute of High Performance Computing, Singapore, Singapore.
PLoS One. 2016 Feb 25;11(2):e0150173. doi: 10.1371/journal.pone.0150173. eCollection 2016.
Zoonotic influenza A viruses constantly pose a health threat to humans as novel strains occasionally emerge from the avian population to cause human infections. Many past epidemic as well as pandemic strains have originated from avian species. While most viruses are restricted to their primary hosts, zoonotic strains can sometimes arise from mutations or reassortment, leading them to acquire the capability to escape host species barrier and successfully infect a new host. Phylogenetic analyses and genetic markers are useful in tracing the origins of zoonotic infections, but there are still no effective means to identify high risk strains prior to an outbreak. Here we show that distinct host tropism protein signatures can be used to identify possible zoonotic strains in avian species which have the potential to cause human infections. We have discovered that influenza A viruses can now be classified into avian, human, or zoonotic strains based on their host tropism protein signatures. Analysis of all influenza A viruses with complete proteome using the host tropism prediction system, based on machine learning classifications of avian and human viral proteins has uncovered distinct signatures of zoonotic strains as mosaics of avian and human viral proteins. This is in contrast with typical avian or human strains where they show mostly avian or human viral proteins in their signatures respectively. Moreover, we have found that zoonotic strains from the same influenza outbreaks carry similar host tropism protein signatures characteristic of a common ancestry. Our results demonstrate that the distinct host tropism protein signature in zoonotic strains may prove useful in influenza surveillance to rapidly identify potential high risk strains circulating in avian species, which may grant us the foresight in anticipating an impending influenza outbreak.
人畜共患甲型流感病毒不断对人类健康构成威胁,因为偶尔会从禽类群体中出现新的毒株,导致人类感染。许多过去的流行毒株以及大流行毒株都源自禽类。虽然大多数病毒局限于其主要宿主,但人畜共患毒株有时会因突变或重配而产生,使其获得突破宿主物种屏障并成功感染新宿主的能力。系统发育分析和遗传标记有助于追踪人畜共患感染的起源,但在疫情爆发前仍没有有效的方法来识别高风险毒株。在此,我们表明,独特的宿主嗜性蛋白特征可用于识别禽类中可能导致人类感染的人畜共患毒株。我们发现,现在可以根据甲型流感病毒的宿主嗜性蛋白特征将其分为禽类、人类或人畜共患毒株。使用基于禽类和人类病毒蛋白机器学习分类的宿主嗜性预测系统,对所有具有完整蛋白质组的甲型流感病毒进行分析,发现人畜共患毒株具有独特的特征,即禽类和人类病毒蛋白的嵌合体。这与典型的禽类或人类毒株形成对比,后者的特征分别主要显示禽类或人类病毒蛋白。此外,我们发现,来自同一流感疫情的人畜共患毒株具有相似的宿主嗜性蛋白特征,这是共同祖先的特征。我们的结果表明,人畜共患毒株中独特的宿主嗜性蛋白特征可能有助于流感监测,以快速识别禽类中传播的潜在高风险毒株,这可能使我们有先见之明,预测即将到来的流感疫情。