The Mutant Mouse Resource and Research Center at The Jackson Laboratory

摘要 到目前为止，使用新冠肺炎小鼠模型进行的大多数研究都是使用转基因的 角蛋白-18(K18)启动子驱动高水平表达人ACE2基因的小鼠模型。 虽然这个模型非常有用，但它也有一些显著的局限性：疾病的进展 在一周内迅速死亡，脑部感染率异常高。 这些特征限制了它在研究与感染急性期相关的生物学方面的使用，留下了一个 更准确地反映ACE2受体表达模式和水平的模型中的差距，以及 这使疾病的病程超出了感染的急性期。 我们将采用一种改进的遗传策略，利用最近发表的人类基因敲入模型 将ACE2基因插入小鼠ACE2基因座。通过将这些hACE2基因敲入的小鼠与近亲交配 协作交叉(CC)创始人菌株，并通过表征结果人性化的反应 F1后代通过与研究人员建立合作伙伴关系存活SARS-CoV-2感染 特鲁多研究所，我们将检验这一假设，即新冠肺炎患者反应的临床变异可以 在具有自然调节的血管紧张素转换酶2的小鼠中更准确地建模和表型特征 在不同的遗传背景下表达。 与MMRRC家长基金的目标一致，即识别和分发鼠标模型给 生物医学界，这项提议旨在迅速为研究界提供一个紧迫的 将新冠肺炎疾病预后的变异性与潜在宿主基因联系起来所需的资源 用于开发感染后后遗症的精确模型。

Abstract To date, most of the research using mouse models for COVID-19 has been done using a transgenic mouse model expressing high levels of the human ACE2gene driven by the Keratin-18(K18) promoter. While this model has been extremely useful, it has some notable limitations: disease progression is rapid and invariably fatal within one week, with an uncharacteristically high infection rate in the brain. These features restrict its use to study the biology related to the acute phase of the infection, leaving a gap in models that more accurately reflect the expression patterns and levels of the ACE2 receptor, and that extend the disease course beyond the acute phase of infection. We will employ a refined genetic strategy utilizing a recently published knock-in model of the human ACE2 cDNA into the mouse Ace2 locus. By crossing these hACE2 knock-in mice with inbred Collaborative Cross (CC) founder strains, and by characterizing the response of resulting humanized F1 progeny to live SARS-CoV-2 infection through an established partnership with researchers at the Trudeau Institute, we will test the hypothesis that clinical variation in COVID-19 patient response can be more accurately modelled and phenotypically characterized in mice with naturally regulated ACE2 expression on variable genetic backgrounds. Consistent with the aims of MMRRC parent grant to identify and distribute mouse models to the biomedical community, this proposal aims to rapidly provide the research community with an urgently needed resource for linking the variability in COVID-19 disease outcome with underlying host genetic features, and for developing precision models for post infection sequelae.