Unbiased forward genetics and systems biology approaches to understanding how gene-environment interactions work to predict susceptibility and outcomes of infections.

M. Kotb, Nourtan Fathey, R. Aziz, Sarah Rowe, Robert W. Williams, Lu Lu
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引用次数: 4

Abstract

Like most human diseases, infectious diseases are effected by complex genetic traits and multiple, interactive environmental and inherent host factors. By linking specific genotypes to disease susceptibility phenotypes we can identify the genetic basis for inter-individual differences in disease susceptibility as well as gain insight into how gene-environment interactions influence infection outcomes. Our research has focused on delineating interactive pathways and molecular events modulating host resistance or susceptibility to specific pathogens. Our model system has been that of Group A Streptococcus infections that can manifest in starkly different ways and cause distinct diseases in genetically distinct individuals. We have extended our work to other pathogens, including those with a potential of causing major, global biological threats. In as much as it is quite difficult to conduct certain infectious disease studies in humans, there has been a critical need for small animal models for infectious diseases. Appreciating the limitations of existing models, we developed several novel and complementary mouse models that are ideal for use in systems genetics studies of complex diseases. These models not only allow biological validation of known genetic associations, but importantly they afford an unbiased tool for discovering novel genes and pathways contributing to disease outcomes, under different environments.
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无偏见的正向遗传学和系统生物学方法,了解基因-环境相互作用如何预测易感性和感染的结果。
像大多数人类疾病一样,传染病受到复杂的遗传特征和多种相互作用的环境和固有宿主因素的影响。通过将特定基因型与疾病易感性表型联系起来,我们可以确定疾病易感性个体间差异的遗传基础,并深入了解基因-环境相互作用如何影响感染结果。我们的研究主要集中在描述相互作用的途径和分子事件调节宿主对特定病原体的抗性或易感性。我们的模型系统是A群链球菌感染,它可以以截然不同的方式表现出来,并在基因不同的个体中引起不同的疾病。我们已将工作扩展到其他病原体,包括那些可能造成重大全球生物威胁的病原体。由于在人类身上进行某些传染病研究相当困难,因此迫切需要传染病的小动物模型。考虑到现有模型的局限性,我们开发了几种新的和互补的小鼠模型,这些模型非常适合用于复杂疾病的系统遗传学研究。这些模型不仅允许对已知的遗传关联进行生物学验证,而且重要的是,它们为发现在不同环境下导致疾病结果的新基因和途径提供了公正的工具。
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