Influenza host specific glycan motif identification through systems biology

项目摘要 甲型流感病毒（IAV）已在世界各地造成大量生命损失，并继续呈现巨大的流行趋势。 公共卫生挑战。IAV可引起鸟类、海洋哺乳动物、低等哺乳动物（例如，猪，狗， 马和人类。以前的研究表明，碳水化合物的结构 受体决定流感宿主和组织的向性。因此，有必要了解受体- IAV的结合特性，并监测它们的变化，特别是在动物-人界面上的IAV。 然而，这种理解受到我们缺乏详细的知识IAV聚糖亚结构的阻碍; 我们的知识仅限于SA 2，3Gal样和SA 2，6 Gal样结构。该项目的目标是 开发并验证机器学习方法，以通过以下方式识别IAV的宿主特异性聚糖亚结构： 使用聚糖阵列数据并鉴定和验证与IAV的宿主向性相关的聚糖基序， 包括人畜共患病IAV的疫苗。这项研究将集中在IAV的自然宿主：人类、猪、犬， 马和各种鸟类物种，包括常见的家禽物种和野生鸟类物种。我们 期望鉴定与人源、猪源、犬源和禽类源受体结合的结构决定簇 IAV这些知识将帮助我们了解导致流感感染的因素， 传播，从而促进开发有效的流感疫苗以预防病毒感染， 阻止病毒传播。这些知识也将帮助我们开发快速检测方法， 流感对动物和人类的威胁。我们还希望开发一种计算方法， 鉴定与流感宿主向性相关的聚糖基序;该方法将能够适用于 确定其他蛋白质、凝集素、抗体、抗血清和微生物的功能性聚糖基序， 包括其它传染性病原体的那些。

Project Summary Influenza A viruses (IAVs) have caused large losses of life around the world and continue to present a great public health challenge. IAVs can cause infections in birds, sea mammals, lower mammals (e.g., pigs, dogs, and horses), and humans. Previous studies have demonstrated that the structures of the carbohydrate receptors determine influenza host and tissue tropisms. Thus, it is necessary to understand the receptor- binding properties for IAVs and monitor changes to them, especially for IAVs at the animal–human interface. However, this understanding is hampered by our lack of detailed knowledge of IAV glycan substructures; most of our knowledge is limited to SA2,3Gal-like and SA2,6Gal-like structures. The goals of this project are to develop and validate a machine learning method to identify host-specific glycan substructures for IAVs by using glycan array data and to identify and validate the glycan motifs associated with the host tropisms of IAVs, including those for zoonotic IAVs. The study will focus on natural hosts of IAVs: humans, swine, canines, equines, and various avian species, including common domestic poultry species and wild bird species. We expect to identify structural determinants for receptor binding with human-, swine-, canine-, and avian-origin IAVs. Such knowledge will help us understand the factors that contribute to influenza infection and transmission and thereby facilitate development of an effective influenza vaccine to prevent virus infection and block virus transmission. This knowledge will also help us develop rapid assays for monitoring emerging influenza threats at the animal–human interface. We also expect to develop a computational method for identifying glycan motifs associated with influenza host tropisms; this method will be able to be adapted to determine functional glycan motifs for other proteins, lectins, antibodies, antisera, and microorganisms, including those of other infectious pathogens, by using glycan arrays.