Influenza host specific glycan motif identification through systems biology

项目摘要 甲型流感病毒(IAV)在世界范围内造成了巨大的生命损失，并继续呈现出巨大的 公共卫生挑战。IAV可引起鸟类、海洋哺乳动物、低等哺乳动物(如猪、狗、 和马)，以及人类。以前的研究已经证明，碳水化合物的结构 受体决定流感宿主和组织的趋向性。因此，有必要了解受体- IAV的结合属性并监测它们的变化，特别是动物-人界面的IAV。 然而，由于我们缺乏对IAV多糖亚结构的详细了解，这一理解受到了阻碍；大多数 我们的知识仅限于类SA2，3Gal和类SA2，6Gal结构。该项目的目标是 开发和验证一种机器学习方法，通过以下方法识别IAV的宿主特异性糖链亚结构 使用多聚糖阵列数据并鉴定和验证与IAV的寄主取向相关的多聚糖基序， 包括针对人畜共患IAV的疫苗。这项研究将集中在IAV的自然宿主上：人、猪、狗、 马类和各种禽类，包括常见的家禽和野生鸟类。我们 期望确定受体与人、猪、犬和禽源结合的结构决定因素 IAV。这些知识将有助于我们了解导致流感感染的因素和 传播，从而促进开发有效的流感疫苗，以防止病毒感染和 阻止病毒传播。这一知识还将帮助我们开发快速分析方法，以监测新兴的 动物-人类界面的流感威胁。我们还希望开发一种计算方法来计算 识别与流感宿主嗜性相关的糖链基序；这种方法将能够适应 确定其他蛋白质、凝集素、抗体、抗血清和微生物的功能糖链基序， 包括其他传染性病原体的那些，通过使用多聚糖阵列。

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.