Proteomic overlap and infectious disease

蛋白质组重叠和传染病

• 批准号: 37207-2010
• 负责人: Kusalik, Anthony
• 金额: $ 1.68万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=521460
• 关键词: Proteomic; overlap; infectious; disease

Our work is in the area of immuno-informatics: the combination of computer science and immunology. A proteome is the entire set of proteins produced by an organism or cell. Proteomic overlap is the degree to which the proteome of one organism is duplicated in the proteome of another organism. A fundamental principle in mammalian immunity is the distinction between "self" and "non-self" proteins. The immune system must be able to recognize non-self proteins, so that it can mount a defence against a foreign pathogen, while tolerating the presence of (not reacting to) self proteins. Obviously, the level of proteomic overlap between organisms will affect the balance between self and non-self proteins (in the case of infection) and will have immunological implications. Unfortunately, we do not yet fully understand the mechanisms behind self/non-self determination, and the immunological implications of non-self proteins. We intend to contribute to resolution of some of the open problems in this area by investigating proteomic overlap. Specifically, using bioinformatics tools we aim to address such questions as: how much overlap can be expected at random between two proteomes of specific sizes? What is the biological and immunological significance of portions of the Hepatitis C virus proteome which have atypically high or low overlap with the human proteome? What proteins might account for specific kinds of drug resistance in strains of Neisseria bacteria (e.g. bacteria which cause meningitis and gonorrhea)? Some small protein fragments (peptides) are not found in the proteome of any organism, and some of these can cause enhanced immunological response when added to the proteins of a pathogen. Why? Pursuing the answers to some of these questions requires design and implementation of new bioinformatics tools. The results of our work may lead to better in treatments for disease, and in new, cheaper, and more effective vaccines.

我们的工作是在免疫信息学领域：计算机科学和免疫学的结合。 蛋白质组是由生物体或细胞产生的整套蛋白质。 蛋白质组重叠是一种生物体的蛋白质组在另一种生物体的蛋白质组中复制的程度。 哺乳动物免疫的一个基本原则是区分“自我”和“非自我”蛋白质。 免疫系统必须能够识别非自身蛋白质，这样它才能对外来病原体进行防御，同时容忍自身蛋白质的存在（不对自身蛋白质发生反应）。 显然，生物体之间的蛋白质组重叠水平将影响自身和非自身蛋白质之间的平衡（在感染的情况下），并将具有免疫学意义。 不幸的是，我们还没有完全理解自我/非自我决定背后的机制，以及非自我蛋白质的免疫学意义。 我们打算通过研究蛋白质组重叠来解决这一领域的一些开放性问题。 具体来说，使用生物信息学工具，我们的目标是解决这样的问题：有多少重叠可以预期在两个特定大小的蛋白质组之间的随机？ 丙型肝炎病毒蛋白质组中与人类蛋白质组重叠程度高或低的部分的生物学和免疫学意义是什么？ 哪些蛋白质可能导致奈瑟氏菌菌株（例如导致脑膜炎和淋病的细菌）的特定耐药性？ 一些小的蛋白质片段（肽）在任何生物体的蛋白质组中都没有发现，其中一些在添加到病原体的蛋白质中时可以引起增强的免疫反应。 为什么？为什么？ 寻求这些问题的答案需要设计和实施新的生物信息学工具。 我们的工作成果可能会带来更好的疾病治疗方法，以及更便宜、更有效的新疫苗。