Measuring multiprotein assemblies that drive biological signals

测量驱动生物信号的多蛋白组装体

• 批准号: 8636491
• 负责人: Adam G. Schrum
• 金额: $ 30.9万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8636491
• 关键词: Binding; Biochemical; Biochemical Process; Biocompatible Materials; Bioinformatics; Biological; Biological Assay; Biology; Cells; Chimeric Proteins; Clinical; Co-Immunoprecipitations; Collection; Complex; Data; Data Analyses; Data Set; Disease; Drug Targeting; Flow Cytometry; Generations; Glioblastoma; Health; Homo; Human; Human Engineering; Imagery; Immune; Immunosuppression; In Vitro; Learning; Malignant Neoplasms; Malignant neoplasm of brain; Maps; Measurement; Measures; Methodology; Methods; Microspheres; Mouse Protein; Mus; Pathway interactions; Patients; Physiological; Predictive Value; Proteins; Publishing; Sample Size; Sampling; Signal Transduction; Source; Systems Analysis; T-Lymphocyte; Testing; Therapeutic; Yeasts; base; biosignature; clinical practice; clinically relevant; design; dimer; field study; innovation; interest; meetings; monomer; novel; outcome forecast; protein complex; protein protein interaction; public health relevance; research study; response; styrofoam; trafficking; yeast two hybrid system; yellow-1; Binding; Biochemical; Biochemical Process; Biocompatible Materials; Bioinformatics; Biological; Biological Assay; Biology; Cells; Chimeric Proteins; Clinical; Co-Immunoprecipitations; Collection; Complex; Data; Data Analyses; Data Set; Disease; Drug Targeting; Flow Cytometry; Generations; Glioblastoma; Health; Homo; Human; Human Engineering; Imagery; Immune; Immunosuppression; In Vitro; Learning; Malignant Neoplasms; Malignant neoplasm of brain; Maps; Measurement; Measures; Methodology; Methods; Microspheres; Mouse Protein; Mus; Pathway interactions; Patients; Physiological; Predictive Value; Proteins; Publishing; Sample Size; Sampling; Signal Transduction; Source; Systems Analysis; T-Lymphocyte; Testing; Therapeutic; Yeasts; base; biosignature; clinical practice; clinically relevant; design; dimer; field study; innovation; interest; meetings; monomer; novel; outcome forecast; protein complex; protein protein interaction; public health relevance; research study; response; styrofoam; trafficking; yeast two hybrid system; yellow-1

DESCRIPTION (provided by applicant): Proteins interact with each other to form complexes, and these complexes can be dynamic and interchanging as they relay biological signals. However, despite their central importance to biology and disease, protein complexes can be difficult to visualize and assess. There are even more technological barriers to analyzing protein complexes when they originate from non-genetically engineered human cells, such as those that would be provided in clinical patient samples. Currently, because physiologic protein complex profiles are virtually unobtainable, clinical practice cannot use them to assist in human health endeavors. We propose to advance a new strategy by mounting a new assay platform, MIF, to bring the analysis of physiologic, human protein complex profiles online. We have already learned how to overcome and control for the technical hurdles, leading us to launch MIF by targeting 21 human proteins that can participate in 231 inter-protein associations (Specific Aim 1). MIF will allow for analysis of small samples and high-throughput formatting, favoring its adoptability for primary human samples originating from clinical patients. Data analysis will involve the generation of Bioinformatics strategies (Specific Aim 2) to focus on three unique parameters of protein complexes: protein abundance, protein multiplicity in shared complexes (commonly thought of as protein plurization/aggregation), and heterotypic protein associations. We will field-test MIF by applying it to the analysis of human protein complexes that may be associated with the immune suppression that accompanies the universally lethal brain cancer, glioblastoma (Specific Aim 3). Together, MIF and its unique analysis will make available the acquisition of physiologic, human complex profiles. We propose that the glioblastoma- derived MIF data will exemplify a new strategy for analyzing these complexes, and illustrate its general applicability to many fields of study and classes of disease.

描述（由申请人提供）：蛋白质相互相互作用以形成复合物，这些复合物可以在中继生物学信号时具有动态和互换。但是，尽管它们对生物学和疾病的重要性至关重要，但蛋白质复合物可能很难可视化和评估。当蛋白质复合物起源于非基因的人类细胞时，例如在临床患者样品中提供的蛋白质复合物时，它们甚至有更多的技术障碍来分析蛋白质复合物。目前，由于生理蛋白质复合物的谱实际上是无法实现的，因此临床实践无法使用它们来帮助人类健康努力。我们建议通过安装新的测定平台MIF来推进新的策略，以在线进行生理，人类蛋白质复合物的分析。我们已经学会了如何克服和控制技术障碍，使我们通过目标21种可以参与231个蛋白质间协会的人类蛋白来推出MIF（特定目标1）。 MIF将允许分析小样本和高通量格式，有利于其对临床患者的原代人样品的可采用性。数据分析将涉及生物信息学策略的产生（特定目的2），以关注蛋白质复合物的三个独特参数：蛋白质丰度，共享复合物中的蛋白质多样性（通常被认为是蛋白质层状/聚集）和杂质蛋白缔合。我们将通过将MIF应用于对人类蛋白质复合物的分析中，这可能与伴随普遍致命的脑癌（特定目标3）相关的免疫抑制作用有关。 MIF及其独特的分析将共同获得生理，人类复杂概况的获取。我们建议，胶质母细胞瘤衍生的MIF数据将举例说明一种分析这些复合物的新策略，并说明了其对许多研究领域和疾病类别的一般适用性。