Development of a parallel, array-based transcription factor expression assay

开发基于阵列的并行转录因子表达测定法

• 批准号: 7347355
• 负责人: Stephen Patrick Walton
• 金额: $ 18.09万
• 依托单位: MICHIGAN STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-03-06 至 2011-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7347355
• 关键词: Abbreviations; Acquired Immunodeficiency Syndrome; Address; Affinity; Base Pairing; Behavior; Binding Proteins; Biological Assay; Biological Models; Cell Line; Cell physiology; Cells; Characteristics; Class; Complement; Computer Systems Development; Condition; Consensus; Consensus Sequence; Cyclic AMP; Cyclic AMP Response Element; Cyclic AMP-Responsive DNA-Binding Protein; DNA Binding; Detection; Development; Disease; Dissociation; EMSA; Electrophoretic Mobility Shift Assay; Elements; Environment; Equilibrium; Event; Fatty Acids; Future; Genetic; Genomics; Global Change; Hepatic; Hepatocyte; Human; In Vitro; Individual; Label; Lactate Dehydrogenase; Lactate Dehydrogenases; Lipopolysaccharides; Liver; Malignant Neoplasms; Measurement; Measures; Mediating; Mediator of activation protein; Methods; Modeling; Molecular; NF-kappa B; Non-Insulin-Dependent Diabetes Mellitus; Nonesterified Fatty Acids; Nuclear; Nucleic Acids; Peroxisome Proliferator-Activated Receptors; Phase; Polyacrylamide Gel Electrophoresis; Polymerase Chain Reaction; Predictive Value; Property; Protein Analysis; Proteins; RXR; Rate; Reading; Reproducibility; Research; Sampling; Sensitivity and Specificity; Signal Transduction; Solutions; Specificity; Standards of Weights and Measures; Sterols; Stimulus; System; TNF gene; Techniques; Testing; Time; Translating; Triglycerides; Tumor Necrosis Factor-alpha; Tumor Necrosis Factors; Work; activating transcription factor 1; base; chicken DcoHalpha protein; concept; cytokine; cytotoxicity; extracellular; hepatoma cell; human TNF protein; improved; protein expression; receptor; response; tool; transcription factor

DESCRIPTION (provided by applicant): Transcription factors are generally the termini of signaling cascades. As such, they are the ultimate mediators of change in cell function resulting from changes in the cellular environment. Inappropriate or unregulated expression of transcription factors has been implicated in many diseases, including cancer, AIDS, and Type II diabetes. As such, a complete understanding of the transcription factor profile of a cell at any time would provide an exquisitely detailed depiction of the current function of that cell as well as strong indications of functional changes that may occur in the future. Despite the importance of this information and its predictive value, few tools exist that provide sensitive, reproducible, and parallel transcription factor expression analysis. It is proposed to address this significant need, leveraging validated tools from genomics. Our proposed method will combine solution-phase detection of transcription factors with a PCR-based readout to achieve detection limits of hundreds of transcription factor molecules per sample. As we have begun to characterize the signaling events that occur upon administration of cytokines and fatty acids to hepatic cells, a model of Type II diabetes, we will use this system as a model system for development and refinement of the analytical technique. The specific aims of the proposed work are to i) quantify in vitro association of TFs to their recognition sequences in MB-cassettes; ii) determine the lower detection limits for measurements of individual and multiple TFs; iii) measure TF level changes following stimulation of HepG2 cells in culture. Transcription factors are cellular proteins that cells call upon to respond to changes in their environment. Altered transcription factor expression is often a hallmark of a disease condition. Our proposed work will provide a better means of measuring global changes in transcription factor expression and, in turn, allow for greater understanding of and better treatment of disease.

描述（由申请人提供）：转录因子通常是信号级联的终点。因此，它们是细胞环境变化引起的细胞功能变化的最终调节者。转录因子的不适当或不受调节的表达与许多疾病有关，包括癌症、艾滋病和二型糖尿病。因此，在任何时候对细胞转录因子谱的完整了解将提供对该细胞当前功能的精确详细描述，以及未来可能发生的功能变化的强烈指示。尽管这些信息及其预测价值很重要，但提供灵敏、可重复和并行转录因子表达分析的工具却很少。建议利用基因组学中经过验证的工具来解决这一重大需求。我们提出的方法将转录因子的溶液相检测与基于 PCR 的读数相结合，以实现每个样品数百个转录因子分子的检测极限。当我们开始表征向肝细胞（II 型糖尿病模型）施用细胞因子和脂肪酸时发生的信号事件时，我们将使用该系统作为开发和完善分析技术的模型系统。拟议工作的具体目标是 i) 量化 TF 与其在 MB 盒中的识别序列的体外关联； ii) 确定单个和多个 TF 测量的检测下限； iii) 测量培养物中刺激 HepG2 细胞后 TF 水平的变化。 转录因子是细胞蛋白质，细胞利用它们来响应环境的变化。转录因子表达的改变通常是疾病的标志。我们提出的工作将提供一种更好的方法来测量转录因子表达的全局变化，反过来，可以更好地理解和更好地治疗疾病。