Genetic circuits for high-throughput, multi-sensory, live cell microRNA prof

用于高通量、多感官、活细胞 microRNA 教授的遗传电路

• 批准号: 8421989
• 负责人: RON WEISS
• 金额: $ 52.26万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8421989
• 关键词: Address; Atlases; Behavior; Biological Assay; Biological Markers; Biosensor; Cancer cell line; Cataloging; Catalogs; Cell Line; Cells; Cellular biology; Classification; Code; DNA; DNA Library; Data; Data Correlations; Data Set; Detection; Development; Disease; Elements; Evaluation; Functional RNA; Gene Library; Genes; Genetic; Genetic Engineering; Human; Individual; Joints; Libraries; Life; Liquid substance; Malignant Neoplasms; Mammalian Cell; Measurable; Measures; Messenger RNA; Metabolic; MicroRNAs; Microfluidic Microchips; Microfluidics; Molecular; Molecular Biology; Molecular Profiling; Oligonucleotides; Oncogenes; Output; Pathway interactions; Pattern; Phenotype; Plasmids; Play; Proteins; Protocols documentation; Reaction; Reagent; Regulatory Element; Reporter; Research; Resources; Role; Sensory; Series; Source; Techniques; Technology; Testing; Therapeutic; Time; Transfection; Translations; Variant; analog; anticancer research; cancer cell; cancer diagnosis; cell type; density; design; digital; experience; gene therapy; in vivo; innovation; insight; interest; nanolitre; novel; operation; public health relevance; repaired; research study; response; screening; sensor; synthetic biology

DESCRIPTION (provided by applicant): The long-term objective of our proposal is to develop a novel technological platform for generating valuable live cell microRNA expression data for cancer cells. MicroRNAs are a class of evolutionary conserved non-coding RNAs that regulate stability and translation efficiency of target mRNAs, playing a critical role in regulating development as well as disease states. While contemporary platforms such as microarrays and RT-qPCR are capable of measuring aggregate miRNA levels, only limited research has addressed single-cell distributions and no systematically created dataset is available for cancer research. Most significantly, distributions and time-series data are required to identify multimodal miRNAs, characterize expression variability, find significant inter-miRNA correlations, and enable more accurate analysis and classification of cancer cell types and states. Finally, no functional datasets exist that characterize the interaction of miRNA with genetic circuit elements that will be useful for both cancer diagnosis and gene-based therapy. We propose an innovative combination of microfluidics and synthetic biology to overcome this hurdle, leading to massive new datasets, large libraries of biosensors, and ultimately therapeutic cancer cures. We will utilize a high throughput microfluidic platform to assemble libraries of genetic circuits that act as sensors to measure microRNA expression levels in target cell lines. These circuits will feature inputs for single or multiple microRNAs. We will assemble a library of single-input microRNA sensors for a large set of experimentally-validated human microRNAs (412, presented in the microRNA atlas) and use these sensors to measure expression levels in 15 target healthy and cancer cell lines. We will use sensors featuring multiple microRNA inputs to generate previously unavailable microRNA correlation data, thus providing an avenue for gaining deeper insight into the operations of pathways important to diseases such as cancer. These expression data sets, in contrast to data derived from microarrays and similar techniques, will be experimentally measured in real-time from large numbers of individual live cells via a separate microfluidic module. We will use the microRNA correlation data to increase the precision of cancer cell classifiers.

描述（由申请人提供）：我们提案的长期目标是开发一个新型的技术平台，用于为癌细胞生成有价值的活细胞microRNA表达数据。 microRNA是一类进化保守的非编码RNA，可调节靶标mRNA的稳定性和翻译效率，在调节发育和疾病状态中起着至关重要的作用。尽管当代平台（例如微阵列和RT-QPCR）能够测量汇总miRNA水平，但只有有限的研究已经解决了单细胞分布，并且没有系统地创建的数据集用于癌症研究。最重要的是，需要分布和时间序列数据来识别多模式miRNA，表征表达变异性，找到明显的miRNA相关性以及对癌细胞类型和状态进行更准确的分析和分类。最后，没有任何功能数据集，它表征miRNA与遗传电路元件的相互作用，这对癌症诊断和基于基因的治疗都有用。我们提出了微流体和合成生物学的创新组合，以克服这一障碍，从而导致大量的新数据集，大型生物传感器库以及最终的治疗性癌症治疗方法。 我们将利用高吞吐量的微流体平台组装遗传回路的库，这些遗传回路是测量目标细胞系中microRNA表达水平的传感器。这些电路将配备单个或多个microRNA的输入。我们将组装一个单输入MicroRNA传感器库，以用于大量实验验证的人MicroRNA（412，在MicroRNA地图集中），并使用这些传感器来测量15个目标健康和癌细胞系中的表达水平。我们将使用具有多个microRNA输入的传感器来生成以前无法使用的microRNA相关数据，从而为对诸如癌症等疾病重要的途径的操作提供了更深入的洞察力。这些表达数据集与从微阵列和类似技术得出的数据相反，将通过单独的微流体模块实时测量大量单个活细胞的实验测量。我们将使用microRNA相关数据来提高癌细胞分类器的精度。