Nanotechnologies for Determining Gene Expression Patterns from Single Cells

描述（由申请人提供）： 所有现有的全球基因表达测定技术都需要相对大量的分析物;为了使用它们与少数或单个细胞中存在的微量mRNA一起使用，需要酶促扩增[5]。这个过程是耗时的，技术上困难的，昂贵的。更重要的是，扩增过程本身会以一种阻止真正定量分析的方式使样品产生偏差[6]。这一点，结合微阵列和DNA测序的特定限制，导致没有直接的方法来研究单细胞中的转录。为了解决这个问题，我们的目标是通过原子力显微镜直接识别单个基因转录分子（以cDNA的形式）。本申请的具体目的是将我们开发的硬件、软件和化学组成部分联合收割机组合成一个集成的功能系统。我们提出的改进将通过减少小样本转录谱分析的时间、成本和技术复杂性来显著影响医学;并将通过产生更容易解释、更高质量的信息来降低生物信息学负担。 公共卫生相关性： 我们研究的长期目标是解剖，理解和控制复杂组织中单细胞的生物学，如脑或恶性肿瘤。进一步的工作需要我们解决单细胞分子分析中一个未解决的问题：缺乏一种常规、可靠和廉价地确定全局基因转录活性的方法。我们正在开发的纳米技术将通过减少小样本转录谱的时间、成本和技术复杂性来显著影响医学;并将通过产生更容易解释、更高质量的信息来降低生物信息学负担。

DESCRIPTION (provided by applicant): Project Summary All existing global gene expression assay techniques require relatively large quantities of analyte; in order to use them with the minute amount of mRNA present in a few or a single cell, enzymatic amplification is required [5]. This process is time consuming, technically difficult, and expensive. More importantly, the amplification process itself biases the sample in a way that prohibits truly quantitative analysis [6]. This, combined with specific limitations of microarrays and DNA sequencing, results in no straightforward method to study transcription in single cells. To solve this problem we aim to directly identify individual gene transcript molecules (in the form of cDNA) via atomic force microscopy. The Specific Aims of this Application are to combine the building blocks of hardware, software and chemistry that we have developed into an integrated, functional system. The improvement we are proposing will significantly impact medicine by reducing time, cost and technical complexity of small sample transcriptional profiling; and will lower the bioinformatics burden by producing easier to interpret, better quality of information. PUBLIC HEALTH RELEVANCE: Project Narrative The long term goal of our research is to dissect, understand, and control the biology of single cells in complex tissues, such as brain, or in malignant tumors. Furthering this body of work requires that we address an unsolved problem in single cell molecular analysis: the lack of a method to routinely, reliably and inexpensively determine global gene transcriptional activity. The nanotechnologies we are developing will significantly impact medicine by reducing time, cost and technical complexity of small sample transcriptional profiling; and will lower the bioinformatics burden by producing easier to interpret, better quality of information.