IDBR (Type A): Deep Proteome Imaging System

IDBR（A 型）：深层蛋白质组成像系统

• 批准号: 1063236
• 负责人: Jonathan Minden
• 金额: $ 36.41万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-06-01 至 2014-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1063236&HistoricalAwards=false
• 关键词: IDBR; Type; Deep; Proteome; Imaging

ABSTRACTCells contain thousands of different types of proteins. These proteins exist in the cell at very different concentrations, from tens of copies per cell to millions of copies per cell, which represents a hundred-thousand-fold concentration range. The goal of comparative proteomics is to discover differences in protein expression patterns between cells, tissues and organisms grown under different conditions, with different genetic backgrounds, or at different stages of development or disease. Current proteome profiling methods are unable to detect and identify the full complement of proteins in a single experiment. This limitation is a serious impediment in many comparative proteomic analyses and is largely due to the fact that no detection system has a dynamic range that is well matched to the roughly 100,000-fold concentration range of cellular proteins. There are two general approaches to comparative proteomics experiments: peptide-centric and protein centric. Peptide-centric methods rely exclusively on mass spectrometers (MSs) for peptide identification and quantification. The dynamic range of typical MSs used for comparative proteomics is ~1,000. In protein-centric methods (which commonly involve fluorescently tagged proteins and difference-gel electrophoresis (DIGE)), protein quantification and identification are done separately by fluorescence imagers and MSs, respectively. Fluorescence imagers have a dynamic range of ~20,000. To quantify protein abundance over a 100,000-fold range, one needs a detection system with at least a million-fold dynamic range, which is essential for detecting both low abundance proteins, such as transcription factors, and high abundance proteins, such as structural proteins, in the same experiment. The goal of this project is to develop an enhanced gel imaging system that can quantify proteins over a million-fold concentration range, yielding a more than 50-fold improvement over existing fluorescent gel imagers.In this project, a structured-illumination, gel imager (SIGI) system will be constructed. The SIGI system will extend the dynamic range of the CCD-based imager to at least one million-fold by incorporating a structured illuminator. Structured illumination allows one to expose regions of a gel that contain low-abundance proteins for long intervals without over-exposing high abundance proteins. The data collection routine consists of a series of images of DIGE gels captured using a range of exposure times. To prevent pixel saturation due to high protein concentrations and long exposure times, a computer-generated illumination mask will be used to only illuminate regions of the gel that contain low-abundance proteins. This series of images will be used to calculate a fluorescence intensity versus exposure time curve for each pixel in the field-of-view (measured in counts per second (CPS)). This masking procedure will generate a CPS image having a dynamic range well over 1,000,000-fold, greatly extending the effective dynamic range of the CCD camera.The broader impacts of fabricating the SIGI system will be to allow proteomics researchers to explore the proteome more deeply than previously possible. This will permit us to ask more probing and precise questions about proteome changes in response to a large number of conditions and treatments. The development of such a sensitive instrument will also stimulate the advancement of other proteomics-related technologies. Results of this work will be made available to the scientific community through publications and open-source web-based resources.Access to our SIGI system (and others built elsewhere) will enhance infrastructure for research and education by helping to establish collaborations with researchers in academic, industry and government laboratories, developing partnerships with international academic institutions and organizations. Access to this instrument will also foster the training of students from smaller, less research oriented institutions.

细胞含有成千上万种不同类型的蛋白质。这些蛋白质以非常不同的浓度存在于细胞中，从每个细胞数十个拷贝到每个细胞数百万个拷贝，这代表了数十万倍的浓度范围。比较蛋白质组学的目标是发现在不同条件下生长的细胞，组织和生物体之间蛋白质表达模式的差异，具有不同的遗传背景，或处于不同的发育阶段或疾病。目前的蛋白质组分析方法无法在单个实验中检测和鉴定完整的蛋白质。这种限制是许多比较蛋白质组学分析中的严重障碍，并且主要是由于没有检测系统具有与细胞蛋白质的大约100，000倍浓度范围良好匹配的动态范围的事实。比较蛋白质组学实验一般有两种方法：以肽为中心和以蛋白质为中心。以肽为中心的方法完全依赖于质谱仪（MS）进行肽识别和定量。用于比较蛋白质组学的典型MS的动态范围为~ 1，000。在以蛋白质为中心的方法（通常涉及荧光标记蛋白质和差异凝胶电泳（DIGE））中，蛋白质定量和鉴定分别通过荧光成像仪和MS进行。荧光成像仪的动态范围约为20，000。为了定量超过100，000倍范围的蛋白质丰度，需要具有至少百万倍动态范围的检测系统，这对于在同一实验中检测低丰度蛋白质（如转录因子）和高丰度蛋白质（如结构蛋白）两者是必不可少的。该项目的目标是开发一种增强型凝胶成像系统，该系统可以在百万倍浓度范围内定量蛋白质，比现有的荧光凝胶成像仪提高50倍以上。在该项目中，将构建结构照明凝胶成像仪（SIGI）系统。SIGI系统将通过结合结构化照明器将基于CCD的成像器的动态范围扩展到至少一百万倍。结构化照明允许长时间暴露含有低丰度蛋白质的凝胶区域，而不会过度暴露高丰度蛋白质。数据收集程序由使用一系列曝光时间捕获的DIGE凝胶的一系列图像组成。为了防止由于高蛋白质浓度和长曝光时间而导致的像素饱和，将使用计算机生成的照明掩模来仅照亮含有低丰度蛋白质的凝胶区域。这一系列图像将用于计算视野中每个像素的荧光强度与暴露时间曲线（以每秒计数（CPS）测量）。这种掩蔽过程将产生动态范围超过1，000，000倍的CPS图像，大大扩展了CCD相机的有效动态范围。制造SIGI系统的更广泛影响将使蛋白质组学研究人员能够比以前更深入地探索蛋白质组。这将使我们能够提出更多关于蛋白质组变化的探索性和精确的问题，以应对大量的条件和治疗。这种灵敏仪器的开发也将促进其他蛋白质组学相关技术的发展。这项工作的成果将通过出版物和开放源网络资源提供给科学界，进入我们的SIGI系统（和其他地方建立的系统）将有助于与学术界、工业界和政府实验室的研究人员建立合作关系，与国际学术机构和组织建立伙伴关系，从而加强研究和教育的基础设施。利用这一工具还将促进对来自较小、研究较少的机构的学生的培训。