High Resolution Separations for Intact Proteins (pp. 419-480)

在基础研究和临床环境中，完整蛋白质的常规分析需要新的分离方法 该平台可以降低混合物的复杂性以及所需的样品量。满足这些 为了满足这些要求，必须优化各个分离策略，以减少样品损失并提高分辨率。 在TR&D 1中，我们将联合收割机色谱和凝胶分离方法相结合，从根本上提高了 自上而下的蛋白质组学能力。我们将本TR&D中描述的新功能置于 国家转化和发展资源中的许多驱动生物医学项目 蛋白质组学在两个具体的目标，我们提出了新的色谱方法，完整的蛋白质分离， 一种新型在线凝胶分离技术，用于自上而下的蛋白质组学，名为“GelSpray”。具体目标1a是有目的地 在资源的第一年内就可以使用，因此是一个渐进的进步。 缺乏具体目标1b和2所提供的创新水平。 开发新的分离平台，与新的和改进的质量 光谱仪器需要由不同的DBPs，以增加自上而下的表征的深度， 蛋白质组学是可行的。通过在质量分析之前更精确地分离复杂的混合物， 对基础生物学和转化研究的更清晰的见解将返回给合作者。此外，本发明还 通过量的提高和样品损失的减少将使所需的研究规模成为可能， 在样本量较小、技术要求较高的临床应用中提取有意义的结果 重复增加了定量结果的深度和置信度（参见TR&D 3），样本数量大。 总之，所有建议的DBP都需要这些努力，这些DBP要求蛋白质的高保真度读数 样品的含量以及关于蛋白质丰度的定量信息。

The routine analysis of intact proteins in basic research and clinical settings requires new separations platforms to reduce both the complexity of mixtures as well as the sample amount required. To satisfy these requirements, individual separations strategies must be optimized to reduce sample loss and increase resolution. In TR&D 1, we combine chromatographic and gel-based separation approaches to radically improve the capability of top-down proteomics. We place the new capabilities described in this TR&D at the epicenter of many of the driving biomedical projects within the National Resource for Translational and Developmental Proteomics. In two Specific Aims, we present new chromatographic methods for intact protein separations and a novel online gel-based separation for top-down proteomics called “GelSpray”. Specific Aim 1a is purposefully constructed to be available within the first year of the resource, and therefore represents an incremental advance lacking the level of innovation offered in Specific Aims 1b and 2. The development of new separations platforms that are intelligently interfaced with new and improved mass spectrometric instrumentation is required by diverse DBPs to increase the depth of characterization of which topdown proteomics is capable. By more accurately separating complex mixtures prior to mass analysis, new and more lucid insights into basic biology and translational research will be returned to collaborators. Further, improvements in throughput and reductions in sample loss will make possible the scale of study required to extract meaningful results in clinical applications where sample size is small, higher numbers of technical replicates increase depth and confidence of quantitative results (c.f. TR&D 3), and sample numbers are large. In sum, these efforts are required by all of the proposed DBPs that demand high fidelity readouts of the protein content of a sample as well as quantitative information regarding protein abundance.