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

在基础研究和临床环境中对完整蛋白质的常规分析需要新的分离 平台，以降低混合物的复杂性和所需的样本量。为了满足这些要求 根据要求，必须优化单独的分离策略，以减少样品损失和提高分辨率。 在研发1中，我们结合了层析和凝胶分离方法，从根本上改进了 自上而下的蛋白质组学能力。我们将此研发中描述的新功能放在 国家翻译和发展资源中的许多推动生物医学项目 蛋白质组学。在两个特定的目标中，我们提出了新的完整蛋白质分离和层析方法 一种新的在线凝胶分离技术，用于自上而下的蛋白质组学，称为“GelSpray”。具体目标1a是有目的的 被构造为在资源的第一年内可用，因此代表递增预付款 缺乏具体目标1b和2中提供的创新水平。 开发新的分离平台，智能地与新的和改进的质量对接 不同的DBP需要光谱仪器，以增加自上而下的表征深度 蛋白质组学是有能力的。通过在质量分析之前更准确地分离复杂混合物，新的和 对基础生物学和翻译研究的更清晰的见解将返回给合作者。此外， 吞吐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 在样本量小、技术含量较高的临床应用中提取有意义的结果 重复增加了量化结果的深度和置信度(参见R&D 3)，样本量大。 总而言之，所有需要高保真蛋白质读数的拟议DBP都需要这些努力 样品的含量以及有关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.