Self Correcting Nanoflow LC-MS for Clinical Proteomics

描述（由申请方提供）：本提案的总体目标是提高肽质谱数据的质量、可靠性和实验室间可比性。质谱（MS）已成为鉴定和定量分析蛋白质、蛋白质相互作用和蛋白质翻译后修饰的基本技术。这些分析是解决生物学问题的重要组成部分，这些问题涉及蛋白质丰度的变化，以应对疾病，药物治疗，遗传或环境扰动。不幸的是，蛋白质质谱测量在临床实验室中的应用受到限制。与大多数使用微流液相色谱法的质谱法的临床测定不同，肽测量通常使用与质谱仪（纳流LC-MS）的纳流液相色谱接口进行。尽管这些纳米流LC-MS方法具有分析能力，但它们难以稳健地应用于涉及来自具有挑战性的样品基质的大量样品的定量测定。我们项目的成功完成将产生一个肽分析平台，可以自动评估nanoflow LC-MS系统的问题，并在分析运行期间纠正问题，并将显着提高肽质谱测量的鲁棒性和重现性。

DESCRIPTION (provided by applicant): The overall goal of this proposal is to improve the quality, reliability, and interlaboratory comparability of peptide mass spectrometry data. Mass spectrometry (MS) has become a fundamental technology for the identification and quantitative analysis of proteins, protein interactions, and protein post-translational modifications. These analyses are an important part of solving biological problems that involve changes in protein abundance in response to disease, drug treatment, and genetic or environmental perturbations. Unfortunately, the application of protein mass spectrometry measurements in the clinical laboratory has been limited. Unlike most clinical assays by mass spectrometry, which use microflow liquid chromatography, peptide measurements are commonly performed using a nanoflow liquid chromatograph interface to the mass spectrometer (nanoflow LC-MS). Despite their analytical power, these nanoflow LC-MS methods have been difficult to apply robustly in quantitative assays involving large numbers of samples from a challenging sample matrix. The successful completion of our project will result in a peptide analysis platform that can automatically assess problems with the nanoflow LC-MS system and correct the problem during an analytical run and will significantly improve the robustness and reproducibility of peptide mass spectrometry measurements.