2D-LC MALDI WITH ON-TARGET DIGESTION FOR HIGH-THROUGHPUT PROTEOMICS

用于高通量蛋白质组学的定向消化的 2D-LC MALDI

• 批准号: 8170887
• 负责人: Mark McComb
• 金额: $ 0.35万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2011-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8170887
• 关键词: Collection; Complex Mixtures; Computer Retrieval of Information on Scientific Projects Database; Coupling; Crystallization; Data; Deposition; Devices; Digestion; Fractionation; Funding; Grant; High Pressure Liquid Chromatography; Institution; Lead; Mass Spectrum Analysis; Methods; Peptide Mapping; Peptides; Preparation; Procedures; Process; Proteins; Proteomics; Reaction; Reflex action; Research; Research Personnel; Resources; Robotics; Sampling; Solutions; Solvents; Source; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; System; Techniques; Technology; Time; United States National Institutes of Health; novel

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Large-scale proteomic analyses necessitate high-throughput sample preparation techniques. However, highly complex mixtures require multi-dimensional fractionation prior to MS analysis to maximize the yield of useful MS data. This geometrically expands sample numbers, dramatically intensifying processing load, commonly involves dilution (e.g., HPLC), often demanding sample concentration, and typically requires multiple steps of sample handling, including transfer to different reaction vessels. These steps are time consuming, lead to sample losses and potential contamination. We have explored the use of a novel, simple, inexpensive (non-robotic) 96-well array technology, the BD MALDI Concentrator, to conduct one-pot on-target sample preparation for MALDI-MS analysis. We have applied this technology with deposition from 1D and 2D protein LC direct-to-target for peptide mapping by MALDI-TOF MS. 1D and 2D-HPLC fractionation of protein mixtures is conducted with a Beckman PF2D system. Fractions can be collected directly into the wells of the BD device, and optimized conditions are used to concentrate, digest in-solution on-target/in-well, and co-crystallize the samples with matrix. MALDI mass spectra are obtained with a Bruker Reflex IV MALDI-TOF MS. Results are compared to other sample handling methods. One-pot on-target/in-well digestion, concentration and sample/matrix co-crystallization under optimized solvent conditions readily yields good quality mass spectra from as little as 10 fmol of peptide standards from up to 200 ¿l starting solution. The coupling of 1D and 2D-protein-LC to MALDI-TOF MS through the collection of LC fractions directly into the 96-well array concentrator enables rapid, high-throughput protein fractionation, digestion, peptide matrix co-crystallization, and MALDI-TOF MS analyses with minimal sample handling. The method is now being applied to proteomic projects of the Resource and the CPC and the results are being evaluated to generate further refinements of the procedures.

该副本是使用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这是调查员的机构。 大规模蛋白质组学分析必要的高通量样品制备技术。但是，高度复杂的混合物需要在MS分析之前进行多维分馏，以最大程度地提高有用的MS数据的产量。该几何量扩展样品数量，动态增强加工载荷，通常涉及稀释（例如HPLC），通常要求样品浓度，通常需要多个样品处理的步骤，包括转移到不同的反应容器。这些步骤是耗时的，导致样本损失和潜在的污染。我们已经探索了一种新颖，简单，廉价（非反复的）96孔阵列技术BD MALDI浓缩器来进行一锅靶向样品样本准备，以进行MALDI-MS分析。我们已经通过MALDI-TOF MS的1D和2D蛋白LC直接靶向靶标的沉积应用了这项技术。蛋白质混合物的1D和2-HPLC分馏是用Beckman PF2D系统进行的。可以将分数直接收集到BD设备的孔中，并使用优化的条件来浓缩，消化内部靶向内目标/内孔，并将样品与矩阵结合结合。 MALDI质谱是通过Bruker反射IV MALDI-TOF MS获得的。将结果与其他样品处理方法进行比较。在优化的溶液条件下，单蛋白靶标/孔内消化，浓度和样品/基质共结晶很容易产生优质的质谱，从最高10 fmol的胡椒标准标准从最高到200 f启动溶液。通过将LC分数直接收集到96孔阵列浓缩液中，1D和2D-蛋白LC与MALDI-TOF MS的偶联能够快速，高通量蛋白分馏，消化，肽矩阵共晶和MALDI-TOF MS分析，并具有最小的样品处理。该方法现在应用于资源的蛋白质组学项目和CPC的蛋白质组学项目，并且正在评估结果以生成对程序的进一步改进。