Robust centrifugal microfluidic miniaturization and automation of target enrichment for protease substrate identification

用于蛋白酶底物鉴定的稳健离心微流体小型化和靶标富集自动化

• 批准号: 405351425
• 负责人: Privatdozent Dr.-Ing. Nils Paust
• 金额: --
• 依托单位: Professur für Anwendungsentwicklung
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/405351425?language=en
• 关键词: Robust; centrifugal; microfluidic; miniaturization; automation

Proteins constitute the functional and structural foundation of living systems. Proteomics is the system-wide analysis of proteins; typically performed by mass spectrometry (MS) to identify 1000s of proteins in minute sample amounts. Modern mass spectrometers are powerful but sample preparation lacks far behind with regard to robustness and reproducibility. This project aims to study centrifugal microfluidic automation of sample preparation for the MS based analysis of proteolytic processing. Proteolysis is the enzyme-catalyzed cleavage of proteins into smaller fragments. Often, these cleavage products are stable and possess novel functionality. Dysregulated proteolysis is a hallmark of numerous diseases such as cancer. MS-based methods to study proteolysis on a proteome-wide scale have recently been invented. To study native proteolytic processing, protein termini are tagged and enriched in complex workflows. Although these schemes are now an integral part in many research efforts, they remain laborious and suffer from low robustness and poor reproducibility. These drawbacks are a major hurdle in using MS-based proteomics to study disease-associated proteolysis in clinical specimens, for which often only limited sample material is available. Our research project studies centrifugal microfluidic automation of complex protein-chemical workflows for highly precise and robust sample preparation. More than 30 processing steps (chemical protection of terminal peptides, washing, solid phase extraction) adding up to more than 100 unit operations (liquid transport, metering, mixing, valving) are integrated into centrifugal cartridges. Based on our experience in centrifugal microfluidics as well as in proteomics, we anticipate that centrifugal microfluidic automation will significantly enhance consistency of the complete analysis chain while at the same time minimizing sample consumption. We aim to ultimately employ centrifugal microfluidic sample processing to study key steps of proteolytic processing in clear cell renal cell cancer, using precious patient samples.Our research will focus on overall system integration, on downscaling of volumes to the microliter range, and on simultaneously studying the impact of each automation step (such as metering, mixing, affinity based separation) on the biochemical performance of the analysis. Thereby, the enrichment strategy of chemically protecting the target peptides of the protein, digesting the protein into peptides and removing all non-protected fragments (negative selection) is investigated with microfluidic automation for the first time. Eventually, we aim to specifically remove more than 90 % of the peptides in the sample in order to perform a focused analysis of the remaining 10 % (here: protein terminal peptides). We anticipate that the proposed research will have a substantial impact in both areas, in centrifugal microfluidics a well as in proteolysis research.

蛋白质构成了生命系统的功能和结构基础。蛋白质组学是蛋白质的全系统分析；通常通过质谱（MS）来鉴定微量样品中的1000个蛋白质。现代质谱仪功能强大，但样品制备在鲁棒性和再现性方面远远落后。本项目旨在研究基于质谱分析的蛋白质水解过程样品制备的离心微流控自动化。蛋白质水解是酶催化的蛋白质裂解成更小的片段。通常，这些解理产物是稳定的，具有新颖的功能。蛋白质水解失调是许多疾病如癌症的标志。最近发明了基于质谱的方法来研究蛋白质组范围内的蛋白质水解。为了研究天然蛋白水解过程，在复杂的工作流程中对蛋白质末端进行了标记和富集。虽然这些方案现在是许多研究工作中不可或缺的一部分，但它们仍然很费力，并且存在鲁棒性低和可重复性差的问题。这些缺点是使用MS-based蛋白质组学在临床标本中研究疾病相关蛋白水解的主要障碍，因为通常只有有限的样品材料可用。我们的研究项目研究复杂蛋白质化学工作流程的离心微流控自动化，用于高精度和鲁棒的样品制备。30多个处理步骤（末端肽的化学保护，洗涤，固相萃取）加起来超过100个单元操作（液体输送，计量，混合，阀门）集成到离心筒中。根据我们在离心微流控和蛋白质组学方面的经验，我们预计离心微流控自动化将显著提高整个分析链的一致性，同时最大限度地减少样品消耗。我们的目标是利用宝贵的患者样本，最终采用离心微流控样品处理来研究透明细胞肾细胞癌蛋白水解处理的关键步骤。我们的研究将侧重于整体系统集成，将体积缩小到微升范围，同时研究每个自动化步骤（如计量、混合、基于亲和的分离）对分析生化性能的影响。因此，首次利用微流控自动化技术研究了化学保护蛋白质的目标肽，将蛋白质消化成肽并去除所有非保护片段（负选择）的富集策略。最终，我们的目标是特异性地去除样品中90%以上的肽，以便对剩余的10%（这里是蛋白质末端肽）进行集中分析。我们预计所提出的研究将在离心微流体和蛋白质水解研究这两个领域产生重大影响。