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发展一种用于天然质谱和碰撞诱导解折叠的自动化高通量方法。

Development of an Automated, High-Throughput Methodology for Native Mass Spectrometry and Collision-Induced Unfolding.

机构信息

Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.

Attribute Sciences, Process Development, Amgen, Thousand Oaks, California 91320, United States.

出版信息

Anal Chem. 2023 Nov 14;95(45):16717-16724. doi: 10.1021/acs.analchem.3c03788. Epub 2023 Nov 4.

Abstract

Native ion mobility mass spectrometry (nIM-MS) has emerged as a useful technology for the rapid evaluation of biomolecular structures. When combined with collisional activation in a collision-induced unfolding (CIU) experiment, nIM-MS experimentation can be leveraged to gain greater insight into biomolecular conformation and stability. However, nIM-MS and CIU remain throughput limited due to nonautomated sample preparation and introduction. Here, we explore the use of a RapidFire robotic sample handling system to develop an automated, high-throughput methodology for nMS and CIU. We describe native RapidFire-MS (nRapidFire-MS) capable of performing online desalting and sample introduction in as little as 10 s per sample. When combined with CIU, our nRapidFire-MS approach can be used to collect CIU fingerprints in 30 s following desalting by using size exclusion chromatography cartridges. When compared to nMS and CIU data collected using standard approaches, ion signals recorded by nRapidFire-MS exhibit identical ion collision cross sections, indicating that the same conformational populations are tracked by the two approaches. Our data further suggest that nRapidFire-MS can be extended to study a variety of biomolecular classes, including proteins and protein complexes ranging from 5 to 300 kDa and oligonucleotides. Furthermore, nRapidFire-MS data acquired for biotherapeutics suggest that nRapidFire-MS has the potential to enable high-throughput nMS analyses of biopharmaceutical samples. We conclude by discussing the potential of nRapidFire-MS for enabling the development of future CIU assays capable of catalyzing breakthroughs in protein engineering, inhibitor discovery, and formulation development for biotherapeutics.

摘要

天然离子淌度质谱(nIM-MS)已成为一种快速评估生物分子结构的有用技术。当与碰撞诱导解折叠(CIU)实验中的碰撞激活相结合时,nIM-MS 实验可以深入了解生物分子构象和稳定性。然而,由于非自动化的样品制备和引入,nIM-MS 和 CIU 仍然受到通量限制。在这里,我们探索使用 RapidFire 机器人样品处理系统开发一种自动化、高通量的 nMS 和 CIU 方法。我们描述了能够在每个样品 10 秒内完成在线脱盐和样品引入的天然 RapidFire-MS(nRapidFire-MS)。当与 CIU 结合使用时,我们的 nRapidFire-MS 方法可以在使用尺寸排阻色谱柱进行脱盐后 30 秒内收集 CIU 指纹。与使用标准方法收集的 nMS 和 CIU 数据相比,nRapidFire-MS 记录的离子信号具有相同的离子碰撞截面,表明两种方法都跟踪相同的构象群体。我们的数据进一步表明,nRapidFire-MS 可以扩展到研究各种生物分子类别,包括 5 至 300 kDa 的蛋白质和蛋白质复合物以及寡核苷酸。此外,对于生物治疗剂的 nRapidFire-MS 数据表明,nRapidFire-MS 有可能实现高通量 nMS 分析生物制药样品。最后,我们讨论了 nRapidFire-MS 为未来能够催化蛋白质工程、抑制剂发现和生物治疗剂配方开发方面的突破的 CIU 分析的潜力。

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