混合四极杆质量过滤器-径向喷射线性离子阱和智能数据采集实现了高度多重靶向蛋白质组学。

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-10-30 DOI:10.1021/acs.jproteome.4c00599
Philip M Remes, Cristina C Jacob, Lilian R Heil, Nicholas Shulman, Brendan X MacLean, Michael J MacCoss
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引用次数: 0

摘要

靶向质谱(MS)方法是对全球发现实验中发现的肽进行选择性和灵敏分析的强大工具。选择反应监测(SRM)因其可靠性和性能而成为最广为接受的临床 MS 方法。然而,SRM 和平行反应监测(PRM)的通量有限,通常用于检测约 100 个或更少的靶标。在此,我们介绍一种新型 MS 平台,该平台采用四极杆质量滤波器、碰撞池和线性离子阱结构,每小时可检测 5000-8000 肽。70-100 Hz 的采集速率和实时色谱配准功能为这种高复用能力提供了便利。我们展示了一个 Skyline 外部软件工具,用于构建基于独立于数据的采集色谱库或重标记标准品的计划外分析的靶向方法。在三重四极杆仪器上进行高度复用检测时,由于平行产物离子积累,我们的平台比传统 SRM 的定量限(LOQ)低 10 倍。最后,我们探讨了分析结果的优劣如何随方法持续时间和分析物数量的变化而变化,为优化分析性能提供了启示。
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Hybrid Quadrupole Mass Filter-Radial Ejection Linear Ion Trap and Intelligent Data Acquisition Enable Highly Multiplex Targeted Proteomics.

Targeted mass spectrometry (MS) methods are powerful tools for the selective and sensitive analysis of peptides identified in global discovery experiments. Selected reaction monitoring (SRM) is the most widely accepted clinical MS method due to its reliability and performance. However, SRM and parallel reaction monitoring (PRM) are limited in throughput and are typically used for assays with around 100 targets or fewer. Here we introduce a new MS platform featuring a quadrupole mass filter, collision cell, and linear ion trap architecture, capable of targeting 5000-8000 peptides per hour. This high multiplexing capability is facilitated by acquisition rates of 70-100 Hz and real-time chromatogram alignment. We present a Skyline external software tool for building targeted methods based on data-independent acquisition chromatogram libraries or unscheduled analysis of heavy labeled standards. Our platform demonstrates ∼10× lower limits of quantitation (LOQs) than traditional SRM on a triple quadrupole instrument for highly multiplexed assays, due to parallel product ion accumulation. Finally, we explore how analytical figures of merit vary with method duration and the number of analytes, providing insights into optimizing assay performance.

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CiteScore
7.20
自引率
4.30%
发文量
567
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