A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline

基于 FAIMS-DIA 质谱的全自动蛋白质组学流程

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作者:Luke Reilly, Erika Lara, Daniel Ramos, Ziyi Li, Caroline B Pantazis, Julia Stadler, Marianita Santiana, Jessica Roberts, Faraz Faghri, Ying Hao, Mike A Nalls, Priyanka Narayan, Yansheng Liu, Andrew B Singleton, Mark R Cookson, Michael E Ward, Yue A Qi

Abstract

Here, we present a standardized, "off-the-shelf" proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at -35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (-35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods.

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