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

一种全自动的基于FAIMS-DIA质谱的蛋白质组学分析流程

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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. Keywords: CP: Biotechnology; CP: Systems biology; DDA; DIA; FAIMS; automation; database search; mass spectrometry; proteomics; single-shot MS.

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