Back to Search Start Over

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

Authors :
Reilly L
Lara E
Ramos D
Li Z
Pantazis CB
Stadler J
Santiana M
Roberts J
Faghri F
Hao Y
Nalls MA
Narayan P
Liu Y
Singleton AB
Cookson MR
Ward ME
Qi YA
Source :
Cell reports methods [Cell Rep Methods] 2023 Oct 23; Vol. 3 (10), pp. 100593. Date of Electronic Publication: 2023 Sep 19.
Publication Year :
2023

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.<br />Competing Interests: Declaration of interests M.A.N.’s and F.F.’s participation in this project was part of a competitive contract awarded to Data Tecnica International, LLC, by the National Institutes of Health to support open science research. M.A.N. also currently serves as an advisor for Clover Therapeutics and Neuron23, Inc.<br /> (Published by Elsevier Inc.)

Details

Language :
English
ISSN :
2667-2375
Volume :
3
Issue :
10
Database :
MEDLINE
Journal :
Cell reports methods
Publication Type :
Academic Journal
Accession number :
37729920
Full Text :
https://doi.org/10.1016/j.crmeth.2023.100593