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

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

Cell Reports: Methods (Oct 2023)

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

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

Affiliations

Luke Reilly: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Erika Lara: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Daniel Ramos: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Ziyi Li: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, LLC, Glen Echo, MD, USA
Caroline B. Pantazis: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Julia Stadler: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Marianita Santiana: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Jessica Roberts: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Faraz Faghri: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, LLC, Glen Echo, MD, USA
Ying Hao: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Mike A. Nalls: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, LLC, Glen Echo, MD, USA
Priyanka Narayan: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Genetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20814, USA
Yansheng Liu: Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06510, USA
Andrew B. Singleton: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
Mark R. Cookson: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
Michael E. Ward: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Yue A. Qi: Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Corresponding author

Journal volume & issue: Vol. 3, no. 10
p. 100593

Abstract

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Summary: 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. Motivation: Although mass spectrometry (MS)-based quantitative proteomics has been significantly advanced in the past decade, reproducibility and robustness are roadblocks preventing this technique from being widely applied to large biomedical research communities. We aim to streamline and automate major components of MS-based proteomics, providing an extensively optimized and validated platform for large-scale studies in modern proteomic laboratories and contract research organizations.

Published in Cell Reports: Methods

ISSN: 2667-2375 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Technology: Chemical technology: Biotechnology; Science: Chemistry: Organic chemistry: Biochemistry
Website: https://www.cell.com/cell-reports-methods

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