Robust and High-Throughput Analytical Flow Proteomics Analysis of Cynomolgus Monkey and Human Matrices With Zeno SWATH Data-Independent Acquisition.

Abstract

Modern mass spectrometers routinely allow deep proteome coverage in a single experiment. These methods are typically operated at nanoflow and microflow regimes, but they often lack throughput and chromatographic robustness, which is critical for large-scale studies. In this context, we have developed, optimized, and benchmarked LC-MS methods combining the robustness and throughput of analytical flow chromatography with the added sensitivity provided by the Zeno trap across a wide range of cynomolgus monkey and human matrices of interest for toxicological studies and clinical biomarker discovery. Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH) data-independent acquisition (DIA) experiments with Zeno trap activated (Zeno SWATH DIA) provided a clear advantage over conventional SWATH DIA in all sample types tested with improved sensitivity, quantitative robustness, and signal linearity as well as increased protein coverage by up to 9-fold. Using a 10-min gradient chromatography, up to 3300 proteins were identified in tissues at 2 μg peptide load. Importantly, the performance gains with Zeno SWATH translated into better biological pathway representation and improved the ability to identify dysregulated proteins and pathways associated with two metabolic diseases in human plasma. Finally, we demonstrate that this method is highly stable over time with the acquisition of reliable data over the injection of 1000+ samples (14.2 days of uninterrupted acquisition) without the need for human intervention or normalization. Altogether, Zeno SWATH DIA methodology allows fast, sensitive, and robust proteomic workflows using analytical flow and is amenable to large-scale studies.

• Authors: Weiwen Sun, Yuan Lin, Yue Huang, Josolyn Chan, Sonia Terrillon, Anton I Rosenbaum, Kévin Contrepois
• Journal: Molecular & cellular proteomics : MCP (Mol Cell Proteomics) Vol. 22 Issue 6 Pg. 100562 (Jun 2023) ISSN: 1535-9484 [Electronic] United States
• PMID: 37142056 (Publication Type: Journal Article)
• Copyright: Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Chemical References

• Proteome

Topics

• Animals
• Humans
• Tandem Mass Spectrometry (methods)
• Macaca fascicularis
• Proteomics (methods)
• Software
• Chromatography, Liquid (methods)
• Proteome