An Optimized Data-Independent Acquisition Strategy for Comprehensive Analysis of Human Plasma Proteome.

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Abstract

Cartography of the plasma proteome remains technically challenging, primarily due to the abundance and dynamic range of plasma proteins and their concentrations, exceeding ten orders of magnitude, including low-abundant tissue-derived proteins in the pg/mL range. Data-independent acquisition mass spectrometry (DIA-MS) has seen advances in unbiased mass spectrometry-based proteomic analysis of the plasma proteome. Here, we describe a comprehensive proteomic workflow of human plasma from clinically relevant sample (10 μL) that includes anti-protein immunodepletion and highly sensitive sample preparation workflow, with optimized scheduled isolation DIA-MS and deep learning analysis. This approach results in over 960 proteins quantified from a single-shot analysis of broad dynamic range, across 8 orders of magnitude (8.2 ng/L to 0.67 g/L). We further compare data-dependent acquisition (DDA) MS to highlight the advantage in protein quantification and inter-sample variation. These developments have provided streamlined identification of the human plasma proteome, including low-abundant tissue-enriched proteins, and applications toward understanding the plasma proteome.© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.