Data-Independent Acquisition: A Milestone and Prospect in Clinical Mass Spectrometry-Based Proteomics

Abstract

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given m/z range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

Keywords: clinical proteomics; data-independent acquisition; mass spectrometry.

Graphical abstract

Fig. 1

Key principles and developments toward state-of-the-art DIA-MS.A, most common isolation window schemes in DIA-MS. B, implementation of DIA-MS over time on different instrument platforms and their usage approximated by citations in Google Scholar. C, schematic overview of state-of-the-art MS instruments with their respective key developments and features highlighted in bold text. The ion flux through the respective ion optics is depicted as a red line with the direction from left to right. D, state-of-the-art DIA-MS strategies based on respective key features of each instrument type. DIA, data-independent acquisition; IM, ion mobility; MS, mass spectrometry.

Fig. 2

Usage metrics of DIA analysis tools between 2010 and 2023.A, annual number of citations of each primary manuscript as indexed by Google Scholar. B, annual co-occurrence of “SoftwareTool” with “proteomics” and either “DIA” or “SWATH” in PMC literature searches (in the case of EncyclopeDIA, “Searle” was additionally used in the co-occurrence search, which probably leads to an underrepresentation). DIA, data-independent acquisition; PMC, PubMed Central; SWATH, sequential window acquisition of all theoretical fragment ion spectra.