数据独立采集:基于临床质谱的蛋白质组学的里程碑和前景。

IF 6.1 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Molecular & Cellular Proteomics Pub Date : 2024-08-01 Epub Date: 2024-06-15 DOI:10.1016/j.mcpro.2024.100800
Klemens Fröhlich, Matthias Fahrner, Eva Brombacher, Adrianna Seredynska, Maximilian Maldacker, Clemens Kreutz, Alexander Schmidt, Oliver Schilling
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引用次数: 0

摘要

在过去几年里,数据独立采集(DIA)在基于质谱(MS)的蛋白质组学领域掀起了一场革命。DIA 的突出之处在于它能够对给定质量-电荷范围内的所有肽段进行系统采样,从而实现无偏采集蛋白质组学数据。与许多传统方法相比,这大大缓解了缺失值的问题,并显著提高了定量的准确性、精确性和可重复性。本综述重点介绍 DIA 分析软件工具的关键作用,主要侧重于其功能及其在蛋白质组学研究中应对的挑战。质谱技术的进步,如俘获离子迁移率光谱法或高场非对称波形离子迁移率光谱法,需要能处理增加的数据复杂性并充分挖掘 DIA 潜力的先进分析软件。我们确定并严格评估了 DIA 领域的领先软件工具,讨论了它们的独特功能及其定量和定性输出的可靠性。我们介绍了 DIA-MS 的生物学和临床相关性,并讨论了为病人标本的深入蛋白质组特征描述铺平道路的重要出版物。此外,我们还透视了临床应用中的新兴趋势,并提出了即将面临的挑战,包括分子诊断中基于 MS 的采集策略的标准化和认证。我们强调需要不断开发软件工具以跟上技术发展的步伐,同时建议研究人员不要不加批判地接受 DIA 软件工具的结果。每种工具都可能有自己的偏差,有些工具的灵敏度或可靠性可能不如其他工具。我们对研究人员和临床医生的总体建议是采用多种 DIA 分析工具,利用正交分析方法来提高研究结果的稳健性和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-Independent Acquisition: A Milestone and Prospect in Clinical Mass Spectrometry-Based Proteomics.

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.

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来源期刊
Molecular & Cellular Proteomics
Molecular & Cellular Proteomics 生物-生化研究方法
CiteScore
11.50
自引率
4.30%
发文量
131
审稿时长
84 days
期刊介绍: The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes
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