Interrogating data-independent acquisition LC-MS/MS for affinity proteomics.

Journal of proteins and proteomics Pub Date : 2024-01-01 Epub Date: 2024-09-17 DOI:10.1007/s42485-024-00166-4
David L Tabb, Mohammed Hanzala Kaniyar, Omar G Rosas Bringas, Heaji Shin, Luciano Di Stefano, Martin S Taylor, Shaoshuai Xie, Omer H Yilmaz, John LaCava
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Abstract

Data-Independent Acquisition (DIA) LC-MS/MS is an attractive partner for co-immunoprecipitation (co-IP) and affinity proteomics in general. Reducing the variability of quantitation by DIA could increase the statistical contrast for detecting specific interactors versus what has been achieved in Data-Dependent Acquisition (DDA). By interrogating affinity proteomes featuring both DDA and DIA experiments, we sought to evaluate the spectral libraries, the missingness of protein quantity tables, and the CV of protein quantities in six studies representing three different instrument manufacturers. We examined four contemporary bioinformatics workflows for DIA: FragPipe, DIA-NN, Spectronaut, and MaxQuant. We determined that (1) identifying spectral libraries directly from DIA experiments works well enough that separate DDA experiments do not produce larger spectral libraries when given equivalent instrument time; (2) experiments involving mock pull-downs or IgG controls may feature such indistinct signals that contemporary software will struggle to quantify them; (3) measured CV values were well controlled by Spectronaut and DIA-NN (and FragPipe, which implements DIA-NN for the quantitation step); and (4) when FragPipe builds spectral libraries and quantifies proteins from DIA experiments rather than performing both operations in DDA experiments, the DIA route results in a larger number of proteins quantified without missing values as well as lower CV for measured protein quantities.

Supplementary information: The online version contains supplementary material available at 10.1007/s42485-024-00166-4.

探究用于亲和蛋白质组学的独立于数据采集的 LC-MS/MS。
独立数据采集(DIA)LC-MS/MS 是免疫共沉淀(co-IP)和亲和蛋白质组学的理想合作伙伴。与数据独立获取(DDA)相比,通过 DIA 减少定量的可变性可以提高检测特定相互作用者的统计对比度。通过分析亲和蛋白质组中的 DDA 和 DIA 实验,我们试图评估代表三个不同仪器制造商的六项研究中的光谱库、蛋白质数量表的缺失以及蛋白质数量的 CV。我们考察了四种当代 DIA 生物信息学工作流程:FragPipe、DIA-NN、Spectronaut 和 MaxQuant。我们发现:(1) 直接从 DIA 实验中识别谱库的效果很好,在仪器时间相当的情况下,单独的 DDA 实验不会产生更大的谱库;(2) 涉及模拟拉低或 IgG 对照的实验可能会出现信号不清晰的情况,当代软件很难对其进行量化;(3) Spectronaut 和 DIA-NN(以及 FragPipe,它在定量步骤中实现了 DIA-NN)能很好地控制测量的 CV 值;(4) 当 FragPipe 从 DIA 实验中建立光谱库并定量蛋白质,而不是在 DDA 实验中执行这两项操作时,DIA 途径会导致更多蛋白质被定量,而不会出现缺失值,同时也会降低蛋白质测量量的 CV 值。补充信息:在线版本包含补充材料,可查阅 10.1007/s42485-024-00166-4。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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