Pino Lindsay K, Baeza Josue, Lauman Richard, Schilling Birgit, Garcia Benjamin A
Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Buck Institute for Research on Aging, Novato, California 94945, United States.
J Proteome Res. 2021 Apr 2;20(4):1918-1927. doi: 10.1021/acs.jproteome.0c00938. Epub 2021 Mar 25.
Stable isotope labeling by amino acids in cell culture (SILAC) coupled to data-dependent acquisition (DDA) is a common approach to quantitative proteomics with the desirable benefit of reducing batch effects during sample processing and data acquisition. More recently, using data-independent acquisition (DIA/SWATH) to systematically measure peptides has gained popularity for its comprehensiveness, reproducibility, and accuracy of quantification. The complementary advantages of these two techniques logically suggests combining them. Here we develop a SILAC-DIA-MS workflow using free, open-source software. We empirically determine that using DIA achieves similar peptide detection numbers as DDA and that DIA improves the quantitative accuracy and precision of SILAC by an order of magnitude. Finally, we apply SILAC-DIA-MS to determine protein turnover rates of cells treated with bortezomib, an FDA-approved 26S proteasome inhibitor for multiple myeloma and mantle cell lymphoma. We observe that SILAC-DIA produces more sensitive protein turnover models. Of the proteins determined to be differentially degraded by both acquisition methods, we find known proteins that are degraded by the ubiquitin-proteasome pathway, such as HNRNPK, EIF3A, and IF4A1/EIF4A-1, and a slower turnover for CATD, a protein implicated in invasive breast cancer. With improved quantification from DIA, we anticipate that this workflow will make SILAC-based experiments like protein turnover more sensitive.
细胞培养中氨基酸稳定同位素标记（SILAC）与数据依赖型采集（DDA）相结合是定量蛋白质组学的常用方法，具有减少样品处理和数据采集过程中批次效应的优点。最近，使用数据非依赖型采集（DIA/SWATH）系统地测量肽段因其全面性、可重复性和定量准确性而受到欢迎。这两种技术的互补优势合理地表明应将它们结合起来。在这里，我们使用免费的开源软件开发了一种SILAC-DIA-MS工作流程。我们通过实验确定，使用DIA获得的肽段检测数量与DDA相似，并且DIA将SILAC的定量准确性和精密度提高了一个数量级。最后，我们应用SILAC-DIA-MS来确定用硼替佐米治疗的细胞的蛋白质周转率，硼替佐米是一种经美国食品药品监督管理局批准用于治疗多发性骨髓瘤和套细胞淋巴瘤的26S蛋白酶体抑制剂。我们观察到SILAC-DIA产生了更敏感的蛋白质周转模型。在通过两种采集方法确定为差异降解的蛋白质中，我们发现了通过泛素-蛋白酶体途径降解的已知蛋白质，如HNRNPK、EIF3A和IF4A1/EIF4A-1，以及与浸润性乳腺癌相关的蛋白质CATD的周转较慢。随着DIA定量的改进，我们预计这种工作流程将使基于SILAC的实验（如蛋白质周转）更加敏感。
