Center for Advanced Biotechnology and Medicine, Piscataway, New Jersey 08854, United States.
URPhyM-Intracellular Trafficking Biology, NARILIS, University of Namur, 61 rue de Bruxelles, Namur 5000, Belgium.
J Proteome Res. 2020 Apr 3;19(4):1718-1730. doi: 10.1021/acs.jproteome.9b00862. Epub 2020 Mar 5.
Knowledge of intracellular location can provide important insights into the function of proteins and their respective organelles, and there is interest in combining classical subcellular fractionation with quantitative mass spectrometry to create global cellular maps. To evaluate mass spectrometric approaches specifically for this application, we analyzed rat liver differential centrifugation and Nycodenz density gradient subcellular fractions by tandem mass tag (TMT) isobaric labeling with reporter ion measurement at the MS2 and MS3 level and with two different label-free peak integration approaches, MS1 and data independent acquisition (DIA). TMT-MS2 provided the greatest proteome coverage, but ratio compression from contaminating background ions resulted in a narrower accurate dynamic range compared to TMT-MS3, MS1, and DIA, which were similar. Using a protein clustering approach to evaluate data quality by assignment of reference proteins to their correct compartments, all methods performed well, with isobaric labeling approaches providing the highest quality localization. Finally, TMT-MS2 gave the lowest percentage of missing quantifiable data when analyzing orthogonal fractionation methods containing overlapping proteomes. In summary, despite inaccuracies resulting from ratio compression, data obtained by TMT-MS2 assigned protein localization as well as other methods but achieved the highest proteome coverage with the lowest proportion of missing values.
对细胞内位置的了解可以为蛋白质及其各自细胞器的功能提供重要的见解,并且人们有兴趣将经典的亚细胞分级分离与定量质谱法相结合,以创建全局细胞图谱。为了专门评估质谱方法在此应用中的适用性,我们通过串联质量标签 (TMT) 等离⼦标记,对大鼠肝差速离心和 Nycodenz 密度梯度亚细胞级分进行了分析,在 MS2 和 MS3 水平上进行了报告离⼦测量,并采用两种不同的无标记峰积分方法(MS1 和数据非依赖性采集 (DIA))。TMT-MS2 提供了最大的蛋白质组覆盖范围,但由于污染背景离⼦的比率压缩,与 TMT-MS3、MS1 和 DIA 相比,其准确的动态范围较窄,后三者相似。使用蛋白质聚类方法通过将参考蛋白分配到其正确的隔室来评估数据质量,所有方法的性能都很好,等离⼦标记方法提供了最高质量的定位。最后,在分析含有重叠蛋白质组的正交分级方法时,TMT-MS2 分析时产生的无法定量的数据百分比最低。总的来说,尽管存在由于比率压缩导致的不准确性,但 TMT-MS2 获得的数据在分配蛋白质定位方面与其他方法一样好,但具有最低的缺失值比例,实现了最高的蛋白质组覆盖率。