Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, United States.
J Proteome Res. 2023 Apr 7;22(4):1270-1279. doi: 10.1021/acs.jproteome.2c00806. Epub 2023 Mar 27.
The reduction of disulfide bonds and their subsequent alkylation are commonplace in typical proteomics workflows. Here, we highlight a sulfhydryl-reactive alkylating reagent with a phosphonic acid group (iodoacetamido-LC-phosphonic acid, 6C-CysPAT) that facilitates the enrichment of cysteine-containing peptides for isobaric tag-based proteome abundance profiling. Specifically, we profile the proteome of the SH-SY5Y human cell line following 24 h treatments with two proteasome inhibitors (bortezomib and MG-132) in a tandem mass tag (TMT)pro9-plex experiment. We acquire three datasets─(1) Cys-peptide enriched, (2) the unbound complement, and (3) the non-depleted control─and compare the peptides and proteins quantified in each dataset, with emphasis on Cys-containing peptides. The data show that enrichment using 6C-Cys phosphonate adaptable tag (6C-CysPAT) can quantify over 38,000 Cys-containing peptides in 5 h with >90% specificity. In addition, our combined dataset provides the research community with a resource of over 9900 protein abundance profiles exhibiting the effects of two different proteasome inhibitors. Overall, the seamless incorporation of alkylation by 6C-CysPAT into a current TMT-based workflow permits the enrichment of a Cys-containing peptide subproteome. The acquisition of this "mini-Cys" dataset can be used to preview and assess the quality of a deep, fractionated dataset.
二硫键的还原及其随后的烷基化在典型的蛋白质组学工作流程中很常见。在这里,我们重点介绍一种带有膦酸基团的巯基反应性烷基化试剂(碘乙酰胺-LC-膦酸,6C-CysPAT),它可以促进含半胱氨酸肽的富集,用于基于等重标记的蛋白质组丰度分析。具体来说,我们在串联质量标签(TMT)pro9 plex 实验中,对 SH-SY5Y 人细胞系在两种蛋白酶体抑制剂(硼替佐米和 MG-132)处理 24 小时后的蛋白质组进行了分析。我们获得了三个数据集:(1)富含半胱氨酸的肽段、(2)未结合的互补部分和(3)非耗尽对照部分,并比较了每个数据集定量的肽段和蛋白质,重点是含半胱氨酸的肽段。数据表明,使用 6C-Cys 磷酸酯适应性标签(6C-CysPAT)进行富集可以在 5 小时内定量超过 38000 个半胱氨酸肽段,特异性大于 90%。此外,我们的组合数据集为研究界提供了超过 9900 个蛋白质丰度谱的资源,这些谱展示了两种不同的蛋白酶体抑制剂的作用。总的来说,6C-CysPAT 的烷基化无缝纳入当前基于 TMT 的工作流程,可以富集含半胱氨酸肽的亚蛋白质组。获取这个“迷你-Cys”数据集可用于预览和评估深度、分级数据集的质量。