Paulo Joao A, Mancias Joseph D, Gygi Steven P
From the *Department of Cell Biology, Harvard Medical School; and †Division of Genomic Stability and DNA Repair, Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA.
Pancreas. 2017 May/Jun;46(5):690-698. doi: 10.1097/MPA.0000000000000800.
Mass spectrometry-based proteomics enables near-comprehensive protein expression profiling. We aimed to compare quantitatively the relative expression levels of thousands of proteins across 5 pancreatic cell lines.
Using tandem mass tags (TMT10-plex), we profiled the global proteomes of 5 cell lines in duplicate in a single multiplexed experiment. We selected cell lines commonly used in pancreatic research: CAPAN-1, HPAC, HPNE, PANC1, and PaSCs. In addition, we examined the effects of different proteases (Lys-C and Lys-C plus trypsin) on the dataset depth.
We quantified over 8000 proteins across the 5 cell lines. Analysis of variance testing of cell lines within each data set resulted in over 1400 statistically significant differences in protein expression levels. Comparing the data sets, 10% more proteins and 30% more peptides were identified in the Lys-C/trypsin data set than in the Lys-C-only data set. The correlation coefficient of quantified proteins common between the data sets was greater than 0.85.
We illustrate protein level differences across pancreatic cell lines. In addition, we highlight the advantages of Lys-C/trypsin over Lys-C-only digests for discovery proteomics. These data sets provide a valuable resource of cell line-dependent peptide and protein differences for future targeted analyses, including those investigating on- or off-target drug effects across cell lines.
基于质谱的蛋白质组学能够实现近乎全面的蛋白质表达谱分析。我们旨在定量比较5种胰腺细胞系中数千种蛋白质的相对表达水平。
使用串联质量标签(TMT10-plex),我们在一次多重实验中对5种细胞系的整体蛋白质组进行了一式两份的分析。我们选择了胰腺研究中常用的细胞系:CAPAN-1、HPAC、HPNE、PANC1和胰腺干细胞(PaSCs)。此外,我们研究了不同蛋白酶(Lys-C和Lys-C加胰蛋白酶)对数据集深度的影响。
我们对5种细胞系中的8000多种蛋白质进行了定量分析。对每个数据集中的细胞系进行方差分析,结果显示蛋白质表达水平存在1400多个具有统计学意义的差异。比较数据集发现,与仅使用Lys-C的数据集相比,Lys-C/胰蛋白酶数据集中鉴定出的蛋白质多10%,肽多30%。数据集中共有定量蛋白质的相关系数大于0.85。
我们阐述了胰腺细胞系之间的蛋白质水平差异。此外,我们强调了Lys-C/胰蛋白酶相对于仅使用Lys-C消化在发现蛋白质组学方面的优势。这些数据集为未来的靶向分析提供了有价值的细胞系依赖性肽和蛋白质差异资源,包括那些研究跨细胞系的靶向或脱靶药物效应的分析。