Mining the Secretome of C2C12 Muscle Cells: Data Dependent Experimental Approach To Analyze Protein Secretion Using Label Free Quantification and Peptide Based Analysis
Mining the Secretome of C2C12 Muscle Cells: Data Dependent Experimental Approach To Analyze Protein Secretion Using Label Free Quantification and Peptide Based Analysis
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DOI：
10.1021/acs.jproteome.7b00684
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发表时间：
2018-02-01
影响因子：
4.4
通讯作者：
Poschmann, Gereon
中科院分区：
文献类型：
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作者：
Grube, Leonie;Dellen, Rafael;Poschmann, Gereon
分泌组分析面临着几个挑战，包括检测低丰度蛋白质和区分真正的分泌蛋白质从假阳性鉴定源于细胞漏液或血清。在这里，我们开发了一种两步分泌组学方法，并将其应用于C2C12骨骼肌细胞分泌蛋白的分析，因为骨骼肌已被确定为分泌肌因子作为信号分子的重要内分泌器官。首先，我们通过基于质谱的蛋白质组学和无标记定量将培养上清液与相应的细胞裂解物进行比较。我们确定了672个蛋白组作为候选分泌蛋白，因为它们在分泌组中具有较高的丰度。基于Brefeldin A介导的经典分泌过程阻断，我们估计我们的实验方法检测经典分泌蛋白的灵敏度为bbbb80 %。第二步，利用新开发的生物信息学工具“Lysate and Secretome peptide Feature Plotter”（LSPFP），将肽水平信息与基于UniProt的蛋白信息整合，检测分泌过程中可能发生的蛋白水解蛋白加工事件。关于概念的证明，我们确定了Plexin-B2蛋白细胞质部分的截断。我们的工作流程提供了实验工作流程和数据分析的有效结合，以确定推定的分泌和蛋白水解加工蛋白。
Secretome analysis faces several challenges including detection of low abundant proteins and the discrimination of bona fide secreted proteins from false-positive identifications stemming from cell leakage or serum. Here, we developed a two-step secretomics approach and applied it to the analysis of secreted proteins of C2C12 skeletal muscle cells since the skeletal muscle has been identified as an important endocrine organ secreting myokines as signaling molecules. First, we compared culture supernatants with corresponding cell lysates by mass spectrometry-based proteomics and label-free quantification. We identified 672 protein groups as candidate secreted proteins due to their higher abundance in the secretome. On the basis of Brefeldin A mediated blocking of classical secretory processes, we estimated a sensitivity of >80% for the detection of classical secreted proteins for our experimental approach. In the second step, the peptide level information was integrated with UniProt based protein information employing the newly developed bioinformatics tool "Lysate and Secretome Peptide Feature Plotter" (LSPFP) to detect proteolytic protein processing events that might occur during secretion. Concerning the proof of concept, we identified truncations of the cytoplasmic part of the protein Plexin-B2. Our workflow provides an efficient combination of experimental workflow and data analysis to identify putative secreted and proteolytic processed proteins.