Wahid Amir, Sohail Amir, Wang Huiyu, Guo Miao, Zhang Lu, Ji Yin, Wang Peng, Xiao Hua
State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
State Key Laboratory of Translational Medicine and Innovative Drug Development, Jiangsu Simcere Pharmaceutical Co., Ltd., Nanjing, 210042, China.
Anal Bioanal Chem. 2022 May;414(12):3697-3708. doi: 10.1007/s00216-022-04013-7. Epub 2022 Mar 19.
Extracellular vesicles (EVs) play critical roles in intercellular communications, which contain valuable biomarkers for the detection of cancers. Phosphoproteomics analysis of human saliva EVs (sEVs) can help to discover lung cancer-related candidates. Due to the low abundance of phosphoproteins in sEVs, an efficient, reproducible, and cost-effective strategy is required for their enrichment. Here, we compared the latest phosphopeptide techniques, including TiO, ZrO, CaTiO, and Ti-IMAC (immobilized metal affinity chromatography) methods, for phosphopeptide isolation. Our data demonstrated that Ti-IMAC was the superior one. By using the optimized Ti-IMAC approach, we identified more than 500 sEV phosphopeptides. Quantitative proteomics was employed to comprehensively decipher the sEV phosphoproteome of the normal group (n = 6) and lung cancer group (n = 6). Accordingly, 524 and 333 phosphopeptides were enriched, respectively, which corresponded to 439 and 282 phosphoproteins. In total, 857 unique sEV phosphopeptides corresponding to 721 phosphoproteins were revealed. Among 493 identified phosphosites, 37 were upregulated (> 1.5) and 217 were downregulated (< 0.66) in the cancer group. Our data collectively demonstrated that Ti-IMAC is an efficient and reproducible technology for comprehensive analysis of sEV phosphoproteome. Differentially expressed sEV phosphoproteins and phosphosites might be used for the detection of lung cancer non-invasively.
细胞外囊泡（EVs）在细胞间通讯中发挥着关键作用，其包含用于癌症检测的有价值生物标志物。对人唾液细胞外囊泡（sEVs）进行磷酸化蛋白质组学分析有助于发现肺癌相关候选物。由于sEVs中磷酸化蛋白质丰度较低，需要一种高效、可重复且经济高效的策略来富集它们。在此，我们比较了最新的磷酸肽技术，包括TiO、ZrO、CaTiO和钛固定化金属亲和色谱（Ti-IMAC）方法，用于磷酸肽分离。我们的数据表明Ti-IMAC是更优的方法。通过使用优化的Ti-IMAC方法，我们鉴定出500多个sEV磷酸肽。采用定量蛋白质组学全面解析正常组（n = 6）和肺癌组（n = 6）的sEV磷酸化蛋白质组。相应地，分别富集了524个和333个磷酸肽，它们对应于439个和282个磷酸化蛋白质。总共揭示了对应于721个磷酸化蛋白质的857个独特sEV磷酸肽。在鉴定出的493个磷酸化位点中，癌症组中有37个上调（> 1.5），217个下调（< 0.66）。我们的数据共同表明，Ti-IMAC是一种用于全面分析sEV磷酸化蛋白质组的高效且可重复的技术。差异表达的sEV磷酸化蛋白质和磷酸化位点可能用于肺癌的无创检测。
