SILAC-based quantitative MS approach for real-time recording protein-mediated cell-cell interactions.
SILAC-based quantitative MS approach for real-time recording protein-mediated cell-cell interactions.
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基于 SILAC 的定量 MS 方法用于实时记录蛋白质介导的细胞间相互作用
DOI:
10.1038/s41598-018-26262-2
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发表时间:
2018-05-31
影响因子:
4.6
通讯作者:
Liang S
中科院分区:
文献类型:
--
作者:
Wang X;He Y;Ye Y;Zhao X;Deng S;He G;Zhu H;Xu N;Liang S
In tumor microenvironment, interactions among multiple cell types are critical for cancer progression. To understand the molecular mechanisms of these complex interplays, the secreted protein analysis between malignant cancer cells and the surrounding nonmalignant stroma is a good viewpoint to investigate cell-cell interactions. Here, we developed two stable isotope labeling of amino acids in cell culture (SILAC)-based mass spectrometry (MS)/MS approaches termed spike-in SILAC and triple-SILAC to quantify changes of protein secretion level in a cell co-cultured system. Within the co-culture system of CT26 and Ana-1 cells, the spike-in SILAC and triple-SILAC MS approaches are sensitive to quantitatively measure protein secretion changes. Three representative quantified proteins (Galectin-1, Cathepsin L1 and Thrombospondin-1) by two SILAC-based MS methods were further validated by Western blotting, and the coming result matched well with SILACs’. We further applied these two SILACs to human cell lines, NCM460 and HT29 co-culture system, for evaluating the feasibility, which confirmed the spike-in and triple SILAC were capable of monitoring the changed secreted proteins of human cell lines. Considering these two strategies in time consuming, sample complexity and proteome coverage, the triple-SILAC way shows more efficiency and economy for real-time recording secreted protein levels in tumor microenvironment.
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影响因子:
3.7
作者:
Brindle NR;Joyce JA;Rostker F;Lawlor ER;Swigart-Brown L;Evan G;Hanahan D;Shchors K
通讯作者:
Shchors K
影响因子:
4.4
作者:
Hilger, Maximiliane;Mann, Matthias
通讯作者:
Mann, Matthias
影响因子:
14.8
作者:
Ong, Shao-En;Mann, Matthias
通讯作者:
Mann, Matthias
影响因子:
14.8
作者:
Geiger, Tamar;Wisniewski, Jacek R.;Mann, Matthias
通讯作者:
Mann, Matthias
影响因子:
--
作者:
Chen B;Zeng X;He Y;Wang X;Liang Z;Liu J;Zhang P;Zhu H;Xu N;Liang S
通讯作者:
Liang S