Center for Network Systems Biology, Boston University, Boston, MA, USA.
Department of Biochemistry, Boston University School of Medicine, Boston, MA, USA.
Nat Commun. 2022 Jul 13;13(1):4043. doi: 10.1038/s41467-022-31809-z.
Co-fractionation/mass spectrometry (CF/MS) enables the mapping of endogenous macromolecular networks on a proteome scale, but current methods are experimentally laborious, resource intensive and afford lesser quantitative accuracy. Here, we present a technically efficient, cost-effective and reproducible multiplex CF/MS (mCF/MS) platform for measuring and comparing, simultaneously, multi-protein assemblies across different experimental samples at a rate that is up to an order of magnitude faster than previous approaches. We apply mCF/MS to map the protein interaction landscape of non-transformed mammary epithelia versus breast cancer cells in parallel, revealing large-scale differences in protein-protein interactions and the relative abundance of associated macromolecules connected with cancer-related pathways and altered cellular processes. The integration of multiplexing capability within an optimized workflow renders mCF/MS as a powerful tool for systematically exploring physical interaction networks in a comparative manner.
共分离/质谱(CF/MS)能够在蛋白质组范围内绘制内源性大分子网络图谱,但目前的方法在实验上繁琐、资源密集,并且定量准确性较差。在这里,我们提出了一种技术上高效、经济高效且可重复的多重 CF/MS(mCF/MS)平台,用于以比以前的方法快一个数量级的速度测量和比较不同实验样本中多蛋白组装,同时进行测量和比较。我们应用 mCF/MS 来平行绘制非转化乳腺上皮细胞与乳腺癌细胞的蛋白质相互作用图谱,揭示了与癌症相关途径和改变的细胞过程相关的蛋白质-蛋白质相互作用和相关大分子的相对丰度的大规模差异。在优化的工作流程中集成多重化能力使得 mCF/MS 成为一种强大的工具,可用于系统地以比较的方式探索物理相互作用网络。
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