Technology for ten-minute resolution protein interaction mapping at proteome scale

项目摘要 基因通过大分子相互作用的网络来介导它们的作用。大规模的研究绘制了 人类和几种模式生物的蛋白质相互作用。然而，即使对于S。酿酒厂，最 尽管深入研究了真核生物模型，但对蛋白质相互作用网络的了解仍然不完整， “静态”，在这个意义上，每个全球互动映射研究基本上使用了相同的增长 环境和遗传背景。此外，尽管有许多已知的信号相互作用的例子， 在环境压力后迅速出现和消失，大规模的相互作用图代表了时间- 一个细胞多代交互作用的平均值。我们之前扩展了酵母双杂交（Y2 H） 使用“条形码融合遗传学”（BFG）策略的相互作用测定，其使用细胞内重组形成 识别诱饵/猎物蛋白组合的嵌合条形码。这种“BFG-Y2 H”方法使得能够多路复用 数以百万计的相互作用测定，具有内部生物复制，所有这些都在一个单一的实验中进行， 已经被用于蛋白质组规模映射酵母相互作用下的四个生长环境。这里 我们提出了进一步的扩展，其中传统上报告相互作用状态的启动子用于 转录嵌合诱饵/猎物条形码基因座。因此，对这些“相互作用标签”进行测序可以提供 启动子输出的定量测量。重要的是，转录产物的快速动态和 降解有可能使相互作用动力学的测量具有约10分钟的时间分辨率， 在蛋白质组的水平上，在活细胞中。

Project Summary Genes mediate their effects through networks of macromolecular interactions. Large-scale studies have mapped protein interactions for humans and several model organisms. However, even for S. cerevisiae, the most intensively-studied eukaryotic model, knowledge of the protein interaction network remains both incomplete and ‘static’, in the sense that each global interaction mapping study has used essentially the same growth environment and genetic background. Moreover, despite the many known examples of signalling interactions that appear and fade rapidly after an environmental stress, large-scale interaction maps represent the time- average of interaction over many generations of a cell. We previously extended the yeast two-hybrid (Y2H) interaction assay with a ‘barcode fusion genetics’ (BFG) strategy, which uses intracellular recombination to form chimeric barcodes that identify bait/prey protein combinations. This ‘BFG-Y2H’ method enabled multiplexing of millions of interaction assays, with internal biological replication, all within a single en masse experiment, and has already been used for proteome-scale mapping of yeast interactions under four growth environments. Here we propose a further extension, in which the promoter that traditionally reports on interaction status is used to transcribe the chimeric bait/prey barcode locus. Sequencing these ‘interaction tags’ can thus provide a quantitative measure of promoter output. Importantly, the rapid dynamics of transcript production and degradation have the potential to enable measurement of interaction dynamics with ~10-minute time resolution, at proteome scale, in living cells.