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开发用于激酶和 GTP 酶的 FRET 生物传感器的优化骨架。

Development of an optimized backbone of FRET biosensors for kinases and GTPases.

机构信息

Laboratory of Bioimaging and Cell Signaling, Graduate School of Biostudies, Kyoto University, Kyoto 606-8501, Japan.

出版信息

Mol Biol Cell. 2011 Dec;22(23):4647-56. doi: 10.1091/mbc.E11-01-0072. Epub 2011 Oct 5.

Abstract

Biosensors based on the principle of Förster (or fluorescence) resonance energy transfer (FRET) have shed new light on the spatiotemporal dynamics of signaling molecules. Among them, intramolecular FRET biosensors have been increasingly used due to their high sensitivity and user-friendliness. Time-consuming optimizations by trial and error, however, obstructed the development of intramolecular FRET biosensors. Here we report an optimized backbone for rapid development of highly sensitive intramolecular FRET biosensors. The key concept is to exclude the "orientation-dependent" FRET and to render the biosensors completely "distance-dependent" with a long, flexible linker. We optimized a pair of fluorescent proteins for distance-dependent biosensors, and then developed a long, flexible linker ranging from 116 to 244 amino acids in length, which reduced the basal FRET signal and thereby increased the gain of the FRET biosensors. Computational simulations provided insight into the mechanisms by which this optimized system was the rational strategy for intramolecular FRET biosensors. With this backbone system, we improved previously reported FRET biosensors of PKA, ERK, JNK, EGFR/Abl, Ras, and Rac1. Furthermore, this backbone enabled us to develop novel FRET biosensors for several kinases of RSK, S6K, Akt, and PKC and to perform quantitative evaluation of kinase inhibitors in living cells.

摘要

基于Förster(或荧光)共振能量转移(FRET)原理的生物传感器为信号分子的时空动态提供了新的视角。其中,由于具有高灵敏度和易用性,分子内 FRET 生物传感器得到了越来越多的应用。然而,通过反复试验进行耗时的优化阻碍了分子内 FRET 生物传感器的发展。在这里,我们报告了一种优化的骨架,用于快速开发高灵敏度的分子内 FRET 生物传感器。其关键概念是排除“取向依赖”的 FRET,并通过长而灵活的接头使生物传感器完全“距离依赖”。我们为距离依赖型生物传感器优化了一对荧光蛋白,然后开发了一条长而灵活的接头,长度从 116 到 244 个氨基酸不等,从而降低了基础 FRET 信号,从而提高了 FRET 生物传感器的增益。计算模拟深入了解了该优化系统的机制,该系统是分子内 FRET 生物传感器的合理策略。通过这个骨架系统,我们改进了先前报道的 PKA、ERK、JNK、EGFR/Abl、Ras 和 Rac1 的 FRET 生物传感器。此外,这个骨架还使我们能够开发用于 RSK、S6K、Akt 和 PKC 的几种激酶的新型 FRET 生物传感器,并在活细胞中对激酶抑制剂进行定量评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a4/3226481/52e71e84d5e0/4647fig1.jpg

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