High-throughput synthesis and selection of DNA G-quadruplex optical probes

特定的富含鸟嘌呤的DNA序列可以折叠成称为G-四链体（G4）的四链结构，其被认为参与健康细胞中的一系列基本生物学功能，并与疾病有关。然而，它们在活生物样品中的检测仍然非常具有挑战性。最近，我们提出了一种基于检测小光学探针的荧光寿命来监测活细胞中G4形成的新方法[Nature Commun 2015，6，8178]。尽管这一成功的概念验证研究，我们的探针需要进一步的修改和优化，以实现高对比度信号结合G4 DNA。探针结构的多种可能变化以及DNA拓扑结构和浓度的变化意味着如果使用标准合成程序和荧光寿命分析来进行新探针的测试将是耗时且费力的。在这里，我们提出了一种策略，高通量的合成和分析大量的衍生物的噻唑橙子（TO），一个分子，显示出显着的承诺作为G4 DNA传感器在我们的概念研究的证明。该项目将开发一种新的方法，以全自动的方式进行高通量合成和结果的统计测试，使我们能够为G4选择理想的光学探针，这些探针在博士学位的时间范围内无法通过标准途径获得。关键词：DNA光学探针，高通量合成和分析，荧光寿命，分子转子，自动化，数据驱动优化

Specific guanine-rich sequences of DNA can fold into four-stranded structures known as G-quadruplexes (G4s), which are thought to be involved in a range of essential biological functions in healthy cells and are implicated in diseases. However, their detection in live biological samples remains very challenging. Recently, we have suggested a novel way of monitoring G4 formation in live cells, based on detection of the fluorescence lifetime of small optical probes [Nature Commun 2015, 6, 8178]. Despite this successful proof of concept study, our probes require further modification and optimization, in order to achieve high contrast signal upon binding to G4 DNA. Multiple possible variations in the probe structure, as well as the variations in DNA topology and concentration, mean that testing of new probes will be time consuming and laborious if performed using standard synthetic procedures and fluorescence lifetime analysis. Here we propose a strategy for high throughput synthesis and analysis of a large number of derivatives of thiazole orange (TO), a molecule which showed significant promise as a G4 DNA sensor in our proof of concept studies. This project will develop a novel methodology for high throughput synthesis and statistical testing of results in a fully automated way, allowing us to select ideal optical probes for G4 that are not accessible through standard routes within the timeframe of a PhD.Keywords: DNA optical probes, high throughput synthesis and analysis, fluorescence lifetime, molecular rotors, automation, data-driven optimisation