I. Physikalisches Institut (IA) , RWTH Aachen , 52074 Aachen , Germany.
ICS-5: Molecular Biophysics , Forschungszentrum Jülich , 52425 Jülich , Germany.
ACS Sens. 2018 Aug 24;3(8):1462-1470. doi: 10.1021/acssensors.8b00143. Epub 2018 Jul 18.
Genetically encoded Förster resonance energy transfer (FRET)-based biosensors for the quantification of ligand molecules change the magnitude of FRET between two fluorescent proteins upon binding a target metabolite. When highly sensitive sensors are being designed, extensive sensor optimization is essential. However, it is often difficult to verify the ideas of modifications made to a sensor during the sensor optimization process because of the limited information content of ensemble FRET measurements. In contrast, single-molecule detection provides detailed information and higher accuracy. Here, we investigated a set of glucose and crowding sensors on the single-molecule level. We report the first comprehensive single-molecule study of FRET-based biosensors with reasonable counting statistics and identify characteristics in the single-molecule FRET histograms that constitute fingerprints of sensor performance. Hence, our single-molecule approach extends the toolbox of methods aiming to understand and optimize the design of FRET-based biosensors.
基于Förster 共振能量转移（FRET）的遗传编码生物传感器可定量检测配体分子，其通过与靶代谢物结合来改变两个荧光蛋白之间的 FRET 强度。在设计高灵敏度传感器时，需要对传感器进行广泛的优化。然而，由于整体 FRET 测量的信息含量有限，传感器优化过程中对传感器进行修改的想法往往难以验证。相比之下，单分子检测提供了更详细的信息和更高的准确性。在这里，我们在单分子水平上研究了一组葡萄糖和拥挤传感器。我们报告了第一个基于 FRET 的生物传感器的全面单分子研究，具有合理的计数统计数据，并确定了构成传感器性能指纹的单分子 FRET 直方图中的特征。因此，我们的单分子方法扩展了旨在理解和优化基于 FRET 的生物传感器设计的方法工具箱。
