Single-molecule detection provides researchers with a unique method to probe kinetics of biomolecules in their native environment, without the need to synchronize the molecular states. However, current single-molecule measurements of DNA hybridization kinetics are mostly performed on a surface or inside an electrokinetic trap, which are not physiologically relevant conditions. Recently we demonstrate a time-resolved, 3D single-molecule tracking (3D-SMT) method that that can follow individual DNA molecules diffusing inside a mammalian cell and observe multiple annealing and melting events on the same molecules. By comparing the hybridization kinetics of the same DNA strand in vitro, we found the association constants can be 13- to 163-fold higher in the molecular crowding cellular environment.
In contrast to other confocal-feedback 3D single-particle tracking demonstrations, we tracked single DNA reporter strands inside a live cell and measured their annealing-melting kinetics. Although camera-based techniques combined with point-spread function engineering can achieve 3D tracking in live cells, they do not offer any lifetime monitoring capability that can be used to reveal the molecular binding kinetics. While two-color colocalization and 2D tracking can provide a full dimerization kinetics analysis of G proteincoupled receptor in live cells, the 2D-TIRF imaging method is not suitable to probe the binding kinetics of a biomolecule deep in cytoplasm. On the contrary, our 3D-SMT method uses multiple single-photon detectors or multiplexed pulsed laser illuminations to achieve spatial filtering, which not only allows for high-resolution 3D localization of single molecules in live cells, but enables simultaneous characterization of molecular binding state through a continuous lifetime measurement. The data acquired can be used to generate new models that can predict in-cellulo hybridization kinetics from sequence, study the molecular crowding inside cells and probe the cellular development and transition states. More details can be found in Chen et al., JACS, 2019.