Quantitative Single-Particle Tracking for Studying Protein Dynamics and Interactions in Live Cells

Abstract

Single-particle tracking (SPT) provides a powerful framework for quantifying protein dynamics in live cells by resolving heterogeneous and transient behaviours at the level of individual molecules. Achieving high-fidelity and reproducible SPT in intracellular environments requires maintaining a sparse emitter density, typically through partial labelling and low-rate photoactivation. While essential for accurate tracking, these requirements substantially reduce the number of detectable interaction events between binding partners, thereby limiting the reliable extraction of dynamic and interaction parameters for proteins expressed at physiological levels. This thesis establishes a quantitative experimental and analytical framework to improve the reliability and interpretability of live-cell SPT by explicitly controlling key experimental determinants, including labelling efficiency, photoactivation probability, and local emitter density. Rather than treating these factors as fixed experimental constraints, they are systematically measured, optimised, and incorporated into the design of SPT experiments and data interpretation. To enable rational optimisation of labelling conditions, a simple and efficient assay is developed to quantify the labelling efficiency of both photostable and photoactivatable organic dyes in live cells under experimentally relevant conditions. This approach defines practical strategies for optimising dual-colour labelling, a prerequisite for quantitative dual-colour SPT aimed at interrogating molecular interactions. In addition, in pulse-chase experiments, near-saturating pulse labelling enables clean separation of pre-existing and newly synthesised protein populations, allowing the single-molecule dynamics of distinct subpopulations to be analysed independently. Building on this quantitative control of labelling, the problem of limited statistical yield of interaction measurements in dual-colour SPT is addressed. A probabilistic framework is introduced to identify the dominant factors constraining the detection of co-diffusing particle pairs. Guided by this analysis, a localised pulsed photoactivation strategy combined with sequential excitation is developed to increase photoactivation probability and temporal overlap between trajectories while preserving sparse tracking conditions. Application of this approach enhances the detection of interaction-related trajectories in live cells, while complementary simulations reveal the practical constraints and identify routes for further improvement. Together, this work establishes a robust quantitative framework for live-cell SPT based on explicit control of labelling and photoactivation parameters, and provides general strategies for extracting reliable protein dynamics and interaction information from single-particle measurements in live cells.