Recent advances in super-resolution imaging have dramatically transformed how we investigate living systems at the molecular scale. Unlike traditional in vitro methods, we can now observe biochemical processes inside intact cells, preserving the natural concentrations of molecules and their true spatial organization. In our lab, by combining single-molecule tracking microscopy with data simulation and sophisticated data analysis, we attempt to reconstruct the full binding cycles of individual proteins or RNAs and gain essential insights into their reaction kinetics. In this proof-of-principle study, we present a method for detecting and quantifying ribosome interactions at the inner membrane of E. coli bacteria during co-translational membrane-protein insertion. We employed two-color, three-dimensional single-molecule tracking using custom-made 3D-printed phase masks to generate a double-helix point spread function across two emission channels. We used geometrical and diffusional patterns of the trajectories to distinguish ribosomes moving in the cytoplasm from those associated with the membrane. To validate and refine our analysis approach, we also used simulated microscopy. Notably, the suggested approach does not rely on direct colocalization of the tracked molecule with membrane reference markers. The measured diffusional and geometrical properties of the trajectory segments can be quantified and fitted using a Hidden Markov modeling approach, allowing extraction of spatial and temporal information about the underlying biological states.
Volkov et al. (2026) studied this question.