Single-particle tracking for direct measurements of Trigger Factor ribosome binding in live cells

Abstract: Trigger Factor (TF) is a prokaryotic chaperone protein that exerts its major chaperone activity while associated with translating ribosomes, assisting de novo folding of the emerging nascent chain. Although much is known about the kinetics behind TF-ribosome binding, most results are based on in vitro experiments which fail to mimic the cellular environment. Single-particle approaches have gained increasing power for studying binding kinetics of biomolecules in living cells. One such method is single-particle tracking by super-resolution fluorescence microscopy, where the position of a fluorescently labelled particle is recorded over time, giving information about the movement of the particle inside the cell. Changes in diffusion behaviour is then used as an indicator of changes in biological activities. In this work, a diffusion model that qualitatively and quantitatively describes TF’s binding to ribosomes is presented. The model was obtained by single-particle tracking of TF labelled with HaloTag. Particle movements were analysed with a Hidden Markov Model-based algorithm that fit the trajectories to a defined set of different diffusion states, where fast diffusion could be related to free TF and slow diffusion to a ribosome-bound state. Moreover, the model could distinguish between two types of ribosome interactions: TF’s stable binding to ribosomes and a faster sampling behaviour. The average time spent stably bound to ribosomes is 670 ms and these interactions account for 53% of TF’s activity. TF is one of many processing proteins that interact with the emerging peptide chain during translation. By using the same approach on more of these factors, the interplay between them and the growing nascent chain can be characterized, giving an increased understanding of the highly complex translation machinery.