Torreno-Pina, J. A. | bioRxiv Science

bioRxiv2022

Particle flow modulates growth dynamics and nanoscale-arrested growth of transcription factor condensates in living cells

Liquid-liquid phase separation (LLPS) is emerging as key physical principle for biological organization inside living cells, forming condensates that play important roles in the regulation of multiple functions. Inside living nuclei, transcription factor (TF) condensates regulate transcriptional initiation and amplify transcriptional output of expressed genes. Yet, the biophysical parameters controlling TF condensation are still poorly understood. Here we applied a battery of single molecule imaging tools, theory and simulations to investigate the physical properties of TF condensates of the Progesterone Receptor (PR) in vivo. Analysis of individual PR trajectories at different ligand concentrations showed marked signatures of a ligand-tunable and regulated LLPS process. Using a machine learning architecture, we uncovered that diffusion within condensates follows fractional Brownian motion, reflecting viscoelastic interactions between PR and chromatin within condensates. High density single molecule localization maps further revealed that condensate growth dynamics is dominated by Brownian motion coalescence (BMC) at shorter times, but deviate at longer timescales reaching a growth plateau with nanoscale condensate sizes. To understand our observations we developed an extension of the BMC model by including stochastic unbinding of particles within condensates. The model reproduced the BMC behavior together with finite condensate sizes a steady-state, fully recapitulating our experimental data. Our results are thus consistent with droplet growth dynamics being regulated by the escaping probability of TFs molecules from condensates. The interplay between condensation assembly and molecular escaping maintains an optimum physical condensate size. Such phenomena must have implications for the biophysical regulation of other TF condensates and could also operate in multiple biological scenarios.

biophysics↗

bioRxiv2020

Phase separation of tunable biomolecular condensates predicted by an interacting particle model

Phase separation is emerging as key principle in the spatiotemporal organization of living cells. Given its relevance in the regulation of numerous biological functions, including gene transcription and chromatin architecture, modeling biomolecular condensation is gaining interest. Yet, most models developed so far rely on specific descriptions and/or experimentally inaccessible properties. Here we propose a theoretical model, where phase separation is explained by means of interaction probabilities between particles. With minimum model requirements, particle condensates emerge above a critical interaction probability. We tested the model predictions with single molecule experiments of tunable transcription factor condensates in the nucleus of living cells. Phase separation, condensate sizes, diffusion behavior, and mobility parameters, quantified by data analysis and machine learning, are fully recapitulated by our model. Our combined theoretical and experimental approach provides a general framework to investigate the biophysical parameters controlling phase separation in living cells and in other soft matter-based interacting systems.

biophysics↗