ABC4M : Approximate Bayesian Computation-driven MultiModal Microscopy to explore the nuclear Mobility of transcription factors

[2020-2024]

Understanding how transcription factors (TFs) explore the nucleus to find their specific binding sites is a major bottleneck in our comprehension of gene expression. Current experimental approaches are hampered by their limited spatiotemporal scale and the complexity of nuclear organization. To overcome this challenge, we propose to combine computer simulations with multiple simultaneous microscopy methods of molecular mobility measurement. We will develop a multimodal and multiscale experimental approach based on simultaneous fluorescence correlation spectroscopy (FCS) and single-molecule localization microscopy (SMLM) to map the spatiotemporal dynamics of the transcription factor P-TEFb. We will perform measurements of P-TEFb motion in the nucleus of live cells at disjoint spatiotemporal scales (FCS and SMLM) and interpolate those observations using an Approximate Bayesian computation (ABC) approach with Monte-Carlo simulations of P-TEFb diffusion as the statistical model used to fit the data. The parameters inferred from ABC will provide us with a multiscale quantification of the experimental data and help us solve potential mismatches between different microscopy modes.