Power-law behavior of transcription factor dynamics at the single-molecule level implies a continuum affinity model

Single-molecule tracking (SMT) allows the study of transcription factor (TF) dynamics in the nucleus, giving important information regarding the diffusion and binding behavior of these proteins in the nuclear environment. Dwell time distributions obtained by SMT for most TFs appear to follow bi-exponential behavior. This has been ascribed to two discrete populations of TFs-one non-specifically bound to chromatin and another specifically bound to target sites, as implied by decades of biochemical studies. However, emerging studies suggest alternate models for dwell-time distributions, indicating the existence of more than two populations of TFs (multiexponential distribution), or even the absence of discrete states altogether (power-law distribution). Here, we present an analytical pipeline to evaluate which model best explains SMT data. We find that a broad spectrum of TFs (including glucocorticoid receptor, oestrogen receptor, FOXA1, CTCF) follow a power-law distribution of dwell-times, blurring the temporal line between non-specific and specific binding, suggesting that productive binding may involve longer binding events than previously believed. From these observations, we propose a continuum of affinities model to explain TF dynamics, that is consistent with complex interactions of TFs with multiple nuclear domains as well as binding and searching on the chromatin template.

Automated summary

Studies show that the dwell time distributions of most transcription factors exhibit bi-exponential behavior, but recent research indicates the presence of more TF populations, or even potentially the absence of discrete states. Certain TFs like the glucocorticoid receptor and estrogen receptor show power-law distributions of dwell times, suggesting a blurred line between non-specific and specific binding, supporting the proposal of a continuum of affinities model for TF dynamics.