Androgen receptor complexes probe DNA for recognition sequences by short random interactions

Abstract

BSTRACTOwing to the tremendous progress in microscopic imaging of fluorescently labeled proteins in living cells, the insight into the highly dynamic behavior of transcription factors has rapidly increased over the past decade. However, a consistent quantitative scheme of their action is still lacking. Using the androgen receptor (AR) as a model system, we combined three different fluorescence microscopy assays: single-molecule microscopy, photobleaching and correlation spectroscopy, to provide a quantitative model of the action of this transcription factor. This approach enabled us to distinguish two types of AR-DNA binding: very brief interactions, in the order of a few hundred milliseconds, and hormone-induced longer-lasting interactions, with a characteristic binding time of several seconds. In addition, freely mobile ARs were slowed down in the presence of hormone, suggesting the formation of large AR-co-regulator complexes in the nucleoplasm upon hormone activation. Our data suggest a model in which mobile hormone-induced complexes of transcription factors and co-regulators probe DNA by briefly binding at random sites, only forming relatively stable transcription initiation complexes when bound to specific recognition sequences.

Repetitive switching between DNA binding modes enables target finding by the glucocorticoid receptor

“…These transient immobilizations were found to be dependent on ligand activation and DNA binding of the GR, and are associated with transcriptional activity (Schaaf and Cidlowski, 2003;Stavreva et al, 2004;Schaaf et al, 2005;Morisaki et al, 2014). More-recent studies also revealed immobilizations at the sub-seconds scale (Groeneweg et al, 2014;Morisaki et al, 2014;Van Royen et al, 2014). Similar dynamic behavior has been uncovered for other steroid receptors (Stenoien et al, 2001;Farla et al, 2004Farla et al, , 2005Marcelli et al, 2006;van Royen et al, 2007), as well as other transcription factors (Dundr et al, 2002;Gorski et al, 2008).…”

“…Similar dynamic behavior has been uncovered for other steroid receptors (Stenoien et al, 2001;Farla et al, 2004Farla et al, , 2005Marcelli et al, 2006;van Royen et al, 2007), as well as other transcription factors (Dundr et al, 2002;Gorski et al, 2008). In addition to these immobilizations, diffusive behavior through the nucleus has been observed for the GR (Gebhardt et al, 2013;Groeneweg et al, 2014;Morisaki et al, 2014;Paakinaho et al, 2017), and other bacterial and mammalian transcription factors, such as the lac repressor (Elf et al, 2007), STAT1 (Speil et al, 2011), p53 (Mazza et al, 2012;Morisaki et al, 2014), and the androgen receptor (AR) (Van Royen et al, 2014). For GR, and the transcription factors STAT1 and p53 (TP53), two diffusion states with distinct diffusion coefficients were found (Speil et al, 2011;Mazza et al, 2012;Gebhardt et al, 2013).…”

The nuclear receptor superfamily: A structural perspective

“…Recent technological advances in live‐cell microscopy and fluorescent labeling are now being leveraged to study NRs as TFs in real‐time . By combining fluorescence correlation spectroscopy, fluorescence recovery after photobleaching, and single‐molecule microscopes, two unique binding events were found in the AR‐DNA recognition process . The first binding event spans only hundreds of μs and is characterized by brief, stochastic DNA interaction, whereas the second event spans several seconds indicating longer, sequence‐specific DNA association.…”

The Effect of F877L and T878A Mutations on Androgen Receptor Response to Enzalutamide

“…In short, a large set of computer-simulated FRAP curves with a 3-population model was generated, containing a diffusing fraction (ranging 1 to 3 m 2 /s) and two bound (immobile) fractions (ranging from 0.65 to 0.8 s and 3 to 15 s, respectively). Ranges in the simulation are based on quantitative FRAP analysis of AR curves in previous work (29). The top 10 simulated curves that are fitting best to the experimental curve (by ordinary least squares) were averaged and provide the properties of the experimental data.…”