Protein-protein interactions constitute the molecular foundations of virtually all biological processes. Co-immunoprecipitation (CoIP) experiments are probably the most widely used method to probe both heterotypic and homotypic protein-protein interactions. Recent advances in super-resolution microscopy have revealed that several nuclear proteins such as transcription factors are spatially distributed into local high-concentration clusters in mammalian cells, suggesting that many nuclear proteins self-interact. These observations have further underscored the need for orthogonal biochemical approaches for testing if self-association occurs, and if so, what the mechanisms are. Here, we describe a CoIP protocol specifically optimized to test self-association of endogenously tagged nuclear proteins (self-CoIP), and to evaluate the role of nucleic acids in such self-interaction. This protocol has proven reliable and robust in our hands, and it can be used to test both homotypic and heterotypic (CoIP) protein-protein interactions.

Folding of mammalian genomes into spatial domains is critical for gene regulation. The insulator protein CTCF and cohesin control domain location by folding domains into loop structures, which are widely thought to be stable. Combining genomic and biochemical approaches we show that CTCF and cohesin co-occupy the same sites and physically interact as a biochemically stable complex. However, using single-molecule imaging we find that CTCF binds chromatin much more dynamically than cohesin (~1-2 min vs. ~22 min residence time). Moreover, after unbinding, CTCF quickly rebinds another cognate site unlike cohesin for which the search process is long (~1 min vs. ~33 min). Thus, CTCF and cohesin form a rapidly exchanging 'dynamic complex' rather than a typical stable complex. Since CTCF and cohesin are required for loop domain formation, our results suggest that chromatin loops are dynamic and frequently break and reform throughout the cell cycle.

Mammalian genomes are folded into topologically associating domains (TADs), consisting of chromatin loops anchored by CTCF and cohesin. Some loops are cell-type specific. Here we asked whether CTCF loops are established by a universal or locus-specific mechanism. Investigating the molecular determinants of CTCF clustering, we found that CTCF self-association in vitro is RNase sensitive and that an internal RNA-binding region (RBR_i) mediates CTCF clustering and RNA interaction in vivo. Strikingly, deleting the RBR_i impairs about half of all chromatin loops in mESCs and causes deregulation of gene expression. Disrupted loop formation correlates with diminished clustering and chromatin binding of RBR_i mutant CTCF, which in turn results in a failure to halt cohesin-mediated extrusion. Thus, CTCF loops fall into at least two classes: RBR_i-independent and RBR_i-dependent loops. We speculate that evidence for RBR_i-dependent loops may provide a molecular mechanism for establishing cell-specific CTCF loops, potentially regulated by RNA(s) or other RBR_i-interacting partners.

Achieving a quantitative and predictive understanding of 3D genome architecture remains a major challenge, as it requires quantitative measurements of the key proteins involved. Here, we report the quantification of CTCF and cohesin, two causal regulators of topologically associating domains (TADs) in mammalian cells. Extending our previous imaging studies (Hansen et al., 2017), we estimate bounds on the density of putatively DNA loop-extruding cohesin complexes and CTCF binding site occupancy. Furthermore, co-immunoprecipitation studies of an endogenously tagged subunit (Rad21) suggest the presence of cohesin dimers and/or oligomers. Finally, based on our cell lines with accurately measured protein abundances, we report a method to conveniently determine the number of molecules of any Halo-tagged protein in the cell. We anticipate that our results and the established tool for measuring cellular protein abundances will advance a more quantitative understanding of 3D genome organization, and facilitate protein quantification, key to comprehend diverse biological processes.