Chromatin Structure and Gene Expression

Division Of Basic Sciences - Nci

Investigators

Linked publications, trials & patents

Abstract

1. The cohesin complex is central to chromatin looping, but mechanisms by which these long-range chromatin interactions are formed and persist remain unclear. We discovered that interactions between a transcription factor (GR) and a multimeric complex, including the cohesin loader NIPBL and cohesin, regulate enhancer dependent gene activity (1). We demonstrated that the glucocorticoid receptor stabilizes the cohesin complex at GR enhancers, promoting loop extrusion and long-range gene regulation. We showed that direct interactions between GR and the cohesion loader cohesin-loader complex (NIPBL/MAU2) are responsible localization at enhancers (2). We identified two clusters of LxxLL motifs within the NIPBL sequence that regulate NIPBL dynamics, interactome, and NIPBL-dependent transcriptional programs. One of these clusters interacts with MAU2 and is necessary for the maintenance of the NIPBL-MAU2 heterodimer. The second cluster binds specifically to the ligand-binding domains of steroid receptors. For the glucocorticoid receptor (GR), we examined in detail its interaction surfaces with NIPBL and MAU2. Using AlphaFold2 and molecular docking algorithms, we uncovered a GR-NIPBL-MAU2 ternary complex and described its importance in GR-dependent gene regulation. Finally, we showed that multiple transcription factors interact with NIPBL-MAU2, likely using interfaces other than those characterized for GR. Follow up experiments suggest that the androgen receptor (AR) also interacts with a similar complex for long range gene regulation. However, further studies show that AR interacts with NIPBL to modulate eRNA levels enhancers, providing an alternate mechanism for modulating the enhancer-promoter long range interactions. Further studies are underway to probe the mechanism by which steroid receptors interact with the cohesin complex to regulate promoter activity. 2. We have adapted recent advances in live cell imaging technology to study the function of T factors in single cells in real time. Single Molecule Tracking (SMT) allows the study of TF dynamics in the nucleus, giving important information regarding the search and binding behavior of these proteins with chromatin in vivo (3). However, how TFs navigate within the intricate nuclear environment to find and bind their response elements on chromatin, recruit the transcription machinery, and ultimately regulate gene expression remains largely unknown. By the implementation of proper photobleaching kinetics, theory-based models and an unbiased model selection approach, we revealed a new model of TF dynamics where TFs binding times are power-law distributed (4). Previous models suggested that TFs bound either non-specifically or specifically, with each mode of binding having their own distribution that was largely discrete from the other. The power-law model, on the other hand, indicates that TFs bind not discretely in these two modes, but with a continuous distribution from fast to very slow kinetics. Using single-molecule tracking coupled with machine learning, we showed that histone H2B and multiple chromatin-bound transcriptional regulators display two distinct low-mobility states (5). Ligand activation results in a marked increase in the propensity of steroid receptors to bind in the lowest-mobility state. Mutational analysis revealed that interactions with chromatin in the lowest-mobility state require an intact DNA binding domain and oligomerization domains. These states are not spatially separated as previously believed, but individual H2B and bound-TF molecules can dynamically switch between them on time scales of seconds. Single bound-TF molecules with different mobilities exhibit different dwell time distributions, suggesting that the mobility of TFs is intimately coupled with their binding dynamics. Our findings identify two unique and distinct low-mobility states that appear to represent common pathways for transcription activation in mammalian cells (6,7). These results are aligned with the theoretical underpinnings of TF motions in the crowded nuclear space and exploration of a complex DNA space. Our approaches enable the coupling of population based assays with real time studies to address many unsolved questions about SRs and chromatin dynamics in normal mammalian cells, in breast cancer cells, and prostate cancer cells. 3. Cancer discovery has been focused primarily on the identification of critical mutated pathways, and the development of drugs to target the gene products of these so called "driver" mutants. Critical driver mutants are not commonly identified, and therapies targeting these pathways are frequently followed by relapse. In fact, the regulatory networks that control global gene expression are massively transformed during cancer initiation and progression. The failure to normalize gene regulation and return cells to normal growth control is likely a major factor in treatment failure. To treat cancer effectively, a key issue is to identify the regulatory elements that create this abnormal expression pattern, rather than simply describing the gene expression pattern in tumor cells. Our primary goal is to analyze the status of enhancer networks in cancer cells, and identify enhancer "signatures" characteristic of progression and metastasis. Enhancer signatures predictive of cancer progression can then inform threat level for a specific tumor, appropriate patient therapy, and treatment progress for favorable response in enhancer status (8). 1. Rinaldi, L., et al., The glucocorticoid receptor associates with the cohesin loader NIPBL to promote long-range gene regulation. Sci Adv, 2022. 8(13): p. eabj8360. 2. Fettweis, G., et al., Transcription factors form a ternary complex with NIPBL/MAU2 to localize cohesin at enhancers. Nucleic Acids Res, 2025. 53(9). 3. Garcia, D.A., et al., An intrinsically disordered region-mediated confinement state contributes to the dynamics and function of transcription factors. Mol Cell, 2021. 81(7): p. 1484-1498.e6. 4. Garcia, D.A., et al., Power-law behavior of transcription factor dynamics at the single-molecule level implies a continuum affinity model. Nucleic Acids Res., 2021. 49(12): p. 6605-6620. 5. Wagh, K., et al., Dynamic switching of transcriptional regulators between two distinct low-mobility chromatin states. Sci Adv, 2023. 9(24): p. eade1122. 6. Wagh, K., D.A. Stavreva, and G.L. Hager, Transcription dynamics and genome organization in the mammalian nucleus: Recent advances. Mol Cell, 2025. 85(2): p. 208-224. 7. Wagh, K., D.A. Stavreva, A. Upadhyaya, and G.L. Hager, Transcription Factor Dynamics: One Molecule at a Time. Annu Rev Cell Dev Biol, 2023. 39: p. 277-305. 8. Shukla, V., et al., Genome-wide Analysis Identifies Nuclear Factor 1C as a Novel Transcription Factor and Potential Therapeutic Target in Small Cell Lung Cancer. J Thorac Oncol, 2024.