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| Funder | NATIONAL CANCER INSTITUTE |
|---|---|
| Recipient Organization | Massachusetts Institute of Technology |
| Country | United States |
| Start Date | Sep 01, 2024 |
| End Date | Aug 31, 2029 |
| Duration | 1,825 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10917488 |
Project Summary Proper gene expression regulation is pivotal for cellular function, and its dysregulation contributes to disease. Transcription factors (TFs) initiate gene expression by identifying binding sites in enhancers and promoters and recruiting the transcriptional machinery. However, the nucleus's crowded nature and the
abundance of non-specific sites make it extremely challenging for TFs to efficiently search for and binding correct DNA binding sites. This project addresses the fundamental question: How do TFs efficiently locate specific sites amidst numerous non-specific ones inside a crowded nucleus? Innovatively, this study employs a new advanced microscopy technique that overcomes the low
spatiotemporal resolution associated with camera-based single-molecule tracking. This approach enables precise tracking of TFs in live human and mouse cells with unprecedented spatial (~2-4 nm) and temporal (one hundred microseconds) precision. This transformative approach represents a substantial advancement over
traditional methods, facilitating the investigation of TF search mechanisms. By comprehensively tracing TFs' 3D diffusion, DNA interactions, and target site discrimination, we will resolve the TF target search mechanism. First, we will optimize and validate the proposed tracking method and develop novel computational
methods for handling and analyzing these new types of tracking data. Second, we will apply this technology to understand how TFs involved in pluripotency and genome structure find their target sites and elucidate how individual protein domains affect the target search mechanisms. Third, we will apply this technology to uncover
the oncogenic potential of fusion TFs in several cancers. Fourth, we will leverage these studies to understand how “search domains” in TFs regulate the target search mechanism and efficiency towards the rational design of synthetic TFs with tunable search properties. Taken together, this proposal will reveal how TFs find their
target sites with applications to synthetic biology and cancer biology.
Massachusetts Institute of Technology
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