# Resolving transcription factor target search mechanisms

> **NIH NIH R01** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2024 · $588,426

## Abstract

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.

## Key facts

- **NIH application ID:** 10917488
- **Project number:** 1R01CA300848-01
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Anders Sejr Hansen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $588,426
- **Award type:** 1
- **Project period:** 2024-09-01 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10917488

## Citation

> US National Institutes of Health, RePORTER application 10917488, Resolving transcription factor target search mechanisms (1R01CA300848-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10917488. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*