# Single-cell and single-molecule profiling of protein-DNA interactions by MACHA

> **NIH NIH R21** · UNIVERSITY OF CHICAGO · 2023 · $243,525

## Abstract

Summary
Protein-DNA interactions are fundamental to DNA-dependent processes such as transcription, replication,
DNA repair, and chromosome organization in all domains of cellular life. Enrichment-based methods to detect
protein-DNA interactions are widely used to obtain genome-wide high-resolution maps of transcription factor
binding and chromatin states. However, these methods have severe shortcomings when applied to single cells.
In single-cell applications, enrichment-based methods cannot distinguish between unbound DNA and
unsuccessful recovery of protein-bound DNA since both lead to absent DNA fragments and the sparse data
makes it difficult or impossible to obtain cell-type-resolved binding profiles of transcription factors starting from
complex tissues. This limitation significantly reduces the information content of single-cell data. MACHA will
detect protein-DNA interactions in cells as cytosine methylation catalyzed by an exogenous GpC
methyltransferase (GpCMTase) that is directed to protein-bound DNA by a primary antibody recognizing the
protein of interest.

## Key facts

- **NIH application ID:** 10705853
- **Project number:** 5R21HG012423-02
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Kohta Ikegami
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $243,525
- **Award type:** 5
- **Project period:** 2022-09-16 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10705853

## Citation

> US National Institutes of Health, RePORTER application 10705853, Single-cell and single-molecule profiling of protein-DNA interactions by MACHA (5R21HG012423-02). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10705853. Licensed CC0.

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