ChIP-DIP: a Multiplexed Method for Mapping Proteins to DNA Uncovers Combinatorics Controlling Gene Expression

Citation

Perez, Andrew Alexander (2024) ChIP-DIP: a Multiplexed Method for Mapping Proteins to DNA Uncovers Combinatorics Controlling Gene Expression. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/691f-y924. https://resolver.caltech.edu/CaltechTHESIS:05262024-003033193

Abstract

Gene regulation is governed by the complex interplay between thousands of regulatory proteins and chromatin states; understanding how these dynamics give rise to precisely controlled, cell type-specific gene expression has been a central goal of molecular biology. Yet, addressing this goal remains challenging because current methods for mapping proteins to DNA are labor-intensive, resource-demanding, and limited to studying a single or a small number of proteins at a time. To overcome this, we developed ChIP-DIP (ChIP Done In Parallel), a novel split-pool-based method that enables simultaneous, genome-wide mapping of hundreds of diverse regulatory proteins in a single experiment. We demonstrate that ChIP-DIP generates highly accurate maps equivalent to traditional approaches, with data quality unaffected by the number of distinct proteins or the composition of proteins measured within a single experiment. We show that, because of this multiplexed capability, ChIP-DIP enables generation of highly accurate maps using several orders of magnitude fewer cells per protein compared to traditional approaches (~30,000 fold), making it a powerful tool for studying a diverse array of proteins–DNA interactions with limited cellular input. In addition, we show that ChIP-DIP can generate high-quality maps for all classes of DNA-associated proteins, including histone modifications, chromatin regulators, transcription factors, and RNA polymerases. Using these data, we explore quantitative combinations of histone modifications and integrate these signatures with RNA polymerase activity, chromatin regulatory protein binding and transcription factor binding to define distinct classes of regulatory elements (e.g., distinct types of enhancer elements), their functional activity (e.g., transcriptional activity), and their regulatory potential (e.g., poised for activation upon stimulation or differentiation). Together, our results demonstratethat ChIP-DIP enables generation of consortium-level data within a single lab and highlight the importance of this approach for studying mechanisms of gene regulation in a context and cell type-specific manner. Lastly, ChIP-DIP provides a powerful platform to multiplex protein detection and provides a unique opportunity to incorporate other split-pool-based assays such as SPRITE and single-cell SPRITE to detect protein specific nuclear structures and multiplexed single-cell chromatin profiles, respectively. This work represents a transformational framework on how to study biology in a holistic manner.

Thesis Files