Highly parallelized characterization of histone reader dysfunction
Full Description
PROJECT SUMMARY
Proper regulation of chromatin is essential for copying, maintaining, and transcribing DNA and errors
in this machinery are frequently associated with a variety of diseases. A critical part of chromatin
regulation are interactions between protein complexes and nucleosomes containing core histone
subunits. Histones can be post-translationally modified and patterns of modifications, including
acetylation, serve as a code to recruit and localize chromatin regulators through “reader” domains.
Histone reader function and binding selectivity are incompletely understood and, with few exceptions,
reader mutations observed in disease are not well characterized, despite being desirable therapeutic
targets. To address these gaps in knowledge, we propose the development of an
ultra-high-throughput platform called phage- and robotics-assisted near continuous selection
(PRANCS), for structure-function analysis of all known readers, their mutations, and the histone
modification interactome. We will use PRANCS to systematically characterize both the natural
specificity and impact of mutations on reader domain interactions with acetyl-modified histone
subunits. First, we will build improved robotics methods to parallelize PRANCS and optimize the scale
of an individual assay (Aim 1). We will develop and apply a two-hybrid assay to study reader domain
recognition of histone subunits modified using non-canonical amino acids (Aim 2). Finally, we will
build and optimize the use of next-gen sequencing methods for enhanced quantitative readouts in
PRANCS, applying this method to systematically assess the impact of thousands of reader mutations
found in disease on histone modification binding (Aim 3). Results from this proposal will elucidate
entirely new insights into the fundamentals of chromatin recognition and the functional impact of
reader domain mutations, collectively building towards refined approaches in disease treatments.
Grant Number: 5F32GM157893-02
NIH Institute/Center: NIH
Principal Investigator: Ryan Boileau
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