Deciphering Transcription Factor-Coregulator Interactions through Innovative Tools

ABSTRACT Transcription factors and their coregulators are pivotal in directing gene regulation, cellular differentiation, and disease progression. Acting as molecular switches, these complexes shape cellular fate during embryonic development, maintain tissue homeostasis, and steer responses to environmental cues. However, disruptions in these interactions can lead to altered gene expression, paving the way for disorders ranging from metabolic imbalances to neurodegenerative conditions. Recognizing the need to study the regulatory dynamics of transcription factors, we developed a proteomics method called RIME. This technique immuno-precipitates epigenetic complexes using antibodies and employs mass spectrometry to pinpoint members of specific protein complexes. Nonetheless, RIME and other similar methods grapple with challenges like low reproducibility and constraints on low-input samples. Over the next five years, our ambition is to pioneer technologies that revolutionize the study of these complexes. A significant shift will be transitioning from mass spectrometry to DNA barcode methods, enhancing signal specificity from individual proteins. Our objective is to devise instruments that bypass sample limitations and inconsistencies introduced by mass spectrometry. Present methods only offer a mean signal for all interactors of a protein, even though it may participate in various distinct complexes. Through our proposal, we plan to craft DNA oligo-based techniques that amplify protein signals and discern which members coexist in the same complex. Beyond tool development, we will apply our methodologies to decipher dynamic shifts in transcription factor complexes, specifically at regulatory elements like enhancers. Our proteomic instruments will seamlessly complement state-of-the-art single-cell multi-omic methods that we are currently employing, enhancing our understanding of how chromatin accessibility, DNA methylation, and transcriptional patterns are influenced by epigenetic complexes.