Biology subjects

Hook, H.

Publications and source records attributed to Hook, H..

4 recordsLinked to original sources

bioRxiv2024

Rapid profiling of transcription factor-cofactor interaction networks reveals principles of epigenetic regulation

Transcription factor (TF)-cofactor (COF) interactions define dynamic, cell-specific networks that govern gene expression; however, these networks are understudied due to a lack of methods for high-throughput profiling of DNA-bound TF-COF complexes. Here we describe the Cofactor Recruitment (CoRec) method for rapid profiling of cell-specific TF-COF complexes. We define a lysine acetyltransferase (KAT)-TF network in resting and stimulated T cells. We find promiscuous recruitment of KATs for many TFs and that 35% of KAT-TF interactions are condition specific. KAT-TF interactions identify NF-{kappa}B as a primary regulator of acutely induced H3K27ac. Finally, we find that heterotypic clustering of CBP/P300-recruiting TFs is a strong predictor of total promoter H3K27ac. Our data supports clustering of TF sites that broadly recruit KATs as a mechanism for widespread co-occurring histone acetylation marks. CoRec can be readily applied to different cell systems and provides a powerful approach to define TF-COF networks impacting chromatin state and gene regulation.

molecular biology↗

bioRxiv2022

Widespread perturbation of ETS factor binding sites in cancer

Although >90% of somatic mutations reside in non-coding regions, few have been reported as cancer drivers. To predict driver non-coding variants (NCVs), we present a novel transcription factor (TF)-aware burden test (TFA-BT) based on a model of coherent TF function in promoters. We applied our TFA-BT to NCVs from the Pan-Cancer Analysis of Whole Genomes cohort and predicted 2,555 driver NCVs in the promoters of 813 genes across 20 cancer-types. These genes are enriched in cancer-related gene ontologies, essential genes, and genes associated with cancer prognosis. We found that 765 candidate driver NCVs alter transcriptional activity, 510 lead to differential binding of TF-cofactor regulatory complexes, and that they primarily impact the binding of ETS factors. Finally, we show that different NCVs within a promoter often affect transcriptional activity through shared mechanisms. Our integrated computational and experimental approach shows that cancer NCVs are widespread and that ETS factors are commonly disrupted.

cancer biology↗

bioRxiv2021

A multi-tiered map of EMT defines major transition points and identifies vulnerabilities

Epithelial to mesenchymal transition (EMT) is a complex cellular program proceeding through a hybrid E/M state linked to cancer-associated stemness, migration and chemoresistance. Deeper molecular understanding of this dynamic physiological landscape is needed to define events which regulate the transition and entry into and exit from the E/M state. Here, we quantified >60,000 molecules across ten time points and twelve omic layers in human mammary epithelial cells undergoing TGF{beta}-induced EMT. Deep proteomic profiles of whole cells, nuclei, extracellular vesicles, secretome, membrane and phosphoproteome defined state-specific signatures and major transition points. Parallel metabolomics showed metabolic reprogramming preceded changes in other layers, while single-cell RNA sequencing identified transcription factors controlling entry into E/M. Covariance analysis exposed unexpected discordance between the molecular layers. Integrative causal modeling revealed co-dependencies governing entry into E/M that were verified experimentally using combinatorial inhibition. Overall, this dataset provides an unprecedented resource on TGF{beta} signaling, EMT and cancer.

systems biology↗

bioRxiv2020

Customizable high-throughput platform for profiling cofactor recruitment to DNA to characterize cis-regulatory elements and screen non-coding single-nucleotide polymorphisms

Determining how DNA variants affect the binding of regulatory complexes to cis-regulatory elements (CREs) and non-coding single-nucleotide polymorphisms (ncSNPs) is a challenge in genomics. To address this challenge, we have developed CASCADE (Comprehensive ASsessment of Complex Assembly at DNA Elements), which is a protein-binding microarray (PBM)-based approach that allows for the high-throughput profiling of cofactor (COF) recruitment to DNA sequence variants. The method also enables one to infer the identity of the transcription factor-cofactor (TF-COF) complexes involved in COF recruitment. We use CASCADE to characterize regulatory complexes binding to CREs and SNP quantitative trait loci (SNP-QTLs) in resting and stimulated human macrophages. By profiling the recruitment of the acetyltransferase p300 and MLL methyltransferase component RBBP5, we identify key regulators of the chemokine CXCL10, and by profiling a set of five functionally diverse COFs we identify a prevalence of ETS sites mediating COF recruitment at SNP-QTLs in macrophages. Our results demonstrate that CASCADE is a customizable, high-throughput platform to link DNA variants with the biophysical complexes that mediate functions such as chromatin modification or remodeling in a cell state-specific manner.

genomics↗