Biology subjects

King, E. A.

Publications and source records attributed to King, E. A..

4 recordsLinked to original sources

bioRxiv2024

The transcription factor Chronophage/BCL11A/B promotes intestinal stem cell proliferation and endocrine differentiation in the Drosophila intestine

Tissue-resident Adult Stem Cells (ASCs) need to continuously adapt their rate of division and differentiation based on their tissue environment. However, the gene regulatory networks that govern these decisions in ASCs and how they respond to challenges such as infection are often not fully understood. We identify a novel role for the transcription factor (TF) Chronophage (Cph) in ISC proliferation and entero-endocrine (EE) cell differentiation. Cph is a Z2H2 zinc TF orthologous to mammalian BCL11A/B that are involved in regulating adult stem cell fate in various contexts. We show here that Cph is expressed in ISCs and EEs in the Drosophila intestine. Increased levels of Cph correlates with increased ISC proliferation and EE differentiation. cph loss-of-function leads to impaired ISC proliferation. Cph levels are elevated during tumourigenesis as well as in ageing and infection conditions. Knockdown of Cph in a Notch-mutant tumour model reduces tumour size and incidence and extends lifespan. Mechanistically, Cph overexpression leads to an increase in enteroendocrine (EE) cells and DamID DNA-binding and qRT-PCR analysis reveals that Cph directly regulates the levels of key EE regulatory genes such as Prospero (pros) and Phyllopod (phyl). In addition, Cph directly regulates core cell cycle regulators such as E2F1 as well as the TF Nerfin-1 that controls ISC proliferation and maintenance. Together, these data support a role for Cph in finetuning the balance between differentiation and proliferation during entero-endocrine differentiation.

developmental biology↗

bioRxiv2022

Chemoproteomics-Enabled Discovery of a Covalent Molecular Glue Degrader Targeting NF-κB

Targeted protein degradation using heterobifunctional Proteolysis-Targeting Chimeras (PROTACs) or molecular glues has arisen as a powerful therapeutic modality for degrading disease targets. While PROTAC design is becoming more modular and straightforward, the discovery of novel molecular glue degraders has been more challenging. While several recent studies have showcased phenotypic screening and counter-screening approaches to discover new molecular glue degraders, mechanistically elucidating the ternary complex induced by the small-molecule that led to the initial phenotype--i.e. identifying the degraded target and relevant components of the ubiquitin-proteasome system--has remained cumbersome and laborious. To overcome these obstacles, we have coupled the screening of a covalent ligand library for anti-proliferative effects in leukemia cells with quantitative proteomic and chemoproteomic approaches to rapidly discover both novel covalent molecular glue degraders and their associated ternary complex components and anti-proliferative mechanisms. We have identified a cysteine-reactive covalent ligand EN450 that impairs leukemia cell viability in a NEDDylation and proteasome-dependent manner. Chemoproteomic profiling revealed covalent interaction of EN450 with an allosteric C111 in the E2 ubiquitin ligase UBE2D. Follow-up quantitative proteomic profiling revealed the proteasome-mediated degradation of the oncogenic transcription factor NFKB1 as a putative degradation target. Subsequent validation studies demonstrated that EN450 induced the ternary complex formation between UBE2D and NFKB1 and that both UBE2D and NFKB1 were important for the anti-proliferative mechanisms of EN450. Our study thus puts forth the discovery of a novel molecular glue degrader that uniquely induced the proximity of an E2 ligase with a transcription factor to induce its degradation and anti-proliferative effects in cancer cells. Taken more broadly, our study showcases a rapid and modular approach for discovering novel covalent molecular glue degraders and their respective ternary complex components in an unbiased fashion.

biochemistry↗

bioRxiv2020

Estimating colocalization probability from limited summary statistics

11.1 MotivationA common approach to understanding the mechanisms of noncoding GWAS associations is to test the GWAS variant for association with lower level cellular phenotypes such as gene expression. However, significant association to gene expression will often arise from linkage disequilibrium to a separate causal variant and be unrelated to the mechanism underlying the GWAS association. Colocalization is a statistical genetic method used to determine whether the same variant is causal for multiple phenotypes and is stronger evidence for understanding mechanism than shared significance. Current colocalization methods require full summary statistics for both traits, limiting their use with the majority of reported GWAS associations (e.g. GWAS Catalog). We propose a new approximation to the popular coloc method [1] that can be applied when limited summary statistics are available, as in the common scenario where a GWAS catalog hit would be tested for colocalization with a GTEx eQTL. Our method (POint EstiMation of Colocalization - POEMColoc) imputes missing summary statistics using LD structure in a reference panel, and performs colocalization between the imputed statistics and full summary statistics for a second trait. 1.2 ResultsAs a test of whether we are able to approximate the posterior probability of colocalization, we apply our method to colocalization of UK Biobank phenotypes and GTEx eQTL. We show good correlation between posterior probabilities of colocalization computed from imputed and observed UK Biobank summary statistics. We perform simulations and show that the POEMColoc method can identify shared causality with similar accuracy to the coloc method. We evaluate scenarios that might reduce POEMColoc performance and show that multiple independent causal variants in a region and imputation from a limited subset of typed variants have a larger effect while mismatched ancestry in the reference panel has a modest effect. We apply POEMColoc to estimate colocalization of GWAS Catalog entries and GTEx eQTL. We find evidence for colocalization of ~ 150,000 trait-gene-tissue triplets. We find that colocalized trait-gene pairs are enriched in tissues relevant to the etiology of the disease (e.g., thyroid eQTLs are enriched in colocalized hypothyroidism GWAS signals). Further, we find that colocalized trait-gene pairs are enriched in approved drug target - indication pairs. 1.3 AvailabilityPOEMColoc is freely available as an R package at https://github.com/AbbVie-ComputationalGenomics/POEMColoc

bioinformatics↗

bioRxiv2019

Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval.

1Despite strong vetting for disease activity, only 10% of candidate new molecular entities in early stage clinical trials are eventually approved. Analyzing historical pipeline data, Nelson et al. 2015 (Nat. Genet.) concluded pipeline drug targets with human genetic evidence of disease association are twice as likely to lead to approved drugs. Taking advantage of recent clinical development advances and rapid growth in GWAS datasets, we extend the original work using updated data, test whether genetic evidence predicts future successes and introduce statistical models adjusting for target and indication-level properties. Our work confirms drugs with genetically supported targets were more likely to be successful in Phases II and III. When causal genes are clear (Mendelian traits and GWAS associations linked to coding variants), we find the use of human genetic evidence increases approval from Phase I by greater than two-fold, and, for Mendelian associations, the positive association holds prospectively. Our findings suggest investments into genomics and genetics are likely to be beneficial to companies deploying this strategy.

genetics↗