Biology subjects

Dilworth, D.

Publications and source records attributed to Dilworth, D..

8 recordsLinked to original sources

bioRxiv2022

PRMT5 regulates ATF4 transcript splicing and oxidative stress response

Protein methyltransferase 5 (PRMT5) symmetrically dimethylates arginine residues leading to regulation of transcription and splicing programs. Although PRMT5 has emerged as an attractive oncology target, the molecular determinants of PRMT5 dependency in cancer remain incompletely understood. Our transcriptomic analysis identified PRMT5 regulation of the activating transcription factor 4 (ATF4) pathway in acute myelogenous leukemia (AML). PRMT5 inhibition resulted in the expression of unstable, intron-retaining ATF4 mRNA that is detained in the nucleus. Concurrently, the decrease in the spliced cytoplasmic transcript of ATF4 led to lower levels of ATF4 protein and downregulation of ATF4 target genes. Upon loss of functional PRMT5, cells with low ATF4 displayed increased oxidative stress, growth arrest, and cellular senescence. Interestingly, leukemia cells with EVI1 oncogene overexpression demonstrated dependence on PRMT5 function. EVI1 and ATF4 regulated gene signatures were inversely correlated. We show that EVI1-high AML cells have reduced ATF4 levels, elevated baseline reactive oxygen species and increased sensitivity to PRMT5 inhibition. Thus, EVI1-high cells demonstrate dependence on PRMT5 function and regulation of oxidative stress response. Overall, our findings identify the PRMT5-ATF4 axis to be safeguarding the cellular redox balance that is especially important in high oxidative stress states, such as those that occur with EVI1 overexpression.

cancer biology↗

bioRxiv2021

Pharmacological targeting of a PWWP domain demonstrates cooperative control of NSD2 localization

NSD2 is the primary enzyme responsible for the dimethylation of lysine 36 of histone 3 (H3K36me2), a mark associated with active gene transcription and intergenic DNA methylation. In addition to a methyltransferase domain, NSD2 harbors two PWWP and five PHD domains believed to serve as chromatin reading modules, but their exact function in the regulation of NSD2 activity remains underexplored. Here we report a first-in-class chemical probe targeting the N-terminal PWWP (PWWP1) domain of NSD2. UNC6934 binds potently (Kd of 91 {+/-} 8 nM) to PWWP1, antagonizes its interaction with nucleosomal H3K36me2, and selectively engages endogenous NSD2 in cells. Crystal structures show that UNC6934 occupies the canonical H3K36me2-binding pocket of PWWP1 which is juxtaposed to the DNA-binding surface. In cells, UNC6934 induces accumulation of endogenous NSD2 in the nucleolus, phenocopying the localization defects of NSD2 protein isoforms lacking PWWP1 as a result of translocations prevalent in multiple myeloma. Mutation of other NSD2 chromatin reader domains also increases NSD2 nucleolar localization, and enhances the effect of UNC6934. Finally we identified two C-terminal nucleolar localization sequences in NSD2 that appear to drive nucleolar accumulation when one or more chromatin reader domains are disabled. These data support a model in which NSD2 chromatin engagement is achieved in a cooperative manner and subcellular localization is controlled by multiple competitive structural determinants. This chemical probe and the accompanying negative control, UNC7145, will be useful tools in defining NSD2 biology.

cell biology↗

bioRxiv2020

Discovery of Small-Molecule Antagonists of the PWWP Domain of NSD2

Increased activity of the lysine methyltrans-ferase NSD2 driven by translocation and activating mutations is associated with multiple myeloma and acute lymphoblastic leukemia, but no NSD2-targeting chemical probe has been reported to date. Here, we present the first antagonists that block the protein-protein interaction between the N-terminal PWWP domain of NSD2 and H3K36me2. Using virtual screening and experimental validation, we identified the small-molecule antagonist 3f, which binds to the NSD2-PWWP1 domain with a Kd of 3.4 M and abrogates histone H3K36me2 binding in cells. This study establishes an alternative approach to targeting NSD2 and provides a small-molecule antagonist that can be further optimized into a chemical probe to better understand the cellular function of this protein.

pharmacology and toxicology↗

bioRxiv2019

Genome sequence of the model rice variety KitaakeX

Here, we report the de novo genome sequencing and analysis of Oryza sativa ssp. japonica variety KitaakeX, a Kitaake plant carrying the rice XA21 immune receptor. Our KitaakeX sequence assembly contains 377.6 Mb, consisting of 33 scaffolds (476 contigs) with a contig N50 of 1.4 Mb. Complementing the assembly are detailed gene annotations of 35,594 protein coding genes. We identified 331,335 genomic variations between KitaakeX and Nipponbare (ssp. japonica), and 2,785,991 variations between KitaakeX and Zhenshan97 (ssp. indica). We also compared Kitaake resequencing reads to the KitaakeX assembly and identified 219 small variations. The high-quality genome of the model rice plant KitaakeX will accelerate rice functional genomics.

genomics↗

bioRxiv2019

Genetic dissection of the redundant and divergent functions of histone chaperone paralogs in yeast

Gene duplications increase organismal robustness by providing freedom for gene divergence or by increasing gene dosage. The yeast histone chaperones Fpr3 and Fpr4 are paralogs that can assemble nucleosomes in vitro, however the genomic locations they target and their functional relationship is poorly understood. We refined the yeast synthetic genetic array (SGA) approach to enable the functional dissection of gene paralogs. Applying this method to Fpr3 and Fpr4 uncovered their redundant and divergent functions: while Fpr3 is uniquely involved in chromosome segregation, Fpr3 and Fpr4 co-operate on some genes and are redundant on others where they impact gene expression and transcriptional processivity. We find that the TRAMP5 RNA exosome is essential in{Delta} fpr3{Delta}fpr4 yeast and leverage this information to identify Fpr3/4 target loci. Amongst these are the non-transcribed spacers of ribosomal DNA where either paralog is sufficient to establish chromatin that is both transcriptionally silent and refractory to recombination. These data provide evidence that Fpr3 and Fpr4 have shared chromatin-centric functions, especially at nucleolar rDNA. However, their distinct genetic interaction profiles show they also have evolved separate functions outside of the nucleolus.

genetics↗

bioRxiv2018

Pharmacological inhibition of PRMT7 links arginine monomethylation to the cellular stress response

Protein arginine methyltransferases (PRMTs) regulate diverse biological processes and are increasingly being recognized for their potential as drug targets. Here we report the discovery of a potent, selective and cell active chemical probe for PRMT7. SGC3027 is a cell permeable prodrug, which in cells, is converted to SGC8158, a potent, SAM-competitive PRMT7 inhibitor. Inhibition or knockout of cellular PRMT7 resulted in drastically reduced levels of arginine monomethylation of HSP70 family members and other stress-associated proteins. Structural and biochemical analysis revealed that PRMT7-driven in vitro methylation of HSP70 at R469 requires an ATP-bound, open conformation of HSP70. In cells, SGC3027 inhibited methylation of both constitutive and inducible forms of HSP70, and led to decreased tolerance for perturbations of proteostasis including heat shock and proteasome inhibitors. These results demonstrate a role for PRMT7 and arginine methylation in stress response.

biochemistry↗

bioRxiv2018

3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification

Quantitative analysis of morphological changes in a cell nucleus is important for the understanding of nuclear architecture and its relationship with pathological conditions such as cancer. However, dimensionality of imaging data, together with a great variability of nuclear shapes, presents challenges for 3D morphological analysis. Thus, there is a compelling need for robust 3D nuclear morphometric techniques to carry out population-wide analysis. We propose a new approach that combines modeling, analysis, and interpretation of morphometric characteristics of cell nuclei and nucleoli in 3D. We used robust surface reconstruction that allows accurate approximation of 3D object boundary. Then, we computed geometric morphological measures characterizing the form of cell nuclei and nucleoli. Using these features, we compared over 450 nuclei with about 1,000 nucleoli of epithelial and mesenchymal prostate cancer cells, as well as 1,000 nuclei with over 2,000 nucleoli from serum-starved and proliferating fibroblast cells. Classification of sets of 9 and 15 cells achieved accuracy of 95.4% and 98%, respectively, for prostate cancer cells, and 95% and 98% for fibroblast cells. To our knowledge, this is the first attempt to combine these methods for 3D nuclear shape modeling and morphometry into a highly parallel pipeline workflow for morphometric analysis of thousands of nuclei and nucleoli in 3D.

bioinformatics↗

bioRxiv2017

3D cell nuclear morphology: microscopy imaging dataset and voxel-based morphometry classification results

Cell deformation is regulated by complex underlying biological mechanisms associated with spatial and temporal morphological changes in the nucleus that are related to cell differentiation, development, proliferation, and disease. Thus, quantitative analysis of changes in size and shape of nuclear structures in 3D microscopic images is important not only for investigating nuclear organization, but also for detecting and treating pathological conditions such as cancer. While many efforts have been made to develop cell and nuclear shape characteristics in 2D or pseudo-3D, several studies have suggested that 3D morphometric measures provide better results for nuclear shape description and discrimination. A few methods have been proposed to classify cell and nuclear morphological phenotypes in 3D, however, there is a lack of publicly available 3D data for the evaluation and comparison of such algorithms. This limitation becomes of great importance when the ability to evaluate different approaches on benchmark data is needed for better dissemination of the current state of the art methods for bioimage analysis. To address this problem, we present a dataset containing two different cell collections, including original 3D microscopic images of cell nuclei and nucleoli. In addition, we perform a baseline evaluation of a number of popular classification algorithms using 2D and 3D voxel-based morphometric measures. To account for batch effects, while enabling calculations of AUROC and AUPR performance metrics, we propose a specific cross-validation scheme that we compare with commonly used k-fold cross-validation. Original and derived imaging data are made publicly available on the project web-page: http://www.socr.umich.edu/projects/3d-cell-morphometry/data.html.

bioinformatics↗