Estrogen-induced transcription at individual alleles is independent of receptor level and active conformation but can be modulated by coactivators activity

Protein Arginine Methyltransferase CARM1 in Human Breast Cancer

Coactivator-associated arginine methyltransferase 1 (CARM1) is a protein arginine methyltransferase that deposits asymmetrical dimethylation marks on both histone and nonhistone substrates. The regulatory role of CARM1 in transcription was first identified in estrogen receptor positive (ER+) breast cancer. Since then, the mechanism of CARM1 in activating ER-target genes has been further interrogated. CARM1 is expressed at the highest level in ER negative (ER-) breast cancer and higher expression correlates with poor prognosis, suggesting an oncogenic role of CARM1. Indeed, in ER- breast cancer, CARM1 can promote proliferation and metastasis at least partly through methylation of proteins and activation of oncogenes. In this review, we summarize the mechanisms of transcriptional activation by CARM1 in breast cancer. The methyltransferase activity of CARM1 is important for many of its functions; here, we also highlight the nonenzymatic roles of CARM1. We also cover the biological processes regulated by CARM1 that are often deregulated in cancer and the ways to harness CARM1 in cancer treatment.

Characterization of flavonoids with potent and subtype-selective actions on estrogen receptors alpha and beta

The initial step in estrogen-regulated transcription is the binding of a ligand to its cognate receptors, named estrogen receptors (ERα and ERβ). Phytochemicals present in foods and environment can compete with endogenous hormones to alter physiological responses. We screened 224 flavonoids in our engineered biosensor ERα and ERβ PRL-array cell lines to characterize their activity on several steps of the estrogen signaling pathway. We identified 83 and 96 flavonoids that can activate ERα or ERβ, respectively. While most act on both receptors, many appear to be subtype-selective, including potent flavonoids that activate ER at sub-micromolar concentrations. We employed an orthogonal assay using a transgenic zebrafish in vivo model that validated the estrogenic potential of these compounds. To our knowledge, this is the largest study thus far on flavonoids and the ER pathway, facilitating the identification of a new set of potential endocrine disruptors acting on both ERα and ERβ.

Arginine methylation and respiratory disease

Arginine methylation, a vital post-translational modification, plays a pivotal role in numerous cellular functions such as signal transduction, DNA damage response and repair, regulation of gene transcription, mRNA splicing, and protein interactions. Central to this modification is the role of protein arginine methyltransferases (PRMTs), which have been increasingly recognized for their involvement in the pathogenesis of various respiratory diseases. This review begins with an exploration of the biochemical underpinnings of arginine methylation, shedding light on the intricate molecular regulatory mechanisms governed by PRMTs. It then delves into the impact of arginine methylation and the dysregulation of arginine methyltransferases in diverse pulmonary disorders. Concluding with a focus on the therapeutic potential and recent advancements in PRMT inhibitors, this article aims to offer novel perspectives and therapeutic avenues for the management and treatment of respiratory diseases.

Gene transcription regulation by ER at the single cell and allele level

In this short review we discuss the current view of how the estrogen receptor (ER), a pivotal member of the nuclear receptor superfamily of transcription factors, regulates gene transcription at the single cell and allele level, focusing on in vitro cell line models. We discuss central topics and new trends in molecular biology including phenotypic heterogeneity, single cell sequencing, nuclear phase separated condensates, single cell imaging, and image analysis methods, with particular focus on the methodologies and results that have been reported in the last few years using microscopy-based techniques. These observations augment the results from biochemical assays that lead to a much more complex and dynamic view of how ER, and arguably most transcription factors, act to regulate gene transcription.

High throughput microscopy and single cell phenotypic image-based analysis in toxicology and drug discovery

Measuring single cell responses to the universe of chemicals (drugs, natural products, environmental toxicants etc.) is of paramount importance to human health as phenotypic variability in sensing stimuli is a hallmark of biology that is considered during high throughput screening. One of the ways to approach this problem is via high throughput, microscopy-based assays coupled with multi-dimensional single cell analysis methods. Here, we will summarize some of the efforts in this vast and growing field, focusing on phenotypic screens (e.g., Cell Painting), single cell analytics and quality control, with particular attention to environmental toxicology and drug screening. We will discuss advantages and limitations of high throughput assays with various end points and levels of complexity.

Analysis and Modeling of Early Estradiol-induced GREB1 Single Allele Gene Transcription at the Population Level

Single molecule fluorescence in situ hybridization (smFISH) can be used to visualize transcriptional activation at the single allele level. We and others have applied this approach to better understand the mechanisms of activation by steroid nuclear receptors. However, there is limited understanding of the interconnection between the activation of target gene alleles inside the same nucleus and within large cell populations. Using the GREB1 gene as an early estrogen receptor (ER) response target, we applied smFISH to track E2-activated GREB1 allelic transcription over early time points to evaluate potential dependencies between alleles within the same nucleus. We compared two types of experiments where we altered the initial status of GREB1 basal transcription by treating cells with and without the elongation inhibitor flavopiridol (FV). E2 stimulation changed the frequencies of active GREB1 alleles in the cell population independently of FV pre-treatment. In FV treated cells, the response time to hormone was delayed, albeit still reaching at 90 minutes the same levels as in cells not treated by FV. We show that the joint frequencies of GREB1 activated alleles observed at the cell population level imply significant dependency between pairs of alleles within the same nucleus. We identify probabilistic models of joint alleles activations by applying a principle of maximum entropy. For pairs of alleles, we have then quantified statistical dependency by computing their mutual information. We have then introduced a stochastic model compatible with allelic statistical dependencies, and we have fitted this model to our data by intensive simulations. This provided estimates of the average lifetime for degradation of GREB1 introns and of the mean time between two successive transcription rounds. Our approach informs on how to extract information on single allele regulation by ER from within a large population of cells, and should be applicable to many other genes.

AUTHOR SUMMARY

After application of a gene transcription stimulus, in this case the hormone 17 β -estradiol, on large populations of cells over a short time period, we focused on quantifying and modeling the frequencies of GREB1 single allele activations. We have established an experimental and computational pipeline to analyze large numbers of high resolution smFISH images to detect and monitor active GREB1 alleles, that can be translatable to any target gene of interest. A key result is that, at the population level, activation of individual GREB1 alleles within the same nucleus do exhibit statistically significant dependencies which we quantify by the mutual information between activation states of pairs of alleles. After noticing that frequencies of joint alleles activations observed over our large cell populations evolve smoothly in time, we have defined a population level stochastic model which we fit to the observed time course of GREB1 activation frequencies. This provided coherent estimates of the mean time between rounds of GREB1 transcription and the mean lifetime of nascent mRNAs. Our algorithmic approach and experimental methods are applicable to many other genes.

The Legend of ATP: From Origin of Life to Precision Medicine

Adenosine triphosphate (ATP) may be the most important biological small molecule. Since it was discovered in 1929, ATP has been regarded as life’s energy reservoir. However, this compound means more to life. Its legend starts at the dawn of life and lasts to this day. ATP must be the basic component of ancient ribozymes and may facilitate the origin of structured proteins. In the existing organisms, ATP continues to construct ribonucleic acid (RNA) and work as a protein cofactor. ATP also functions as a biological hydrotrope, which may keep macromolecules soluble in the primitive environment and can regulate phase separation in modern cells. These functions are involved in the pathogenesis of aging-related diseases and breast cancer, providing clues to discovering anti-aging agents and precision medicine tactics for breast cancer.

Quality Control for Single Cell Imaging Analytics Using Endocrine Disruptor-Induced Changes in Estrogen Receptor Expression

BACKGROUND

Diverse toxicants and mixtures that affect hormone responsive cells [endocrine disrupting chemicals (EDCs)] are highly pervasive in the environment and are directly linked to human disease. They often target the nuclear receptor family of transcription factors modulating their levels and activity. Many high-throughput assays have been developed to query such toxicants; however, single-cell analysis of EDC effects on endogenous receptors has been missing, in part due to the lack of quality control metrics to reproducibly measure cell-to-cell variability in responses.

OBJECTIVE

We began by developing single-cell imaging and informatic workflows to query whether the single cell distribution of the estrogen receptor-α (ER), used as a model system, can be used to measure effects of EDCs in a sensitive and reproducible manner.

METHODS

We used high-throughput microscopy, coupled with image analytics to measure changes in single cell ER nuclear levels on treatment with ∼100 toxicants, over a large number of biological and technical replicates.

RESULTS

We developed a two-tiered quality control pipeline for single cell analysis and tested it against a large set of biological replicates, and toxicants from the EPA and Agency for Toxic Substances and Disease Registry lists. We also identified a subset of potentially novel EDCs that were active only on the endogenous ER level and activity as measured by single molecule RNA fluorescence in situ hybridization (RNA FISH).

DISCUSSION

We demonstrated that the distribution of ER levels per cell, and the changes upon chemical challenges were remarkably stable features; and importantly, these features could be used for quality control and identification of endocrine disruptor toxicants with high sensitivity. When coupled with orthogonal assays, ER single cell distribution is a valuable resource for high-throughput screening of environmental toxicants. https://doi.org/10.1289/EHP9297.

Ligands and DNA in the allosteric control of retinoid receptors function

Retinoids are a family of compounds that include both vitamin A (all-trans retinol) and its naturally occurring metabolites such as retinoic acids (e.g. all-trans retinoic acid) as well as synthetic analogs. They are critically involved in the regulation of a wide variety of essential biological processes, such as embryogenesis and organogenesis, apoptosis, reproduction, vision, and the growth and differentiation of normal and neoplastic cells in vertebrates. The ability of these small molecules to control the expression of several hundred genes through binding to nuclear ligand-dependent transcription factors accounts for most of their functions. Three retinoic acid receptor (RARα,β,γ) and three retinoid X receptor (RXRα,β,γ) subtypes form a variety of RXR-RAR heterodimers that have been shown to mediate the pleiotropic effects of retinoids through the recruitment of high-molecular weight co-regulatory complexes to response-element DNA sequences found in the promoter region of their target genes. Hence, heterodimeric retinoid receptors are multidomain entities that respond to various incoming signals, such as ligand and DNA binding, by allosteric structural alterations which are the basis of further signal propagation. Here, we provide an overview of the current state of knowledge with regard to the structural mechanisms by which retinoids and DNA response elements act as allosteric effectors that may combine to finely tune RXR-RAR heterodimers activity.

Physiologically Relevant Estrogen Receptor Alpha Pathway Reporters for Single-Cell Imaging-Based Carcinogenic Hazard Assessment of Estrogenic Compounds

Estrogen receptor alpha (ERα) belongs to the nuclear hormone receptor family of ligand-inducible transcription factors and regulates gene networks in biological processes such as cell growth and proliferation. Disruption of these networks by chemical compounds with estrogenic activity can result in adverse outcomes such as unscheduled cell proliferation, ultimately culminating in tumor formation. To distinguish disruptive activation from normal physiological responses, it is essential to quantify relationships between different key events leading to a particular adverse outcome. For this purpose, we established fluorescent protein MCF7 reporter cell lines for ERα-induced proliferation by bacterial artificial chromosome-based tagging of 3 ERα target genes: GREB1, PGR, and TFF1. These target genes are inducible by the non-genotoxic carcinogen and ERα agonist 17β-estradiol in an ERα-dependent manner and are essential for ERα-dependent cell-cycle progression and proliferation. The 3 GFP reporter cell lines were characterized in detail and showed different activation dynamics upon exposure to 17β-estradiol. In addition, they demonstrated specific activation in response to other established reference estrogenic compounds of different potencies, with similar sensitivities as validated OECD test methods. This study shows that these fluorescent reporter cell lines can be used to monitor the spatial and temporal dynamics of ERα pathway activation at the single-cell level for more mechanistic insight, thereby allowing a detailed assessment of the potential carcinogenic activity of estrogenic compounds in humans.

Mechanisms of enhancer action: the known and the unknown

Differential gene expression mechanisms ensure cellular differentiation and plasticity to shape ontogenetic and phylogenetic diversity of cell types. A key regulator of differential gene expression programs are the enhancers, the gene-distal cis-regulatory sequences that govern spatiotemporal and quantitative expression dynamics of target genes. Enhancers are widely believed to physically contact the target promoters to effect transcriptional activation. However, our understanding of the full complement of regulatory proteins and the definitive mechanics of enhancer action is incomplete. Here, we review recent findings to present some emerging concepts on enhancer action and also outline a set of outstanding questions.

Genetic evidence for partial redundancy between the arginine methyltransferases CARM1 and PRMT6

CARM1 is a protein arginine methyltransferase (PRMT) that acts as a coactivator in a number of transcriptional programs. CARM1 orchestrates this coactivator activity in part by depositing the H3R17me2a histone mark in the vicinity of gene promoters that it regulates. However, the gross levels of H3R17me2a in CARM1 KO mice did not significantly decrease, indicating that other PRMT(s) may compensate for this loss. We thus performed a screen of type I PRMTs, which revealed that PRMT6 can also deposit the H3R17me2a mark in vitro CARM1 knockout mice are perinatally lethal and display a reduced fetal size, whereas PRMT6 null mice are viable, which permits the generation of double knockouts. Embryos that are null for both CARM1 and PRMT6 are noticeably smaller than CARM1 null embryos, providing in vivo evidence of redundancy. Mouse embryonic fibroblasts (MEFs) from the double knockout embryos display an absence of the H3R17me2a mark during mitosis and increased signs of DNA damage. Moreover, using the combination of CARM1 and PRMT6 inhibitors suppresses the cell proliferation of WT MEFs, suggesting a synergistic effect between CARM1 and PRMT6 inhibitions. These studies provide direct evidence that PRMT6 also deposits the H3R17me2a mark and acts redundantly with CARM1.

NUDT5 as a novel drug target and prognostic biomarker for ER-positive breast cancer

Breast cancer (BRCA) is the most common malignant tumor in women. The estrogen receptor-positive (ER⁺) subtype accounts for ∼70% of BRCA cases. Estrogen is a crucial hormone that directly stimulates the growth and development of mammary glands. Recent studies revealed that, as an estrogen cofactor, ATP has an important role in determining the action of estrogen by mediating phase separation. NUDT5 has been recognized as a key factor for ATP production in the nucleus of BRCA cells and, therefore, could represent a novel drug target for ER⁺ BRCA. Based on a survival analysis of patients with BRCA documented in The Cancer Genome Atlas (TGCA) database, we show that NUDT5 is also a potential prognostic biomarker for ER⁺ BRCA.

Single Cell Analysis Of Transcriptionally Active Alleles By Single Molecule FISH

Gene transcription is an essential process in cell biology, and allows cells to interpret and respond to internal and external cues. Traditional bulk population methods (Northern blot, PCR, and RNAseq) that measure mRNA levels lack the ability to provide information on cell-to-cell variation in responses. Precise single cell and allelic visualization and quantification is possible via single molecule RNA fluorescence in situ hybridization (smFISH). RNA-FISH is performed by hybridizing target RNAs with labeled oligonucleotide probes. These can be imaged in medium/high throughput modalities, and, through image analysis pipelines, provide quantitative data on both mature and nascent RNAs, all at the single cell level. The fixation, permeabilization, hybridization and imaging steps have been optimized in the lab over many years using the model system described herein, which results in successful and robust single cell analysis of smFISH labeling. The main goal with sample preparation and processing is to produce high quality images characterized by a high signal-to-noise ratio to reduce false positives and provide data that are more accurate. Here, we present a protocol describing the pipeline from sample preparation to data analysis in conjunction with suggestions and optimization steps to tailor to specific samples.