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

SPACe (Swift Phenotypic Analysis of Cells): an open-source, single cell analysis of Cell Painting data

Phenotypic profiling by high throughput microscopy has become one of the leading tools for screening large sets of perturbations in cellular models. Of the numerous methods used over the years, the flexible and economical Cell Painting (CP) assay has been central in the field, allowing for large screening campaigns leading to a vast number of data-rich images. Currently, to analyze data of this scale, available open-source software ( i.e. , CellProfiler) requires computational resources that are not available to most laboratories worldwide. In addition, the image-embedded cell-to-cell variation of responses within a population, while collected and analyzed, is usually averaged and unused. Here we introduce SPACe ( S wift P henotypic A nalysis of Ce lls), an open source, Python-based platform for the analysis of single cell image-based morphological profiles produced by CP experiments. SPACe can process a typical dataset approximately ten times faster than CellProfiler on common desktop computers without loss in mechanism of action (MOA) recognition accuracy. It also computes directional distribution-based distances (Earth Mover's Distance - EMD) of morphological features for quality control and hit calling. We highlight several advantages of SPACe analysis on CP assays, including reproducibility across multiple biological replicates, easy applicability to multiple (∼20) cell lines, sensitivity to variable cell-to-cell responses, and biological interpretability to explain image-based features. We ultimately illustrate the advantages of SPACe in a screening campaign of cell metabolism small molecule inhibitors which we performed in seven cell lines to highlight the importance of testing perturbations across models.

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.

A novel ERβ high throughput microscopy platform for testing endocrine disrupting chemicals

In this study we present an inducible biosensor model for the Estrogen Receptor Beta (ERβ), GFP-ERβ:PRL-HeLa, a single-cell-based high throughput (HT) in vitro assay that allows direct visualization and measurement of GFP-tagged ERβ binding to ER-specific DNA response elements (EREs), ERβ-induced chromatin remodeling, and monitor transcriptional alterations via mRNA fluorescence in situ hybridization for a prolactin (PRL)-dsRED2 reporter gene. The model was used to accurately (Z' = 0.58-0.8) differentiate ERβ-selective ligands from ERα ligands when treated with a panel of selective agonists and antagonists. Next, we tested an Environmental Protection Agency (EPA)-provided set of 45 estrogenic reference chemicals with known ERα in vivo activity and identified several that activated ERβ as well, with varying sensitivity, including a subset that is completely novel. We then used an orthogonal ERE-containing transgenic zebrafish (ZF) model to cross validate ERβ and ERα selective activities at the organism level. Using this environmentally relevant ZF assay, some compounds were confirmed to have ERβ activity, validating the GFP-ERβ:PRL-HeLa assay as a screening tool for potential ERβ active endocrine disruptors (EDCs). These data demonstrate the value of sensitive multiplex mechanistic data gathered by the GFP-ERβ:PRL-HeLa assay coupled with an orthogonal zebrafish model to rapidly identify environmentally relevant ERβ EDCs and improve upon currently available screening tools for this understudied nuclear receptor.

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.

Long intergenic non-protein coding RNA 847 promotes laryngeal squamous cell carcinoma progression through the microRNA-181a-5p/zinc finger E-box binding homeobox 2 axis

The present study is targeted at investigating the effects of long intergenic non-protein coding RNA 847 (LINC00847) on the malignant biological behaviors of laryngeal squamous cell carcinoma (LSCC) cells, and the mechanisms. Quantitative real-time PCR and Western blotting were conducted for detecting the expressions of LINC00847, microRNA-181a-5p (miR-181a-5p) and zinc finger E-box binding homeobox 2 (ZEB2) in LSCC cell lines and tissue samples. BrdU, cell counting kit-8, scratch wound healing, Transwell and flow cytometry assays were utilized for detecting cell proliferation, migration, invasion, and cell cycle progression. Dual-luciferase reporter gene, RNA binding protein immunoprecipitation (RIP), and RNA pull-down assays were utilized to investigate the interaction among LINC00847, miR-181a-5p, and ZEB2. The subcellular location of LINC00847 was determined by RNA fluorescence in situ hybridization (RNA-FISH) assay. Tumor growth was evaluated using a xenograft model of nude mice. It was revealed that LINC00847 expression was increased in LSCC tissues, and its high expression was associated with lymph node metastasis and poor differentiation. LINC00847 was mainly located in the cytoplasm of LSCC cells, and LINC00847 overexpression promoted LSCC cell proliferation, migration, invasion, and accelerated the cell cycle progression while knocking down LINC00847 had the opposite effects in vitro and inhibited the tumor growth in vivo. LINC00847 directly targeted miR-181a-5p and negatively modulated miR-181a-5p expression. ZEB2 was a target gene of miR-181a-5p, and was positively and indirectly modulated by LINC00847. Our data suggest that LINC00847 promotes LSCC progression by regulating the miR-181a-5p/ZEB2 axis.