A high-content glucocorticoid receptor translocation assay for compound mechanism-of-action evaluation

Treating the Side Effects of Exogenous Glucocorticoids; Can We Separate the Good From the Bad?

It is estimated that 2% to 3% of the population are currently prescribed systemic or topical glucocorticoid treatment. The potent anti-inflammatory action of glucocorticoids to deliver therapeutic benefit is not in doubt. However, the side effects associated with their use, including central weight gain, hypertension, insulin resistance, type 2 diabetes (T2D), and osteoporosis, often collectively termed iatrogenic Cushing's syndrome, are associated with a significant health and economic burden. The precise cellular mechanisms underpinning the differential action of glucocorticoids to drive the desirable and undesirable effects are still not completely understood. Faced with the unmet clinical need to limit glucocorticoid-induced adverse effects alongside ensuring the preservation of anti-inflammatory actions, several strategies have been pursued. The coprescription of existing licensed drugs to treat incident adverse effects can be effective, but data examining the prevention of adverse effects are limited. Novel selective glucocorticoid receptor agonists and selective glucocorticoid receptor modulators have been designed that aim to specifically and selectively activate anti-inflammatory responses based upon their interaction with the glucocorticoid receptor. Several of these compounds are currently in clinical trials to evaluate their efficacy. More recently, strategies exploiting tissue-specific glucocorticoid metabolism through the isoforms of 11β-hydroxysteroid dehydrogenase has shown early potential, although data from clinical trials are limited. The aim of any treatment is to maximize benefit while minimizing risk, and within this review we define the adverse effect profile associated with glucocorticoid use and evaluate current and developing strategies that aim to limit side effects but preserve desirable therapeutic efficacy.

Intein-Mediated Protein Engineering for Cell-Based Biosensors

Cell-based sensors provide a flexible platform for screening biologically active targets and for monitoring their interactions in live cells. Their applicability extends across a vast array of biological research and clinical applications. Particularly, cell-based sensors are becoming a potent tool in drug discovery and cell-signaling studies by allowing function-based screening of targets in biologically relevant environments and enabling the in vivo visualization of cellular signals in real-time with an outstanding spatiotemporal resolution. In this review, we aim to provide a clear view of current cell-based sensor technologies, their limitations, and how the recent improvements were using intein-mediated protein engineering. We first discuss the characteristics of cell-based sensors and present several representative examples with a focus on their design strategies, which differentiate cell-based sensors from in vitro analytical biosensors. We then describe the application of intein-mediated protein engineering technology for cell-based sensor fabrication. Finally, we explain the characteristics of intein-mediated reactions and present examples of how the intein-mediated reactions are used to improve existing methods and develop new approaches in sensor cell fabrication to address the limitations of current technologies.

Rapid Screening of Glucocorticoid Receptor (GR) Effectors Using Cortisol-Detecting Sensor Cells

Cortisol, a stress hormone, plays key roles in mediating stress and anti-inflammatory responses. As abnormal cortisol levels can induce various adverse effects, screening cortisol and cortisol analogues is important for monitoring stress levels and for identifying drug candidates. A novel cell-based sensing system was adopted for rapid screening of cortisol and its functional analogues under complex cellular regulation. We used glucocorticoid receptor (GR) fused to a split intein which reconstituted with the counterpart to trigger conditional protein splicing (CPS) in the presence of targets. CPS generates functional signal peptides which promptly translocate the fluorescent cargo. The sensor cells exhibited exceptional performance in discriminating between the functional and structural analogues of cortisol with improved sensitivity. Essential oil extracts with stress relief activity were screened using the sensor cells to identify GR effectors. The sensor cells responded to peppermint oil, and L-limonene and L-menthol were identified as potential GR effectors from the major components of peppermint oil. Further analysis indicated L-limonene as a selective GR agonist (SEGRA) which is a potential anti-inflammatory agent as it attenuates proinflammatory responses without causing notable adverse effects of GR agonists.

Screening protocol for the identification of modulators by immunofluorescent cell-based assay

High-throughput assays are a common strategy for the identification of compounds able to modulate a certain cellular activity. Here, we show an automatized analysis platform for the quantification of nuclear foci as inhibitory effect of compounds on a target protein labeled by fluorescent antibodies. Our experience led us to a fast analysis platform that combines cell-based assays, high-content screening, and confocal microscopy, with an automatic and user-friendly statistical analysis of plate-based assays including positive and negative controls, able to identify inhibitory effect of compounds tested together with the Z-prime and Window of individual plate-based assays to assess the reliability of the results. The platform integrates a web-based tool implemented in Pipeline Pilot and R, and allows computing the inhibition values of different parameters obtained from the high-content screening and confocal microscopy analysis. This facilitates the exploration of the results using the different parameters, providing information at different levels as the number of foci observed, the sum of intensity of foci, area of foci, etc, the detection and filtering of outliers over the assay plate, and finally providing a set of statistics of the parameters studied together with a set of plots that we believe significantly helps to the interpretation of the assay results.

A High-Throughput Drug Screening Strategy for Detecting Rhodopsin P23H Mutant Rescue and Degradation

PURPOSE

Inherent instability of the P23H mutant opsin accounts for approximately 10% of autosomal dominant retinitis pigmentosa cases. Our purpose was to develop an overall set of reliable screening strategies to assess if either stabilization or enhanced degradation of mutant rhodopsin could rescue rod photoreceptors expressing this mutant protein. These strategies promise to reveal active compounds and clarify molecular mechanisms of biologically important processes, such as inhibition of target degradation or enhanced target folding.

METHODS

Cell-based bioluminescence reporter assays were developed and validated for high-throughput screening (HTS) of compounds that promote either stabilization or degradation of P23H mutant opsin. Such assays were further complemented by immunoblotting and image-based analyses.

RESULTS

Two stabilization assays of P23H mutant opsin were developed and validated, one based on β-galactosidase complementarity and a second assay involving bioluminescence resonance energy transfer (BRET) technology. Moreover, two additional assays evaluating mutant protein degradation also were employed, one based on the disappearance of luminescence and another employing the ALPHA immunoassay. Imaging of cells revealed the cellular localization of mutant rhodopsin, whereas immunoblots identified changes in the aggregation and glycosylation of P23H mutant opsin.

CONCLUSIONS

Our findings indicate that these initial HTS and following assays can identify active therapeutic compounds, even for difficult targets such as mutant rhodopsin. The assays are readily scalable and their function has been proven with model compounds. High-throughput screening, supported by automated imaging and classic immunoassays, can further characterize multiple steps and pathways in the biosynthesis and degradation of this essential visual system protein.

Synthetic molecules: helping to unravel plant signal transduction

The application of small molecules has played a crucial role in identifying novel components involved in plant signalling. Compared to classic genetic approaches, small molecule screens offer notable advantages in dissecting plant biological processes, such as technical simplicity, low start-up costs, and most importantly, bypassing the problems of lethality and redundancy. To identify small molecules that target a biological process or protein of interest, robust and well-reasoned high-throughput screening approaches are essential. In this review, we present a series of principles and valuable approaches in small molecule screening in the plant model system Arabidopsis thaliana. We also provide an overview of small molecules that led to breakthroughs in uncovering phytohormone signalling pathways, endomembrane signalling cascades, novel growth regulators, and plant defence mechanisms. Meanwhile, the strategies to deciphering the mechanisms of these small molecules on Arabidopsis are highlighted. Moreover, the opportunities and challenges of small molecule applications in translational biology are discussed.

Endocrine disruptors provoke differential modulatory responses on androgen receptor and pregnane and xenobiotic receptor: potential implications in metabolic disorders

A systematic comparison of the impact of some potential endocrine disruptors (EDs) on modulation of androgen receptor (AR) and pregnane and xenobiotic receptor (PXR) function was conducted in a multi-step analysis. Promoter-reporter-based transcription assays were performed in conjunction with receptor dynamic studies in living cells that helped implicating the suspected EDs for their deleterious effects. We demonstrate that most of the selected EDs not only inhibit AR transcriptional activity, but also alter its subcellular dynamics. Conversely, some of these anti-androgenic compounds were potent activator of xeno-sensing nuclear receptor, PXR. Interestingly, agonist-activated AR that associates with the mitotic chromatin fails to achieve this association when bound to anti-androgenic EDs. Conclusively, most EDs (except BCH) behaved like pure antagonist for AR while as agonist for PXR. Subsequent experiments with DDT treatment in mice model indicated that in testis AR and its regulated genes PEM and ODC levels are down-regulated, whereas in liver of same mice PEM is up-regulated while AR and ODC remain unchanged. On the contrary, PXR and its regulated genes CYP3A11 and MDR1 levels in mice liver were up-regulated while in testis PXR remained unchanged, CYP3A11 up-regulated and MDR1 were down-regulated. Based on a novel "Biopit" concept it is speculated that long-term exposure to endocrine disrupting chemicals may influence the epigenetic profile of target cells via transcription factors thereby making them vulnerable to onset of chemically induced endocrine-related malignancies or metabolic disorders.

High-content imaging for automated determination of host-cell infection rate by the intracellular parasite Trypanosoma cruzi

Chagas disease affects 8-11 million people, mostly in Latin America. Sequelae include cardiac, peripheral nervous and/or gastrointestinal disorders, thus placing a large economic and social burden on endemic countries. The pathogenesis and the evolutive pattern of the disease are not fully clarified. Moreover, available drugs are partially effective and toxic, and there is no vaccine. Therefore, there is an urgent need to speed up basic and translational research in the field. Here, we applied automated high-content imaging to generate multiparametric data on a cell-by-cell basis to precisely and quickly determine several parameters associated with in vitro infection of host cell by Trypanosoma cruzi, the causative agent of Chagas disease. Automated and manual quantifications were used to determine the percentage of T. cruzi-infected cells in a 96-well microplate format and the data generated was statistically evaluated. Most importantly, this automated approach can be widely applied for discovery of potential drugs as well as molecular pathway elucidation not only in T. cruzi but also in other human intracellular pathogens.

HCS Road

The effective analysis and interpretation of high-content screening (HCS) data requires joining results to information on experimental treatments and controls, normalizing data, and selecting hits or fitting concentration-response curves. HCS data have unique requirements that are not supported by traditional high-throughput screening databases, including the ability to designate separate positive and negative controls for different measurements in multiplexed assays; the ability to capture information on the cell lines, fluorescent reagents, and treatments in each assay; the ability to store and use individual-cell and image data; and the ability to support HCS readers and software from multiple vendors along with third-party image analysis tools. To address these requirements, the authors developed an enterprise system for the storage and processing of HCS images and results. This system, HCS Road, supports target identification, lead discovery, lead evaluation, and lead profiling activities. A dedicated client supports experimental design, data review, and core analyses and displays images together with results for assay development, hit assessment, and troubleshooting. Data can be exported to third-party applications for further analysis and exploration. HCS Road provides a single source for high-content results across the organization, regardless of the group or instrument that produced them.

Effect of anabolic-androgenic steroids and glucocorticoids on the kinetics of hAR and hGR nucleocytoplasmic translocation

Although the qualitative nucleocytoplasmic transport of nuclear hormone receptors (NHRs) has been studied, there is little documentation of the cellular kinetics of this transport. Here, translocation studies using the human androgen receptor (hAR) and the human glucocorticoid receptor (hGR) were performed to aid in identifying the mechanism by which anabolic-androgenic steroids (AAS) were activating hAR and potentially interacting with hGR and how glucocorticoid ligands were interacting with the hGR and hAR. The real-time analysis of EGFP-labeled hAR and hGR ligand-induced cytoplasm-to-nucleus translocation was performed using fluorescence microscopy to better understand the action of these NHRs in a physiologically relevant cell-based model. After transient transfection, the hAR and hGR individually translocate as expected (i.e., transport is ligand-induced and dose-dependent) in this model biological system. Testosterone (TEST) had the fastest translocation rate for the hAR of 0.0525 min(-1). The other endogenous steroids, androstenedione (ANE) and dihydrotestosterone (DHT), had considerably lower hAR transport rates. The rates of hAR transport for the exogenous steroids methyltrienelone (MET), nandrolone (NAN), and oxandrolone (OXA) are lower than that of testosterone and similar to those of the endogenous steroids ANE and DHT. The hGR transport rates for cortisol (COR) and dexamethasone (DEX) are also presented. The synthetic GC, DEX, had a more rapid translocation rate (0.1599 min(-1)) at the highest dose of 100 nM compared to the endogenous GC COR (0.0431 min(-1)). The data obtained agrees with the existing qualitative data and adds an important ligand-dependent kinetic component to hAR and hGR transport. These kinetic data can aid our understanding of NHR action and interaction with other regulatory proteins, and can be useful in the development of new therapies.

Applications of high content screening in life science research

Over the last decade, imaging as a detection mode for cell based assays has opened a new world of opportunities to measure "phenotypic endpoints" in both current and developing biological models. These "high content" methods combine multiple measurements of cell physiology, whether it comes from sub-cellular compartments, multicellular structures, or model organisms. The resulting multifaceted data can be used to derive new insights into complex phenomena from cell differentiation to compound pharmacology and toxicity. Exploring the major application areas through review of the growing compendium of literature provides evidence that this technology is having a tangible impact on drug discovery and the life sciences.

Estrogen receptor beta functions through nongenomic mechanisms in lung cancer cells

Recent studies have shown that estrogens promote the growth of lung cancer cells and may potentially be responsible for increased susceptibility to lung cancer in women. These observations raise the possibility of using antiestrogens in treating and preventing lung cancer. However, it is not clear how estrogen receptors (ERs) modulate the growth of non-small cell lung cancer (NSCLC) cells. Our Western blotting and real-time PCR analysis showed that NSCLC cells expressed ERbeta, but not ERalpha. In addition, ERbeta-specific ligands, but not ERalpha-specific ligands, promoted the growth of lung cancer cells. Furthermore, knockdown of ERbeta by short hairpin RNA constructs resulted in loss of estrogen-dependent growth of lung cancer cells. Interestingly, endogenous ERbeta failed to transcriptionally activate estrogen response element (ERE)-luciferase constructs in NSCLC cells, suggesting a lack of genomic function. Upon further investigation, ERbeta was found to be in the cytoplasm in all lung cancer cells and failed to translocate to the nucleus in the presence of estrogen, as observed by biochemical, ArrayScan, and confocal microscopy experiments. Nonetheless, estrogen caused rapid activation of cAMP, Akt, and MAPK signaling pathways in lung cancer cells. Immunohistochemical analysis of lung tumor biopsies showed strong ERbeta staining in the cytoplasm, whereas no staining was observed for ERalpha. In conclusion, our results suggest that that proliferative effects of estrogen in lung cancer cells is mediated primarily, if not exclusively, by the nongenomic action of ERbeta.