A Cell-based beta-Lactamase Reporter Gene Assay for the CREB Signaling Pathway

β-Lactamase Tools for Establishing Cell Internalization and Cytosolic Delivery of Cell Penetrating Peptides

The ability of cell penetrating peptides (CPPs) to deliver biologically relevant cargos into cells is becoming more important as targets in the intracellular space continue to be explored. We have developed two assays based on CPP-dependent, intracellular delivery of TEM-1 β-lactamase enzyme, a functional biological molecule comparable in size to many protein therapeutics. The first assay focuses on the delivery of full-length β-lactamase to evaluate the internalization potential of a CPP sequence. The second assay uses a split-protein system where one component of β-lactamase is constitutively expressed in the cytoplasm of a stable cell line and the other component is delivered by a CPP. The delivery of a split β-lactamase component evaluates the cytosolic delivery capacity of a CPP. We demonstrate that these assays are rapid, flexible and have potential for use with any cell type and CPP sequence. Both assays are validated using canonical and novel CPPs, with limits of detection from <500 nM to 1 µM. Together, the β-lactamase assays provide compatible tools for functional characterization of CPP activity and the delivery of biological cargos into cells.

Expanding biological space coverage enhances the prediction of drug adverse effects in human using in vitro activity profiles

In vitro assay data have recently emerged as a potential alternative to traditional animal toxicity studies to aid in the prediction of adverse effects of chemicals on humans. Here we evaluate the data generated from a battery of quantitative high-throughput screening (qHTS) assays applied to a large and diverse collection of chemicals, including approved drugs, for their capacity in predicting human toxicity. Models were built with animal in vivo toxicity data, in vitro human cell-based assay data, as well as in combination with chemical structure and/or drug-target information to predict adverse effects observed for drugs in humans. Interestingly, we found that the models built with the human cell-based assay data performed close to those of the models based on animal in vivo toxicity data. Furthermore, expanding the biological space coverage of assays by including additional drug-target annotations was shown to significantly improve model performance. We identified a small set of targets, which, when added to the current suite of in vitro human cell-based assay data, result in models that greatly outperform those built with the existing animal toxicity data. Assays can be developed for this set of targets to screen compounds for construction of robust models for human toxicity prediction.

Identification of compounds that modulate retinol signaling using a cell-based qHTS assay

In vertebrates, the retinol (vitamin A) signaling pathway (RSP) controls the biosynthesis and catabolism of all-trans retinoic acid (atRA), which regulates transcription of genes essential for embryonic development. Chemicals that interfere with the RSP to cause abnormal intracellular levels of atRA are potential developmental toxicants. To assess chemicals for the ability to interfere with retinol signaling, we have developed a cell-based RARE (Retinoic Acid Response Element) reporter gene assay to identify RSP disruptors. To validate this assay in a quantitative high-throughput screening (qHTS) platform, we screened the Library of Pharmacologically Active Compounds (LOPAC) in both agonist and antagonist modes. The screens detected known RSP agonists, demonstrating assay reliability, and also identified novel RSP agonists including kenpaullone, niclosamide, PD98059 and SU4312, and RSP antagonists including Bay 11-7085, LY294002, 3,4-Methylenedioxy-β-nitrostyrene, and topoisomerase inhibitors (camptothecin, topotecan, amsacrine hydrochloride, and idarubicin). When evaluated in the P19 pluripotent cell, these compounds were found to affect the expression of the Hoxa1 gene that is essential for embryo body patterning. These results show that the RARE assay is an effective qHTS approach for screening large compound libraries to identify chemicals that have the potential to adversely affect embryonic development through interference with retinol signaling.

Paradigm shift in toxicity testing and modeling

The limitations of traditional toxicity testing characterized by high-cost animal models with low-throughput readouts, inconsistent responses, ethical issues, and extrapolability to humans call for alternative strategies for chemical risk assessment. A new strategy using in vitro human cell-based assays has been designed to identify key toxicity pathways and molecular mechanisms leading to the prediction of an in vivo response. The emergence of quantitative high-throughput screening (qHTS) technology has proved to be an efficient way to decompose complex toxicological end points to specific pathways of targeted organs. In addition, qHTS has made a significant impact on computational toxicology in two aspects. First, the ease of mechanism of action identification brought about by in vitro assays has enhanced the simplicity and effectiveness of machine learning, and second, the high-throughput nature and high reproducibility of qHTS have greatly improved the data quality and increased the quantity of training datasets available for predictive model construction. In this review, the benefits of qHTS routinely used in the US Tox21 program will be highlighted. Quantitative structure-activity relationships models built on traditional in vivo data and new qHTS data will be compared and analyzed. In conjunction with the transition from the pilot phase to the production phase of the Tox21 program, more qHTS data will be made available that will enrich the data pool for predictive toxicology. It is perceivable that new in silico toxicity models based on high-quality qHTS data will achieve unprecedented reliability and robustness, thus becoming a valuable tool for risk assessment and drug discovery.

Inhibition of morphine-induced cAMP overshoot: a cell-based assay model in a high-throughput format

Opiates are not only potent analgesics but also drugs of abuse mainly because they produce euphoria. Chronic use of opiates results in the development of tolerance and dependence. Dr Marshall Nirenberg's group at the National Institutes of Health (NIH) was the first to use a cellular model system of Neuroblastoma × Glioma hybrid cells (NG108-15) to study morphine addiction. They showed that opiates affect adenylyl cyclase (AC) by two opposing mechanisms mediated by the opiate receptor. Although the cellular mechanisms that cause addiction are not yet completely understood, the most observed correlative biochemical adaptation is the upregulation of AC. This model also provides the opportunity to look for compounds which could dissociate the acute effect of opiates from the delayed response, upregulation of AC, and thus lead to the discovery of non-addictive drugs. To identify small molecule compounds that can inhibit morphine-induced cAMP overshoot, we have validated and optimized a cell-based assay in a high throughput format that measures cellular cAMP production after morphine withdrawal. The assay performed well in the 1536-well plate format. The LOPAC library of 1,280 compounds was screened in this assay on a quantitative high-throughput screening (qHTS) platform. A group of compounds that can inhibit morphine-induced cAMP overshoot were identified. The most potent compounds are eight naloxone-related compounds, including levallorphan tartrate, naloxonazine dihydrochloride, naloxone hydrochloride, naltrexone hydrochloride, and naltriben methanesulfonate. The qHTS approach we used in this study will be useful in identifying novel inhibitors of morphine induced addiction from a larger scale screening.

Two High Throughput Screen Assays for Measurement of TNF-α in THP-1 Cells

Tumor Necrosis Factor-α (TNF-α), a secreted cytokine, plays an important role in inflammatory diseases and immune disorders, and is a potential target for drug development. The traditional assays for detecting TNF-α, enzyme linked immunosorbent assay (ELISA) and radioimmunoassay, are not suitable for the large size compound screens. Both assays suffer from a complicated protocol, multiple plate wash steps and/or excessive radioactive waste. A simple and quick measurement of TNF-α production in a cell based assay is needed for high throughput screening to identify the lead compounds from the compound library. We have developed and optimized two homogeneous TNF-α assays using the HTRF (homogeneous time resolved fluorescence) and AlphaLISA assay formats. We have validated the HTRF based TNF-α assay in a 1536-well plate format by screening a library of 1280 pharmacologically active compounds. The active compounds identified from the screen were confirmed in the AlphaLISA TNF-α assay using a bead-based technology. These compounds were also confirmed in a traditional ELISA assay. From this study, several beta adrenergic agonists have been identified as TNF-α inhibitors. We also identified several novel inhibitors of TNF-α, such as BTO-1, CCG-2046, ellipticine, and PD 169316. The results demonstrated that both homogeneous TNF-α assays are robust and suitable for high throughput screening.