High-Throughput Screening to Advance In Vitro Toxicology: Accomplishments, Challenges, and Future Directions.

Traditionally, chemical toxicity is determined by in vivo animal studies, which are low throughput, expensive, and sometimes fail to predict compound toxicity in humans. Due to the increasing number of chemicals in use and the high rate of drug candidate failure due to toxicity, it is imperative to develop in vitro, high-throughput screening methods to determine toxicity. The Tox21 program, a unique research consortium of federal public health agencies, was established to address and identify toxicity concerns in a high-throughput, concentration-responsive manner using a battery of in vitro assays. In this article, we review the advancements in high-throughput robotic screening methodology and informatics processes to enable the generation of toxicological data, and their impact on the field; further, we discuss the future of assessing environmental toxicity utilizing efficient and scalable methods that better represent the corresponding biological and toxicodynamic processes in humans.

Transcriptomic profiling in canines and humans reveals cancer specific gene modules and biological mechanisms common to both species.

Understanding relationships between spontaneous cancer in companion (pet) canines and humans can facilitate biomarker and drug development in both species. Towards this end we developed an experimental-bioinformatic protocol that analyzes canine transcriptomics data in the context of existing human data to evaluate comparative relevance of canine to human cancer. We used this protocol to characterize five canine cancers: melanoma, osteosarcoma, pulmonary carcinoma, B- and T-cell lymphoma, in 60 dogs. We applied an unsupervised, iterative clustering method that yielded five co-expression modules and found that each cancer exhibited a unique module expression profile. We constructed cancer models based on the co-expression modules and used the models to successfully classify the canine data. These canine-derived models also successfully classified human tumors representing the same cancers, indicating shared cancer biology between canines and humans. Annotation of the module genes identified cancer specific pathways relevant to cells-of-origin and tumor biology. For example, annotations associated with melanin production (PMEL, GPNMB, and BACE2), synthesis of bone material (COL5A2, COL6A3, and COL12A1), synthesis of pulmonary surfactant (CTSH, LPCAT1, and NAPSA), ribosomal proteins (RPL8, RPS7, and RPLP0), and epigenetic regulation (EDEM1, PTK2B, and JAK1) were unique to melanoma, osteosarcoma, pulmonary carcinoma, B- and T-cell lymphoma, respectively. In total, 152 biomarker candidates were selected from highly expressing modules for each cancer type. Many of these biomarker candidates are under-explored as drug discovery targets and warrant further study. The demonstrated transferability of classification models from canines to humans enforces the idea that tumor biology, biomarker targets, and associated therapeutics, discovered in canines, may translate to human medicine.

Stem Cell-Derived Endothelial Cell Model that Responds to Tobacco Smoke Like Primary Endothelial Cells.

To clarify how smoking leads to heart attack and stroke, we developed an endothelial cell model (iECs) generated from human induced Pluripotent Stem Cells (iPSC) and evaluated its responses to tobacco smoke. These iECs exhibited a uniform endothelial morphology, and expressed markers PECAM1/CD31, VWF/ von Willebrand Factor, and CDH5/VE-Cadherin. The iECs also exhibited tube formation and acetyl-LDL uptake comparable to primary endothelial cells (EC). RNA sequencing (RNA-Seq) revealed a robust correlation coefficient between iECs and EC (R = 0.76), whereas gene responses to smoke were qualitatively nearly identical between iECs and primary ECs (R = 0.86). Further analysis of transcriptional responses implicated 18 transcription factors in regulating responses to smoke treatment, and identified gene sets regulated by each transcription factor, including pathways for oxidative stress, DNA damage/repair, ER stress, apoptosis, and cell cycle arrest. Assays for 42 cytokines in HUVEC cells and iECs identified 23 cytokines that responded dynamically to cigarette smoke. These cytokines and cellular stress response pathways describe endothelial responses for lymphocyte attachment, activation of coagulation and complement, lymphocyte growth factors, and inflammation and fibrosis; EC-initiated events that collectively lead to atherosclerosis. Thus, these studies validate the iEC model and identify transcriptional response networks by which ECs respond to tobacco smoke. Our results systematically trace how ECs use these response networks to regulate genes and pathways, and finally cytokine signals to other cells, to initiate the diverse processes that lead to atherosclerosis and cardiovascular disease.

The Toxmatrix: Chemo-Genomic Profiling Identifies Interactions That Reveal Mechanisms of Toxicity.

A chemical genomics "Toxmatrix" method was developed to elucidate mechanisms of cytotoxicity using neuronal models. Quantitative high-throughput screening (qHTS) was applied to systematically screen each toxicant against a panel of 70 modulators, drugs or chemicals that act on a known target, to identify interactions that either protect or sensitize cells to each toxicant. Thirty-two toxicants were tested at 10 concentrations for cytotoxicity to SH-SY5Y human neuroblastoma cells, with results fitted to the Hill equation to determine an IC50 for each toxicant. Thirty-three toxicant:modulator interactions were identified in SH-SY5Y cells for 14 toxicants, as modulators that shifted toxicant IC50 values lower or higher. The target of each modulator that sensitizes cells or protects cells from a toxicant suggests a mode of toxicant action or cellular adaptation. In secondary screening, we tested modulator-toxicant pairs identified from the SH-SY5Y primary screening for interactions in three differentiated neuronal human cell lines: dSH-SY5Y, conditionally immortalized dopaminergic neurons (LUHMES), and neural stem cells. Twenty toxicant-modulator pairs showed pronounced interactions in one or several differentiated cell models. Additional testing confirmed that several modulators acted through their primary targets. For example, several chelators protected differentiated LUHMES neurons from four toxicants by chelation of divalent cations and buthionine sulphoximine sensitized cells to 6-hydroxydopamine and 4-(methylamino)phenol hemisulfate by blocking glutathione synthesis. Such modulators that interact with multiple neurotoxicants suggest these may be vulnerable toxicity pathways in neurons. Thus, the Toxmatrix method is a systematic high-throughput approach that can identify mechanisms of toxicity and cellular adaptation.

Characterization of three human cell line models for high-throughput neuronal cytotoxicity screening.

More than 75 000 man-made chemicals contaminate the environment; many of these have not been tested for toxicities. These chemicals demand quantitative high-throughput screening assays to assess them for causative roles in neurotoxicities, including Parkinson's disease and other neurodegenerative disorders. To facilitate high throughput screening for cytotoxicity to neurons, three human neuronal cellular models were compared: SH-SY5Y neuroblastoma cells, LUHMES conditionally-immortalized dopaminergic neurons, and Neural Stem Cells (NSC) derived from human fetal brain. These three cell lines were evaluated for rapidity and degree of differentiation, and sensitivity to 32 known or candidate neurotoxicants. First, expression of neural differentiation genes was assayed during a 7-day differentiation period. Of the three cell lines, LUHMES showed the highest gene expression of neuronal markers after differentiation. Both in the undifferentiated state and after 7 days of neuronal differentiation, LUHMES cells exhibited greater cytotoxic sensitivity to most of 32 suspected or known neurotoxicants than SH-SY5Y or NSCs. LUHMES cells were also unique in being more susceptible to several compounds in the differentiating state than in the undifferentiated state; including known neurotoxicants colchicine, methyl-mercury (II), and vincristine. Gene expression results suggest that differentiating LUHMES cells may be susceptible to apoptosis because they express low levels of anti-apoptotic genes BCL2 and BIRC5/survivin, whereas SH-SY5Y cells may be resistant to apoptosis because they express high levels of BCL2, BIRC5/survivin, and BIRC3 genes. Thus, LUHMES cells exhibited favorable characteristics for neuro-cytotoxicity screening: rapid differentiation into neurons that exhibit high level expression neuronal marker genes, and marked sensitivity of LUHMES cells to known neurotoxicants. Copyright © 2016 John Wiley & Sons, Ltd.

3D-Suspension culture platform for high throughput screening of neurotoxic chemicals using LUHMES dopaminergic neurons.

Three-dimensional (3D) cell culture in vitro promises to improve representation of neuron physiology in vivo. This inspired development of a 3D culture platform for LUHMES (Lund Human Mesencephalic) dopaminergic neurons for high-throughput screening (HTS) of chemicals for neurotoxicity. Three culture platforms, adhesion (2D-monolayer), 3D-suspension, and 3D-shaken, were compared to monitor mRNA expression of seven neuronal marker genes, DCX, DRD2, ENO2, NEUROD4, SYN1, TH, and TUBB3. These seven marker genes reached similar maxima in all three formats, with the two 3D platforms showing similar kinetics, whereas several markers peaked earlier in 2D adhesion compared to both 3D culture platforms. The differentiated LUHMES (dLUHMES) neurons treated with ziram, methylmercury or thiram dynamically increased expression of metallothionein biomarker genes MT1G, MT1E and MT2A at 6 h. These gene expression increases were generally more dynamic in 2D adhesion cultures than in 3D cultures, but were generally comparable between 3D-suspension and 3D-u plate (low binding) platforms. Finally, we adapted 3D-suspension culture of dLUHMES and neural stem cells to 1536 well plates with a HTS cytotoxicity assay. This HTS assay revealed that cytotoxicity IC50 values were not significantly different between adhesion and 3D-suspension platforms for 31 of 34 (91%) neurotoxicants tested, whereas IC50 values were significantly different for at least two toxicants. In summary, the 3D-suspension culture platform for LUHMES dopaminergic neurons supported full differentiation and reproducible assay results, enabling quantitative HTS (qHTS) for cytotoxicity in 1536 well format with a Robust Z' score of 0.68.

Better therapeutics through microarrays.

DNA microarrays are an integral part of the process for therapeutic discovery, optimization and clinical validation. At an early stage, investigators use arrays to prioritize a few genes as potential therapeutic targets on the basis of various criteria. Subsequently, gene expression analysis assists in drug discovery and toxicology by eliminating poor compounds and optimizing the selection of promising leads. Integral to this process is the use of sophisticated statistics, mathematics and bioinformatics to define statistically valid observations and to deduce complex patterns of phenotypes and biological pathways. In short, microarrays are redefining the drug discovery process by providing greater knowledge at each step and by illuminating the complex workings of biological systems.

Transcriptional profiling of canine osteosarcoma identifies prognostic gene expression signatures with translational value for humans.

Canine osteosarcoma is increasingly recognized as an informative model for human osteosarcoma. Here we show in one of the largest clinically annotated canine osteosarcoma transcriptional datasets that two previously reported, as well as de novo gene signatures devised through single sample Gene Set Enrichment Analysis (ssGSEA), have prognostic utility in both human and canine patients. Shared molecular pathway alterations are seen in immune cell signaling and activation including TH1 and TH2 signaling, interferon signaling, and inflammatory responses. Virtual cell sorting to estimate immune cell populations within canine and human tumors showed similar trends, predominantly for macrophages and CD8+ T cells. Immunohistochemical staining verified the increased presence of immune cells in tumors exhibiting immune gene enrichment. Collectively these findings further validate naturally occurring osteosarcoma of the pet dog as a translationally relevant patient model for humans and improve our understanding of the immunologic and genomic landscape of the disease in both species.

LUHMES Dopaminergic Neurons Are Uniquely Susceptible to Ferroptosis.

Ferroptosis is a necrotic cell death caused by lipid oxidation that may be responsible for neural degeneration in Parkinson's disease. We assessed whether three neuronal cell lines are sensitive to killing by ferroptosis. Ferroptosis inducer erastin killed LUHMES neurons at sub-micromolar concentrations, whereas neuronal cells derived from SH-SY5Y cells or neural stem cells were at least 50-fold less sensitive. LUHMES differentiated neurons were likewise sensitive to killing by RSL3 or ML210, inhibitors of the glutathione peroxidase 4 enzyme (GPX4) that consumes GSH to detoxify lipid peroxides. Additional assays showed that erastin, RSL3, and ML210 increased lipid peroxide levels, and that LUHMES neurons were protected from both peroxide accumulation and cell death by ferrostatin-1. A possible role of iron was assessed by evaluating the effects of five metal chelators on cytotoxicity of erastin and RSL3. LUHMES neurons were protected from RSL3 by three of the chelators, 2,3-dimercapto-1-propanesulfonic acid (DMPS), deferoxiprone (DFX), and deferiprone (DFP). Collectively, these results demonstrate the vulnerability of LUHMES neurons to ferroptosis by chemical treatments that disrupt glutathione synthesis, lipid peroxide detoxification, or iron metabolism. The same vulnerabilities may occur in CNS neurons, which reportedly generate low levels of GSH and metallothioneins, limiting their ability to neutralize oxidative stresses and toxic metals. These results suggest a rationale and methods to search for environmental toxicants that may exploit these vulnerabilities and promote neurodegenerative diseases.

Universal Toxicity Gene Signatures for Early Identification of Drug-Induced Tissue Injuries in Rats.

A new safety testing paradigm that relies on gene expression biomarker panels was developed to easily and quickly identify drug-induced injuries across tissues in rats prior to drug candidate selection. Here, we describe the development, qualification, and implementation of gene expression signatures that diagnose tissue degeneration/necrosis for use in early rat safety studies. Approximately 400 differentially expressed genes were first identified that were consistently regulated across 4 prioritized tissues (liver, kidney, heart, and skeletal muscle), following injuries induced by known toxicants. Hundred of these "universal" genes were chosen for quantitative PCR, and the most consistent and robustly responding transcripts selected, resulting in a final 22-gene set from which unique sets of 12 genes were chosen as optimal for each tissue. The approach was extended across 4 additional tissues (pancreas, gastrointestinal tract, bladder, and testes) where toxicities are less common. Mathematical algorithms were generated to convert each tissue's 12-gene expression values to a single metric, scaled between 0 and 1, and a positive threshold set. For liver, kidney, heart, and skeletal muscle, this was established using a training set of 22 compounds and performance determined by testing a set of approximately 100 additional compounds, resulting in 74%-94% sensitivity and 94%-100% specificity for liver, kidney, and skeletal muscle, and 54%-62% sensitivity and 95%-98% specificity for heart. Similar performance was observed across a set of 15 studies for pancreas, gastrointestinal tract, bladder, and testes. Bundled together, we have incorporated these tissue signatures into a 4-day rat study, providing a rapid assessment of commonly seen compound liabilities to guide selection of lead candidates without the necessity to perform time-consuming histopathologic analyses.

The MT1G Gene in LUHMES Neurons Is a Sensitive Biomarker of Neurotoxicity.

Identification of toxicants that underlie neurological diseases is a neglected area awaiting a valid strategy to identify such toxicants. We sought biomarkers that respond to known neurotoxicants in LUHMES immortalized neurons and evaluated these biomarkers for use in screening libraries of environmental toxicants. LUHMES immortalized human dopaminergic neurons were surveyed by RNA sequencing following challenge with parkinsonian toxicants rotenone, 6-hydroxydopamine, MPP+, and ziram (zinc dimethyldithiocarbamate; Zn2+DDC2), as well as additional toxicants paraquat, MS275, and methylmercury. The metallothionein gene MT1G was the most dynamic gene expression response to all seven toxicants. Multiple toxicants also increased transcripts for SLC30A1 and SLC30A2 zinc secretion transporters, the SLC7A11 xCT cystine/glutamate antiporter important for glutathione synthesis, DNA damage inducible transcript 3 (DDIT3), and secreted growth factors FIBIN and CXCL12, whereas several toxicants decreased expression of the apelin growth factor (APLN). These biomarker genes revealed stress responses to many toxicants at sub-cytotoxic concentrations. Since several of these biomarker genes and prior neurological disease studies implicated disruption of metal distribution, we tested metal chelator thiram (dimethyldithiocarbamate, DDC), ziram, and several other metals and metal chelates for cytotoxicity and induction of MT1G expression. Metals and chelators that caused dynamic increases in MT1G expression also caused cytotoxicity, except Ni2+DDC2 induced MT1G at 5 µM, but lacked cytotoxicity up to 100 µM. These results bolster prior work suggesting that neurons are characteristically sensitive to depletion of glutathione or to disruption of cellular metal distribution and provide biomarkers to search for such neurotoxicants in chemical libraries.

Phospholipidosis assay in HepG2 cells and rat or rhesus hepatocytes using phospholipid probe NBD-PE.

Phospholipidosis (PLD) is an accumulation of phospholipids in lysosome-derived multilamellar vesicles. More than 50 commercial drugs are known to cause PLD. In vitro screening assays were developed in HepG2 cells, rat primary hepatocytes, and rhesus monkey hepatocytes using the fluorescent-labeled phospholipid probe N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)-1,2-dihexadecanoyl-sn-glycero-3-phosphoethanolamine (NBD-PE) or Nile Red lipid stain. The assays were qualified using amiodarone and fluoxetine as positive controls and precocene and valproic acid as negative controls. NBD-PE accumulation and Nile Red staining were first measured using fluorescence microscopy with morphometric analysis, and the throughput of the NBD-PE assay in HepG2 cells was increased by measuring fluorescence with a multiwell spectrofluorometer. The PLD potential values obtained for the tested compounds from the morphometric analysis were similar to the values obtained from the spectrofluorometer, suggesting the plate reader assay was effective at measuring the induction of NBD-PE accumulation. Fifteen commercial compounds were evaluated using the NBD-PE assay in HepG2 cells, rat primary hepatocytes, and rhesus monkey hepatocytes. The relative NBD-PE accumulation and PLD potentials of the evaluated compounds were similar and comparable to the values observed from other in vitro PLD assays referenced in the literature using different probes and cell lines. NBD-PE accumulations observed in rat hepatocytes after drug treatments were similar to those in HepG2 cells. NBD-PE accumulation potential observed in rhesus monkey hepatocytes after drug treatment was different for tamoxifen, perhexiline, clomipramine, and haloperidol. These agents caused potent NBD-PE accumulation in HepG2 cells, but minimal or no activity was observed in rhesus monkey hepatocytes. These data suggest that the NBD-PE spectrofluorometer assay in HepG2 cells has the speed and throughput to sensitively and quantitatively determine the PLD potential of various drug candidates. In addition, these data demonstrate the species differences in PLD potential between rat and monkey hepatocytes.

A hybrid gene selection approach to create the S1500+ targeted gene sets for use in high-throughput transcriptomics.

Changes in gene expression can help reveal the mechanisms of disease processes and the mode of action for toxicities and adverse effects on cellular responses induced by exposures to chemicals, drugs and environment agents. The U.S. Tox21 Federal collaboration, which currently quantifies the biological effects of nearly 10,000 chemicals via quantitative high-throughput screening(qHTS) in in vitro model systems, is now making an effort to incorporate gene expression profiling into the existing battery of assays. Whole transcriptome analyses performed on large numbers of samples using microarrays or RNA-Seq is currently cost-prohibitive. Accordingly, the Tox21 Program is pursuing a high-throughput transcriptomics (HTT) method that focuses on the targeted detection of gene expression for a carefully selected subset of the transcriptome that potentially can reduce the cost by a factor of 10-fold, allowing for the analysis of larger numbers of samples. To identify the optimal transcriptome subset, genes were sought that are (1) representative of the highly diverse biological space, (2) capable of serving as a proxy for expression changes in unmeasured genes, and (3) sufficient to provide coverage of well described biological pathways. A hybrid method for gene selection is presented herein that combines data-driven and knowledge-driven concepts into one cohesive method. Our approach is modular, applicable to any species, and facilitates a robust, quantitative evaluation of performance. In particular, we were able to perform gene selection such that the resulting set of "sentinel genes" adequately represents all known canonical pathways from Molecular Signature Database (MSigDB v4.0) and can be used to infer expression changes for the remainder of the transcriptome. The resulting computational model allowed us to choose a purely data-driven subset of 1500 sentinel genes, referred to as the S1500 set, which was then augmented using a knowledge-driven selection of additional genes to create the final S1500+ gene set. Our results indicate that the sentinel genes selected can be used to accurately predict pathway perturbations and biological relationships for samples under study.

Comprehensive Analyses and Prioritization of Tox21 10K Chemicals Affecting Mitochondrial Function by in-Depth Mechanistic Studies.

BACKGROUND: A central challenge in toxicity testing is the large number of chemicals in commerce that lack toxicological assessment. In response, the Tox21 program is re-focusing toxicity testing from animal studies to less expensive and higher throughput in vitro methods using target/pathway-specific, mechanism-driven assays. OBJECTIVES: Our objective was to use an in-depth mechanistic study approach to prioritize and characterize the chemicals affecting mitochondrial function. METHODS: We used a tiered testing approach to prioritize for more extensive testing 622 compounds identified from a primary, quantitative high-throughput screen of 8,300 unique small molecules, including drugs and industrial chemicals, as potential mitochondrial toxicants by their ability to significantly decrease the mitochondrial membrane potential (MMP). Based on results from secondary MMP assays in HepG2 cells and rat hepatocytes, 34 compounds were selected for testing in tertiary assays that included formation of reactive oxygen species (ROS), upregulation of p53 and nuclear erythroid 2-related factor 2/antioxidant response element (Nrf2/ARE), mitochondrial oxygen consumption, cellular Parkin translocation, and larval development and ATP status in the nematode Caenorhabditis elegans. RESULTS: A group of known mitochondrial complex inhibitors (e.g., rotenone) and uncouplers (e.g., chlorfenapyr), as well as potential novel complex inhibitors and uncouplers, were detected. From this study, we identified four not well-characterized potential mitochondrial toxicants (lasalocid, picoxystrobin, pinacyanol, and triclocarban) that merit additional in vivo characterization. CONCLUSIONS: The tier-based approach for identifying and mechanistically characterizing mitochondrial toxicants can potentially reduce animal use in toxicological testing. https://doi.org/10.1289/EHP2589.

Diagnosis of drug-induced renal tubular toxicity using global gene expression profiles.

Toxicogenomics can measure the expression of thousands of genes to identify changes associated with drug induced toxicities. It is expected that toxicogenomics can be an alternative or complementary approach in preclinical drug safety evaluation to identify or predict drug induced toxicities. One of the major concerns in applying toxicogenomics to diagnose or predict drug induced organ toxicity, is how generalizable the statistical classification model is when derived from small datasets? Here we presented that a diagnosis of kidney proximal tubule toxicity, measured by pathology, can successfully be achieved even with a study design of limited number of training studies or samples. We selected a total of ten kidney toxicants, designed the in life study with multiple dose and multiple time points to cover samples at doses and time points with or without concurrent toxicity. We employed SVM (Support Vector Machine) as the classification algorithm for the toxicogenomic diagnosis of kidney proximal tubule toxicity. Instead of applying cross validation methods, we used an independent testing set by dividing the studies or samples into independent training and testing sets to evaluate the diagnostic performance. We achieved a Sn (sensitivity) = 88% and a Sp (specificity) = 91%. The diagnosis performance underscores the potential application of toxicogenomics in a preclinical lead optimization process of drugs entering into development.

Good Cell Culture Practice for stem cells and stem-cell-derived models.

The first guidance on Good Cell Culture Practice (GCCP) dates back to 2005. This document expands this to include aspects of quality assurance for in vitro cell culture focusing on the increasingly diverse cell types and culture formats used in research, product development, testing and manufacture of biotechnology products and cell-based medicines. It provides a set of basic principles of best practice that can be used in training new personnel, reviewing and improving local procedures, and helping to assure standard practices and conditions for the comparison of data between laboratories and experimentation performed at different times. This includes recommendations for the documentation and reporting of culture conditions. It is intended as guidance to facilitate the generation of reliable data from cell culture systems, and is not intended to conflict with local or higher level legislation or regulatory requirements. It may not be possible to meet all recommendations in this guidance for practical, legal or other reasons. However, when it is necessary to divert from the principles of GCCP, the risk of decreasing the quality of work and the safety of laboratory staff should be addressed and any conclusions or alternative approaches justified. This workshop report is considered a first step toward a revised GCCP 2.0.

A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives.

Comparative assessment of potential human health impacts is a critical step in evaluating both chemical alternatives and existing products on the market. Most alternatives assessments are conducted on a chemical-by-chemical basis and it is seldom acknowledged that humans are exposed to complex products, not individual substances. Indeed, substances of Unknown or Variable composition, Complex reaction products, and Biological materials (UVCBs) are ubiquitous in commerce yet they present a major challenge for registration and health assessments. Here, we present a comprehensive experimental and computational approach to categorize UVCBs according to global similarities in their bioactivity using a suite of in vitro models. We used petroleum substances, an important group of UVCBs which are grouped for regulatory approval and read-across primarily on physico-chemical properties and the manufacturing process, and only partially based on toxicity data, as a case study. We exposed induced pluripotent stem cell-derived cardiomyocytes and hepatocytes to DMSO-soluble extracts of 21 petroleum substances from five product groups. Concentration-response data from high-content imaging in cardiomyocytes and hepatocytes, as well as targeted high-throughput transcriptomic analysis of the hepatocytes, revealed distinct groups of petroleum substances. Data integration showed that bioactivity profiling affords clustering of petroleum substances in a manner similar to the manufacturing process-based categories. Moreover, we observed a high degree of correlation between bioactivity profiles and physico-chemical properties, as well as improved groupings when chemical and biological data were combined. Altogether, we demonstrate how novel in vitro screening approaches can be effectively utilized in combination with physico-chemical characteristics to group complex substances and enable read-across. This approach allows for rapid and scientifically-informed evaluation of health impacts of both existing substances and their chemical alternatives.

Androgenic induction of growth and differentiation in the rodent uterus involves the modulation of estrogen-regulated genetic pathways.

The androgen receptor (AR) is expressed in the uterus; however, the role of AR in female reproductive physiology is poorly understood. Here we examined the effects of androgens on uterine growth and gene expression in adult ovariectomized rats. Nonaromatizable AR-selective agonists potently stimulate hypertrophy and induce significant myometrial expansion distinct from that induced by 17beta-estradiol (E2). In the endometrium, androgens only modestly increase epithelial cell height and antagonize the trophic effects of E2. To identify underlying mechanisms, global changes in RNA levels 24 h after stimulation with E2 and 5alpha-dihydrotestosterone (DHT) were compared. A total of 491 genes were differentially expressed after E2 treatment, including key regulators of tissue remodeling, cell signaling, metabolism, and gene expression. Of the 164 transcripts regulated by DHT, 86% were also affected by E2, including trophic genes like IGF-I and epithelial secretory genes such as uterocalin. In estrogen receptor (ER)alpha knockout mice, DHT cannot induce uterine growth, suggesting a key role for ERalpha. However, DHT appears not to activate ERalpha directly because DHT induction of IGF-I is blocked by the AR antagonist bicalutamide, and multiple genes regulated directly by ERalpha were not induced by DHT. The similarity between estrogens and androgens instead could reflect general trophic signaling in reproductive tissues because 93 of the 503 genes regulated in the uterus are similarly affected during prostate growth. Thus androgens regulate the trophic environment and architecture of the rodent uterus via a gene expression program that is overlapping but distinct from the estrogen response.

Identification of new human cadherin genes using a combination of protein motif search and gene finding methods.

We have combined protein motif search and gene finding methods to identify genes encoding proteins containing specific domains. Particularly, we have focused on finding new human genes of the cadherin superfamily proteins, which represent a major group of cell-cell adhesion receptors contributing to embryonic neuronal morphogenesis. Models for three cadherin protein motifs were generated from over 100 already annotated cadherin domains and used to search the complete translated human genome. The genomic sequence regions containing motif "hits" were analyzed by eukaryotic GeneMark.hmm to identify the exon-intron structure of new genes. Three new genes CDH-J, PCDH-J and FAT-J were found. The predicted proteins PCDH-J and FAT-J were classified into protocadherin and FAT-like subfamilies, respectively, based on the number and organization of cadherin domains and presence of subfamily-specific conserved amino acid residues. Expression of FAT-J was shown in almost all tested tissues. The exon-intron organization of CDH-J was experimentally verified by PCR with specifically designed primers and its tissue-specific expression was demonstrated. The described methodology can be applied to discover new genes encoding proteins from families with well-characterized structural and functional domains.