Advanced biological and chemical discovery (ABCD): centralizing discovery knowledge in an inherently decentralized world.

We present ABCD, an integrated drug discovery informatics platform developed at Johnson & Johnson Pharmaceutical Research & Development, L.L.C. ABCD is an attempt to bridge multiple continents, data systems, and cultures using modern information technology and to provide scientists with tools that allow them to analyze multifactorial SAR and make informed, data-driven decisions. The system consists of three major components: (1) a data warehouse, which combines data from multiple chemical and pharmacological transactional databases, designed for supreme query performance; (2) a state-of-the-art application suite, which facilitates data upload, retrieval, mining, and reporting, and (3) a workspace, which facilitates collaboration and data sharing by allowing users to share queries, templates, results, and reports across project teams, campuses, and other organizational units. Chemical intelligence, performance, and analytical sophistication lie at the heart of the new system, which was developed entirely in-house. ABCD is used routinely by more than 1000 scientists around the world and is rapidly expanding into other functional areas within the J&J organization.

Predictive toxicogenomics approaches reveal underlying molecular mechanisms of nongenotoxic carcinogenicity.

Toxicogenomics technology defines toxicity gene expression signatures for early predictions and hypotheses generation for mechanistic studies, which are important approaches for evaluating toxicity of drug candidate compounds. A large gene expression database built using cDNA microarrays and liver samples treated with over one hundred paradigm compounds was mined to determine gene expression signatures for nongenotoxic carcinogens (NGTCs). Data were obtained from male rats treated for 24 h. Training/testing sets of 24 NGTCs and 28 noncarcinogens were used to select genes. A semiexhaustive, nonredundant gene selection algorithm yielded six genes (nuclear transport factor 2, NUTF2; progesterone receptor membrane component 1, Pgrmc1; liver uridine diphosphate glucuronyltransferase, phenobarbital-inducible form, UDPGTr2; metallothionein 1A, MT1A; suppressor of lin-12 homolog, Sel1h; and methionine adenosyltransferase 1, alpha, Mat1a), which identified NGTCs with 88.5% prediction accuracy estimated by cross-validation. This six genes signature set also predicted NGTCs with 84% accuracy when samples were hybridized to commercially available CodeLink oligo-based microarrays. To unveil molecular mechanisms of nongenotoxic carcinogenesis, 125 differentially expressed genes (P<0.01) were selected by Student's t-test. These genes appear biologically relevant, of 71 well-annotated genes from these 125 genes, 62 were overrepresented in five biochemical pathway networks (most linked to cancer), and all of these networks were linked by one gene, c-myc. Gene expression profiling at early time points accurately predicts NGTC potential of compounds, and the same data can be mined effectively for other toxicity signatures. Predictive genes confirm prior work and suggest pathways critical for early stages of carcinogenesis.

Drug-induced oxidative stress in rat liver from a toxicogenomics perspective.

Macrophage activators (MA), peroxisome proliferators (PP), and oxidative stressors/reactive metabolites (OS/RM) all produce oxidative stress and hepatotoxicity in rats. However, these three classes of hepatotoxicants give three distinct gene transcriptional profiles on cDNA microarrays, an indication that rat hepatocytes respond/adapt quite differently to these three classes of oxidative stressors. The differential gene responses largely reflect differential activation of transcription factors: MA activate Stat-3 and NFkB, PP activate PPARa, and OS/RM activate Nrf2. We have used gene signature profiles for each of these three classes of hepatotoxicants to categorize over 100 paradigm (and 50+ in-house proprietary) compounds as to their oxidative stress potential in rat liver. In addition to a role for microarrays in predictive toxicology, analyses of small subsets of these signature profiles, genes within a specific pathway, or even single genes often provide important insights into possible mechanisms involved in the toxicities of these compounds.

A gene expression signature for oxidant stress/reactive metabolites in rat liver.

Formation of free radicals and other reactive molecules is responsible for the adverse effects produced by a number of hepatotoxic compounds. cDNA microarray technology was used to compare transcriptional profiles elicited by training and testing sets of 15 oxidant stressors/reactive metabolite treatments to those produced by approximately 85 other paradigm compounds (mostly hepatotoxicants) to determine a shared signature profile for oxidant stress-associated hepatotoxicity. Initially, 100 genes were chosen that responded significantly different to oxidant stressors/reactive metabolites (OS/RM) compared to other samples in the database, then a 25-gene subset was selected by multivariate analysis. Many of the selected genes (e.g., aflatoxin aldehyde reductase, diaphorase, epoxide hydrolase, heme oxgenase and several glutathione transferases) are well-characterized oxidant stress/Nrf-2-responsive genes. Less than 10 other compounds co-cluster with our training and testing set compounds and these are known to generate OS/RMs as part of their mechanisms of toxicity. Using OS/RM signature gene sets, compounds previously associated with macrophage activation formed a distinct cluster separate from OS/RM and other compounds. A 69-gene set was chosen to maximally separate compounds in control, macrophage activator, peroxisome proliferator and OS/RM classes. The ease with which these 'oxidative stressor' classes can be separated indicates a role for microarray technology in early prediction and classification of hepatotoxicants. The ability to rapidly screen the oxidant stress potential of compounds may aid in avoidance of some idiosyncratic drug reactions as well as overtly toxic compounds.

Dynamic integration of gene annotation and its application to microarray analysis.

Comprehensive and structured annotations for all genes on a microarray chip are essential for the interpretation of its expression data. Currently, most chip gene annotations are one-line free text descriptions that are often partial, outdated and unsuitable for large-scale data analysis. Therefore the interpretation of microarray gene expression clusters is often limited. Although researchers can manually navigate a collection of databases for better annotations, it is only practical for limited number of genes. Existing meta-databases fail to provide comprehensive categorized annotations for hundreds of genes simultaneously. We have developed an automatic system to address this issue. GeneView system monitors various data sources, extracts gene information from a source whenever it is updated, comprehensively matches genes, and integrates them into a central database by categories, such as pathway, genetic mapping, phenotype, expression profile, domain structure, protein interaction, disease association, and references. The system consists of four major components: (1) relational database; (2) data processing; (3) user curation; (4) data query. We evaluated it by analyzing genes on cDNA and Affymetrix Oligo chips. In both cases, the system provided more accurate and comprehensive information than those provided by the vendors or the chip users, and helped identify new common functions among genes in the same expression clusters.

Induction of dendritic cell maturation by IL-18.

IL-18 is a pluripotent proinflammatory cytokine produced primarily by antigen presenting cells involved in numerous aspects of immune regulation most notably on lymphoid cells. The effect of IL-18 stimulation on cells in the myeloid compartment, however, has been poorly studied. Human monocytes did not respond to IL-18. However, the human myelomonocytic cell line KG-1 and monocyte-derived dendritic cells (generated by GM-CSF+IL-4) showed a marked increase in CD83, HLA-DR, and several costimulatory molecules upon stimulation with IL-18. Furthermore, IL-18 decreased pinocytosis of these cells and increased their ability to stimulate alloreactive T cell proliferation, all characteristics of mature dendritic cells. These results suggest that IL-18 is involved in the maturation of myeloid DCs, but not differentiation of monocytes into DCs. The finding that IL-18 is involved in the maturation of dendritic cells is both novel and unexpected and indicates another important role for IL-18 as a key regulator of immune responses.

Inverse gene expression patterns for macrophage activating hepatotoxicants and peroxisome proliferators in rat liver.

Macrophage activation contributes to adverse effects produced by a number of hepatotoxic compounds. Transcriptional profiles elicited by two macrophage activators, LPS and zymosan A, were compared to those produced by 100 paradigm compounds (mostly hepatotoxicants) using cDNA microarrays. Several hepatotoxicants previously reported to activate liver macrophages produced transcriptional responses similar to LPS and zymosan, and these were used to construct a gene signature profile for macrophage activators in the liver. Measurement of cytokine mRNAs in the same liver samples by RT-PCR independently confirmed that these compounds are associated with macrophage activation. In addition to expected effects on acute phase proteins and metabolic pathways that are regulated by LPS and inflammation, a strong induction was observed for many endoplasmic reticulum-associated stress/chaperone proteins. Additionally, many genes in our macrophage activator signature profile were well-characterized PPARalpha-induced genes which were repressed by macrophage activators. A shared gene signature profile for peroxisome proliferators was determined using a training set of clofibrate, WY 14643, diethylhexylphthalate, diisononylphthalate, perfluorodecanoic acid, perfluoroheptanoic acid, and perfluorooctanoic acid. The signature profile included macrophage activator-induced genes that were repressed by peroxisome proliferators. NSAIDs comprised an interesting pharmacological class in that some compounds, notably diflunisal, co-clustered with peroxisome proliferators whereas several others co-clustered with macrophage activators, possibly due to endotoxin exposure secondary to their adverse effects on the gastrointestinal system. While much of these data confirmed findings from the literature, the transcriptional patterns detected using this toxicogenomics approach showed relationships between genes and biological pathways requiring complex analysis to be discerned.

Single-cell laser-capture microdissection and RNA amplification.

Generating gene-expression profiles from laser-captured cells requires the successful combination of laser-capture microdissection, RNA extraction, RNA amplification, and microarray analysis. To permit single-cell gene-expression profiling, the RNA amplification method has to be sufficiently powerful to bridge the gap between the amount of RNA available from a single cell to what is required by the microarray, a gap that spans 5 to 6 orders of magnitude. This chapter focuses on the amplification of RNA using a two-round T7 RNA amplification method. The protocols described are adapted for laser-captured material and have been used to generate gene expression profiles from single laser-captured cells.

Single-cell microarray analysis in hippocampus CA1: demonstration and validation of cellular heterogeneity.

Laser capture microdissection in combination with microarrays allows for the expression analysis of thousands of genes in selected cells. Here we describe single-cell gene expression profiling of CA1 neurons in the rat hippocampus using a combination of laser capture, T7 RNA amplification, and cDNA microarray analysis. Subsequent cluster analysis of the microarray data identified two different cell types: pyramidal neurons and an interneuron. Cluster analysis also revealed differences among the pyramidal neurons, indicating that even a single cell type in vivo is not a homogeneous population of cells at the gene expression level. Microarray data were confirmed by quantitative RT-PCR and in situ hybridization. We also report on the reproducibility and sensitivity of this combination of methods. Single-cell gene expression profiling offers a powerful tool to tackle the complexity of the mammalian brain.

Comparison of the changes in global gene expression of Escherichia coli induced by four bactericidal agents.

DNA microarrays provide a global view of the physiological state of the cell by parallel analysis of the expression levels of all the genes in an organism. The effects of four bactericidal agents on the expression pattern of Escherichia coli MG1655 were assessed. Compounds were chosen on the basis of their different mechanisms of action and included inhibitors of DNA replication and recombination, translation, transcription and cell wall biosynthesis. The addition of rifampin resulted in increased expression of the target, rpoB, as well as several genes involved in nucleotide salvage and purine biosynthesis. The addition of ampicillin resulted in overall changes in gene expression that showed some similarity to changes induced by rifampin. The addition of the antibiotics kanamycin or norfloxacin resulted in the induction of unique gene expression signatures: a heat shock response to kanamycin and an SOS response to norfloxacin. Several genes of unknown function showed expression profiles similar to the genes associated with the SOS or the heat shock response. Thus, these profiles define families of genes with similar expression phenotypes that can be tested for related function.

Identification of genes with differential regulation in primate endometrium during the proliferative and secretory phases of the cycle.

To study gene expression in the endometrium at different stages of the menstrual cycle, differential mRNA display and reverse Northern analysis were performed on uterine tissues from cynomolgus monkeys. Eutopic endometrial RNA was prepared from uteri of animals that were either ovariectomized and supplemented with hormones, or were not ovariectomized but were subjected to surgically induced endometriosis. A number of genes were identified whose levels fluctuated between the proliferative and secretory phases of the cycle. Expression of four genes thus identified was further examined by in situ hybridization to normal human endometrial biopsies. Iodothyronine deiodinase was uniformly expressed at all stages of the human cycle that were studied: proliferative, secretory, and menstrual. Fibulin 1, osteopontin, and cathepsin H exhibited complex temporal and spatial regulation. Fibulin 1 was expressed in glandular epithelia during the menstrual phase, but expression switched to the stroma during the secretory phase. During the menstrual phase, osteopontin was expressed at high levels in glandular epithelia and in isolated stromal cells that may be of immune origin. Secretory phase expression of osteopontin was confined to a sub-population of epithelial cells. Cathepsin H was expressed in proliferative and menstrual phase endometrium, but expression disappeared in the secretory phase. Messenger RNA for fibulin 1, osteopontin, and iodothyronine deiodinase was detected in an endometriosis sample. Our data support functional roles for fibulin 1, osteopontin, cathepsin H and thyroid hormone in endometrium.