High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures.

The ToxCast in vitro screening program has provided concentration-response bioactivity data across more than a thousand assay endpoints for thousands of chemicals found in our environment and commerce. However, most ToxCast screening assays have evaluated individual biological targets in cancer cell lines lacking integrated physiological functionality (such as receptor signaling, metabolism). We evaluated differentiated HepaRGTM cells, a human liver-derived cell model understood to effectively model physiologically relevant hepatic signaling. Expression of 93 gene transcripts was measured by quantitative polymerase chain reaction using Fluidigm 96.96 dynamic arrays in response to 1060 chemicals tested in eight-point concentration-response. A Bayesian framework quantitatively modeled chemical-induced changes in gene expression via six transcription factors including: aryl hydrocarbon receptor, constitutive androstane receptor, pregnane X receptor, farnesoid X receptor, androgen receptor, and peroxisome proliferator-activated receptor alpha. For these chemicals the network model translates transcriptomic data into Bayesian inferences about molecular targets known to activate toxicological adverse outcome pathways. These data also provide new insights into the molecular signaling network of HepaRGTM cell cultures.

Design, Optimization, and Multisite Evaluation of a Targeted Next-Generation Sequencing Assay System for Chimeric RNAs from Gene Fusions and Exon-Skipping Events in Non-Small Cell Lung Cancer.

Lung cancer accounts for approximately 14% of all newly diagnosed cancers and is the leading cause of cancer-related deaths. Chimeric RNA resulting from gene fusions (RNA fusions) and other RNA splicing errors are driver events and clinically addressable targets for non-small cell lung cancer (NSCLC). The reliable assessment of these RNA markers by next-generation sequencing requires integrated reagents, protocols, and interpretive software that can harmonize procedures and ensure consistent results across laboratories. We describe the development and verification of a system for targeted RNA sequencing for the analysis of challenging, low-input solid tumor biopsies that includes reagents for nucleic acid quantification and library preparation, run controls, and companion bioinformatics software. Assay development reconciled sequence discrepancies in public databases, created predictive formalin-fixed, paraffin-embedded RNA qualification metrics, and eliminated read misidentification attributable to index hopping events on the next-generation sequencing flow cell. The optimized and standardized system was analytically verified internally and in a multiphase study conducted at five independent laboratories. The results show accurate, reproducible, and sensitive detection of RNA fusions, alternative splicing events, and other expression markers of NSCLC. This comprehensive approach, combining sample quantification, quality control, library preparation, and interpretive bioinformatics software, may accelerate the routine implementation of targeted RNA sequencing of formalin-fixed, paraffin-embedded samples relevant to NSCLC.

Validation of a real-time PCR-based qualitative assay for the detection of methylated SEPT9 DNA in human plasma.

BACKGROUND: Epi proColon® is a new blood-based colorectal cancer (CRC) screening test designed to determine the methylation status of a promoter region of the SEPT9 (septin 9) gene in cell-free DNA isolated from plasma. We describe the analytical and clinical performance of the test. METHODS: Analytical performance at 4 testing laboratories included determination of limit of detection, precision, and reproducibility of the SEPT9 test. Clinical performance was evaluated in a prospective study by use of samples (n = 1544) from subjects enrolled in the PRESEPT clinical trial. Results were analyzed by comparison with colonoscopy, the reference standard. RESULTS: The limit of detection for methylated SEPT9 DNA was 7.8 pg/mL (95% CI 6-11 pg/mL) corresponding to <2 genome copies of methylated SEPT9 per milliliter of plasma. In the prospective clinical trial, sensitivity for all stages of CRC was 68% (95% CI 53%-80%) and for stage I-III CRC, 64% (48%-77%). Adjusted specificity, on the basis of negative colonoscopy findings, was 80.0% (78%-82%). SIGNIFICANCE: The Epi proColon test is a simple, real-time PCR-based assay for the detection of methylated SEPT9 DNA in blood that may provide a noninvasive CRC screening alternative for people noncompliant with current CRC screening guidelines.

Efficient and accurate whole genome assembly and methylome profiling of E. coli.

BACKGROUND: With the price of next generation sequencing steadily decreasing, bacterial genome assembly is now accessible to a wide range of researchers. It is therefore necessary to understand the best methods for generating a genome assembly, specifically, which combination of sequencing and bioinformatics strategies result in the most accurate assemblies. Here, we sequence three E. coli strains on the Illumina MiSeq, Life Technologies Ion Torrent PGM, and Pacific Biosciences RS. We then perform genome assemblies on all three datasets alone or in combination to determine the best methods for the assembly of bacterial genomes. RESULTS: Three E. coli strains - BL21(DE3), Bal225, and DH5α - were sequenced to a depth of 100× on the MiSeq and Ion Torrent machines and to at least 125× on the PacBio RS. Four assembly methods were examined and compared. The previously published BL21(DE3) genome [GenBank:AM946981.2], allowed us to evaluate the accuracy of each of the BL21(DE3) assemblies. BL21(DE3) PacBio-only assemblies resulted in a 90% reduction in contigs versus short read only assemblies, while N50 numbers increased by over 7-fold. Strikingly, the number of SNPs in PacBio-only assemblies were less than half that seen with short read assemblies (~20 SNPs vs. ~50 SNPs) and indels also saw dramatic reductions (~2 indel >5 bp in PacBio-only assemblies vs. ~12 for short-read only assemblies). Assemblies that used a mixture of PacBio and short read data generally fell in between these two extremes. Use of PacBio sequencing reads also allowed us to call covalent base modifications for the three strains. Each of the strains used here had a known covalent base modification genotype, which was confirmed by PacBio sequencing. CONCLUSION: Using data generated solely from the Pacific Biosciences RS, we were able to generate the most complete and accurate de novo assemblies of E. coli strains. We found that the addition of other sequencing technology data offered no improvements over use of PacBio data alone. In addition, the sequencing data from the PacBio RS allowed for sensitive and specific calling of covalent base modifications.

A newly-developed community microarray resource for transcriptome profiling in Brassica species enables the confirmation of Brassica-specific expressed sequences.

BACKGROUND: The Brassica species include an important group of crops and provide opportunities for studying the evolutionary consequences of polyploidy. They are related to Arabidopsis thaliana, for which the first complete plant genome sequence was obtained and their genomes show extensive, although imperfect, conserved synteny with that of A. thaliana. A large number of EST sequences, derived from a range of different Brassica species, are available in the public database, but no public microarray resource has so far been developed for these species. RESULTS: We assembled unigenes using approximately 800,000 EST sequences, mainly from three species: B. napus, B. rapa and B. oleracea. The assembly was conducted with the aim of co-assembling ESTs of orthologous genes (including homoeologous pairs of genes in B. napus from each of the A and C genomes), but resolving assemblies of paralogous, or paleo-homoeologous, genes (i.e. the genes related by the ancestral genome triplication observed in diploid Brassica species). 90,864 unique sequence assemblies were developed. These were incorporated into the BAC sequence annotation for the Brassica rapa Genome Sequencing Project, enabling the identification of cognate genomic sequences for a proportion of them. A 60-mer oligo microarray comprising 94,558 probes was developed using the unigene sequences. Gene expression was analysed in reciprocal resynthesised B. napus lines and the B. oleracea and B. rapa lines used to produce them. The analysis showed that significant expression could consistently be detected in leaf tissue for 35,386 unigenes. Expression was detected across all four genotypes for 27,355 unigenes, genome-specific expression patterns were observed for 7,851 unigenes and 180 unigenes displayed other classes of expression pattern. Principal component analysis (PCA) clearly resolved the individual microarray datasets for B. rapa, B. oleracea and resynthesised B. napus. Quantitative differences in expression were observed between the resynthesised B. napus lines for 98 unigenes, most of which could be classified into non-additive expression patterns, including 17 that showed cytoplasm-specific patterns. We further characterized the unigenes for which A genome-specific expression was observed and cognate genomic sequences could be identified. Ten of these unigenes were found to be Brassica-specific sequences, including two that originate from complex loci comprising gene clusters. CONCLUSION: We succeeded in developing a Brassica community microarray resource. Although expression can be measured for the majority of unigenes across species, there were numerous probes that reported in a genome-specific manner. We anticipate that some proportion of these will represent species-specific transcripts and the remainder will be the consequence of variation of sequences within the regions represented by the array probes. Our studies demonstrated that the datasets obtained from the arrays can be used for typical analyses, including PCA and the analysis of differential expression. We have also demonstrated that Brassica-specific transcripts identified in silico in the sequence assembly of public EST database accessions are indeed reported by the array. These would not be detectable using arrays designed using A. thaliana sequences.

Gene expression response in target organ and whole blood varies as a function of target organ injury phenotype.

This report details the standardized experimental design and the different data streams that were collected (histopathology, clinical chemistry, hematology and gene expression from the target tissue (liver) and a bio-available tissue (blood)) after treatment with eight known hepatotoxicants (at multiple time points and doses with multiple biological replicates). The results of the study demonstrate the classification of histopathological differences, likely reflecting differences in mechanisms of cell-specific toxicity, using either liver tissue or blood transcriptomic data.

Multicenter study of acetaminophen hepatotoxicity reveals the importance of biological endpoints in genomic analyses.

Gene expression profiling is a widely used technique with data from the majority of published microarray studies being publicly available. These data are being used for meta-analyses and in silico discovery; however, the comparability of toxicogenomic data generated in multiple laboratories has not been critically evaluated. Using the power of prospective multilaboratory investigations, seven centers individually conducted a common toxicogenomics experiment designed to advance understanding of molecular pathways perturbed in liver by an acute toxic dose of N-acetyl-p-aminophenol (APAP) and to uncover reproducible genomic signatures of APAP-induced toxicity. The nonhepatotoxic APAP isomer N-acetyl-m-aminophenol was used to identify gene expression changes unique to APAP. Our data show that c-Myc is induced by APAP and that c-Myc-centered interactomes are the most significant networks of proteins associated with liver injury. Furthermore, sources of error and data variability among Centers and methods to accommodate this variability were identified by coupling gene expression with extensive toxicological evaluation of the toxic responses. We show that phenotypic anchoring of gene expression data is required for biologically meaningful analysis of toxicogenomic experiments.

Identification of primary transcriptional regulation of cell cycle-regulated genes upon DNA damage.

The changes in global gene expression in response to DNA damage may derive from either direct induction or repression by transcriptional regulation or indirectly by synchronization of cells to specific cell cycle phases, such as G1 or G2. We developed a model that successfully estimated the expression levels of >400 cell cycle-regulated genes in normal human fibroblasts based on the proportions of cells in each phase of the cell cycle. By isolating effects on the gene expression associated with the cell cycle phase redistribution after genotoxin treatment, the direct transcriptional target genes were distinguished from genes for which expression changed secondary to cell synchronization. Application of this model to ionizing radiation (IR)-treated normal human fibroblasts identified 150 of 406 cycle-regulated genes as putative direct transcriptional targets of IR-induced DNA damage. Changes in expression of these genes after IR treatment derived from both direct transcriptional regulation and cell cycle synchronization.

Application of visualization tools to the analysis of histopathological data enhances biological insight and interpretation.

Gene expression profiling, metabolomic screens, and other high-dimensional methods have become an integral part of many biological investigations. To facilitate interpretation of these data, it is important to have detailed phenotypic data--including histopathology--to which these data can be associated, or anchored. However, as the amount of phenotypic data increases, associations within and across these data can be difficult to visualize and interpret. We have developed an approach for categorizing and clustering biologically related histopathological diagnoses to facilitate their visualization, thereby increasing the possibility of identifying associations and facilitating the comparison with other data streams. In this study, we utilize histopathological data generated as part of a standardized toxicogenomics compendium study to generate composite histopathological scores and to develop visualizations that facilitate biological insight. The validity of this approach is illustrated by the identification of transcripts that correlate with the pathology diagnoses that comprise the categories of "response to hepatocellular injury" and "repair." This approach is broadly applicable to studies in which histopathology is used to phenotypically anchor other data, and results in visualizations that facilitate biological interpretation and the identification of associations and relationships within the data.

Rat toxicogenomic study reveals analytical consistency across microarray platforms.

To validate and extend the findings of the MicroArray Quality Control (MAQC) project, a biologically relevant toxicogenomics data set was generated using 36 RNA samples from rats treated with three chemicals (aristolochic acid, riddelliine and comfrey) and each sample was hybridized to four microarray platforms. The MAQC project assessed concordance in intersite and cross-platform comparisons and the impact of gene selection methods on the reproducibility of profiling data in terms of differentially expressed genes using distinct reference RNA samples. The real-world toxicogenomic data set reported here showed high concordance in intersite and cross-platform comparisons. Further, gene lists generated by fold-change ranking were more reproducible than those obtained by t-test P value or Significance Analysis of Microarrays. Finally, gene lists generated by fold-change ranking with a nonstringent P-value cutoff showed increased consistency in Gene Ontology terms and pathways, and hence the biological impact of chemical exposure could be reliably deduced from all platforms analyzed.

Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project.

Microarray-based expression profiling experiments typically use either a one-color or a two-color design to measure mRNA abundance. The validity of each approach has been amply demonstrated. Here we provide a simultaneous comparison of results from one- and two-color labeling designs, using two independent RNA samples from the Microarray Quality Control (MAQC) project, tested on each of three different microarray platforms. The data were evaluated in terms of reproducibility, specificity, sensitivity and accuracy to determine if the two approaches provide comparable results. For each of the three microarray platforms tested, the results show good agreement with high correlation coefficients and high concordance of differentially expressed gene lists within each platform. Cumulatively, these comparisons indicate that data quality is essentially equivalent between the one- and two-color approaches and strongly suggest that this variable need not be a primary factor in decisions regarding experimental microarray design.

Profiles of global gene expression in ionizing-radiation-damaged human diploid fibroblasts reveal synchronization behind the G1 checkpoint in a G0-like state of quiescence.

Cell cycle arrest and stereotypic transcriptional responses to DNA damage induced by ionizing radiation (IR) were quantified in telomerase-expressing human diploid fibroblasts. Analysis of cytotoxicity demonstrated that 1.5 Gy IR inactivated colony formation by 40-45% in three fibroblast lines; this dose was used in all subsequent analyses. Fibroblasts exhibited > 90% arrest of progression from G2 to M at 2 hr post-IR and a similarly severe arrest of progression from G1 to S at 6 and 12 hr post-IR. Normal rates of DNA synthesis and mitosis 6 and 12 hr post-IR caused the S and M compartments to empty by > 70% at 24 hr. Global gene expression was analyzed in IR-treated cells. A microarray analysis algorithm, EPIG, identified nine IR-responsive patterns of gene expression that were common to the three fibroblast lines, including a dominant p53-dependent G1 checkpoint response. Many p53 target genes, such as CDKN1A, GADD45, BTG2, and PLK3, were significantly up-regulated at 2 hr post-IR. Many genes whose expression is regulated by E2F family transcription factors, including CDK2, CCNE1, CDC6, CDC2, MCM2, were significantly down-regulated at 24 hr post-IR. Numerous genes that participate in DNA metabolism were also markedly repressed in arrested fibroblasts apparently as a result of cell synchronization behind the G1 checkpoint. However, cluster and principal component analyses of gene expression revealed a profile 24 hr post-IR with similarity to that of G0 growth quiescence. The results reveal a highly stereotypic pattern of response to IR in human diploid fibroblasts that reflects primarily synchronization behind the G1 checkpoint but with prominent induction of additional markers of G0 quiescence such as GAS1.

Variation in the hepatic gene expression in individual male Fischer rats.

A new tool beginning to have wider application in toxicology studies is transcript profiling using microarrays. Microarrays provide an opportunity to directly compare transcript populations in the tissues of chemical-exposed and unexposed animals. While several studies have addressed variation between microarray platforms and between different laboratories, much less effort has been directed toward individual animal differences especially among control animals where RNA samples are usually pooled. Estimation of the variation in gene expression in tissues from untreated animals is essential for the recognition and interpretation of subtle changes associated with chemical exposure. In this study hepatic gene expression as well as standard toxicological parameters were evaluated in 24 rats receiving vehicle only in 2 independent experiments. Unsupervised clustering demonstrated some individual variation but supervised clustering suggested that differentially expressed genes were generally random. The level of hepatic gene expression under carefully controlled study conditions is less than 1.5-fold for most genes. The impact of individual animal variability on microarray data can be minimized through experimental design.

Standardizing global gene expression analysis between laboratories and across platforms.

To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.

MicroRNA expression detected by oligonucleotide microarrays: system establishment and expression profiling in human tissues.

MicroRNAs (MIRs) are a novel group of conserved short approximately 22 nucleotide-long RNAs with important roles in regulating gene expression. We have established a MIR-specific oligonucleotide microarray system that enables efficient analysis of the expression of the human MIRs identified so far. We show that the 60-mer oligonucleotide probes on the microarrays hybridize with labeled cRNA of MIRs, but not with their precursor hairpin RNAs, derived from amplified, size-fractionated, total RNA of human origin. Signal intensity is related to the location of the MIR sequences within the 60-mer probes, with location at the 5' region giving the highest signals, and at the 3' end, giving the lowest signals. Accordingly, 60-mer probes harboring one MIR copy at the 5' end gave signals of similar intensity to probes containing two or three MIR copies. Mismatch analysis shows that mutations within the MIR sequence significantly reduce or eliminate the signal, suggesting that the observed signals faithfully reflect the abundance of matching MIRs in the labeled cRNA. Expression profiling of 150 MIRs in five human tissues and in HeLa cells revealed a good overall concordance with previously published results, but also with some differences. We present novel data on MIR expression in thymus, testes, and placenta, and have identified MIRs highly enriched in these tissues. Taken together, these results highlight the increased sensitivity of the DNA microarray over other methods for the detection and study of MIRs, and the immense potential in applying such microarrays for the study of MIRs in health and disease.

The auxin-induced transcriptome for etiolated Arabidopsis seedlings using a structure/function approach.

To increase our understanding of the mode of action of auxin, we analyzed auxin-induced changes in the Arabidopsis transcriptome with microarrays representing 20426 Arabidopsis genes. Treatment of etiolated seedlings with low concentrations of the auxin, indole-3-acetic acid (IAA), decreased the expression levels of 23 genes, whereas it increased the expression levels of 47 genes within 20 min. After 40 min, the directional trend in genomic change was predominantly an increase in gene expression. Among the most rapidly induced changes are those in genes encoding transcription factors. Promoter regions of transiently induced genes contained DNA motifs that bind auxin response (ARFAT) and silence element binding factors whereas genes induced by IAA during the entire experimental period contained MYC and ARFAT DNA motifs at higher frequencies. Six structurally diverse auxins were analyzed to determine genes that are unique to a specific auxin, as well as a common set of genes that are rapidly regulated by all tested auxins, thus enabling the identification of shared DNA motifs. In addition to ARFAT, analysis of promoter regions of genes induced by all six auxins revealed the presence of an abscisic-acid-responsive DC3 promoter-binding factor and low temperature responsive elements suggesting a possible role for abscisic acid in modulating auxin-induced responses.

Microarray analyses of the metabolic responses of Saccharomyces cerevisiae to organic solvent dimethyl sulfoxide.

The toxic effects that organic solvents have on whole cells are important drawbacks in the application of these solvents in the production of fine chemicals by whole-cell stereoselective biotransformations. Although early studies found that organic solvents mainly destroyed the integrity of cell membranes by accumulating in the lipid bilayer of plasma membranes, the cellular metabolic responses to the presence of an organic solvent remain unclear. With the rapid development of genomics, it is possible to study cellular metabolism under perturbed conditions at the genome level. In this paper, the global gene expression profiles of Saccharomyces cerevisiae BY4743 grown in media with a high concentration of the organic solvent dimethyl sulfoxide (DMSO) were determined by microarray analysis of ~6,200 yeast open reading frames (ORFs). From cells grown in SD minimal medium containing 1.0% (v/v) DMSO, changes in transcript abundance greater than or equal to 2.5-fold were classified. Genomic analyses showed that 1,338 genes were significantly regulated by the presence of DMSO in yeast. Among them, only 400 genes were previously found to be responsive to general environmental stresses, such as temperature shock, amino acid starvation, nitrogen source depletion, and progression into stationary phase. The DMSO-responsive genes were involved in a variety of cellular functions, including carbohydrate, amino acid and lipid metabolism, cellular stress responses, and energy metabolism. Most of the genes in the lipid biosynthetic pathways were down-regulated by DMSO treatment, whereas genes involved in amino acid biosynthesis were mostly up-regulated. The results demonstrate that the application of microarray technology allows better interpretation of metabolic responses, and the information obtained will be useful for the construction of engineered yeast strains with better tolerance of organic solvents.