Clustering of hepatotoxins based on mechanism of toxicity using gene expression profiles

Chlorogenic acid suppresses the expression of matrix metalloproteinase-7 and cell invasiveness to almost the same extent as isofraxidin in human colorectal cancer cells

The expression of matrix metalloproteinase (MMP)-7 is reported to be correlated with invasion and metastasis of colorectal cancer (CRC). Therefore, the inhibition of MMP-7 would be beneficial for the suppression or prevention of CRC cell invasion and metastasis. The stem bark of Acanthopanax senticosus, a widely used medicinal herb, contains isofraxidin (IF) and chlorogenic acid (CGA) as major components. Previously we reported that IF suppressed the expression of MMP-7 and cell invasion in human hepatoma cells. In this study, we investigated the effects of CGA on cell invasion, MMP-7 mRNA expression and the phosphorylation of extracellular signal-regulated kinase 1/2 (ERK1/2) and compared it with those of IF in human CRC cells (HT-29). We found that CGA significantly suppressed 12-O-tetradecanoylphorbol-13-acetate (TPA)-induced cell invasion, MMP-7 expression and the expression of activated form of MMP-7 to almost the same extent as IF. Meanwhile, we also found that TPA-induced expression of MMP-7 mRNA and ERK1/2 phosphorylation were significantly suppressed when cells were exposed to the ERK1/2 inhibitor U0126 and that CGA was a little more potent than IF at inhibiting TPA-induced ERK1/2 phosphorylation. Taken together, the present results indicate that CGA suppresses cell invasion, MMP-7 expression and ERK1/2 phosphorylation to almost the same extent as IF and suggest that not only IF but also CGA suppresses cell invasion by inhibiting MMP-7 expression via the inhibition of at least ERK1/2 phosphorylation and Acanthopanax senticosus, which contains two components with anti-MMP-7 activity, may be a beneficial herb with anti-invasive effects against human CRC cells.

Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach

Translational research in toxicology has significantly benefited from transcriptomic profiling, particularly in drug safety. However, its application has predominantly focused on limited organs, notably the liver, due to resource constraints. This paper presents TransTox, an innovative AI model using a generative adversarial network (GAN) method to facilitate the bidirectional translation of transcriptomic profiles between the liver and kidney under drug treatment. TransTox demonstrates robust performance, validated across independent datasets and laboratories. First, the concordance between real experimental data and synthetic data generated by TransTox was demonstrated in characterizing toxicity mechanisms compared to real experimental settings. Second, TransTox proved valuable in gene expression predictive models, where synthetic data could be used to develop gene expression predictive models or serve as "digital twins" for diagnostic applications. The TransTox approach holds the potential for multi-organ toxicity assessment with AI and advancing the field of precision toxicology.

Advancing Computational Toxicology by Interpretable Machine Learning

Chemical toxicity evaluations for drugs, consumer products, and environmental chemicals have a critical impact on human health. Traditional animal models to evaluate chemical toxicity are expensive, time-consuming, and often fail to detect toxicants in humans. Computational toxicology is a promising alternative approach that utilizes machine learning (ML) and deep learning (DL) techniques to predict the toxicity potentials of chemicals. Although the applications of ML- and DL-based computational models in chemical toxicity predictions are attractive, many toxicity models are "black boxes" in nature and difficult to interpret by toxicologists, which hampers the chemical risk assessments using these models. The recent progress of interpretable ML (IML) in the computer science field meets this urgent need to unveil the underlying toxicity mechanisms and elucidate the domain knowledge of toxicity models. In this review, we focused on the applications of IML in computational toxicology, including toxicity feature data, model interpretation methods, use of knowledge base frameworks in IML development, and recent applications. The challenges and future directions of IML modeling in toxicology are also discussed. We hope this review can encourage efforts in developing interpretable models with new IML algorithms that can assist new chemical assessments by illustrating toxicity mechanisms in humans.

Toxicogenomics Approaches to Address Toxicity and Carcinogenicity in the Liver

Toxicogenomic technologies query the genome, transcriptome, proteome, and the epigenome in a variety of toxicological conditions. Due to practical considerations related to the dynamic range of the assays, sensitivity, cost, and technological limitations, transcriptomic approaches are predominantly used in toxicogenomics. Toxicogenomics is being used to understand the mechanisms of toxicity and carcinogenicity, evaluate the translational relevance of toxicological responses from in vivo and in vitro models, and identify predictive biomarkers of disease and exposure. In this session, a brief overview of various transcriptomic technologies and practical considerations related to experimental design was provided. The advantages of gene network analyses to define mechanisms were also discussed. An assessment of the utility of toxicogenomic technologies in the environmental and pharmaceutical space showed that these technologies are being increasingly used to gain mechanistic insights and determining the translational relevance of adverse findings. Within the environmental toxicology area, there is a broader regulatory consideration of benchmark doses derived from toxicogenomics data. In contrast, these approaches are mainly used for internal decision-making in pharmaceutical development. Finally, the development and application of toxicogenomic signatures for prediction of apical endpoints of regulatory concern continues to be area of intense research.

SigCom LINCS: data and metadata search engine for a million gene expression signatures

Millions of transcriptome samples were generated by the Library of Integrated Network-based Cellular Signatures (LINCS) program. When these data are processed into searchable signatures along with signatures extracted from Genotype-Tissue Expression (GTEx) and Gene Expression Omnibus (GEO), connections between drugs, genes, pathways and diseases can be illuminated. SigCom LINCS is a webserver that serves over a million gene expression signatures processed, analyzed, and visualized from LINCS, GTEx, and GEO. SigCom LINCS is built with Signature Commons, a cloud-agnostic skeleton Data Commons with a focus on serving searchable signatures. SigCom LINCS provides a rapid signature similarity search for mimickers and reversers given sets of up and down genes, a gene set, a single gene, or any search term. Additionally, users of SigCom LINCS can perform a metadata search to find and analyze subsets of signatures and find information about genes and drugs. SigCom LINCS is findable, accessible, interoperable, and reusable (FAIR) with metadata linked to standard ontologies and vocabularies. In addition, all the data and signatures within SigCom LINCS are available via a well-documented API. In summary, SigCom LINCS, available at https://maayanlab.cloud/sigcom-lincs, is a rich webserver resource for accelerating drug and target discovery in systems pharmacology.

Genome-wide evaluation of transcriptomic responses of human tissues to smoke: A systems biology study

The harmful compounds in various sources of smoke threaten human health. So far, many studies have investigated the effects of compounds of smoke on transcriptome changes in different human tissues. However, no study has been conducted on the effects of these compounds on transcriptome changes in different human tissues simultaneously. Hence, the present study was conducted to identify smoke-related genes (SRGs) and their response mechanisms to smoke in various human cells and tissues using systems biology based methods. A total of 6,484 SRGs were identified in the studied tissues, among which 4,095 SRGs were up-regulated and 2,389 SRGs were down-regulated. Totally, 459 SRGs were smoke-related transcription factors (SRTFs). Gene regulatory network analysis showed that the studied cells and tissues have different gene regulation and responses to compounds of smoke. The comparison of different tissues revealed no common SRG among the all studied tissues. However, the CYP1B1 gene was common among seven cells and tissues, and had the same expression trend. Network analysis showed that the CYP1B1 is a hub gene among SRGs in various cells and tissues. To the best of our knowledge, for the first time, our results showed that compounds of smoke induce and increase the expression of CYP1B1 key gene in all target and non-target tissues of human. Moreover, despite the specific characteristics of CYP1B1 gene and its identical expression trend in target and non-target tissues, it can be used as a biomarker for diagnosis and prognosis.

High-Throughput Transcriptomics Platform for Screening Environmental Chemicals

New approach methodologies (NAMs) that efficiently provide information about chemical hazard without using whole animals are needed to accelerate the pace of chemical risk assessments. Technological advancements in gene expression assays have made in vitro high-throughput transcriptomics (HTTr) a feasible option for NAMs-based hazard characterization of environmental chemicals. In this study, we evaluated the Templated Oligo with Sequencing Readout (TempO-Seq) assay for HTTr concentration-response screening of a small set of chemicals in the human-derived MCF7 cell model. Our experimental design included a variety of reference samples and reference chemical treatments in order to objectively evaluate TempO-Seq assay performance. To facilitate analysis of these data, we developed a robust and scalable bioinformatics pipeline using open-source tools. We also developed a novel gene expression signature-based concentration-response modeling approach and compared the results to a previously implemented workflow for concentration-response analysis of transcriptomics data using BMDExpress. Analysis of reference samples and reference chemical treatments demonstrated highly reproducible differential gene expression signatures. In addition, we found that aggregating signals from individual genes into gene signatures prior to concentration-response modeling yielded in vitro transcriptional biological pathway altering concentrations (BPACs) that were closely aligned with previous ToxCast high-throughput screening assays. Often these identified signatures were associated with the known molecular target of the chemicals in our test set as the most sensitive components of the overall transcriptional response. This work has resulted in a novel and scalable in vitro HTTr workflow that is suitable for high-throughput hazard evaluation of environmental chemicals.

Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment

Transcriptomics data are relevant to address a number of challenges in Toxicogenomics (TGx). After careful planning of exposure conditions and data preprocessing, the TGx data can be used in predictive toxicology, where more advanced modelling techniques are applied. The large volume of molecular profiles produced by omics-based technologies allows the development and application of artificial intelligence (AI) methods in TGx. Indeed, the publicly available omics datasets are constantly increasing together with a plethora of different methods that are made available to facilitate their analysis, interpretation and the generation of accurate and stable predictive models. In this review, we present the state-of-the-art of data modelling applied to transcriptomics data in TGx. We show how the benchmark dose (BMD) analysis can be applied to TGx data. We review read across and adverse outcome pathways (AOP) modelling methodologies. We discuss how network-based approaches can be successfully employed to clarify the mechanism of action (MOA) or specific biomarkers of exposure. We also describe the main AI methodologies applied to TGx data to create predictive classification and regression models and we address current challenges. Finally, we present a short description of deep learning (DL) and data integration methodologies applied in these contexts. Modelling of TGx data represents a valuable tool for more accurate chemical safety assessment. This review is the third part of a three-article series on Transcriptomics in Toxicogenomics.

Towards early-warning gene signature of Chlamydomonas reinhardtii exposed to Hg-containing complex media

The potential of using gene expression signature as a biomarker of toxicants exposure was explored in the microalga Chlamydomonas reinhardtii exposed 2 h to mercury (Hg) as inorganic mercury (IHg) and methyl mercury (MeHg) in presence of copper (Cu) and Suwannee River Humic Acid (SRHA). Total cellular Hg (THg = IHg + MeHg) decreased in presence of SRHA for 0.7 nM IHg and 0.4 nM MeHg, but increased for 70 nM IHg exposure. In mixtures of IHg + MeHg and (IHg or MeHg) + Cu, SRHA decreased THg uptake, except for 0.7 nM IHg + 0.4 nM MeHg which was unchanged (p-value>0.05). In the absence of SRHA, 0.5 μM Cu strongly decreased intracellular THg concentration for 70 nM IHg, while it had no effect for 0.7 nM IHg and 0.4 nM MeHg. The expression of single transcripts was not correlated with measured THg uptake, but a subset of 60 transcripts showed signatures specific to the exposed metal(s) and was congruent with exposure concentration. Notably, the range of fold change values of this subset correlated with THg bioaccumulation with a two-slope pattern in line with [THg]_intra/[THg]_med ratios. Gene expression signature seems a promising approach to complement chemical analyses to assess bioavailability of toxicants in presence of other metals and organic matter.

Connectivity Mapping: Methods and Applications

Connectivity mapping resources consist of signatures representing changes in cellular state following systematic small-molecule, disease, gene, or other form of perturbations. Such resources enable the characterization of signatures from novel perturbations based on similarity; provide a global view of the space of many themed perturbations; and allow the ability to predict cellular, tissue, and organismal phenotypes for perturbagens. A signature search engine enables hypothesis generation by finding connections between query signatures and the database of signatures. This framework has been used to identify connections between small molecules and their targets, to discover cell-specific responses to perturbations and ways to reverse disease expression states with small molecules, and to predict small-molecule mimickers for existing drugs. This review provides a historical perspective and the current state of connectivity mapping resources with a focus on both methodology and community implementations.

Expression Profiling of Inflammatory and Immunological Genes in Collagenous Colitis

BACKGROUND

Collagenous colitis [CC] is a common idiopathic cause of chronic watery diarrhoea. We investigated its pathogenesis by means of gene expression analysis.

METHODS

We analysed the expression of genes implicated in immunological and inflammatory pathways in paired colonic biopsies of histologically involved and uninvolved mucosa from five patients with histologically patchy CC, in pooled colonic biopsies of eight other patients with diffuse CC, and in pooled biopsies of eight normal controls. Analyses were performed with the Nanostring nCounter system. Expression ratios were generated and confirmed by quantitative reverse transcription PCR.

RESULTS

CC mucosa was characterized by enhanced expression of nitric oxide synthase 2; of matrix metalloproteinases 3 and 9 and tissue inhibitor of metalloproteinase 1, but not transforming growth factor β1; of mediators of T-helper 1 immunity including interleukins 12A [IL12A], 12B, IL12 receptor B1 and interferon γ; of immune mediators of the leukocyte immunoglobulin-like receptor subfamily B; and of multiple T cell cytokines and their receptors. The mitogen-activated protein kinase signalling pathway was unchanged. There were no increases in IL22, IL22RA2 or tumour necrosis factor α, which are reportedly elevated in chronic inflammatory bowel disease. In four of five patients with patchy CC, similar gene expression profiles were observed in histologically involved and uninvolved mucosa.

CONCLUSIONS

CC is characterized by altered expression of a limited repertoire of genes involved in nitric oxide synthesis, extracellular matrix remodelling, T-helper 1 immunity and immune modulation. The abnormal gene expression in patchy CC may be expressed in mucosa with and without histological disease manifestations.

Evaluation of phenol-induced ecotoxicity in two model ciliate species: Population growth dynamics and antioxidant enzyme activity

The application of identical exposure dosages in different species generally leads to a limited understanding of dose-response patterns because of species-specific factors. To evaluate phenol-induced ecotoxicity, antioxidant enzyme activity and population growth dynamics were compared in two model ciliates, the marine species Euplotes vannus and the freshwater species Paramecium multimicronucleatum. Dosage ranges of phenol exposure were based on tolerance limits of test ciliates as determined by their carrying capacity (K) and growth rate (r). When the exposure duration of phenol increased from 48 h to 96 h, the median effective dose (ED₅₀) for P. multimicronucleatum decreased faster than that for E. vannus_, and the ratio of the former to the latter declined from 2.75 to 0.30. When E. vannus was exposed to increasing concentrations of phenol (0-140 mg l^-1), r rose initially and then dropped significantly at concentrations higher than 40 mg l^-1, whereas K decreased linearly over the entire range. For P. multimicronucleatum, both r and K declined gradually over the range 0-200 mg l^-1 phenol. Dose-response patterns of activities of three individual antioxidant enzymes, and the integrative index of the three enzymes, presented a biphasic (inverse U-shaped) curve at each of four durations of exposure, i.e. 12 h, 24 h, 36 h and 48 h. Cluster analyses and multidimensional scaling analyses of antioxidant enzyme activities revealed differences in the temporal succession of physiological states between the two model ciliates. In brief, combining ED₅₀ with growth dynamic parameters is helpful for designing exposure dosages of toxicants in ecotoxicity tests.

Transcriptomics in toxicology

Xenobiotics, of which many are toxic, may enter the human body through multiple routes. Excessive human exposure to xenobiotics may exceed the body's capacity to defend against the xenobiotic-induced toxicity and result in potentially fatal adverse health effects. Prevention of the adverse health effects, potentially associated with human exposure to the xenobiotics, may be achieved by detecting the toxic effects at an early, reversible and, therefore, preventable stage. Additionally, an understanding of the molecular mechanisms underlying the toxicity may be helpful in preventing and/or managing the ensuing adverse health effects. Human exposures to a large number of xenobiotics are associated with hepatotoxicity or pulmonary toxicity. Global gene expression changes taking place in biological systems, in response to exposure to xenobiotics, may represent the early and mechanistically relevant cellular events contributing to the onset and progression of xenobiotic-induced adverse health outcomes. Hepatotoxicity and pulmonary toxicity resulting from exposure to xenobiotics are discussed as specific examples to demonstrate the potential application of transcriptomics or global gene expression analysis in the prevention of adverse health effects associated with exposure to xenobiotics.

Integrative analysis of hepatic microRNA and mRNA to identify potential biological pathways associated with monocrotaline-induced liver injury in mice

Pyrrolizidine alkaloids (PAs) are a type of natural hepatotoxic compounds. Monocrotaline (MCT), belongs to PAs, is a main compound distributed in medicinal herb Crotalaria ferruginea Grah. ex Benth. This study aims to identify the potential biological signaling pathway associated with MCT-induced liver injury by analyzing the integrative altered hepatic microRNA (miRNA) and mRNA expression profile. C57BL/6 mice were orally given with MCT (270, 330mg/kg). Serum alanine/aspartate aminotransferase (ALT/AST) activity, total bilirubin (TBil) amount and liver histological evaluation showed the liver injury induced by MCT. Results of miRNA chip analysis showed that the hepatic expression of 15 miRNAs (whose signal intensity>200) was significantly altered in MCT-treated mice, and among them total 11 miRNAs passed further validation by using Real-time PCR assay. Results of mRNA chip analysis demonstrated that the hepatic expression of 569 genes was up-regulated and of other 417 genes was down-regulated in MCT-treated mice. There are total 426 predicted target genes of those above altered 11 miRNAs, and among them total 10 genes were also altered in mice treated with both MCT (270mg/kg) and MCT (330mg/kg) from the results of mRNA chip. Among these above 10 genes, total 8 genes passed further validation by using Real-time PCR assay. Only 1 biological signaling pathway was annotated by using those above 8 genes, which is phagosome. In conclusion, this study demonstrated the integrative altered expression profile of liver miRNA and mRNA, and identified that innate immunity may be critically involved in MCT-induced liver injury in mice.

A Retrospective Analysis of Toxicogenomics in the Safety Assessment of Drug Candidates

Toxicogenomics is considered a valuable tool for reducing pharmaceutical candidate attrition by facilitating earlier identification, prediction and understanding of toxicities. A retrospective evaluation of 3 years of routine transcriptional profiling in non-clinical safety studies was undertaken to assess the utility of toxicogenomics in drug safety assessment. Based on the analysis of studies with 33 compounds, marked global transcriptional changes (>4% transcripts at p < 0.01) were shown to be a robust biomarker for dosages considered to be toxic. In general, there was an inconsistent correlation between transcription and histopathology, most likely due to differences in sensitivity to focal microscopic lesions, to secondary effects, and to events that precede structural tissue changes. For 60% of toxicities investigated with multiple time-point data, transcriptional changes were observed prior to changes in traditional study endpoints. Candidate transcriptional markers of pharmacologic effects were detected in 40% of targets profiled. Mechanistic classification of toxicity was obtained for 30% of targets. Furthermore, data comparison to compendia of transcriptional changes provided assessments of the specificity of transcriptional responses. Overall, our experience suggests that toxicogenomics has contributed to a greater understanding of mechanisms of toxicity and to reducing drug attrition by empiric analysis where safety assessment combines toxicogenomic and traditional evaluations.

Gene Expression Profiles in Rat Liver Slices Exposed to Hepatocarcinogenic Enzyme Inducers, Peroxisome Proliferators, and 17α-Ethinylestradiol

Transcription profiling is used as an in vivo method for predicting the mode-of-action class of nongenotoxic carcinogens. To set up a reliable in vitro short-term test system DNA microarray technology was combined with rat liver slices. Seven compounds known to act as tumor promoters were selected, which included the enzyme inducers phenobarbital, α-hexachlorocyclohexane, and cyproterone acetate; the peroxisome proliferators WY-14,643, dehydroepiandrosterone, and ciprofibrate; and the hormone 17 α-ethinylestradiol. Rat liver slices were exposed to various concentrations of the compounds for 24 h. Toxicology-focused TOXaminer™ DNA microarrays containing approximately 1500 genes were used for generating gene expression profiles for each of the test compound. Hierarchical cluster analysis revealed that (i) gene expression profiles generated in rat liver slices in vitro were specific allowing classification of compounds with similar mode of action and (ii) expression profiles of rat liver slices exposed in vitro correlate with those induced after in vivo treatment (reported previously). Enzyme inducers and peroxisome proliferators formed two separate clusters, confirming that they act through different mechanisms. Expression profiles of the hormone 17 α-ethinylestradiol were not similar to any of the other compounds. In conclusion, gene expression profiles induced by compounds that act via similar mechanisms showed common effects on transcription upon treatment in vivo and in rat liver slices in vitro.

Microvesicular Steatosis Induced by a Short Chain Fatty Acid: Effects on Mitochondrial Function and Correlation with Gene Expression

Hepatotoxicity characterized by microvesicular steatosis (MVS) is characterized by an abnormal accumulation of numerous small cytoplasmic lipid droplets in hepatocytes. Fulminant or progressive cases of microvesicular steatosis may lead to liver failure and death. Experimentally, short-chain carboxylic acids are known to induce microvesicular steatosis. The identification of gene changes that correlate with MVS concomitant with biochemical and histological indices could provide a better understanding of how this toxicity occurs as well as biomarkers that could be used to avoid this toxicity in the future. Sprague—Dawley rats were dosed days with cyclopropane carboxylic acid (CPCA) a short-chain fatty acid that can induce microvesicular steatosis, and with butyrate, a short chain fatty acid that served as a negative control. CPCA initiated microvesicular steatosis while butyrate did not. In addition, CPCA inhibited beta-oxidation in a concentration-dependent manner in vitro and caused a reduction in mitochondrial respiration ex vivo; no inhibition was evident with butyrate. Microarray results showed that gene expression changes with CPCA resulted in regulation of genes involved in beta-oxidation, as well as other genes associated with mitochondrial function. Overall, these results support altered hepatic mitochondrial function as a mechanism of the toxicity induced by a short-chain fatty acid and may provide potential biomarkers for this toxicity.

Identification of gene expression signature for cigarette smoke exposure response--from man to mouse

Gene expression profiling data can be used in toxicology to assess both the level and impact of toxicant exposure, aligned with a vision of 21st century toxicology. Here, we present a whole blood-derived gene signature that can distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. Such a signature that can be measured in a surrogate tissue (whole blood) may help in monitoring smoking exposure as well as discontinuation of exposure when the primarily impacted tissue (e.g., lung) is not readily accessible. The signature consisted of LRRN3, SASH1, PALLD, RGL1, TNFRSF17, CDKN1C, IGJ, RRM2, ID3, SERPING1, and FUCA1. Several members of this signature have been previously described in the context of smoking. The signature translated well across species and could distinguish mice that were exposed to cigarette smoke from ones exposed to air only or had been withdrawn from cigarette smoke exposure. Finally, the small signature of only 11 genes could be converted into a polymerase chain reaction-based assay that could serve as a marker to monitor compliance with a smoking abstinence protocol.

Subchronic Exposure to Arsenic Through Drinking Water Alters Expression of Cancer-Related Genes in Rat Liver

Although arsenic exposure causes liver disease and/or hepatoma, little is known about molecular mechanisms of arsenic-induced liver toxicity or carcinogenesis. We investigated the effects of arsenic on expression of cancer-related genes in a rat liver following subchronic exposure to sodium arsenate (1, 10, 100 ppm in drinking water), by using real-time quantitative RT-PCR and immunohistochemical analyses. Arsenic accumulated in the rat liver dose-dependently and caused hepatic histopathological changes, such as disruption of hepatic cords, sinusoidal dilation, and fatty infiltration. A 1-month exposure to arsenic significantly increased hepatic mRNA levels of cyclin D1 (10 ppm), ILK (1 ppm), and p27Kip1 (10 ppm), whereas it reduced mRNA levels of PTEN (1 ppm) and β-catenin (100 ppm). In contrast, a 4-month arsenic exposure showed increased mRNA expression of cyclin D1 (100 ppm), ILK (1 ppm), and p27Kip1 (1 and 10 ppm), and decreased expression of both PTEN and β-catenin at all 3 doses. An immunohistochemical study revealed that each protein expression accords closely with each gene expression of mRNA level. In conclusion, subchronic exposure to inorganic arsenate caused pathological changes and altered expression of cyclin D1, p27Kip1, ILK, PTEN, and β-catenin in the liver. This implies that arsenic liver toxicity involves disturbances of some cancer-related molecules.

Profiles of Metabolites and Gene Expression in Rats with Chemically Induced Hepatic Necrosis

This study investigated whether integrated analysis of transcriptomics and metabolomics data increased the sensitivity of detection and provided new insight in the mechanisms of hepatotoxicity. Metabolite levels in plasma or urine were analyzed in relation to changes in hepatic gene expression in rats that received bromobenzene to induce acute hepatic centrilobular necrosis. Bromobenzene-induced lesions were only observed after treatment with the highest of 3 dose levels. Multivariate statistical analysis showed that metabolite profiles of blood plasma were largely different from controls when the rats were treated with bromobenzene, also at doses that did not elicit histopathological changes. Changes in levels of genes and metabolites were related to the degree of necrosis, providing putative novel markers of hepatotoxicity. Levels of endogenous metabolites like alanine, lactate, tyrosine and dimethylglycine differed in plasma from treated and control rats. The metabolite profiles of urine were found to be reflective of the exposure levels. This integrated analysis of hepatic transcriptomics and plasma metabolomics was able to more sensitively detect changes related to hepatotoxicity and discover novel markers. The relation between gene expression and metabolite levels was explored and additional insight in the role of various biological pathways in bromobenzene-induced hepatic necrosis was obtained, including the involvement of apoptosis and changes in glycolysis and amino acid metabolism.

The complete Table 2 is available as a supplemental file online at http://taylorandfrancis.metapress.com/openurlasp?genre=journal&issn=0192-6233 . To access the file, click on the issue link for 33(4), then select this article. A download option appears at the bottom of this abstract. In order to access the full article online, you must either have an individual subscription or a member subscription accessed through www.toxpath.org .

Prediction of Nephrotoxicant Action and Identification of Candidate Toxicity-Related Biomarkers

A vast majority of pharmacological compounds and their metabolites are excreted via the urine, and within the complex structure of the kidney, the proximal tubules are a main target site of nephrotoxic compounds. We used the model nephrotoxicants mercuric chloride, 2-bromoethylamine hydrobromide, hexachlorobutadiene, mitomycin, amphotericin, and puromycin to elucidate time- and dose-dependent global gene expression changes associated with proximal tubular toxicity. Male Sprague–Dawley rats were dosed via intraperitoneal injection once daily for mercuric chloride and amphotericin (up to 7 doses), while a single dose was given for all other compounds. Animals were exposed to 2 different doses of these compounds and kidney tissues were collected on day 1, 3, and 7 postdosing. Gene expression profiles were generated from kidney RNA using 17K rat cDNA dual dye microarray and analyzed in conjunction with histopathology. Analysis of gene expression profiles showed that the profiles clustered based on similarities in the severity and type of pathology of individual animals. Further, the expression changes were indicative of tubular toxicity showing hallmarks of tubular degeneration/regeneration and necrosis. Use of gene expression data in predicting the type of nephrotoxicity was then tested with a support vector machine (SVM)-based approach. A SVM prediction module was trained using 120 profiles of total profiles divided into four classes based on the severity of pathology and clustering. Although mitomycin C and amphotericin B treatments did not cause toxicity, their expression profiles were included in the SVM prediction module to increase the sample size. Using this classifier, the SVM predicted the type of pathology of 28 test profiles with 100% selectivity and 82% sensitivity. These data indicate that valid predictions could be made based on gene expression changes from a small set of expression profiles. A set of potential biomarkers showing a time- and dose-response with respect to the progression of proximal tubular toxicity were identified. These include several transporters ( Slc21a2, Slc15, Slc34a2), Kim 1, IGFbp-1, osteopontin, α -fibrinogen, and Gstα.

Transcriptional Profiles in Liver from Mice Treated with Hepatotumorigenic and Nonhepatotumorigenic Triazole Conazole Fungicides: Propiconazole, Triadimefon, and Myclobutanil

Conazoles are environmental and pharmaceutical fungicides. The present study relates the toxicological effects of conazoles to alterations of gene and pathway transcription and identifies potential modes of tumorigenic action. In a companion study employing conventional toxicological bioassays ( Allen et al., 2006 ), male CD-1 mice were fed triadimefon, propiconazole, or myclobutanil in a continuous oral-dose regimen for 4, 30, or 90 days. These conazoles were found to induce hepatomegaly, to induce high levels of hepatic pentoxyresorufin-O-dealkylase activity, to increase hepatic cell proliferation, to decrease serum cholesterol, and to increase serum triglycerides. Differentially expressed genes and pathways were identified using Affymetrix GeneChips. Gene-pathway associations were obtained from the Kyoto Encyclopedia of Genes and Genomes, Biocarta, and MetaCore compendia. The pathway profiles of each conazole were different at each time point. In general, the number of altered metabolism, signaling, and growth pathways increased with time and dose and were greatest with propiconazole. All conazoles had effects on nuclear receptors as evidenced by increased expression and enzymatic activities of a series of related cytochrome P450s (CYP). A subset of altered genes and pathways distinguished the three conazoles from each other. Triadimefon and propiconazole both altered apoptosis, cell cycle, adherens junction, calcium signaling, and EGFR signaling pathways. Triadimefon produced greater changes in cholesterol biosynthesis and retinoic acid metabolism genes and in selected signaling pathways. Propiconazole had greater effects on genes responding to oxidative stress and on the IGF/P13K/AKt/PTEN/mTor and Wnt-β-catenin pathways. In conclusion, while triadimefon, propiconazole, and myclobutanil had similar effects in mouse liver on hepatomegaly, histology, CYP activities, cell proliferation, and serum cholesterol, genomic analyses revealed major differences in their gene expression profiles.

A Cytoplasmic Form of Gaussia luciferase Provides a Highly Sensitive Test for Cytotoxicity

The elimination of unfavorable chemicals from our environment and commercial products requires a sensitive and high-throughput in vitro assay system for drug-induced hepatotoxicity. Some previous methods for evaluating hepatotoxicity measure the amounts of cytoplasmic enzymes secreted from damaged cells into the peripheral blood or culture medium. However, most of these enzymes are proteolytically digested in the extracellular milieu, dramatically reducing the sensitivity and reliability of such assays. Other methods measure the decrease in cell viability following exposure to a compound, but such endpoint assays are often confounded by proliferation of surviving cells that replace dead or damaged cells. In this study, with the goal of preventing false-negative diagnoses, we developed a sensitive luminometric cytotoxicity test using a stable form of luciferase. Specifically, we converted Gaussia luciferase (G-Luc) from an actively secreted form to a cytoplasmic form by adding an ER-retention signal composed of the four amino acids KDEL. The bioluminescent signal was >30-fold higher in transgenic HepG2 human hepatoblastoma cells expressing G-Luc+KDEL than in cells expressing wild-type G-Luc. Moreover, G-Luc+KDEL secreted from damaged cells was stable in culture medium after 24 hr at 37°C. We evaluated the accuracy of our cytotoxicity test by subjecting identical samples obtained from chemically treated transgenic HepG2 cells to the G-Luc+KDEL assay and luminometric analyses based on secretion of endogenous adenylate kinase or cellular ATP level. Time-dependent accumulation of G-Luc+KDEL in the medium increased the sensitivity of our assay above those of existing tests. Our findings demonstrate that strong and stable luminescence of G-Luc+KDEL in human hepatocyte-like cells, which have high levels of metabolic activity, make it suitable for use in a high-throughput screening system for monitoring time-dependent cytotoxicity in a limited number of cells.

Exposure to cypermethrin and mancozeb alters the expression profile of THBS1, SPP1, FEZ1 and GPNMB in human peripheral blood mononuclear cells

The complex immune system displays a coordinated transcriptional response to xenobiotic exposure by altering expression of designated transcription factors that, in turn, trigger immune responses. Despite the identification of several transcription factors that contribute to regulatory response, very little is known about the specific role of factors that are triggered due to exposure to obnoxious pesticides. Here, for the first time, alterations in human peripheral blood lymphocyte expression of transcriptional factors - thrombospondin-1 (THBS-1), secretory phospho-protein-1 (SPP-1), glycoprotein non-metastatic-β (GPNMB) and fasciculation and elongation factor ζ-1 (FEZ-1), due to in vitro exposure to the crop protection chemicals cypermethrin and mancozeb are reported. Results revealed significant changes in expression profiles due to mancozeb exposure, supporting its immune dysfunction potential; in contrast, cypermethrin exposure did not cause significant changes. Based on these effects on gene expression across the doses tested, it was likely key components of immune mechanisms such as proliferation, cell adhesion, apoptosis and cell activation in human PBMC were affected. Although these data are from in vitro experiments, the results point out the potential role for changes in these factors in the etiology of defective T-cell immune function seen in humans occupationally exposed to crop protection chemicals like mancozeb. These studies suggest the involvement of transcription factors in regulation of pesticide-induced immune dysfunction; these studies also represent a novel approach for identifying potential immune-related dysfunctions due to exposure to pesticides. Further studies are needed to better understand the functional significance of these in vitro findings.

Integrated expression profiles of mRNA and microRNA in the liver of Fructus Meliae Toosendan water extract injured mice

Liver toxicity is a severe problem associated with Traditional Chinese Medicine (TCM). Fructus Meliae Toosendan (FMT) is a known hepatotoxic TCM, however, the toxicological mechanisms of liver injury caused by FMT treatment still remain largely unknown. In this study, we aimed to reveal possible mechanisms of FMT water extract-induced liver injury using a systemic approach. After three consecutive daily dosing of FMT water extract, significant increases of alanine transaminase, aspartate transaminase, and alkaline phosphatase activities, along with elevated total bilirubin and total cholesterol levels and a decrease of triglyceride level, were detected in mice serum. Moreover, hydropic degeneration was observed in hepatocytes, suggesting the presence of FMT-induced liver injury. mRNA and microRNA expression profiles of liver samples from injured mice were analyzed and revealed 8 miRNAs and 1,723 mRNAs were significantly changed after FMT water extract treatment. For the eight differentially expressed miRNAs, their predicted target genes were collected and a final set of 125 genes and 4 miRNAs (miR-139-5p, miR-199a-5p, miR-2861, and miR-3960) was selected to investigate important processes involved in FMT hepatotoxicity. Our results demonstrated several cellular functions were disordered after FMT treatment, such as cellular growth and proliferation, gene expression and cellular development. We hypothesized that liver cell necrosis was the main liver toxicity of FMT water extract, which was possibly caused by oxidative stress responses.

Multilevel evaluations of potential liver injury of bifenthrin

The widespread use of pesticides, such as pyrethroids, increases health risks to non-target organisms. The potential toxicity of pyrethroids to the liver remains unclear and could be easily overlooked if only the common clinical indicators of liver disease are examined. In the present study, BALB/c mice were given intraperitoneal injections of 0, 2, 4, or 8 mg/kg bifenthrin (BF) for 7 days. The potential liver injury of BF and its underlying mechanism were then investigated through multilevel evaluations. Histological analyses and serum enzyme activities showed no obvious clinical evidence of liver damage. Oxidative stress was induced and caspases were activated in response to increased BF concentrations. Exposure to BF also significantly altered the expression levels of mitochondrial apoptosis-related genes in dose-dependent relationships. The microarray results showed that BF could disturb the metabolic profile and extensively induce genes related to oxidative stress, including the cytochrome P450 family, glutathione peroxidases, glutathione s-transferases and kinases. In the in vivo model, BF induced liver injury through caspase-mediated mitochondrial-dependent cell death, a process that is closely related to oxidative stress, even in the absence of classical clinical biomarkers of liver dysfunction. The results of this study suggest that classical evaluations are not adequate for liver toxicity of pyrethroids, and highlight the need for more comprehensive assessment of health risks of these widely used pesticides.

p53 Contributes to Differentiating Gene Expression Following Exposure to Acetaminophen and Its Less Hepatotoxic Regioisomer Both In Vitro and In Vivo

The goal of the present study was to compare hepatic toxicogenomic signatures across in vitro and in vivo mouse models following exposure to acetaminophen (APAP) or its relatively nontoxic regioisomer 3′-hydroxyacetanilide (AMAP). Two different Affymetrix microarray platforms and one Agilent Oligonucleotide microarray were utilized. APAP and AMAP treatments resulted in significant and large changes in gene expression that were quite disparate, and likely related to their different toxicologic profiles. Ten transcripts, all of which have been implicated in p53 signaling, were identified as differentially regulated at all time-points following APAP and AMAP treatments across multiple microarray platforms. Protein-level quantification of p53 activity aligned with results from the transcriptomic analysis, thus supporting the implicated mechanism of APAP-induced toxicity. Therefore, the results of this study provide good evidence that APAP-induced p53 phosphorylation and an altered p53-driven transcriptional response are fundamental steps in APAP-induced toxicity.

Alterations in the proteome of the respiratory tract in response to single and multiple exposures to naphthalene

Protein adduction is considered to be critical to the loss of cellular homeostasis associated with environmental chemicals undergoing metabolic activation. Despite considerable effort, our understanding of the key proteins mediating the pathologic consequences from protein modification by electrophiles is incomplete. This work focused on naphthalene (NA) induced acute injury of respiratory epithelial cells and tolerance which arises after multiple toxicant doses to define the initial cellular proteomic response and later protective actions related to tolerance. Airways and nasal olfactory epithelium from mice exposed to 15 ppm NA either for 4 h (acute) or for 4 h/day × 7 days (tolerant) were used for label-free protein quantitation by LC/MS/MS. Cytochrome P450 2F2 and secretoglobin 1A1 are decreased dramatically in airways of mice exposed for 4 h, a finding consistent with the fact that CYPs are localized primarily in Clara cells. A number of heat shock proteins and protein disulfide isomerases, which had previously been identified as adduct targets for reactive metabolites from several lung toxicants, were upregulated in airways but not olfactory epithelium of tolerant mice. Protein targets that are upregulated in tolerance may be key players in the pathophysiology associated with reactive metabolite protein adduction. All MS data have been deposited in the ProteomeXchange with identifier PXD000846 (http://proteomecentral.proteomexchange.org/dataset/PXD000846).

An introduction to systems toxicology

Systems toxicology combines novel and historical experimental data to generate increasingly complex models of the biological response to chemical exposure.

Metabonomic analysis of serum of workers occupationally exposed to arsenic, cadmium and lead for biomarker research: a preliminary study

Environmental metabonomics is the application of metabonomics to characterize the interactions of organisms with their environment. Metabolic profiling is an exciting addition to the armory of the epidemiologist for the discovery of new disease risk biomarkers and diagnostics. This work is a continuation of research searching for preclinical serum markers in a group of 389 healthy smelter workers exposed to lead, cadmium and arsenic. Changes in the metabolic profiles were studied using Proton Nuclear Magnetic Resonance Spectroscopy on pooled serum samples from both the metal exposed and control groups. These multivariate metabonomic datasets were analyzed with Principal Component Analysis and Partial Least Squares Discriminant Analysis. Analysis of metabolic profiles of people exposed to heavy metals suggests energy metabolism disturbance induced by heavy metals. Changes in lipid fraction (very-low-density lipoprotein - VLDL, low-density lipoprotein - LDL), unsaturated lipids and in the level of amino acids suggest perturbation of the metabolism of lipids and amino acids. This study illustrated the high reliability of NMR-based metabonomic profiling on the study of the biochemical effects induced by the mixture of heavy metals. This approach is capable of identifying intermediate biomarkers of response to toxicants at environmental/occupational concentrations, paving the way to its use in a monitoring of smelter workers exposed to low doses of lead, cadmium and arsenic.

Identification of biomarkers that distinguish chemical contaminants based on gene expression profiles

Background

High throughput transcriptomics profiles such as those generated using microarrays have been useful in identifying biomarkers for different classification and toxicity prediction purposes. Here, we investigated the use of microarrays to predict chemical toxicants and their possible mechanisms of action.

Results

In this study, in vitro cultures of primary rat hepatocytes were exposed to 105 chemicals and vehicle controls, representing 14 compound classes. We comprehensively compared various normalization of gene expression profiles, feature selection and classification algorithms for the classification of these 105 chemicals into14 compound classes. We found that normalization had little effect on the averaged classification accuracy. Two support vector machine (SVM) methods, LibSVM and sequential minimal optimization, had better classification performance than other methods. SVM recursive feature selection (SVM-RFE) had the highest overfitting rate when an independent dataset was used for a prediction. Therefore, we developed a new feature selection algorithm called gradient method that had a relatively high training classification as well as prediction accuracy with the lowest overfitting rate of the methods tested. Analysis of biomarkers that distinguished the 14 classes of compounds identified a group of genes principally involved in cell cycle function that were significantly downregulated by metal and inflammatory compounds, but were induced by anti-microbial, cancer related drugs, pesticides, and PXR mediators.

Conclusions

Our results indicate that using microarrays and a supervised machine learning approach to predict chemical toxicants, their potential toxicity and mechanisms of action is practical and efficient. Choosing the right feature and classification algorithms for this multiple category classification and prediction is critical.

Omics technologies and their applications to evaluate metal toxicity in mice M. spretus as a bioindicator

Metals are important components of living organisms since many biological functions critically depend on their interaction with some metal in the cell. However, human activities have increased toxic metal levels in the terrestrial and aquatic ecosystems affecting living organisms. The impact of metals on cellular metabolism and global homeostasis has been traditionally assessed in free-living organisms by using conventional biomarkers; however, to obtain a global vision of metal toxicity mechanisms and the responses that metals elicit in the organisms, new analytical methodologies are needed. We review the use of omics approaches to assess the response of living organisms under metal stress illustrating the possibilities of different methodologies on the basis of our previous results. Most of this research has been based on free-living mice Mus spretus, a conventional bioindicator used to monitor metal pollution in Doñana National Park (DNP) (SW Spain), which is an important European biological reserve for migrating birds affected by agricultural, mining and industrial activities. The benefits of using omic techniques such as heterologous microarrays, proteomics methodologies (2-DE, iTRAQ®), metallomics, ionomics or metabolomics has been remarked; however, the complexity of these areas requires the integration of omics to achieve a comprehensive assessment of their environmental status. This article is part of a Special Issue entitled: Environmental and structural proteomics.

BIOLOGICAL SIGNIFICANCE

This work presents new contributions in the study of environmental metal pollution in terrestrial ecosystems using Mus spretus mice as bioindicator in Doñana National Park (SW Spain) and surroundings. In addition, it has been demonstrated that the integration of omics multi-analytical approaches provides a very suitable approach for the study of the biological response and metal interactions in exposed and free-living mice (Mus musculus and Mus spretus, respectively) under metal pollution.

Hepatic gene expression in herbivores on diets with natural and novel plant secondary compounds

Herbivores are predicted to evolve appropriate mechanisms to process the plant secondary compounds (PSCs) in their diet, and these mechanisms are likely specific to particular suites of PSCs. Changes in diet composition over evolutionary time should select for appropriate alterations in metabolism of the more recent dietary components. We investigated differences in gene expression profiles in the liver with respect to prior ecological and evolutionary experience with PSCs in the desert woodrat, Neotoma lepida. This woodrat species has populations in the Mojave Desert that have switched from feeding on juniper to feeding on creosote at the end of the Holocene as well as populations in the Great Basin Desert that still feed on the ancestral diet of juniper and are naïve to creosote. Juniper and creosote have notable differences in secondary chemistry. Woodrats from the Mojave and Great Basin Deserts were subjected to a fully crossed feeding trial on diets of juniper and creosote after which their livers were analyzed for gene expression. Hybridization of hepatic mRNAs to laboratory rat microarrays resulted in a total of 20,031 genes that met quality control standards. We analyzed differences in large-scale patterns of liver gene expression with respect to GO term enrichment. Diet had a larger effect on gene expression than population membership. However, woodrats with no prior evolutionary experience to the diet upregulated a greater proportion of genes indicative of physiological stress compared with those on their natural diet. This pattern may be the result of a naïve animal's attempting to mitigate physiological damage caused by novel PSCs.

Survey of Clustering

This article is a survey into clustering applications and algorithms. A number of important well-known clustering methods are discussed. The authors present a brief history of the development of the field of clustering, discuss various types of clustering, and mention some of the current research directions in the field of clustering. More specifically, top-down and bottom-up hierarchical clustering are described. Additionally, K-Means and K-Medians clustering algorithms are also shown. The concept of representative points is introduced and the technique of discovering them is presented. Immense data sets in clustering often necessitate parallel computation. The authors discuss issues involving parallel clustering as well. Clustering deals with a large number of experimental results. The authors provide references to these works throughout the article. A table for comparing various clustering methods is given in the end. The authors give a summary and an extensive list of references, including some of the latest works in the field, to conclude the article.

Blood transcriptomics: applications in toxicology

The number of new chemicals that are being synthesized each year has been steadily increasing. While chemicals are of immense benefit to mankind, many of them have a significant negative impact, primarily owing to their inherent chemistry and toxicity, on the environment as well as human health. In addition to chemical exposures, human exposures to numerous non-chemical toxic agents take place in the environment and workplace. Given that human exposure to toxic agents is often unavoidable and many of these agents are found to have detrimental human health effects, it is important to develop strategies to prevent the adverse health effects associated with toxic exposures. Early detection of adverse health effects as well as a clear understanding of the mechanisms, especially at the molecular level, underlying these effects are key elements in preventing the adverse health effects associated with human exposure to toxic agents. Recent developments in genomics, especially transcriptomics, have prompted investigations into this important area of toxicology. Previous studies conducted in our laboratory and elsewhere have demonstrated the potential application of blood gene expression profiling as a sensitive, mechanistically relevant and practical surrogate approach for the early detection of adverse health effects associated with exposure to toxic agents. The advantages of blood gene expression profiling as a surrogate approach to detect early target organ toxicity and the molecular mechanisms underlying the toxicity are illustrated and discussed using recent studies on hepatotoxicity and pulmonary toxicity. Furthermore, the important challenges this emerging field in toxicology faces are presented in this review article.

Pyrosequencing-based transcriptomic resources in the pond snail Lymnaea stagnalis, with a focus on genes involved in molecular response to diquat-induced stress

Due to their ability to explore whole genome response to drugs and stressors, omics-based approaches are widely used in toxicology and ecotoxicology, and identified as powerful tools for future ecological risk assessment and environmental monitoring programs. Understanding the long-term effects of contaminants may indeed benefit from the coupling of genomics and eco-evolutionary hypotheses. Next-generation sequencing provides a new way to investigate pollutants impact, by targeting early responses, screening chemicals, and directly quantifying gene expression, even in organisms without reference genome. Lymnaea stagnalis is a freshwater mollusk in which access to genomic resources is critical for many scientific issues, especially in ecotoxicology. We used 454-pyrosequencing to obtain new transcriptomic resources in L. stagnalis and to preliminarily explore gene expression response to a redox-cycling pesticide, diquat. We obtained 151,967 and 128,945 high-quality reads from control and diquat-exposed individuals, respectively. Sequence assembly provided 141,999 contigs, of which 124,387 were singletons. BlastX search revealed significant match for 34.6 % of the contigs (21.2 % protein hits). KEGG annotation showed a predominance of hits with genes involved in energy metabolism and circulatory system, and revealed more than 400 putative genes involved in oxidative stress, cellular/molecular stress and signaling pathways, apoptosis, and metabolism of xenobiotics. Results also suggest that diquat may have a great diversity of molecular effects. Moreover, new genetic markers (putative SNPs) were discovered. We also created a Ensembl-like web-tool for data-mining ( http://genotoul-contigbrowser.toulouse.inra.fr:9095/Lymnaea_stagnalis/index.html ). This resource is expected to be relevant for any genomic approach aimed at understanding the molecular basis of physiological and evolutionary responses to environmental stress in L. stagnalis.

Molecular insights into the progression of crystalline silica-induced pulmonary toxicity in rats

Identification of molecular target(s) and mechanism(s) of silica-induced pulmonary toxicity is important for the intervention and/or prevention of diseases associated with exposure to silica. Rats were exposed to crystalline silica by inhalation (15 mg m(-3), 6 h per day, 5 days) and global gene expression profile was determined in the lungs by microarray analysis at 1, 2, 4, 8 and 16 weeks following termination of silica exposure. The number of significantly differentially expressed genes (>1.5-fold change and <0.01 false discovery rate P-value) detected in the lungs during the post-exposure time intervals analyzed exhibited a steady increase in parallel with the progression of silica-induced pulmonary toxicity noticed in the rats. Quantitative real-time PCR analysis of a representative set of 10 genes confirmed the microarray findings. The number of biological functions, canonical pathways and molecular networks significantly affected by silica exposure, as identified by the bioinformatics analysis of the significantly differentially expressed genes detected during the post-exposure time intervals, also exhibited a steady increase similar to the silica-induced pulmonary toxicity. Genes involved in oxidative stress, inflammation, respiratory diseases, cancer, and tissue remodeling and fibrosis were significantly differentially expressed in the rat lungs; however, unresolved inflammation was the single most significant biological response to pulmonary exposure to silica. Excessive mucus production, as implicated by significant overexpression of the pendrin coding gene, SLC26A4, was identified as a potential novel mechanism for silica-induced pulmonary toxicity. Collectively, the findings of our study provided insights into the molecular mechanisms underlying the progression of crystalline silica-induced pulmonary toxicity in the rat. Published 2012. This article is a US Government work and is in the public domain in the USA.

Mechanisms of crystalline silica-induced pulmonary toxicity revealed by global gene expression profiling

A proper understanding of the mechanisms underlying crystalline silica-induced pulmonary toxicity has implications in the management and potential prevention of the adverse health effects associated with silica exposure including silicosis, cancer and several auto-immune diseases. Human lung type II epithelial cells and rat lungs exposed to crystalline silica were employed as experimental models to determine global gene expression changes in order to understand the molecular mechanisms underlying silica-induced pulmonary toxicity. The differential gene expression profile induced by silica correlated with its toxicity in the A549 cells. The biological processes perturbed by silica exposure in the A549 cells and rat lungs, as identified by the bioinformatics analysis of the differentially expressed genes, demonstrated significant similarity. Functional categorization of the differentially expressed genes identified cancer, cellular movement, cellular growth and proliferation, cell death, inflammatory response, cell cycle, cellular development, and genetic disorder as top ranking biological functions perturbed by silica exposure in A549 cells and rat lungs. Results of our study, in addition to confirming several previously identified molecular targets and mechanisms involved in silica toxicity, identified novel molecular targets and mechanisms potentially involved in silica-induced pulmonary toxicity. Further investigations, including those focused on the novel molecular targets and mechanisms identified in the current study may result in better management and, possibly, reduction and/or prevention of the potential adverse health effects associated with crystalline silica exposure.

Modulatory profiling identifies mechanisms of small molecule-induced cell death

Cell death is a complex process that plays a vital role in development, homeostasis, and disease. Our understanding of and ability to control cell death is impeded by an incomplete characterization of the full range of cell death processes that occur in mammalian systems, especially in response to exogenous perturbations. We present here a general approach to address this problem, which we call modulatory profiling. Modulatory profiles are composed of the changes in potency and efficacy of lethal compounds produced by a second cell death-modulating agent in human cell lines. We show that compounds with the same characterized mechanism of action have similar modulatory profiles. Furthermore, clustering of modulatory profiles revealed relationships not evident when clustering lethal compounds based on gene expression profiles alone. Finally, modulatory profiling of compounds correctly predicted three previously uncharacterized compounds to be microtubule-destabilizing agents, classified numerous compounds that act nonspecifically, and identified compounds that cause cell death through a mechanism that is morphologically and biochemically distinct from previously established ones.

Inflammatory response in rat lungs with recurrent exposure to welding fumes

As chronic exposure to welding fumes causes pulmonary diseases, such as pneumoconiosis, public concern has increased regarding continued exposure to these hazardous gases in the workplace. In a previous study, the inflammatory response to welding fume exposure was analysed in rat lungs in the case of recurrent exposure and recovery periods. Thus using lung samples, well-annotated by histological observation and biochemical analysis, this study examines the gene expression profiles to identify phenotype-anchored genes corresponding to lung inflammation and the repair phenomenon after recurrent welding fume exposure. Seven genes ( Mmp12, Cd5l, LOC50101, LOC69183, Spp1, and Slc26a4) were found to be significantly up-regulated according to the severity of the lung injury. In addition, the transcription and translation of Trem2, which was up-regulated in response to the repair process, were validated using a real-time polymerase chain reaction, Western blotting, and immunohistochemistry. The differentially expressed genes in the exposure and recovery groups were also classified using k-means and hierarchical clustering, plus their toxicological function and canonical pathways were further analysed using Ingenuity Pathways Analysis Software. As a result, this comprehensive and integrative analysis of the transcriptional changes that occur during repeated exposure provides important information on the inflammation and repair processes after welding-fume-induced lung injury.

Omic approaches in environmental issues

Biomonitoring requires the application of batteries of different biomarkers, as environmental contaminants induce multiple responses in organisms that are not necessarily correlated. Omic technologies were proposed as an alternative to conventional biomarkers since these techniques quantitatively monitor many biological molecules in a high-throughput manner and thus provide a general appraisal of biological responses altered by exposure to contaminants. As the studies using omic technologies increase, it is becoming clear that any single omic approach may not be sufficient to characterize the complexity of ecosystems. This work aims to provide a preliminary working scheme for the use of combined transcriptomic and proteomic methodologies in environmental biomonitoring. There are difficulties in working with nonmodel organisms as bioindicators when combining several omic approaches. As a whole, our results with heterologous microarrays in M. spretus and suppressive subtractive hybridization (SSH) in P. clarkii indicated that animals sustaining a heavy pollution burden exhibited an enhanced immune response and/or cell apoptosis. The proteomic studies, although preliminary, provide a holistic insight regarding the manner by which pollution shifts protein intensity in two-dimensional gel electrophoresis (2-DE), completing the transcriptomic approach. In our study, the sediment element concentration was in agreement with the intensity of protein expression changes in C. maenas crabs. In conclusion, omics are useful technologies in addressing environmental issues and the determination of contamination threats.

HPLC-MS/MS methods for the quantitative analysis of ophthalmic acid in rodent plasma and hepatic cell line culture medium

Ophthalmic acid (OA), an endogenous tripeptide analogue of glutathione, has been suggested as a potential biomarker for paracetamol/acetaminophen hepatotoxicity. Here HPLC-MS/MS methods have been developed for the precise, sensitive and specific detection and quantification of OA in in vitro cell culture medium and plasma. For the cell culture medium the LLOQ was found to be 1 ng/ml, with less than 1% between sample carry over at all concentrations and precision below 15% for within day and below 9% for between day analyses. For rat plasma the presence of endogenous OA resulted in the LLOQ being 25 ng/ml (defined as the lowest concentration on the calibration curve where the base peak was less than 20% of the LLOQ). For the plasma assay the percentage carry over was less than 1% for all concentrations and within and between batch precision was below 21%. The methods were linear for both sample types from the LLOQ up to 5 μg/ml. The method was successfully applied to the determination of OA in samples obtained following the chronic administration of the rat hepatotoxin methapyrilene, where plasma OA concentrations were observed to show a weak negative correlation with those of established liver injury biomarkers such as aspartate aminotransferase (AST).