Genomic comparisons between hepatocarcinogenic and non-hepatocarcinogenic organophosphate insecticides in the mouse liver.

Short-term biomarkers of toxicity have an increasingly important role in the screening and prioritization of new chemicals. In this study, we examined early indicators of liver toxicity for three reference organophosphate (OP) chemicals, which are among the most widely used insecticides in the world. The OP methidathion was previously shown to increase the incidence of liver toxicity, including hepatocellular tumors, in male mice. To provide insights into the adverse outcome pathway (AOP) that underlies these tumors, effects of methidathion in the male mouse liver were examined after 7 and 28 day exposures and compared to those of two other OPs that either do not increase (fenthion) or possibly suppress liver cancer (parathion) in mice. None of the chemicals caused increases in liver weight/body weight or histopathological changes in the liver. Parathion decreased liver cell proliferation after 7 and 28 days while the other chemicals had no effects. There was no evidence for hepatotoxicity in any of the treatment groups. Full-genome microarray analysis of the livers from the 7 and 28 day treatments demonstrated that methidathion and fenthion regulated a large number of overlapping genes, while parathion regulated a unique set of genes. Examination of cytochrome P450 enzyme activities and use of predictive gene expression biomarkers found no consistent evidence for activation of AhR, CAR, PXR, or PPARα. Parathion suppressed the male-specific gene expression pattern through STAT5b, similar to genetic and dietary conditions that decrease liver tumor incidence in mice. Overall, these findings indicate that methidathion causes liver cancer by a mechanism that does not involve common mechanisms of liver cancer induction.

A Gene Expression Biomarker Identifies Chemical Modulators of Estrogen Receptor α in an MCF-7 Microarray Compendium.

Identification of chemicals that affect hormone-regulated systems will help to predict endocrine disruption. In our previous study, a 46 gene biomarker was found to be an accurate predictor of estrogen receptor (ER) α modulation in chemically treated MCF-7 cells. Here, potential ERα modulators were identified using the biomarker by screening a microarray compendium consisting of ∼1600 gene expression comparisons representing exposure to ∼1200 chemicals. A total of ∼170 chemicals were identified as potential ERα modulators. In the Connectivity Map 2.0 collection, 75 and 39 chemicals were predicted to activate or suppress ERα, and they included 12 and six known ERα agonists and antagonists/selective ERα modulators, respectively. Nineteen and eight of the total number were also identified as active in an ERα transactivation assay carried out in an MCF-7-derived cell line used to screen the Tox21 10K chemical library in agonist or antagonist modes, respectively. Chemicals predicted to modulate ERα in MCF-7 cells were examined further using global and targeted gene expression in wild-type and ERα-null cells, transactivation assays, and cell-free ERα coregulator interaction assays. Environmental chemicals classified as weak and very weak agonists were confirmed to activate ERα including apigenin, kaempferol, and oxybenzone. Novel activators included digoxin, nabumetone, ivermectin, and six progestins. Novel suppressors included emetine, mifepristone, niclosamide, and proscillaridin. Our strategy will be useful to identify environmentally relevant ERα modulators in future high-throughput transcriptomic screens.

In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs.

Historically, identifying carcinogens has relied primarily on tumor studies in rodents, which require enormous resources in both money and time. In silico models have been developed for predicting rodent carcinogens but have not yet found general regulatory acceptance, in part due to the lack of a generally accepted protocol for performing such an assessment as well as limitations in predictive performance and scope. There remains a need for additional, improved in silico carcinogenicity models, especially ones that are more human-relevant, for use in research and regulatory decision-making. As part of an international effort to develop in silico toxicological protocols, a consortium of toxicologists, computational scientists, and regulatory scientists across several industries and governmental agencies evaluated the extent to which in silico models exist for each of the recently defined 10 key characteristics (KCs) of carcinogens. This position paper summarizes the current status of in silico tools for the assessment of each KC and identifies the data gaps that need to be addressed before a comprehensive in silico carcinogenicity protocol can be developed for regulatory use.

Thresholds Derived From Common Measures in Rat Studies Are Predictive of Liver Tumorigenic Chemicals.

We hypothesized that typical tissue and clinical chemistry (ClinChem) end points measured in rat toxicity studies exhibit chemical-independent biological thresholds beyond which cancer occurs. Using the rat in vivo TG-GATES study, 75 chemicals were examined across chemical-dose-time comparisons that could be linked to liver tumor outcomes. Thresholds for liver weight to body weight (LW/BW) and 21 serum ClinChem end points were defined as the maximum and minimum values for those exposures that did not lead to liver tumors in rats. Upper thresholds were identified for LW/BW (117%), aspartate aminotransferase (195%), alanine aminotransferase (141%), alkaline phosphatase (152%), and total bilirubin (115%), and lower thresholds were identified for phospholipids (82%), relative albumin (93%), total cholesterol (82%), and total protein (94%). Thresholds derived from the TG-GATES data set were consistent across other acute and subchronic rat studies. A training set of ClinChem and LW/BW thresholds derived from a 38 chemical training set from TG-GATES was predictive of liver tumor outcomes for a test set of 37 independent TG-GATES chemicals (91%). The thresholds were most predictive when applied to 7d treatments (98%). These findings provide support that biological thresholds for common end points in rodent studies can be used to predict chemical tumorigenic potential.

Mining a human transcriptome database for chemical modulators of NRF2.

Nuclear factor erythroid-2 related factor 2 (NRF2) encoded by the NFE2L2 gene is a transcription factor critical for protecting cells from chemically-induced oxidative stress. We developed computational procedures to identify chemical modulators of NRF2 in a large database of human microarray data. A gene expression biomarker was built from statistically-filtered gene lists derived from microarray experiments in primary human hepatocytes and cancer cell lines exposed to NRF2-activating chemicals (oltipraz, sulforaphane, CDDO-Im) or in which the NRF2 suppressor Keap1 was knocked down by siRNA. Directionally consistent biomarker genes were further filtered for those dependent on NRF2 using a microarray dataset from cells after NFE2L2 siRNA knockdown. The resulting 143-gene biomarker was evaluated as a predictive tool using the correlation-based Running Fisher algorithm. Using 59 gene expression comparisons from chemically-treated cells with known NRF2 activating potential, the biomarker gave a balanced accuracy of 93%. The biomarker was comprised of many well-known NRF2 target genes (AKR1B10, AKR1C1, NQO1, TXNRD1, SRXN1, GCLC, GCLM), 69% of which were found to be bound directly by NRF2 using ChIP-Seq. NRF2 activity was assessed across ~9840 microarray comparisons from ~1460 studies examining the effects of ~2260 chemicals in human cell lines. A total of 260 and 43 chemicals were found to activate or suppress NRF2, respectively, most of which have not been previously reported to modulate NRF2 activity. Using a NRF2-responsive reporter gene in HepG2 cells, we confirmed the activity of a set of chemicals predicted using the biomarker. The biomarker will be useful for future gene expression screening studies of environmentally-relevant chemicals.

Gene Expression Thresholds Derived From Short-term Exposures Identify Rat Liver Tumorigens.

Traditional methods for cancer risk assessment are resource-intensive, retrospective, and not feasible for the vast majority of environmental chemicals. In this study, we investigated whether quantitative genomic data from short-term studies may be used to set protective thresholds for potential tumorigenic effects. We hypothesized that gene expression biomarkers measuring activation of the key early events in established pathways for rodent liver cancer exhibit cross-chemical thresholds for tumorigenesis predictive for liver cancer risk. We defined biomarker thresholds for 6 major liver cancer pathways using training sets of chemicals with short-term genomic data (3-29 days of exposure) from the TG-GATES (n = 77 chemicals) and DrugMatrix (n = 86 chemicals) databases and then tested these thresholds within and between datasets. The 6 pathway biomarkers represented genotoxicity, cytotoxicity, and activation of xenobiotic, steroid, and lipid receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Thresholds were calculated as the maximum values derived from exposures without detectable liver tumor outcomes. We identified clear response values that were consistent across training and test sets. Thresholds derived from the TG-GATES training set were highly predictive (97%) in a test set of independent chemicals, whereas thresholds derived from the DrugMatrix study were 96%-97% predictive for the TG-GATES study. Threshold values derived from an abridged gene list (2/biomarker) also exhibited high predictive accuracy (91%-94%). These findings support the idea that early genomic changes can be used to establish threshold estimates or "molecular tipping points" that are predictive of later-life health outcomes.

A Set of Six Gene Expression Biomarkers Identify Rat Liver Tumorigens in Short-term Assays.

Chemical-induced liver cancer occurs in rodents through well-characterized adverse outcome pathways. We hypothesized that measurement of the 6 most common molecular initiating events (MIEs) in liver cancer adverse outcome pathways in short-term assays using only gene expression will allow early identification of chemicals and their associated doses that are likely to be tumorigenic in the liver in 2-year bioassays. We tested this hypothesis using transcript data from a rat liver microarray compendium consisting of 2013 comparisons of 146 chemicals administered at doses with previously established effects on rat liver tumor induction. Five MIEs were measured using previously characterized gene expression biomarkers composed of gene sets predictive for genotoxicity and activation of 1 or more xenobiotic receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Because chronic injury can be important in tumorigenesis, we also developed a biomarker for cytotoxicity that had a 96% balanced accuracy. Characterization of the genes in each biomarker set using the unsupervised TXG-MAP network model demonstrated that the genes were associated with distinct functional coexpression modules. Using the Toxicological Priority Index to rank chemicals based on their ability to activate the MIEs showed that chemicals administered at tumorigenic doses clearly gave the highest ranked scores. Balanced accuracies using thresholds derived from either TG-GATES or DrugMatrix data sets to predict tumorigenicity in independent sets of chemicals were up to 93%. These results show that a MIE-directed approach using only gene expression biomarkers could be used in short-term assays to identify chemicals and their doses that cause tumors.

Chemical Activation of the Constitutive Androstane Receptor Leads to Activation of Oxidant-Induced Nrf2.

Exposure to environmentally relevant chemicals that activate the xenobiotic receptors aryl hydrocarbon receptor (AhR), constitutive androstane receptor (CAR), and peroxisome proliferator-activated receptor alpha (PPARα) in rodent test systems often leads to increases in oxidative stress (OS) that contributes to liver cancer induction. We hypothesized that activation of the oxidant-induced transcription factor Nrf2 could be used as a surrogate endpoint for increases in OS. We examined the relationships between activation of xenobiotic receptors and Nrf2 using previously characterized gene expression biomarkers that accurately predict modulation. Using a correlation approach (Running Fisher Test), the biomarkers were compared with microarray profiles in a mouse liver gene expression compendium. Out of the 163 chemicals examined, 47% from 53 studies activated Nrf2. We found consistent coupling between CAR and Nrf2 activation. Out of the 41 chemicals from 32 studies that activated CAR, 90% also activated Nrf2. CAR was activated earlier and at lower doses than Nrf2, indicating CAR activation preceded Nrf2 activation. Nrf2 activation by 2 CAR activators was abolished in CAR-null mice. We hypothesized that Nrf2 is activated by reactive oxygen species from the increased activity of enzymes encoded by Cyp2b family members. However, Nrf2 was similarly activated in the livers of both TCPOBOP-treated wild-type and Cyp2b9/10/13-null mice. This study provides evidence that Nrf2 activation (1) often occurs after exposure to xenobiotic chemicals, (2) is tightly linked to activation of CAR, and (3) does not require induction of 3 Cyp2b genes secondary to CAR activation.

Activation of Nrf2 in the liver is associated with stress resistance mediated by suppression of the growth hormone-regulated STAT5b transcription factor.

The transcription factor Nrf2 (encoded by Nfe2l2) induces expression of numerous detoxifying and antioxidant genes in response to oxidative stress. The cytoplasmic protein Keap1 interacts with and represses Nrf2 function. Computational approaches were developed to identify factors that modulate Nrf2 in a mouse liver gene expression compendium. Forty-eight Nrf2 biomarker genes were identified using profiles from the livers of mice in which Nrf2 was activated genetically in Keap1-null mice or chemically by a potent activator of Nrf2 signaling. The rank-based Running Fisher statistical test was used to determine the correlation between the Nrf2 biomarker genes and a test set of 81 profiles with known Nrf2 activation status demonstrating a balanced accuracy of 96%. For a large number of factors examined in the compendium, we found consistent relationships between activation of Nrf2 and feminization of the liver transcriptome through suppression of the male-specific growth hormone (GH)-regulated transcription factor STAT5b. The livers of female mice exhibited higher Nrf2 activation than male mice in untreated or chemical-treated conditions. In male mice, Nrf2 was activated by treatment with ethinyl estradiol, whereas in female mice, Nrf2 was suppressed by treatment with testosterone. Nrf2 was activated in 5 models of disrupted GH signaling containing mutations in Pit1, Prop1, Ghrh, Ghrhr, and Ghr. Out of 59 chemical treatments that activated Nrf2, 36 exhibited STAT5b suppression in the male liver. The Nrf2-STAT5b coupling was absent in in vitro comparisons of chemical treatments. Treatment of male and female mice with 11 chemicals that induce oxidative stress led to activation of Nrf2 to greater extents in females than males. The enhanced basal and inducible levels of Nrf2 activation in females relative to males provides a molecular explanation for the greater resistance often seen in females vs. males to age-dependent diseases and chemical-induced toxicity.

Identification of Androgen Receptor Modulators in a Prostate Cancer Cell Line Microarray Compendium.

High-throughput transcriptomic (HTTr) technologies are increasingly being used to screen environmental chemicals in vitro to identify molecular targets and provide mechanistic context for regulatory testing. Here, we describe the development and validation of a novel gene expression biomarker to identify androgen receptor (AR)-modulating chemicals using a pattern matching method. Androgen receptor biomarker genes were identified by their consistent expression after exposure to 4 AR agonists and 4 AR antagonists and included only those genes that were regulated by AR. The 51 gene biomarker was evaluated as a predictive tool using the fold-change, rank-based Running Fisher algorithm. Using 158 comparisons from cells treated with 95 chemicals, the biomarker gave balanced accuracies for prediction of AR activation or AR suppression of 97% or 98%, respectively. The biomarker correctly classified 16 out of the 17 AR reference antagonists including those that are "weak" and "very weak". Predictions based on microarray profiles from AR-positive LAPC-4 cells treated with 28 chemicals in antagonist mode were compared with those from an AR pathway model which used 11 in vitro HT assays. The balanced accuracy for suppression was 93%. Using our approach, we identified conditions in which AR was modulated in a large collection of microarray profiles from prostate cancer cell lines including (1) constitutively active mutants or knockdown of AR, (2) decreases in availability of androgens by castration or removal from media, and (3) exposure to chemical modulators that work through indirect mechanisms including suppression of AR expression. These results demonstrate that the AR gene expression biomarker could be a useful tool in HTTr to identify AR modulators.

Adverse outcome pathway-driven identification of rat liver tumorigens in short-term assays.

Chemicals induce liver cancer in rodents through well characterized adverse outcome pathways (AOPs). We hypothesized that measurement of molecular initiating events (MIEs) and downstream key events (KEs) in liver cancer AOPs in short-term assays will allow early identification of chemicals and their associated doses that are likely to be tumorigenic in the liver in two-year bioassays. We tested this hypothesis using the rat in vivo TG-GATES study data to measure MIEs (genotoxicity, cytotoxicity, AhR, CAR, ER, PPARα) and associated KEs (oxidative stress, cell proliferation, liver to body weights) across 77 chemicals that could be linked to doses with previously established effects on rat liver tumor induction. Gene expression biomarkers for MIEs generally considered to be rodent specific and human irrelevant (CAR, PPARα) and for MIEs that would be considered of greater risk at human relevant exposures (ER, AhR) were built using microarray comparisons from the livers of rats treated with prototypical activators of the receptors. The genotoxicity biomarker, also a potentially human relevant MIE, was comprised of 7 p53-responsive genes known to be induced upon DNA damage. The ability of the biomarkers to accurately predict MIE activation ranged from 91% to 98%. The Toxicological Priority Index (ToxPi) was used to rank chemicals based on their ability to activate MIEs/KEs. Chemicals administered at tumorigenic doses clearly gave the highest ranked scores. Our AOP-directed approach could be used in short term assays to identify chemicals and their doses that would be predicted to cause liver tumors in rats.

From the Cover: Genomic Effects of Androstenedione and Sex-Specific Liver Cancer Susceptibility in Mice.

Current strategies for predicting carcinogenic mode of action for nongenotoxic chemicals are based on identification of early key events in toxicity pathways. The goal of this study was to evaluate short-term key event indicators resulting from exposure to androstenedione (A4), an androgen receptor agonist and known liver carcinogen in mice. Liver cancer is more prevalent in men compared with women, but androgen-related pathways underlying this sex difference have not been clearly identified. Short-term hepatic effects of A4 were compared with reference agonists of the estrogen receptor (ethinyl estradiol, EE) and glucocorticoid receptor (prednisone, PRED). Male B6C3F1 mice were exposed for 7 or 28 days to A4, EE, or PRED. EE increased and PRED suppressed hepatocyte proliferation, while A4 had no detectable effects. In a microarray analysis, EE and PRED altered >3000 and >670 genes, respectively, in a dose-dependent manner, whereas A4 did not significantly alter any genes. Gene expression was subsequently examined in archival liver samples from male and female B6C3F1 mice exposed to A4 for 90 days. A4 altered more genes in females than males and did not alter expression of genes linked to activation of the mitogenic xenobiotic receptors AhR, CAR, and PPARα in either sex. A gene expression biomarker was used to show that in female mice, the high dose of A4 activated the growth hormone-regulated transcription factor STAT5b, which controls sexually dimorphic gene expression in the liver. These findings suggest that A4 induces subtle age-related effects on STAT5b signaling that may contribute to the higher risk of liver cancer in males compared with females.

PPARα-independent transcriptional targets of perfluoroalkyl acids revealed by transcript profiling.

Perfluoroalkyl acids (PFAAs) are ubiquitous and persistent environmental contaminants. Compounds such as perfluoroocanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorononanoic acid (PFNA), and perfluorohexane sulfonate (PFHxS) are readily found in the tissues of humans and wildlife. While PFOA and PFOS have been the subject of numerous studies since they were first described over a decade ago, less is known about the biological activity of PFHxS and PFNA. Most PFAAs are activators of peroxisome proliferator-activated receptor α (PPARα), although the biological effects of these compounds are likely mediated by other factors in addition to PPARα. To evaluate the effects of PFHxS and PFNA, male wild-type and Pparα-null mice were dosed by oral gavage with PFHxS (3 or 10mg/kg/day), PFNA (1 or 3mg/kg/day), or vehicle for 7days, and liver gene expression was evaluated by full-genome microarrays. Gene expression patterns were then compared to historical in-house data for PFOA and PFOS in addition to the experimental hypolipidemic agent, WY-14,643. While WY-14,643 altered most genes in a PPARα-dependent manner, approximately 11-24% of regulated genes in PFAA-treated mice were independent of PPARα. The possibility that PFAAs regulate gene expression through other molecular pathways was evaluated. Using data available through a microarray database, PFAA gene expression profiles were found to exhibit significant similarity to profiles from mouse tissues exposed to agonists of the constitutive activated receptor (CAR), estrogen receptor α (ERα), and PPARγ. Human PPARγ and ERα were activated by all four PFAAs in trans-activation assays from the ToxCast screening program. Predictive gene expression biomarkers showed that PFAAs activate CAR in both genotypes and cause feminization of the liver transcriptome through suppression of signal transducer and activator of transcription 5B (STAT5B). These results indicate that, in addition to activating PPARα as a primary target, PFAAs also have the potential to activate CAR, PPARγ, and ERα as well as suppress STAT5B.

Seahorse Xfe 24 Extracellular Flux Analyzer-Based Analysis of Cellular Respiration in Caenorhabditis elegans.

Mitochondria are critical for their role in ATP production as well as multiple nonenergetic functions, and mitochondrial dysfunction is causal in myriad human diseases. Less well appreciated is the fact that mitochondria integrate environmental and intercellular as well as intracellular signals to modulate function. Because mitochondria function in an organismal milieu, there is need for assays capable of rapidly assessing mitochondrial health in vivo. Here, using the Seahorse XF(e) 24 Extracellular Flux Analyzer and the pharmacological inhibitors dicyclohexylcarbodiimide (DCCD, ATP synthase inhibitor), carbonyl cyanide-p-trifluoromethoxyphenylhydrazone (FCCP, mitochondrial uncoupler), and sodium azide (cytochrome c oxidase inhibitor), we describe how to obtain in vivo measurements of the fundamental parameters [basal oxygen consumption rate (OCR), ATP-linked respiration, maximal OCR, spare respiratory capacity, and proton leak] of the mitochondrial respiratory chain in the model organism Caenorhabditis elegans.

Mitochondrial Morphology and Fundamental Parameters of the Mitochondrial Respiratory Chain Are Altered in Caenorhabditis elegans Strains Deficient in Mitochondrial Dynamics and Homeostasis Processes.

Mitochondrial dysfunction has been linked to myriad human diseases and toxicant exposures, highlighting the need for assays capable of rapidly assessing mitochondrial health in vivo. Here, using the Seahorse XFe24 Analyzer and the pharmacological inhibitors dicyclohexylcarbodiimide and oligomycin (ATP-synthase inhibitors), carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone (mitochondrial uncoupler) and sodium azide (cytochrome c oxidase inhibitor), we measured the fundamental parameters of mitochondrial respiratory chain function: basal oxygen consumption, ATP-linked respiration, maximal respiratory capacity, spare respiratory capacity and proton leak in the model organism Caenhorhabditis elegans. Since mutations in mitochondrial homeostasis genes cause mitochondrial dysfunction and have been linked to human disease, we measured mitochondrial respiratory function in mitochondrial fission (drp-1)-, fusion (fzo-1)-, mitophagy (pdr-1, pink-1)-, and electron transport chain complex III (isp-1)-deficient C. elegans. All showed altered function, but the nature of the alterations varied between the tested strains. We report increased basal oxygen consumption in drp-1; reduced maximal respiration in drp-1, fzo-1, and isp-1; reduced spare respiratory capacity in drp-1 and fzo-1; reduced proton leak in fzo-1 and isp-1; and increased proton leak in pink-1 nematodes. As mitochondrial morphology can play a role in mitochondrial energetics, we also quantified the mitochondrial aspect ratio for each mutant strain using a novel method, and for the first time report increased aspect ratios in pdr-1- and pink-1-deficient nematodes.

Effects of mutations in mitochondrial dynamics-related genes on the mitochondrial response to ultraviolet C radiation in developing Caenorhabditis elegans.

We recently found that genes involved in mitochondrial dynamics and autophagy are required for removal of UVC-induced mitochondrial DNA damage. However, drp-1 and pink-1, unlike the autophagy and fusion genes tested, were not necessary for larval development after exposure. We hypothesized that increased fusion resulting from mutations in these genes facilitated recovery of mitochondrial function. In this work, we investigated this hypothesis by studying the effects of fis-1, fis-2, drp-1 and pink-1 mutations on mitochondrial responses to UVC exposure including ATP levels, mitochondrial DNA copy number, larval development and mitochondrial morphology. Our results suggest that mutations that promote highly networked mitochondria have the capacity to lessen the effects of mitochondrial genotoxicants on the function of this organelle.

Effects of early life exposure to ultraviolet C radiation on mitochondrial DNA content, transcription, ATP production, and oxygen consumption in developing Caenorhabditis elegans.

BACKGROUND: Mitochondrial DNA (mtDNA) is present in multiple copies per cell and undergoes dramatic amplification during development. The impacts of mtDNA damage incurred early in development are not well understood, especially in the case of types of mtDNA damage that are irreparable, such as ultraviolet C radiation (UVC)-induced photodimers. METHODS: We exposed first larval stage nematodes to UVC using a protocol that results in accumulated mtDNA damage but permits nuclear DNA (nDNA) repair. We then measured the transcriptional response, as well as oxygen consumption, ATP levels, and mtDNA copy number through adulthood. RESULTS: Although the mtDNA damage persisted to the fourth larval stage, we observed only a relatively minor ~40% decrease in mtDNA copy number. Transcriptomic analysis suggested an inhibition of aerobic metabolism and developmental processes; mRNA levels for mtDNA-encoded genes were reduced ~50% at 3 hours post-treatment, but recovered and, in some cases, were upregulated at 24 and 48 hours post-exposure. The mtDNA polymerase γ was also induced ~8-fold at 48 hours post-exposure. Moreover, ATP levels and oxygen consumption were reduced in response to UVC exposure, with marked reductions of ~50% at the later larval stages. CONCLUSIONS: These results support the hypothesis that early life exposure to mitochondrial genotoxicants could result in mitochondrial dysfunction at later stages of life, thereby highlighting the potential health hazards of time-delayed effects of these genotoxicants in the environment.

Autophagy-dependent regulation of the DNA damage response protein ribonucleotide reductase 1.

Protein synthesis and degradation are posttranscriptional pathways used by cells to regulate protein levels. We have developed a systems biology approach to identify targets of posttranscriptional regulation and we have employed this system in Saccharomyces cerevisiae to study the DNA damage response. We present evidence that 50% to 75% of the transcripts induced by alkylation damage are regulated posttranscriptionally. Significantly, we demonstrate that two transcriptionally-induced DNA damage response genes, RNR1 and RNR4, fail to show soluble protein level increases after DNA damage. To determine one of the associated mechanisms of posttranscriptional regulation, we tracked ribonucleotide reductase 1 (Rnr1) protein levels during the DNA damage response. We show that RNR1 is actively translated after damage and that a large fraction of the corresponding Rnr1 protein is packaged into a membrane-bound structure and transported to the vacuole for degradation, with these last two steps dependent on autophagy proteins. We found that inhibition of target of rapamycin (TOR) signaling and subsequent induction of autophagy promoted an increase in targeting of Rnr1 to the vacuole and a decrease in soluble Rnr1 protein levels. In addition, we demonstrate that defects in autophagy result in an increase in soluble Rnr1 protein levels and a DNA damage phenotype. Our results highlight roles for autophagy and TOR signaling in regulating a specific protein and demonstrate the importance of these pathways in optimizing the DNA damage response.

A genome-wide deletion mutant screen identifies pathways affected by nickel sulfate in Saccharomyces cerevisiae.

BACKGROUND: The understanding of the biological function, regulation, and cellular interactions of the yeast genome and proteome, along with the high conservation in gene function found between yeast genes and their human homologues, has allowed for Saccharomyces cerevisiae to be used as a model organism to deduce biological processes in human cells. Here, we have completed a systematic screen of the entire set of 4,733 haploid S. cerevisiae gene deletion strains (the entire set of nonessential genes for this organism) to identify gene products that modulate cellular toxicity to nickel sulfate (NiSO(4)). RESULTS: We have identified 149 genes whose gene deletion causes sensitivity to NiSO(4) and 119 genes whose gene deletion confers resistance. Pathways analysis with proteins whose absence renders cells sensitive and resistant to nickel identified a wide range of cellular processes engaged in the toxicity of S. cerevisiae to NiSO(4). Functional categories overrepresented with proteins whose absence renders cells sensitive to NiSO(4) include homeostasis of protons, cation transport, transport ATPases, endocytosis, siderophore-iron transport, homeostasis of metal ions, and the diphthamide biosynthesis pathway. Functional categories overrepresented with proteins whose absence renders cells resistant to nickel include functioning and transport of the vacuole and lysosome, protein targeting, sorting, and translocation, intra-Golgi transport, regulation of C-compound and carbohydrate metabolism, transcriptional repression, and chromosome segregation/division. Interactome analysis mapped seven nickel toxicity modulating and ten nickel-resistance networks. Additionally, we studied the degree of sensitivity or resistance of the 111 nickel-sensitive and 72 -resistant strains whose gene deletion product has a similar protein in human cells. CONCLUSION: We have undertaken a whole genome approach in order to further understand the mechanism(s) regulating the cell's toxicity to nickel compounds. We have used computational methods to integrate the data and generate global models of the yeast's cellular response to NiSO(4). The results of our study shed light on molecular pathways associated with the cellular response of eukaryotic cells to nickel compounds and provide potential implications for further understanding the toxic effects of nickel compounds to human cells.

A genome-wide screen in Saccharomyces cerevisiae reveals pathways affected by arsenic toxicity.

We have used Saccharomyces cerevisiae to identify toxicologically important proteins and pathways involved in arsenic-induced toxicity and carcinogenicity in humans. We performed a systemic screen of the complete set of 4733 haploid S. cerevisiae single-gene-deletion mutants to identify those that have decreased or increased growth, relative to wild type, after exposure to sodium arsenite (NaAsO(2)). IC(50) values for all mutants were determined to further validate our results. Ultimately we identified 248 mutants sensitive to arsenite and 5 mutants resistant to arsenite exposure. We analyzed the proteins corresponding to arsenite-sensitive mutants and determined that they belonged to functional categories that include protein binding, phosphate metabolism, vacuolar/lysosomal transport, protein targeting, sorting, and translocation, cell growth/morphogenesis, cell polarity and filament formation. Furthermore, these data were mapped onto a protein interactome to identify arsenite-toxicity-modulating networks. These networks are associated with the cytoskeleton, ubiquitination, histone acetylation and the MAPK signaling pathway. Our studies have potential implications for understanding toxicity and carcinogenesis in arsenic-induced human conditions, such as cancer and aging.