Epigenetic effect of the mycotoxin fumonisin B1 on DNA methylation.

Mycotoxin fumonisin B1 (FB1) is a secondary metabolite that is produced by certain Fusarium species. Although numerous studies demonstrate toxic and carcinogenic effects of FB1, the underlying mechanisms have not been fully elucidated. In this study, we evaluated the epigenetic effects of FB1 for the first time using FLO assays, which detect epigenetic changes that affect the flocculation gene (FLO1) promoter activity in budding yeast. FLO assays showed increased reporter activities of the FLO1 promoter in the presence of 10 and 20 µM FB1. FB1 (20 µM) treatments also promoted flocculation. In subsequent in vitro methylation assays of a bacterial DNA methyltransferase (DNMT), FB1 treatments increased DNMT activities. Moreover, global DNA methylation was significantly increased in HEK293 cells treated with 100 µM FB1. Taken together, these results suggest that FB1 exposure leads to unique epigenetic alterations due to increased DNMT activities and demonstrate that FB1 may be an important risk factor for epigenetic dysfunction-associated human diseases including cancer.

Benchmark dose analysis of multiple genotoxicity endpoints in gpt delta mice exposed to aristolochic acid I.

As the carcinogenic risk of herbs containing aristolochic acids (AAs) is a global health issue, quantitative evaluation of toxicity is needed for the regulatory decision-making and risk assessment of AAs. In this study, we selected AA I (AAI), the most abundant and representative compound in AAs, to treat transgenic gpt delta mice at six gradient doses ranging from 0.125 to 4 mg/kg/day for 28 days. AAI-DNA adduct frequencies and gpt gene mutation frequencies (MFs) in the kidney, as well as Pig-a gene MFs and micronucleated reticulocytes (MN-RETs) frequencies in peripheral blood, were monitored. The dose-response (DR) relationship data for these in vivo genotoxicity endpoints were quantitatively evaluated using an advanced benchmark dose (BMD) approach with different critical effect sizes (CESs; i.e., BMD5, BMD10, BMD50 and BMD100). The results showed that the AAI-DNA adduct frequencies, gpt MFs and the MN-RETs presented good DR relationship to the administrated doses, and the corresponding BMDL100 (the lower 90% confidence interval of the BMD100) values were 0.017, 0.509 and 3.9 mg/kg/day, respectively. No positive responses were observed in the Pig-a MFs due to bone marrow suppression caused by AAI. Overall, we quantitatively evaluated the genotoxicity of AAI at low doses for multiple endpoints for the first time. Comparisons of BMD100 values across different endpoints provide a basis for the risk assessment and regulatory decision-making of AAs and are also valuable for understanding the genotoxicity mechanism of AAs.

Follow-up genotoxicity assessment of Ames-positive/equivocal chemicals using the improved thymidine kinase gene mutation assay in DNA repair-deficient human TK6 cells.

Genotoxicity testing plays an important role in the safety assessment of pharmaceuticals, pesticides and chemical substances. Among the guidelines for various genotoxicity tests, the in vitro genotoxicity test battery comprises the bacterial Ames test and mammalian cell assays. Several chemicals exhibit conflicting results for the bacterial Ames test and mammalian cell genotoxicity studies, which may stem from the differences in DNA repair capacity or metabolism, between different cell types or species. For better understanding the mechanistic implications regarding conflict outcomes between different assay systems, it is necessary to develop in vitro genotoxicity testing approaches with higher specificity towards DNA-damaging reagents. We have recently established an improved thymidine kinase (TK) gene mutation assay (TK assay) i.e. deficient in DNA excision repair system using human lymphoblastoid TK6 cells lacking XRCC1 and XPA (XRCC1-/-/XPA-/-), the core factors of base excision repair (BER) and nucleotide excision repair (NER), respectively. This DNA repair-deficient TK6 cell line is expected to specifically evaluate the genotoxic potential of chemical substances based on the DNA damage. We focussed on four reagents, N-(1-naphthyl)ethylenediamine dihydrochloride (NEDA), p-phenylenediamine (PPD), auramine and malachite green (MG) as the Ames test-positive chemicals. In our assay, assessment using XRCC1-/-/XPA-/- cells revealed no statistically significant increase in the mutant frequencies after treatment with NEDA, PPD and MG, suggesting the chemicals to be non-genotoxic in humans. The observations were consistent with that of the follow-up in vivo studies. In contrast, the mutant frequency was markedly increased in XRCC1-/-/XPA-/- cells after treatment with auramine. The results suggest that auramine is the genotoxic reagent that preferentially induces DNA damages resolved by BER and/or NER in mammals. Taken together, BER/NER-deficient cell-based genotoxicity testing will contribute to elucidate the mechanism of genotoxicity and therefore play a pivotal role in the accurate safety assessment of chemical substances.

Detection of genome-wide low-frequency mutations with Paired-End and Complementary Consensus Sequencing (PECC-Seq) revealed end-repair-derived artifacts as residual errors.

To improve the accuracy and the cost-efficiency of next-generation sequencing in ultralow-frequency mutation detection, we developed the Paired-End and Complementary Consensus Sequencing (PECC-Seq), a PCR-free duplex consensus sequencing approach. PECC-Seq employed shear points as endogenous barcodes to identify consensus sequences from the overlap in the shortened, complementary DNA strand-derived paired-end reads for sequencing error correction. With the high accuracy of PECC-Seq, we identified the characteristic base substitution errors introduced by the end-repair process of mechanical fragmentation-based library preparations, which were prominent at the terminal 7 bp of the library fragments in the 5'-NpCpA-3' and 5'-NpCpT-3' trinucleotide context. As demonstrated at the human genome scale (TK6 cells), after removing these potential end-repair artifacts from the terminal 7 bp, PECC-Seq could reduce the sequencing error frequency to mid-10-7 with a relatively low sequencing depth. For TA base pairs, the background error rate could be suppressed to mid-10-8. In mutagen-treated (6 µg/mL methyl methanesulfonate or 12 µg/mL N-nitroso-N-ethylurea) TK6, increases in mutagen treatment-related mutant frequencies could be detected, indicating the potential of PECC-Seq in detecting genome-wide ultra-rare mutations. In addition, our finding on the patterns of end-repair artifacts may provide new insights into further reducing technical errors not only for PECC-Seq, but also for other next-generation sequencing techniques.

A practice of expert review by read-across using QSAR Toolbox.

The International Council for Harmonisation of Technical Requirement for Pharmaceuticals for Human Use (ICH) M7 guideline on 'Assessment and Control of DNA Reactive (Mutagenic) Impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk' provides the application of two types of quantitative structure-activity relationship (QSAR) systems (rule- and statistics-based) as an alternative to the Ames test for evaluating the mutagenicity of impurities in pharmaceuticals. M7 guideline also states that the expert reviews can be applied when the outcomes of the two QSAR analyses show any conflicting or inconclusive prediction. However, the guideline does not provide any information of how to conduct expert reviews. Therefore, a conservative approach was chosen in this study, which is based on the intention to capture any mutagenic chemical substances. The 36 chemical substances, which are the model chemical substances in which positive mutagenicity was not observed according to the two types of QSAR analyses (i.e. the results are either conflicting or both negative), were selected from the list of chemical substances with strong mutagenicity known as the reported chemicals under the Industrial Safety and Health Act in Japan. The QSAR Toolbox was used in this study to rationally determine the positive mutagenicity of the 36 model chemical substances by applying a read-across method, a technique to evaluate the endpoint of the model chemical substances using the endpoint information of chemicals that are structurally similar to the model chemical substances. Resulting from the expert review by the read-across method, the 23 model chemical substances (63.8%) were rationally concluded as positive. In addition, 9 out of 11 model chemical substances that were assessed as negative for mutagenicity by both of the QSAR systems had positive analogues, supporting their mutagenicity. These results suggested that the read-across is a useful method, when conducting a conservative approach intended to capture any mutagenic chemical substances.

Inhibitory effect of ochratoxin A on DNMT-mediated flocculation of yeast.

The mycotoxin ochratoxin A (OTA) is considered to be a human carcinogen. However, the mode of its carcinogenetic action has not been elucidated. Recently, it has become evident that epigenetic changes influence the risk of developing cancer. Since it has been revealed that the yeast flocculation displayed by the strains transformed with human DNA methyltransferases (DNMT) can be regulated by epigenetic mechanisms, we examined the effect of OTA on the transcription level of FLO1, which mediates the flocculation phenotype. OTA but not a non-carcinogenetic mycotoxin deoxynivalenol (DON) inhibited the intensity of GFP fluorescence under the transcriptional regulation of FLO1 promoter in a dose-dependent manner. At the same time, OTA had no effect on the reporter activity under the control of modified FLO1 promoter with reduced CpG motifs. In addition, it was confirmed that the flocculation and FLO1 mRNA of DNMT gene-transformed yeast (DNMT yeast) were decreased by OTA. In vitro methylation assay using a bacterial DNMT revealed an inhibitory effect of OTA on the DNMT activity, and OTA treatment reduced the frequency of abnormally shaped nuclei which were often observed in DNMT yeast. These results suggest that the carcinogenicity of OTA may involve inhibition of DNMT-mediated epigenetic regulation.

Validation of the performance of TIMES genotoxicity models with EFSA pesticide data.

This study validates the performance of the TIssue MEtabolism Simulator (TIMES) genotoxicity models with data on pesticide chemicals included in a recently released European Food Safety Authority (EFSA) genotoxicity database. The EFSA database is biased towards negative chemicals. A comparison of substances included in the EFSA database and TIMES genotoxicity databases showed that the majority of the EFSA pesticides is not included in the TIMES genotoxicity databases and, thus, out of the applicability domains of the current TIMES models. However, the EFSA genotoxicity database provides an opportunity to expand the TIMES models. Where there is overlap of substances, consistency between EFSA and TIMES databases for the chemicals with documented data is found to be high (>80%) with respect to the Ames data and lower than the Ames data with respect to chromosomal aberration (CA) and mouse lymphoma assay (MLA) data. No conclusion for consistency with respect to micronucleus test and comet genotoxicity data can be provided due to the limited number of overlapping substances. Specificity of the models is important, given the prevalence of negative genotoxicity data in the EFSA database. High specificity (>80%) is obtained for prediction of the EFSA pesticides with Ames data. Moreover, this high specificity of the TIMES Ames models is not dependant on pesticides being within the domains. Specificity of the TIMES CA and MLA models is lower (>40%) to pesticides for out of domain. Sensitivity of TIMES in vitro and in vivo models cannot be properly estimated due to the small number of positive chemicals in the EFSA database.

In silico prediction of chromosome damage: comparison of three (Q)SAR models.

Two major endpoints for genotoxicity tests are gene mutation and chromosome damage (CD), which includes clastogenicity and aneugenicity detected by chromosomal aberration (CA) test or micronucleus (MN) test. Many in silico prediction systems for bacterial mutagenicity (i.e. Ames test results) have been developed and marketed. They show good performance for prediction of Ames mutagenicity. On the other hand, it seems that in silico prediction of CD does not progress as much as Ames prediction. Reasons for this include different mechanisms and detection methods, many false positives and conflicting test results. However, some (quantitative) structure-activity relationship ((Q)SAR) models (e.g. Derek Nexus [Derek], ADMEWorks [AWorks] and CASE Ultra [MCase]) can predict CA test results. Therefore, performances of the three (Q)SAR models were compared using the expanded Carcinogenicity Genotoxicity eXperience (CGX) dataset for understanding current situations and future development. The constructed dataset contained 440 chemicals (325 carcinogens and 115 non-carcinogens). Sensitivity, specificity, accuracy or applicability of each model were 56.0, 86.9, 68.6 or 89.1% in Derek, 67.7, 61.5, 65.2 or 99.3% in AWorks, and 91.0, 64.9, 80.5 or 97.7% in MCase, respectively. The performances (sensitivity and accuracy) of MCase were higher than those of Derek or AWorks. Analysis of predictivity of (Q)SAR models of certain chemical classes revealed no remarkable differences among the models. The tendency of positive prediction by (Q)SAR models was observed in alkylating agents, aromatic amines or amides, aromatic nitro compounds, epoxides, halides and N-nitro or N-nitroso compounds. In an additional investigation, high sensitivity but low specificity was noted in in vivo MN prediction by MCase. Refinement of test data to be used for in silico system (e.g. consideration of cytotoxicity or re-evaluation of conflicting test results) will be needed to improve performance of CD prediction.

Extrapolation of in vitro structural alerts for mutagenicity to the in vivo endpoint.

As part of the hazard and risk assessment of chemicals in man, it is important to assess the ability of a chemical to induce mutations in vivo. Because of the commonalities in the molecular initiating event, mutagenicity in vitro can correlate well to the in vivo endpoint for certain compound classes; however, the difficulty lies in identifying when this correlation holds true. In silico alerts for in vitro mutagenicity may therefore be used as the basis for alerts for mutagenicity in vivo where an expert assessment is carried out to establish the relevance of the correlation. Taking this into account, a data set of publicly available transgenic rodent gene mutation assay data, provided by the National Institute of Health Sciences of Japan, was processed in the expert system Derek Nexus against the in vitro mutagenicity endpoint. The resulting predictivity was expertly reviewed to assess the validity of the observed correlations in activity and mechanism of action between the two endpoints to identify suitable in vitro alerts for extension to the in vivo endpoint. In total, 20 alerts were extended to predict in vivo mutagenicity, which has significantly improved the coverage of this endpoint in Derek Nexus against the data set provided. Updating the Derek Nexus knowledge base in this way led to an increase in sensitivity for this data set against this endpoint from 9% to 66% while maintaining a good specificity of 89%.

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: is aromatic N-oxide a structural alert for predicting DNA-reactive mutagenicity?

(Quantitative) structure-activity relationship or (Q)SAR predictions of DNA-reactive mutagenicity are important to support both the design of new chemicals and the assessment of impurities, degradants, metabolites, extractables and leachables, as well as existing chemicals. Aromatic N-oxides represent a class of compounds that are often considered alerting for mutagenicity yet the scientific rationale of this structural alert is not clear and has been questioned. Because aromatic N-oxide-containing compounds may be encountered as impurities, degradants and metabolites, it is important to accurately predict mutagenicity of this chemical class. This article analysed a series of publicly available aromatic N-oxide data in search of supporting information. The article also used a previously developed structure-activity relationship (SAR) fingerprint methodology where a series of aromatic N-oxide substructures was generated and matched against public and proprietary databases, including pharmaceutical data. An assessment of the number of mutagenic and non-mutagenic compounds matching each substructure across all sources was used to understand whether the general class or any specific subclasses appear to lead to mutagenicity. This analysis resulted in a downgrade of the general aromatic N-oxide alert. However, it was determined there were enough public and proprietary data to assign the quindioxin and related chemicals as well as benzo[c][1,2,5]oxadiazole 1-oxide subclasses as alerts. The overall results of this analysis were incorporated into Leadscope's expert-rule-based model to enhance its predictive accuracy.

Improvement of quantitative structure-activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge Project.

The International Conference on Harmonization (ICH) M7 guideline allows the use of in silico approaches for predicting Ames mutagenicity for the initial assessment of impurities in pharmaceuticals. This is the first international guideline that addresses the use of quantitative structure-activity relationship (QSAR) models in lieu of actual toxicological studies for human health assessment. Therefore, QSAR models for Ames mutagenicity now require higher predictive power for identifying mutagenic chemicals. To increase the predictive power of QSAR models, larger experimental datasets from reliable sources are required. The Division of Genetics and Mutagenesis, National Institute of Health Sciences (DGM/NIHS) of Japan recently established a unique proprietary Ames mutagenicity database containing 12140 new chemicals that have not been previously used for developing QSAR models. The DGM/NIHS provided this Ames database to QSAR vendors to validate and improve their QSAR tools. The Ames/QSAR International Challenge Project was initiated in 2014 with 12 QSAR vendors testing 17 QSAR tools against these compounds in three phases. We now present the final results. All tools were considerably improved by participation in this project. Most tools achieved >50% sensitivity (positive prediction among all Ames positives) and predictive power (accuracy) was as high as 80%, almost equivalent to the inter-laboratory reproducibility of Ames tests. To further increase the predictive power of QSAR tools, accumulation of additional Ames test data is required as well as re-evaluation of some previous Ames test results. Indeed, some Ames-positive or Ames-negative chemicals may have previously been incorrectly classified because of methodological weakness, resulting in false-positive or false-negative predictions by QSAR tools. These incorrect data hamper prediction and are a source of noise in the development of QSAR models. It is thus essential to establish a large benchmark database consisting only of well-validated Ames test results to build more accurate QSAR models.

Principles and procedures for handling out-of-domain and indeterminate results as part of ICH M7 recommended (Q)SAR analyses.

The International Council for Harmonization (ICH) M7 guideline describes a hazard assessment process for impurities that have the potential to be present in a drug substance or drug product. In the absence of adequate experimental bacterial mutagenicity data, (Q)SAR analysis may be used as a test to predict impurities' DNA reactive (mutagenic) potential. However, in certain situations, (Q)SAR software is unable to generate a positive or negative prediction either because of conflicting information or because the impurity is outside the applicability domain of the model. Such results present challenges in generating an overall mutagenicity prediction and highlight the importance of performing a thorough expert review. The following paper reviews pharmaceutical and regulatory experiences handling such situations. The paper also presents an analysis of proprietary data to help understand the likelihood of misclassifying a mutagenic impurity as non-mutagenic based on different combinations of (Q)SAR results. This information may be taken into consideration when supporting the (Q)SAR results with an expert review, especially when out-of-domain results are generated during a (Q)SAR evaluation.

Genetic toxicology in silico protocol.

In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.

Gene mutation and micronucleus assays in gpt delta mice treated with 2,2',4,4'-tetrabromodiphenyl ether.

Flame retardant polybrominated diphenyl ethers (PBDEs) are a class of persistent organic pollutants (POPs). 2,2',4,4'-Tetrabromodiphenyl ether (BDE-47) is a representative PBDE congener with widespread distribution and relatively high toxicity potential. Although it has been reported that BDE-47 can cause DNA damage in various in vitro systems, few studies have provided in vivo genotoxicity information. The aim of the present study was to investigate the genotoxicity of BDE-47 in mice. Male gpt delta mice were administered BDE-47 by gavage at 0, 0.0015, 1.5, 10 and 30 mg/kg/day, and 6 days per week for six consecutive weeks. Before the first treatment, and at 2.5 and 5 weeks after the first treatment, peripheral blood was collected from tails and the micronucleus assay and the Pig-a gene mutation assay were performed. After the last treatment, the mutant frequencies of the gpt gene in the liver and the germ cells from seminiferous tubules were determined. All these assays failed to produce positive results, suggesting that BDE-47 was neither clastogenic nor mutagenic in both target and non-target tissues in gpt delta mice.

In silico toxicology protocols.

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.

Impact of Ribonucleotide Backbone on Translesion Synthesis and Repair of 7,8-Dihydro-8-oxoguanine.

Numerous ribonucleotides are incorporated into the genome during DNA replication. Oxidized ribonucleotides can also be erroneously incorporated into DNA. Embedded ribonucleotides destabilize the structure of DNA and retard DNA synthesis by DNA polymerases (pols), leading to genomic instability. Mammalian cells possess translesion DNA synthesis (TLS) pols that bypass DNA damage. The mechanism of TLS and repair of oxidized ribonucleotides remains to be elucidated. To address this, we analyzed the miscoding properties of the ribonucleotides riboguanosine (rG) and 7,8-dihydro-8-oxo-riboguanosine (8-oxo-rG) during TLS catalyzed by the human TLS pols κ and η in vitro The primer extension reaction catalyzed by human replicative pol α was strongly blocked by 8-oxo-rG. pol κ inefficiently bypassed rG and 8-oxo-rG compared with dG and 7,8-dihydro-8-oxo-2'-deoxyguanosine (8-oxo-dG), whereas pol η easily bypassed the ribonucleotides. pol α exclusively inserted dAMP opposite 8-oxo-rG. Interestingly, pol κ preferentially inserted dCMP opposite 8-oxo-rG, whereas the insertion of dAMP was favored opposite 8-oxo-dG. In addition, pol η accurately bypassed 8-oxo-rG. Furthermore, we examined the activity of the base excision repair (BER) enzymes 8-oxoguanine DNA glycosylase (OGG1) and apurinic/apyrimidinic endonuclease 1 on the substrates, including rG and 8-oxo-rG. Both BER enzymes were completely inactive against 8-oxo-rG in DNA. However, OGG1 suppressed 8-oxo-rG excision by RNase H2, which is involved in the removal of ribonucleotides from DNA. These results suggest that the different sugar backbones between 8-oxo-rG and 8-oxo-dG alter the capacity of TLS and repair of 8-oxoguanine.

Detection of epigenetic mutagens including anthracene-derived compounds using yeast FLO1 promoter GFP reporter gene assay.

Recently, we have reported that the FLO1-mediated flocculation levels of yeast are affected by an epigenetic mutagen, alizarin. Alizarin promoted flocculation and reduced the bulk levels of histone H3 in yeast cells. Since alizarin has been known to possess carcinogenesis-promoting properties, it is important to estimate the effect of alizarin-related compounds on epigenome as measured by the flocculation of yeast. In this study, we examined the effects of two anthracene-derived compounds other than alizarin on the flocculation level of yeast. Purpurin significantly promoted the flocculation in a dose-dependent manner. While, quinizarin had a weaker promoting effect than purpurin. The strain treated with purprin showed FLO1 mRNA upregulation and reduced histone H3 expression similarly to alizarin. We also confirmed that the purprin-treated cells frequently exhibited abnormally shaped nuclei. Moreover, fluorescence intensities of green fluorescent protein (GFP) reporter under the FLO1 promoter control were dose-dependently increased by purprin and alizarin in the yeast. Taken together, these results suggest that the GFP reporter gene system utilising the FLO1 promoter is useful for the detection of epigenetic mutagens including anthracene-derived compounds.

Integrating computational methods to predict mutagenicity of aromatic azo compounds.

Azo dyes have several industrial uses. However, these azo dyes and their degradation products showed mutagenicity, inducing damage in environmental and human systems. Computational methods are proposed as cheap and rapid alternatives to predict the toxicity of azo dyes. A benchmark dataset of Ames data for 354 azo dyes was employed to develop three classification strategies using knowledge-based methods and docking simulations. Results were compared and integrated with three models from the literature, developing a series of consensus strategies. The good results confirm the usefulness of in silico methods as a support for experimental methods to predict the mutagenicity of azo compounds.

Smarcal1 promotes double-strand-break repair by nonhomologous end-joining.

Smarcal1 is a SWI/SNF-family protein with an ATPase domain involved in DNA-annealing activities and a binding site for the RPA single-strand-DNA-binding protein. Although the role played by Smarcal1 in the maintenance of replication forks has been established, it remains unknown whether Smarcal1 contributes to genomic DNA maintenance outside of the S phase. We disrupted the SMARCAL1 gene in both the chicken DT40 and the human TK6 B cell lines. The resulting SMARCAL1(-/-) clones exhibited sensitivity to chemotherapeutic topoisomerase 2 inhibitors, just as nonhomologous end-joining (NHEJ) null-deficient cells do. SMARCAL1(-/-) cells also exhibited an increase in radiosensitivity in the G1 phase. Moreover, the loss of Smarcal1 in NHEJ null-deficient cells does not further increase their radiosensitivity. These results demonstrate that Smarcal1 is required for efficient NHEJ-mediated DSB repair. Both inactivation of the ATPase domain and deletion of the RPA-binding site cause the same phenotype as does null-mutation of Smarcal1, suggesting that Smarcal1 enhances NHEJ, presumably by interacting with RPA at unwound single-strand sequences and then facilitating annealing at DSB ends. SMARCAL1(-/-)cells showed a poor accumulation of Ku70/DNA-PKcs and XRCC4 at DNA-damage sites. We propose that Smarcal1 maintains the duplex status of DSBs to ensure proper recruitment of NHEJ factors to DSB sites.

Epigenetic mutagen as histone modulator can be detected by yeast flocculation.

We have previously reported that flocculation of a yeast co-transformed with the human DNA methyltransferase 1 (DNMT1) and DNMT3B genes was inhibited by DNMT inhibitors. It is well known that epigenetic mutagens can disturb nucleosome positioning via DNA methylation and/or histone modification. In this study we first examined the effects of trichostatin A (TSA), a histone deacetylase inhibitor, on the flocculation level of yeast. TSA dose-dependently promoted the flocculation exhibited by the yeast transformed with the DNMT genes or empty vectors. Furthermore, TSA induced the expression of the flocculin-encoding gene FLO1 The anthracene-derived alizarin, a natural madder root dye, has a potential for carcinogenesis promotion; however, the mode of action has not been elucidated. It is considered that epigenetic changes can promote cancer. Alizarin but not anthracene enhanced the flocculation level of the yeast. Similar to TSA, alizarin also upregulated FLO1 mRNA. Surprisingly, western blotting indicated that alizarin, but not anthracene, reduced the level of histone H3 in yeast, and alizarin-treated cells frequently displayed abnormally shaped nuclei. These findings suggest that alizarin uniquely influences nucleosome structure. Taken together with our previous findings, this study suggests that the DNMT gene-transformed yeast strains are a useful tool for screening various classes of epigenetic mutagens.