Abstract
Genotoxicity testing, a technique which is used to identify chemicals that cause genetic alterations, includes tests that aid determination of irreversible genetic alterations, as well as those that provide indirect evidence of DNA damage. A panel of tests is commonly considered to comprehensively evaluate the ability of a chemical to induce genotoxicity, since individual tests do not provide information on all end points. Although a standard panel for genotoxicity testing has been considered traditionally for decades, changes based on novel and emerging methodologies have been introduced. The present review provides a brief introduction to the commonly used basic tests intended for regulatory purposes, advanced genotoxicity testing including cells used in genotoxicity testing, application of quantitative structure activity relationship (QSAR), representative genotoxicity high-throughput in vitro assays, and high-dimensional/high information content assays, with specific reference to the application of next-generation sequencing (NGS), which enable genome-wide analyses of mutations in non-cancer cells, thereby revealing the effects of various environmental mutagens.
Similar content being viewed by others
References
Abascal, F., Harvey, L. M. R., Mitchell, E., Lawson, A. R. J., Lensing, S. V., Ellis, P., & Martincorena, I. (2021). Somatic mutation landscapes at single-molecule resolution. Nature, 593(7859), 405–410. https://doi.org/10.1038/s41586-021-03477-4
Albert, O., Reintsch, W. E., Chan, P., & Robaire, B. (2016). HT-COMET: A novel automated approach for high throughput assessment of human sperm chromatin quality. Human Reproduction, 31(5), 938–946. https://doi.org/10.1093/humrep/dew030
Ando, M., Yoshikawa, K., Iwase, Y., & Ishiura, S. (2014). Usefulness of monitoring γ-H2AX and cell cycle arrest in HepG2 cells for estimating genotoxicity using a high-content analysis system. Journal of Biomolecular Screening, 19(9), 1246–1254. https://doi.org/10.1177/1087057114541147
Arbeithuber, B., Makova, K. D., & Tiemann-Boege, I. (2016). Artifactual mutations resulting from DNA lesions limit detection levels in ultrasensitive sequencing applications. DNA Research, 23(6), 547–559. https://doi.org/10.1093/dnares/dsw038
Baba, T. W., Giroir, B. P., & Humphries, E. H. (1985). Cell lines derived from avian lymphomas exhibit two distinct phenotypes. Virology, 144(1), 139–151. https://doi.org/10.1016/0042-6822(85)90312-5
Bajpayee, M., Kumar, A., & Dhawan, A. (2019). The comet assay: assessment of in vitro and in vivo DNA damage. Methods in Molecular Biology, 2031, 237–257. https://doi.org/10.1007/978-1-4939-9646-9_12
Bieging, K. T., Mello, S. S., & Attardi, L. D. (2014). Unravelling mechanisms of p53-mediated tumour suppression. Nature Reviews Cancer, 14(5), 359–370. https://doi.org/10.1038/nrc3711
Bryce, S. M., Bernacki, D. T., Smith-Roe, S. L., Witt, K. L., Bemis, J. C., & Dertinger, S. D. (2018). Investigating the generalizability of the MultiFlow ® DNA damage assay and several companion machine learning models with a set of 103 diverse test chemicals. Toxicological Sciences, 162(1), 146–166. https://doi.org/10.1093/toxsci/kfx235
Cao, Y., Wang, T., Xi, J., Zhang, G., Wang, T., Liu, W., & Luan, Y. (2020a). PIG-A gene mutation as a genotoxicity biomarker in human population studies: An investigation in lead-exposed workers. Environmental and Molecular Mutagenesis, 61(6), 611–621. https://doi.org/10.1002/em.22373
Cao, Y., Wang, X., Liu, W., Feng, N., Xi, J., You, X., & Luan, Y. (2020b). The potential application of human PIG-A assay on azathioprine-treated inflammatory bowel disease patients. Environmental and Molecular Mutagenesis, 61(4), 456–464. https://doi.org/10.1002/em.22348
Chan, W., Zheng, Y., & Cai, Z. (2007). Liquid chromatography-tandem mass spectrometry analysis of the DNA adducts of aristolochic acids. Journal of the American Society for Mass Spectrometry, 18(4), 642–650. https://doi.org/10.1016/j.jasms.2006.11.010
Chang, Y. J., Cooke, M. S., Chen, Y. R., Yang, S. F., Li, P. S., Hu, C. W., & Chao, M. R. (2021). Is high resolution a strict requirement for mass spectrometry-based cellular DNA adductomics? Chemosphere, 274, 129991. https://doi.org/10.1016/j.chemosphere.2021.129991
Chapin, R. E., & Stedman, D. B. (2009). Endless possibilities: Stem cells and the vision for toxicology testing in the 21st century. Toxicological Sciences, 112(1), 17–22. https://doi.org/10.1093/toxsci/kfp202
Chen, R., Lin, Y. T., Fornace, A. J., Jr., & Li, H. H. (2021). A high-throughput and highly automated genotoxicity screening assay. Altex. https://doi.org/10.14573/altex.2102121
Chen, R., Zhou, C., Cao, Y., Xi, J., Ohira, T., He, L., & Luan, Y. (2020). Assessment of Pig-a, micronucleus, and comet assay endpoints in Tg.RasH2 mice carcinogenicity study of aristolochic acid I. Environmental and Molecular Mutagenesis, 61(2), 266–275. https://doi.org/10.1002/em.22325
Clark, T. A., Spittle, K. E., Turner, S. W., & Korlach, J. (2011). Direct detection and sequencing of damaged DNA bases. Genome Integr, 2, 10. https://doi.org/10.1186/2041-9414-2-10
Coltman, N. J., Coke, B. A., Chatzi, K., Shepherd, E. L., Lalor, P. F., Schulz-Utermoehl, T., & Hodges, N. J. (2021). Application of HepG2/C3A liver spheroids as a model system for genotoxicity studies. Toxicology Letters, 345, 34–45. https://doi.org/10.1016/j.toxlet.2021.04.004
Costello, M., Pugh, T. J., Fennell, T. J., Stewart, C., Lichtenstein, L., Meldrim, J. C., & Getz, G. (2013). Discovery and characterization of artifactual mutations in deep coverage targeted capture sequencing data due to oxidative DNA damage during sample preparation. Nucleic Acids Research, 41(6), e67. https://doi.org/10.1093/nar/gks1443
Decordier, I., Papine, A., Vande Loock, K., Plas, G., Soussaline, F., & Kirsch-Volders, M. (2011). Automated image analysis of micronuclei by IMSTAR for biomonitoring. Mutagenesis, 26(1), 163–168. https://doi.org/10.1093/mutage/geq063
Dertinger, S. D., Torous, D. K., Hayashi, M., & MacGregor, J. T. (2011). Flow cytometric scoring of micronucleated erythrocytes: An efficient platform for assessing in vivo cytogenetic damage. Mutagenesis, 26(1), 139–145. https://doi.org/10.1093/mutage/geq055
Di Bucchianico, S., Cappellini, F., Le Bihanic, F., Zhang, Y., Dreij, K., & Karlsson, H. L. (2017). Genotoxicity of TiO2 nanoparticles assessed by mini-gel comet assay and micronucleus scoring with flow cytometry. Mutagenesis, 32(1), 127–137. https://doi.org/10.1093/mutage/gew030
François, M., Hochstenbach, K., Leifert, W., & Fenech, M. F. (2014). Automation of the cytokinesis-block micronucleus cytome assay by laser scanning cytometry and its potential application in radiation biodosimetry. BioTechniques, 57(6), 309–312. https://doi.org/10.2144/000114239
Furihata, C., Toyoda, T., Ogawa, K., & Suzuki, T. (2018). Using RNA-Seq with 11 marker genes to evaluate 1,4-dioxane compared with typical genotoxic and non-genotoxic rat hepatocarcinogens. Mutation Research, Genetic Toxicology and Environmental Mutagenesis, 834, 51–55. https://doi.org/10.1016/j.mrgentox.2018.07.002
Ganapathy, S., Muraleedharan, A., Sathidevi, P. S., Chand, P., & Rajkumar, R. P. (2016). CometQ: An automated tool for the detection and quantification of DNA damage using comet assay image analysis. Computer Methods and Programs in Biomedicine, 133, 143–154. https://doi.org/10.1016/j.cmpb.2016.05.020
Ge, J., Chow, D. N., Fessler, J. L., Weingeist, D. M., Wood, D. K., & Engelward, B. P. (2015). Micropatterned comet assay enables high throughput and sensitive DNA damage quantification. Mutagenesis, 30(1), 11–19. https://doi.org/10.1093/mutage/geu063
Gerets, H. H., Tilmant, K., Gerin, B., Chanteux, H., Depelchin, B. O., Dhalluin, S., & Atienzar, F. A. (2012). Characterization of primary human hepatocytes, HepG2 cells, and HepaRG cells at the mRNA level and CYP activity in response to inducers and their predictivity for the detection of human hepatotoxins. Cell Biology and Toxicology, 28(2), 69–87. https://doi.org/10.1007/s10565-011-9208-4
Guo, J., & Turesky, R. J. (2019). Emerging technologies in mass spectrometry-based DNA adductomics. High Throughput. https://doi.org/10.3390/ht8020013
Gyori, B. M., Venkatachalam, G., Thiagarajan, P. S., Hsu, D., & Clement, M. V. (2014). OpenComet: An automated tool for comet assay image analysis. Redox Biology, 2, 457–465. https://doi.org/10.1016/j.redox.2013.12.020
Haboubi, H. N., Lawrence, R. L., Rees, B., Williams, L., Manson, J. M., Al-Mossawi, N., & Jenkins, G. J. (2019). Developing a blood-based gene mutation assay as a novel biomarker for oesophageal adenocarcinoma. Scientific reports, 9(1), 5168. https://doi.org/10.1038/s41598-019-41490-w
Hamada, S., Ohyama, W., Takashima, R., Shimada, K., Matsumoto, K., Kawakami, S., & Hayashi, M. (2015). Evaluation of the repeated-dose liver and gastrointestinal tract micronucleus assays with 22 chemicals using young adult rats: Summary of the collaborative study by the Collaborative Study Group for the Micronucleus Test (CSGMT)/The Japanese Environmental Mutagen Society (JEMS) - Mammalian Mutagenicity Study Group (MMS). Mutation Research, Genetic Toxicology and Environmental Mutagenesis, 780–781, 2–17. https://doi.org/10.1016/j.mrgentox.2015.01.001
Hayasi, M. (1991). 小核試験 : 実験法からデータの評価まで. サイエンティスト社. (林真). https://iss.ndl.go.jp/books/R100000002-I000002117592-00?ar=4e1f&locale=zh
Hemeryck, L. Y., Rombouts, C., De Paepe, E., & Vanhaecke, L. (2018). DNA adduct profiling of in vitro colonic meat digests to map red vs. white meat genotoxicity. Food and Chemical Toxicology, 115, 73–87. https://doi.org/10.1016/j.fct.2018.02.032
Hendriks, G., Derr, R. S., Misovic, B., Morolli, B., Calléja, F. M., & Vrieling, H. (2016). The extended toxtracker assay discriminates between induction of dna damage, oxidative stress, and protein misfolding. Toxicological Sciences, 150(1), 190–203. https://doi.org/10.1093/toxsci/kfv323
Hoang, M. L., Kinde, I., Tomasetti, C., McMahon, K. W., Rosenquist, T. A., Grollman, A. P., & Papadopoulos, N. (2016). Genome-wide quantification of rare somatic mutations in normal human tissues using massively parallel sequencing. Proceedings of National Academy of Science USA, 113(35), 9846–9851. https://doi.org/10.1073/pnas.1607794113
Honma, M. (2009). 遺伝毒性物質に閾値はあるのか?(話題). ファルマシア, 45(2), 143–148. https://doi.org/10.14894/faruawpsj.45.2_143 本間正充.
Honma, M. (2020). An assessment of mutagenicity of chemical substances by (quantitative) structure-activity relationship. Genes Environ, 42, 23. https://doi.org/10.1186/s41021-020-00163-1
Honma, M., & Hayashi, M. (2011). Comparison of in vitro micronucleus and gene mutation assay results for p53-competent versus p53-deficient human lymphoblastoid cells. Environmental and Molecular Mutagenesis, 52(5), 373–384. https://doi.org/10.1002/em.20634
Honma, M., Sakuraba, M., Koizumi, T., Takashima, Y., Sakamoto, H., & Hayashi, M. (2007). Non-homologous end-joining for repairing I-SceI-induced DNA double strand breaks in human cells. DNA Repair (amst), 6(6), 781–788. https://doi.org/10.1016/j.dnarep.2007.01.004
Hopp, N., Hagen, J., Aggeler, B., & Kalyuzhny, A. E. (2017). Automated high-content screening of γ-H2AX Expression in HeLa cells. Methods in Molecular Biology, 1554, 273–283. https://doi.org/10.1007/978-1-4939-6759-9_20
Hori, H., Shimoyoshi, S., Tanaka, Y., Momonami, A., Masumura, K., Yamada, M., Fujii, W., & Kitagawa, Y. (2019). Integration of micronucleus tests with a gene mutation assay in F344 gpt delta transgenic rats using benzo[a]pyrene. Mutation Research, Genetic Toxicology and Environmental Mutagenesis, 837, 1–7. https://doi.org/10.1016/j.mrgentox.2018.09.003
https://linkinghub.elsevier.com/retrieve/pii/S1383-5718(18)30049-4
ICH. (2011). S2(R1) guidance on genotoxicity testing and data interpretation for pharmaceuticals intended for human use. ICH.
ICH. (2014). M7, assessment and control of dna reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk. ICH.
Ishino, K., Kato, T., Kato, M., Shibata, T., Watanabe, M., Wakabayashi, K., & Totsuka, Y. (2015). Comprehensive DNA adduct analysis reveals pulmonary inflammatory response contributes to genotoxic action of magnetite nanoparticles. International Journal of Molecular Sciences, 16(2), 3474–3492. https://doi.org/10.3390/ijms16023474
JaCVAM. (2009). The protocol of an international validation study on the in vivo rodent alkaline Comet assay. http://cometassay.com/JaCVAM.pdf. Accessed 30 Nov 2009
Johnson, T. E., Umbenhauer, D. R., & Galloway, S. M. (1996). Human liver S-9 metabolic activation: Proficiency in cytogenetic assays and comparison with phenobarbital/beta-naphthoflavone or aroclor 1254 induced rat S-9. Environmental and Molecular Mutagenesis, 28(1), 51–59. https://doi.org/10.1002/(sici)1098-2280(1996)28:1%3c51::Aid-em8%3e3.0.Co;2-h
Kanaly, R. A., Hanaoka, T., Sugimura, H., Toda, H., Matsui, S., & Matsuda, T. (2006). Development of the adductome approach to detect DNA damage in humans. Antioxidants and Redox Signaling, 8(5–6), 993–1001. https://doi.org/10.1089/ars.2006.8.993
Kang, K.-S., & Trosko, J. E. (2011). Stem cells in toxicology: fundamental biology and practical considerations. Toxicological Sciences, 120(suppl_1), S269–S289. https://doi.org/10.1093/toxsci/kfq370
Keka, I. S., Mohiuddin, M. Y., Rahman, M. M., Sakuma, T., Honma, M., & Sasanuma, H. (2015). Smarcal1 promotes double-strand-break repair by nonhomologous end-joining. Nucleic Acids Research, 43(13), 6359–6372. https://doi.org/10.1093/nar/gkv621
Kennedy, S. R., Schmitt, M. W., Fox, E. J., Kohrn, B. F., Salk, J. J., Ahn, E. H., & Loeb, L. A. (2014). Detecting ultralow-frequency mutations by Duplex Sequencing. Nature Protocols, 9(11), 2586–2606. https://doi.org/10.1038/nprot.2014.170
Kirkland, D., Aardema, M., Henderson, L., & Müller, L. (2005). Evaluation of the ability of a battery of three in vitro genotoxicity tests to discriminate rodent carcinogens and non-carcinogens I. Sensitivity, specificity and relative predictivity. Mutation Research, 584(1–2), 1–256. https://doi.org/10.1016/j.mrgentox.2005.02.004
Kirsch-Volders, M., Sofuni, T., Aardema, M., Albertini, S., Eastmond, D., Fenech, M., & Wakata, A. (2003). Report from the in vitro micronucleus assay working group. Mutation Research, 540(2), 153–163. https://doi.org/10.1016/j.mrgentox.2003.07.005
Knight, A. W., Little, S., Houck, K., Dix, D., Judson, R., Richard, A., & Walmsley, R. M. (2009). Evaluation of high-throughput genotoxicity assays used in profiling the US EPA ToxCast chemicals. Regulatory Toxicology and Pharmacology, 55(2), 188–199. https://doi.org/10.1016/j.yrtph.2009.07.004
Lambert, M., Meudec, E., Verbaere, A., Mazerolles, G., Wirth, J., Masson, G., & Sommerer, N. (2015). A high-throughput UHPLC-QqQ-MS method for polyphenol profiling in rosé wines. Molecules, 20(5), 7890–7914. https://doi.org/10.3390/molecules20057890
Lee, T., Lee, S., Sim, W. Y., Jung, Y. M., Han, S., Won, J. H., & Yoon, S. (2018). HiComet: A high-throughput comet analysis tool for large-scale DNA damage assessment. BMC Bioinformatics, 19(Suppl 1), 44. https://doi.org/10.1186/s12859-018-2015-7
Li, H. H., Chen, R., Hyduke, D. R., Williams, A., Frötschl, R., Ellinger-Ziegelbauer, H., & Fornace, A. J., Jr. (2017). Development and validation of a high-throughput transcriptomic biomarker to address 21st century genetic toxicology needs. Proceedings of National Academy of Science USA, 114(51), E10881-e10889. https://doi.org/10.1073/pnas.1714109114
Li, H. H., Hyduke, D. R., Chen, R., Heard, P., Yauk, C. L., Aubrecht, J., & Fornace, A. J., Jr. (2015). Development of a toxicogenomics signature for genotoxicity using a dose-optimization and informatics strategy in human cells. Environmental and Molecular Mutagenesis, 56(6), 505–519. https://doi.org/10.1002/em.21941
Liu, B., van Gerwen, M., Bonassi, S., & Taioli, E. (2017). Epidemiology of environmental exposure and malignant mesothelioma. Journal of Thoracic Oncology, 12(7), 1031–1045. https://doi.org/10.1016/j.jtho.2017.04.002
Liu, W., Xi, J., Cao, Y., You, X., Chen, R., Zhang, X., & Luan, Y. (2019). An adaption of human-induced hepatocytes to in vitro genetic toxicity tests. Mutagenesis, 34(2), 165–171. https://doi.org/10.1093/mutage/gey041
Luch, A. (2005). Nature and nurture – lessons from chemical carcinogenesis. Nature Reviews Cancer, 5(2), 113–125. https://doi.org/10.1038/nrc1546
Lynch, M. (2010). Rate, molecular spectrum, and consequences of human mutation. Proceedings of the National Academy of Science USA, 107(3), 961–968. https://doi.org/10.1073/pnas.0912629107
Mah, L. J., El-Osta, A., & Karagiannis, T. C. (2010). gammaH2AX: A sensitive molecular marker of DNA damage and repair. Leukemia, 24(4), 679–686. https://doi.org/10.1038/leu.2010.6
Mahadevan, B., Snyder, R. D., Waters, M. D., Benz, R. D., Kemper, R. A., Tice, R. R., & Richard, A. M. (2011). Genetic toxicology in the 21st century: reflections and future directions. Environ Mol Mutagen 52(5):339–354. https://doi.org/10.1002/em.20653
Maron, D. M., & Ames, B. N. (1983). Revised methods for the Salmonella mutagenicity test. Mutation Research, 113(3–4), 173–215. https://doi.org/10.1016/0165-1161(83)90010-9
Matsumura, S., Sato, H., Otsubo, Y., Tasaki, J., Ikeda, N., & Morita, O. (2019). Genome-wide somatic mutation analysis via Hawk-Seq™ reveals mutation profiles associated with chemical mutagens. Archives of Toxicology, 93(9), 2689–2701. https://doi.org/10.1007/s00204-019-02541-3
Matsushima, T., Hayashi, M., Matsuoka, A., Ishidate, M., Miura, F. K., Shimizu, H., & Sofuni, H. (1999). Validation study of the in vitro micronucleus test in a Chinese hamster lung cell line (CHL/IU). Mutagenesis, 14(6), 569–580. https://doi.org/10.1093/mutage/14.6.569
Merrick, B. A., Chang, J. S., Phadke, D. P., Bostrom, M. A., Shah, R. R., Wang, X., & Wright, G. M. (2018). HAfTs are novel lncRNA transcripts from aflatoxin exposure. PLoS ONE, 13(1), e0190992. https://doi.org/10.1371/journal.pone.0190992
Miura, D., Dobrovolsky, V. N., Mittelstaedt, R. A., Kasahara, Y., Katsuura, Y., & Heflich, R. H. (2008). Development of an in vivo gene mutation assay using the endogenous Pig-A gene: II. Selection of Pig-A mutant rat spleen T-cells with proaerolysin and sequencing Pig-A cDNA from the mutants. Environmental and Molecular Mutagenesis, 49(8), 622–630. https://doi.org/10.1002/em.20413
Mortelmans, K., & Riccio, E. S. (2000). The bacterial tryptophan reverse mutation assay with Escherichia coli WP2. Mutation Research, 455(1–2), 61–69. https://doi.org/10.1016/s0027-5107(00)00076-2
Mortelmans, K., & Zeiger, E. (2000). The Ames Salmonella/microsome mutagenicity assay. Mutation Research, 455(1–2), 29–60. https://doi.org/10.1016/s0027-5107(00)00064-6
Nishihara, K., Huang, R., Zhao, J., Shahane, S. A., Witt, K. L., Smith-Roe, S. L., & Xia, M. (2016). Identification of genotoxic compounds using isogenic DNA repair deficient DT40 cell lines on a quantitative high throughput screening platform. Mutagenesis, 31(1), 69–81. https://doi.org/10.1093/mutage/gev055
Nishimura, S. (2011). 8-Hydroxyguanine: A base for discovery. DNA Repair (amst), 10(11), 1078–1083.
Nohmi, T. (2018). Thresholds of genotoxic and non-genotoxic carcinogens. Toxicological Research, 34(4), 281–290. https://doi.org/10.5487/TR.2018.34.4.281
Nohmi, T., Suzuki, T., & Masumura, K. (2000). Recent advances in the protocols of transgenic mouse mutation assays. Mutation Research, 455(1–2), 191–215. https://doi.org/10.1016/s0027-5107(00)00077-4
OECD. (2010). OECD guideline for testing of chemicals, full list of test guidelines. OECD.
OECD. (2015). Test no. 490, in vitro mammalian cell gene mutation tests using the thymidine kinase gene. OECD.
Otsubo, Y., Matsumura, S., Ikeda, N., & Morita, O. (2021). Hawk-Seq™ differentiates between various mutations in Salmonella typhimurium TA100 strain caused by exposure to Ames test-positive mutagens. Mutagenesis, 36(3), 245–254. https://doi.org/10.1093/mutage/geab006
Pfuhler, S., Downs, T. R., Hewitt, N. J., Hoffmann, S., Mun, G. C., Ouedraogo, G., & Aardema, M. J. (2021). Validation of the 3D reconstructed human skin micronucleus (RSMN) assay: An animal-free alternative for following-up positive results from standard in vitro genotoxicity assays. Mutagenesis, 36(1), 1–17. https://doi.org/10.1093/mutage/geaa035
Pfuhler, S., van Benthem, J., Curren, R., Doak, S. H., Dusinska, M., Hayashi, M., & Corvi, R. (2020). Use of in vitro 3D tissue models in genotoxicity testing: Strategic fit, validation status and way forward. Report of the working group from the 7(th) International Workshop on Genotoxicity Testing (IWGT). Mutation Research Genetic Toxicology and Environmental Mutagenesis, 850–851, 503135. https://doi.org/10.1016/j.mrgentox.2020.503135
Pietsch, K. E., van Midwoud, P. M., Villalta, P. W., & Sturla, S. J. (2013). Quantification of acylfulvene- and illudin S-DNA adducts in cells with variable bioactivation capacities. Chemical Research in Toxicology, 26(1), 146–155. https://doi.org/10.1021/tx300430r
Revollo, J. R., Miranda, J. A., & Dobrovolsky, V. N. (2021). PacBio sequencing detects genome-wide ultra-low-frequency substitution mutations resulting from exposure to chemical mutagens. Environmental and Molecular Mutagenesis, 62(8), 438–445. https://doi.org/10.1002/em.22462
Rodrigues, M. A., Beaton-Green, L. A., Wilkins, R. C., & Fenech, M. F. (2018). The potential for complete automated scoring of the cytokinesis block micronucleus cytome assay using imaging flow cytometry. Mutat Res Genet Toxicol Environ Mutagen, 836(Pt A), 53–64. https://doi.org/10.1016/j.mrgentox.2018.05.003https://europepmc.org/articles/PMC6435702?pdf=renderhttps://europepmc.org/articles/PMC6435702
Rogakou, E. P., Pilch, D. R., Orr, A. H., Ivanova, V. S., & Bonner, W. M. (1998). DNA double-stranded breaks induce histone H2AX phosphorylation on serine 139. Journal of Biological Chemistry, 273(10), 5858–5868. https://doi.org/10.1074/jbc.273.10.5858
Rossnerova, A., Spatova, M., Schunck, C., & Sram, R. J. (2011). Automated scoring of lymphocyte micronuclei by the metasystems metafer image cytometry system and its application in studies of human mutagen sensitivity and biodosimetry of genotoxin exposure. Mutagenesis, 26(1), 169–175. https://doi.org/10.1093/mutage/geq057
Salk, J. J., Schmitt, M. W., & Loeb, L. A. (2018). Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations. Nature Reviews Genetics, 19(5), 269–285. https://doi.org/10.1038/nrg.2017.117
Schmitt, M. W., Kennedy, S. R., Salk, J. J., Fox, E. J., Hiatt, J. B., & Loeb, L. A. (2012). Detection of ultra-rare mutations by next-generation sequencing. Proceedings of the National Academy of Science USA, 109(36), 14508–14513. https://doi.org/10.1073/pnas.1208715109
Scott, D., & Roberts, S. A. (1987). Extrapolation from in vitro tests to human risk: Experience with sodium fluoride clastogenicity. Mutation Research, 189(1), 47–58. https://doi.org/10.1016/0165-1218(87)90032-2
Sedelnikova, O. A., Rogakou, E. P., Panyutin, I. G., & Bonner, W. M. (2002). Quantitative detection of (125)IdU-induced DNA double-strand breaks with gamma-H2AX antibody. Radiation Research, 158(4), 486–492. https://doi.org/10.1002/1097-0320(20010601)44:2<153::AID-CYTO1095>3.0.CO;2-H
Shendure, J., & Ji, H. (2008). Next-generation DNA sequencing. Nature Biotechnology, 26(10), 1135–1145. https://doi.org/10.1038/nbt1486
Smart, D. J., Ahmedi, K. P., Harvey, J. S., & Lynch, A. M. (2011). Genotoxicity screening via the γH2AX by flow assay. Mutation Research, 715(1–2), 25–31. https://doi.org/10.1016/j.mrfmmm.2011.07.001
Sofuni, T. (2005). 染色体異常試験 センショクタイ イジョウ シケン. サイエンティスト社. (祖父尼, 俊雄). http://lib.kyoto-wu.ac.jp/opc/recordID/catalog.bib/BA73202779
Stang, A., & Witte, I. (2009). Performance of the comet assay in a high-throughput version. Mutation Research, 675(1–2), 5–10. https://doi.org/10.1016/j.mrgentox.2009.01.007
Stang, A., & Witte, I. (2010). The ability of the high-throughput comet assay to measure the sensitivity of five cell lines toward methyl methanesulfonate, hydrogen peroxide, and pentachlorophenol. Mutation Research, 701(2), 103–106. https://doi.org/10.1016/j.mrgentox.2010.04.011
Styles, J. A., Clark, H., Festing, M. F. W., & Rew, D. A. (2001). Automation of mouse micronucleus genotoxicity assay by laser scanning cytometry. Cytometry, 44(2), 153–155. https://doi.org/10.1002/1097-0320(20010601)44:2%3c153::AID-CYTO1095%3e3.0.CO;2-H
Takao, N., Kato, H., Mori, R., Morrison, C., Sonada, E., Sun, X., & Yamamoto, K. (1999). Disruption of ATM in p53-null cells causes multiple functional abnormalities in cellular response to ionizing radiation. Oncogene, 18(50), 7002–7009. https://doi.org/10.1038/sj.onc.1203172
Takashima, Y., Sakuraba, M., Koizumi, T., Sakamoto, H., Hayashi, M., & Honma, M. (2009). Dependence of DNA double strand break repair pathways on cell cycle phase in human lymphoblastoid cells. Environmental and Molecular Mutagenesis, 50(9), 815–822. https://doi.org/10.1002/em.20481
Tay, I. J., Park, J. J. H., Price, A. L., Engelward, B. P., & Floyd, S. R. (2020). HTS-compatible cometchip enables genetic screening for modulators of apoptosis and DNA double-strand break repair. SLAS Discovery, 25(8), 906–922. https://doi.org/10.1177/2472555220918367
Thybaud, V., Dean, S., Nohmi, T., de Boer, J., Douglas, G. R., Glickman, B. W., & Yajima, N. (2003). In vivo transgenic mutation assays. Mutation Research, 540(2), 141–151. https://doi.org/10.1016/j.mrgentox.2003.07.004
Tice, R. R., Agurell, E., Anderson, D., Burlinson, B., Hartmann, A., Kobayashi, H., & Sasaki, Y. F. (2000). Single cell gel/comet assay: Guidelines for in vitro and in vivo genetic toxicology testing. Environmental and Molecular Mutagenesis, 35(3), 206–221. https://doi.org/10.1002/(SICI)1098-2280(2000)35:3%3c206::AID-EM8%3e3.0.CO;2-J
Villalta, P. W., & Balbo, S. (2017). The future of DNA adductomic analysis. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms18091870
Wang, Q., Rodrigues, M. A., Repin, M., Pampou, S., Beaton-Green, L. A., Perrier, J., & Wilkins, R. C. (2019). Automated triage radiation biodosimetry: Integrating imaging flow cytometry with high-throughput robotics to perform the cytokinesis-block micronucleus assay. Radiation Research, 191(4), 342–351. https://doi.org/10.1667/RR15243.1
Wang, Y., Mittelstaedt, R. A., Wynne, R., Chen, Y., Cao, X., Muskhelishvili, L., & Heflich, R. H. (2021). Genetic toxicity testing using human in vitro organotypic airway cultures: Assessing DNA damage with the CometChip and mutagenesis by Duplex Sequencing. Environmental and Molecular Mutagenesis, 62(5), 306–318. https://doi.org/10.1002/em.22444
Watson, C., Ge, J., Cohen, J., Pyrgiotakis, G., Engelward, B. P., & Demokritou, P. (2014). High-throughput screening platform for engineered nanoparticle-mediated genotoxicity using CometChip technology. ACS Nano, 8(3), 2118–2133. https://doi.org/10.1021/nn404871p
Wei, Z., Wang, W., Hu, P., Lyon, G. J., & Hakonarson, H. (2011). SNVer: A statistical tool for variant calling in analysis of pooled or individual next-generation sequencing data. Nucleic Acids Research, 39(19), e132. https://doi.org/10.1093/nar/gkr599
Wilde, S., Dambowsky, M., Hempt, C., Sutter, A., & Queisser, N. (2017). Classification of in vitro genotoxicants using a novel multiplexed biomarker assay compared to the flow cytometric micronucleus test. Environmental and Molecular Mutagenesis, 58(9), 662–677. https://doi.org/10.1002/em.22130
Wilm, A., Aw, P. P., Bertrand, D., Yeo, G. H., Ong, S. H., Wong, C. H., & Nagarajan, N. (2012). LoFreq: A sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets. Nucleic Acids Research, 40(22), 11189–11201. https://doi.org/10.1093/nar/gks918
Winkelbeiner, N., Wandt, V. K., Ebert, F., Lossow, K., Bankoglu, E. E., Martin, M., & Schwerdtle, T. (2020). A multi-endpoint approach to base excision repair incision activity augmented by parylation and DNA damage levels in mice: Impact of sex and age. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms21186600
Witte, I., Plappert, U., de Wall, H., & Hartmann, A. (2007). Genetic toxicity assessment: Employing the best science for human safety evaluation part III: The comet assay as an alternative to in vitro clastogenicity tests for early drug candidate selection. Toxicological Sciences, 97(1), 21–26. https://doi.org/10.1093/toxsci/kfl192
Yamamoto, K. N., Hirota, K., Kono, K., Takeda, S., Sakamuru, S., Xia, M., & Tice, R. R. (2011). Characterization of environmental chemicals with potential for DNA damage using isogenic DNA repair-deficient chicken DT40 cell lines. Environmental and Molecular Mutagenesis, 52(7), 547–561. https://doi.org/10.1002/em.20656
Yamanaka, S., & Blau, H. M. (2010). Nuclear reprogramming to a pluripotent state by three approaches. Nature, 465(7299), 704–712. https://doi.org/10.1038/nature09229
You, X. (2021). Environmental agents-induced ultra-low frequency mutation detection by molecular consensus sequencing. Shanghai Jiao Tong University.
You, X., Thiruppathi, S., Liu, W., Cao, Y., Naito, M., Furihata, C., & Suzuki, T. (2020). Detection of genome-wide low-frequency mutations with paired-end and complementary consensus sequencing (PECC-Seq) revealed end-repair-derived artifacts as residual errors. Archives of Toxicology, 94(10), 3475–3485. https://doi.org/10.1007/s00204-020-02832-0
Yun, B. H., Rosenquist, T. A., Sidorenko, V., Iden, C. R., Chen, C. H., Pu, Y. S., & Turesky, R. J. (2012). Biomonitoring of aristolactam-DNA adducts in human tissues using ultra-performance liquid chromatography/ion-trap mass spectrometry. Chemical Research in Toxicology, 25(5), 1119–1131. https://doi.org/10.1021/tx3000889
Zhou, C., Li, Z., Diao, H., Yu, Y., Zhu, W., Dai, Y., & Yang, J. (2006). DNA damage evaluated by gammaH2AX foci formation by a selective group of chemical/physical stressors. Mutation Research, 604(1–2), 8–18. https://doi.org/10.1016/j.mrgentox.2005.12.004
Acknowledgements
This work is supported by the Major Program of the National Natural Science Foundation of China, grant number 41991314.
Funding
This work is supported by the Major Program of the National Natural Science Foundation of China, grant number 41991314.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Conflict of interest
There are no conflicts of interest to declare.
Rights and permissions
About this article
Cite this article
Luan, Y., Honma, M. Genotoxicity testing and recent advances. GENOME INSTAB. DIS. 3, 1–21 (2022). https://doi.org/10.1007/s42764-021-00058-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s42764-021-00058-7