Ekolojik Risk Değerlendirmede Ekotoksikogenomik Kavramı ve Verdiği Katkılar

Year 2020, Volume: 9 Issue: 1, 144 - 161, 18.06.2020

Mehmet Kürşat Şahin

https://doi.org/10.46810/tdfd.712763

Abstract

Ekotoksikolojide, ekotoksikogenomik yaklaşımlar önemli bir alan olmaya başlamıştır. Toksikogenomikler önceleri kimyasalların insanlara risklerini belirlemek amacıyla kullanımdayken, bu konudaki son gelişmeler bu yaklaşımın diğer organizmalara da uygulanabilirliğini göstermiştir. Ekotoksikogenomik, ekosistemi temsil eden ve bireyler üzerinde olduğu kadar ekosistem üzerinde de kimyasalların zararlı etkilerinin çalışıldığı, organizmalara yönelik toksikogenomik bir uygulamadır. Ekotoksikogenomik belli bir toksikanta biyolojik sistemlerin bir yanıtı olarak, öncül gen ekspresyon çalışmalarından gelişmiştir. Zaman içinde olgunlaşan çalışmalar çeşitli –omik alanlarının toksikoloji ve patolojide kullanılmasına olanak sağlamıştır. Bu bağlamda ekolojik risk değerlendirme çalışmalarında çeşitli enzimler ve proteinlerin (örneğin Glutatyon S-transferaz, metallotiyonin, kolinesterazlar, ısı – şok proteinleri) biyobelirteç olarak kullanılması canlılar üzerindeki potansiyel etkilerin gözlemlenmesine olanak sağlamıştır. Ayrıca birçok omurgalı ve omurgasız canlıda toksik etkiye maruz kalmanın belirlenmesinde mikroçip veya gen çiplerinden yararlanılarak hangi genlerin hücrede, dokuda, organda “up/down regüle” olarak ifade edilmesinin belirlenmesi de bu yaklaşımın bir diğer alanıdır. Etki ve genin sonuç özgü örüntüsü, protein ve metabolit profilleri, toksisitenin biyobelirteçleri olarak moleküler değişimleri tanımlamada kullanılmakta ve bu profiller, toksisite mekanizmalarını açıklamayı da sağlamaktadır. Bu yaklaşım ile çok sayıda farklı etkenin etki mekanizmalarını belirlenerek, belli tür ve populasyon alt gruplarında bu mekanizmaları yorumlayabilen genetik özellikleri gösterebilmektedir. Son yıllarda çevresel maruz kalma ile oluşan etkilerden korunma ya da etkinin azaltılmasında ekotoksikogenomik çalışmalar, multidisipliner kimliği ile hem erken uyarı değerlendirilmesini hem de maruz kalmanın ekosistemde oluşturduğu risklerin moleküler düzeyde etki mekanizmalarının açıklanmasını sağlayan bir bilim dalı olarak gelişmesini sürdürmektedir.

Keywords

ekotoksikogenomik, toksikant, biyobelirteç, Ekolojik risk değerlendirilmesi

Ecotoxicogenomics Concept and Its Contributions to Ecological Risk Assessment

Abstract

Ecotoxicogenomic approach has become an important area in ecotoxicology. While toxicogenomics were previously used to determine the risks of chemicals to humans, recent developments in this area have demonstrated that this approach is also applicable for other organisms.Ecotoxicogenomic is a toxicogenomic practice that represents the ecosystem and where harmful effects of chemicals are studied on the ecosystem as well as on individuals. Ecotoxicogenomics evolved from precursor gene expression studies as a response to a particular toxicant biological systems. Studies that have matured over time have allowed various -omic fields to be used in toxicology and pathology. In this context, the use of various enzymes and proteins (eg Glutathione S-transferase, metallothionine, cholinesterases, heat-shock proteins) as biomarkers in ecological risk assessment studies has enabled the observation of potential effects on living things. In addition, determining which genes are expressed as “up / down regulated” in the cell, tissue and organ by using microarrays or gene chips in determining the exposure to toxic effects in many vertebrates and invertebrates. The result-specific pattern of effect and gene, protein and metabolite profiles are used to define molecular changes as biomarkers of toxicity, and these profiles also explain the mechanisms of toxicity. With this approach, by determining the mechanisms of action of many different factors, it can show genetic features that can interpret these mechanisms in certain species and population subgroups. In recent years, ecotoxicogenomic studies continue to be developed as a branch of science that provides both early warning assessment and explanation of the mechanisms of action at the molecular level of the risks posed by the exposure in the ecosystem, with its multidisciplinary identity.  

Keywords

Ecotoxicogenomic, Toxicant, Biomarker, Ecological risk assessment

References

• [1] Snape JR, Maund SJ, Pickford DB, Hutchinson TH. Ecotoxicogenomics: the challenge of integrating genomics into aquatic and terrestrial ecotoxicology. Aquatic toxicology. 2004;67(2):143-54.
• [2] Nuwaysir EF, Bittner M, Trent J, Barrett JC, Afshari CA. Microarrays and toxicology: the advent of toxicogenomics. Molecular Carcinogenesis: Published in cooperation with the University of Texas MD Anderson Cancer Center. 1999;24(3):153-9.
• [3] Fielden MR, Zacharewski TR. Challenges and limitations of gene expression profiling in mechanistic and predictive toxicology. Toxicological sciences. 2001;60(1):6-10.
• [4] Thomas RS, Rank DR, Penn SG, Zastrow GM, Hayes KR, Pande K, vd. Identification of toxicologically predictive gene sets using cDNA microarrays. Molecular Pharmacology. 2001;60(6):1189-94.
• [5] Hamadeh HK, Bushel PR, Jayadev S, Martin K, DiSorbo O, Sieber S, vd. Gene expression analysis reveals chemical-specific profiles. Toxicological Sciences. 2002;67(2):219-31.
• [6] Tennant RW. The National Center for Toxicogenomics: using new technologies to inform mechanistic toxicology. Environmental health perspectives. 2002;110(1):A8-10.
• [7] Ulrich R, Friend SH. Toxicogenomics and drug discovery: will new technologies help us produce better drugs? Nature Reviews Drug Discovery. 2002;1(1):84-8.
• [8] Olden K. Genomics in environmental health research—opportunities and challenges. Toxicology. 2004;198(1-3):19-24.
• [9] Lettieri T. Recent applications of DNA microarray technology to toxicology and ecotoxicology. Environmental health perspectives. 2006;114(1):4-9.
• [10] Sanchez BC, Ralston‐Hooper K, Sepúlveda MS. Review of recent proteomic applications in aquatic toxicology. Environmental toxicology and chemistry. 2011;30(2):274-82.
• [11] Dorts J, Kestemont P, Marchand P-A, D’Hollander W, Thézenas M-L, Raes M, vd. Ecotoxicoproteomics in gills of the sentinel fish species, Cottus gobio, exposed to perfluorooctane sulfonate (PFOS). Aquatic Toxicology. 2011;103(1-2):1-8.
• [12] Gomes T, Pereira CG, Cardoso C, Pinheiro JP, Cancio I, Bebianno MJ. Accumulation and toxicity of copper oxide nanoparticles in the digestive gland of Mytilus galloprovincialis. Aquatic Toxicology. 2012;118:72-9.
• [13] Vidal-Dorsch DE, Bay SM, Moore S, Layton B, Mehinto AC, Vulpe CD, vd. Ecotoxicogenomics: Microarray interlaboratory comparability. Chemosphere. 2016;144:193-200.
• [14] Abbas A, Valek L, Schneider I, Bollmann A, Knopp G, Seitz W, vd. Ecotoxicological impacts of surface water and wastewater from conventional and advanced treatment technologies on brood size, larval length, and cytochrome P450 (35A3) expression in Caenorhabditis elegans. Environmental Science and Pollution Research. 2018;25(14):13868-80.
• [15] Campos B, Fletcher D, Piña B, Tauler R, Barata C. Differential gene transcription across the life cycle in Daphnia magna using a new all genome custom-made microarray. BMC genomics. 2018;19(1):370.
• [16] Campana O, Wlodkowic D. Ecotoxicology goes on a chip: embracing miniaturized bioanalysis in aquatic risk assessment. Environmental science & technology. 2018;52(3):932-46.
• [17] Prat O, Degli-Esposti D. New Challenges: Omics Technologies in Ecotoxicology. Içinde: Ecotoxicology. Elsevier; 2019. s. 181-208.
• [18] Lee B-Y, Choi B-S, Kim M-S, Park JC, Jeong C-B, Han J, vd. The genome of the freshwater water flea Daphnia magna: A potential use for freshwater molecular ecotoxicology. Aquatic Toxicology. 2019;210:69-84.
• [19] Fröhlich E. Role of omics techniques in the toxicity testing of nanoparticles. Journal of nanobiotechnology. 2017;15(1):84.
• [20] Simões T, Novais SC, Natal-da-Luz T, Devreese B, de Boer T, Roelofs D, vd. An integrative omics approach to unravel toxicity mechanisms of environmental chemicals: effects of a formulated herbicide. Scientific reports. 2018;8(1):1-12.
• [21] Martínez R, Navarro-Martín L, Luccarelli C, Ortiz-Villanueva E, Codina AE, Raldúa D, vd. Applying omic techniques to unravel distinct pathways of PFOS toxicity in zebrafish eleutheroembryos. 2019;
• [22] Krizkova S, Kepinska M, Emri G, Rodrigo MAM, Tmejova K, Nerudova D, vd. Microarray analysis of metallothioneins in human diseases—A review. Journal of pharmaceutical and biomedical analysis. 2016;117:464-73.
• [23] Searfoss GH, Jordan WH, Calligaro DO, Galbreath EJ, Schirtzinger LM, Berridge BR, vd. Adipsin, a biomarker of gastrointestinal toxicity mediated by a functional γ-secretase inhibitor. Journal of Biological Chemistry. 2003;278(46):46107-16.
• [24] Ampe F. The use of nanopore sequencıng ın ecotoxıcology. Ghent University; 2019.
• [25] Bláha L, Hofman J. Ecotoxicology of Environmental Pollutants. Içinde: Advanced Nano-Bio Technologies for Water and Soil Treatment. Springer; 2020. s. 549-72.
• [26] Poynton HC. Insights from ‘Omics on the Exposure and Effects of Engineered Nanomaterials on Aquatic Organisms. Içinde: Ecotoxicology of Nanoparticles in Aquatic Systems. CRC Press; 2019. s. 189-207.
• [27] Caballero-Gallardo K, Olivero-Verbel J, L Freeman J. Toxicogenomics to evaluate endocrine disrupting effects of environmental chemicals using the zebrafish model. Current genomics. 2016;17(6): s515-27.
• [28] Messerlian C, Martinez RM, Hauser R, Baccarelli AA. “Omics” and endocrine-disrupting chemicals—new paths forward. Nature Reviews Endocrinology. 2017;13(12):740.
• [29] Oliveira E, Barata C, Piña B. Endocrine disruption in the omics era: new views, new hazards, new approaches. The Open Biotechnology Journal. 2016;10(1): s20-35.
• [30] Kim B-M, Kim J, Choi I-Y, Raisuddin S, Au DW, Leung KM, vd. Omics of the marine medaka (Oryzias melastigma) and its relevance to marine environmental research. Marine environmental research. 2016;113:141-52.
• [31] Lv X, Xiao S, Zhang G, Jiang P, Tang F. Occurrence and removal of phenolic endocrine disrupting chemicals in the water treatment processes. Scientific reports. 2016;6(1):1-10.
• [32] Mennigen JA, Thompson LM, Bell M, Santos MT, Gore AC. Transgenerational effects of polychlorinated biphenyls: 1. Development and physiology across 3 generations of rats. Environmental Health. 2018;17(1):18.
• [33] Chen H, Zhao L, Yu QJ. Determination and reduced life expectancy model and molecular docking analyses of estrogenic potentials of 17β-estradiol, bisphenol A and nonylphenol on expression of vitellogenin gene (vtg1) in zebrafish. Chemosphere. 2019;221:727-34.
• [34] Rao MS, Van Vleet TR, Ciurlionis R, Buck WR, Mittelstadt SW, Blomme EA, vd. Comparison of RNA-seq and microarray gene expression platforms for the toxicogenomic evaluation of liver from short-term rat toxicity studies. Frontiers in genetics. 2019;9:636.
• [35] Gismondi E. Identification of molt-inhibiting hormone and ecdysteroid receptor cDNA sequences in Gammarus pulex, and variations after endocrine disruptor exposures. Ecotoxicology and environmental safety. 2018;158:9-17.
• [36] Salama RM, Abd Elwahab AH, Abd-Elgalil MM, Elmongy NF, Schaalan MF. LCZ696 (sacubitril/valsartan) protects against cyclophosphamide-induced testicular toxicity in rats: Role of neprilysin inhibition and lncRNA TUG1 in ameliorating apoptosis. Toxicology. 2020;152439.
• [37] Jiang W, Zhao H, Zhang L, Wu B, Zha Z. Maintenance of mitochondrial function by astaxanthin protects against bisphenol A-induced kidney toxicity in rats. Biomedicine & Pharmacotherapy. 2020;121:109629.
• [38] Osorio D, Pinzón A, Martín-Jiménez C, Barreto GE, González J. Multiple pathways involved in palmitic acid-induced toxicity: A system biology approach. Frontiers in neuroscience. 2020;13:1410.
• [39] Sharma N, Saifi MA, Singh SB, Godugu C. In vivo studies: toxicity and biodistribution of nanocarriers in organisms. Içinde: Nanotoxicity. Elsevier; 2020. s. 41-70.
• [40] Yauk CL, Harrill AH, Ellinger-Ziegelbauer H, van der Laan JW, Moggs J, Froetschl R, vd. A cross-sector call to improve carcinogenicity risk assessment through use of genomic methodologies. Regulatory Toxicology and Pharmacology. 2020;110:104526.
• [41] Lemos MF, Soares AM, Correia AC, Esteves AC. Proteins in ecotoxicology–how, why and why not? Proteomics. 2010;10(4):873-87.
• [42] Veldhoen N, Ikonomou MG, Helbing CC. Molecular profiling of marine fauna: integration of omics with environmental assessment of the world’s oceans. Ecotoxicology and environmental safety. 2012;76:23-38.
• [43] Zhang Q, Li J, Middleton A, Bhattacharya S, Conolly RB. Bridging the data gap from in vitro toxicity testing to chemical safety assessment through computational modeling. Frontiers in public health. 2018;6:261.
• [44] Udofia UU, Edet UO, Antai SP. Potential Benefits of Applying “Omics” Technology in Cleaning up Incessant Crude Oil Spillages in the Niger Delta Region of Nigeria. Advances in Research. 2018;1-8.
• [45] Campos A, Tedesco S, Vasconcelos V, Cristobal S. Proteomic research in bivalves: towards the identification of molecular markers of aquatic pollution. Journal of Proteomics. 2012;75(14):4346-59.
• [46] Waters MD, Fostel JM. Toxicogenomics and systems toxicology: aims and prospects. Nature Reviews Genetics. 2004;5(12):936-48.
• [47] Hines A, Staff FJ, Widdows J, Compton RM, Falciani F, Viant MR. Discovery of metabolic signatures for predicting whole organism toxicology. Toxicological Sciences. 2010;115(2):369-78.
• [48] Nair PMG, Choi J. Identification, characterization and expression profiles of Chironomus riparius glutathione S-transferase (GST) genes in response to cadmium and silver nanoparticles exposure. Aquatic toxicology. 2011;101(3-4):550-60.
• [49] Dondero F, Banni M, Negri A, Boatti L, Dagnino A, Viarengo A. Interactions of a pesticide/heavy metal mixture in marine bivalves: a transcriptomic assessment. BMC genomics. 2011;12(1):195.
• [50] Choi JS, Kim R-O, Yoon S, Kim W-K. Developmental toxicity of zinc oxide nanoparticles to zebrafish (Danio rerio): a transcriptomic analysis. PLoS One. 2016;11(8).
• [51] Morgens DW, Wainberg M, Boyle EA, Ursu O, Araya CL, Tsui CK, vd. Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens. Nature communications. 2017;8(1):1-8.
• [52] Hook SE, Mondon J, Revill AT, Greenfield PA, Smith RA, Turner RD, vd. Transcriptomic, lipid, and histological profiles suggest changes in health in fish from a pesticide hot spot. Marine environmental research. 2018;140:299-321.
• [53] Davis AP, Grondin CJ, Johnson RJ, Sciaky D, McMorran R, Wiegers J, vd. The comparative toxicogenomics database: update 2019. Nucleic acids research. 2019;47(D1):D948-54.
• [54] Aguayo-Orozco A, Taboureau O, Brunak S. The use of systems biology in chemical risk assessment. Current Opinion in Toxicology. 2019;
• [55] Jager T, Vandenbrouck T, Baas J, De Coen WM, Kooijman SA. A biology-based approach for mixture toxicity of multiple endpoints over the life cycle. Ecotoxicology. 2010;19(2):351-61.
• [56] Kumar R, Weigel S, Meyer R, Niemeyer CM, Fuchs H, Hirtz M. Multi-color polymer pen lithography for oligonucleotide arrays. Chemical Communications. 2016;52(83):12310-3.
• [57] Lobenhofer EK, Cui X, Bennett L, Cable PL, Merrick BA, Churchill GA, vd. Exploration of low-dose estrogen effects: identification of No Observed Transcriptional Effect Level (NOTEL). Toxicologic pathology. 2004;32(4):482-92.
• [58] Fukushima T, Hara-Yamamura H, Nakashima K, Tan LC, Okabe S. Multiple-endpoints gene alteration-based (MEGA) assay: A toxicogenomics approach for water quality assessment of wastewater effluents. Chemosphere. 2017;188:312-9.
• [59] Poynton HC, Loguinov AV, Varshavsky JR, Chan S, Perkins EJ, Vulpe CD. Gene expression profiling in Daphnia magna part I: concentration-dependent profiles provide support for the no observed transcriptional effect level. Environmental science & technology. 2008;42(16):6250-6.
• [60] Crawford KA, Clark BW, Heiger-Bernays WJ, Karchner SI, Henn BGC, Griffith KN, vd. Altered lipid homeostasis in a PCB-resistant Atlantic killifish (Fundulus heteroclitus) population from New Bedford Harbor, MA, USA. Aquatic toxicology. 2019;210:30-43.
• [61] Riley AK, Chernick M, Brown DR, Hinton DE, Di Giulio RT. Hepatic responses of juvenile Fundulus heteroclitus from pollution-adapted and nonadapted populations exposed to Elizabeth River sediment extract. Toxicologic pathology. 2016;44(5):738-48.
• [62] Li H, Zhang J, You J. Diagnosis of complex mixture toxicity in sediments: Application of toxicity identification evaluation (TIE) and effect-directed analysis (EDA). Environmental Pollution. 2018;237:944-54.
• [63] Arzuaga X, Walker T, Yost E, Radke E, Hotchkiss A. Use of the Adverse Outcome Pathway (AOP) framework to evaluate species concordance and human relevance of Dibutyl Phthalate (DBP)-induced male reproductive toxicity. Reproductive Toxicology. 2019;
• [64] Liu W, Wu Y, Wang C, Li HC, Wang T, Liao CY, vd. Impact of silver nanoparticles on human cells: effect of particle size. Nanotoxicology. 2010;4(3):319-30.
• [65] Krasnov A, Koskinen H, Rexroad C, Afanasyev S, Mölsä H, Oikari A. Transcriptome responses to carbon tetrachloride and pyrene in the kidney and liver of juvenile rainbow trout (Oncorhynchus mykiss). Aquatic Toxicology. 2005;74(1):70-81.
• [66] Henry TB, Menn F-M, Fleming JT, Wilgus J, Compton RN, Sayler GS. Attributing effects of aqueous C60 nano-aggregates to tetrahydrofuran decomposition products in larval zebrafish by assessment of gene expression. Environmental Health Perspectives. 2007;115(7):1059-65.
• [67] Wagner M, Kienle C, Vermeirssen EL, Oehlmann J. Endocrine disruption and in vitro ecotoxicology: Recent advances and approaches. Içinde: In vitro Environmental Toxicology-Concepts, Application and Assessment. Springer; 2017. s. 1-58.
• [68] Roper C, Tanguay RL. Zebrafish as a model for developmental biology and toxicology. Içinde: Handbook of Developmental Neurotoxicology. Elsevier; 2018. s. 143-51.
• [69] Bertotto LB, Catron TR, Tal T. Exploring interactions between xenobiotics, microbiota, and neurotoxicity in zebrafish. NeuroToxicology. 2020;76:235-44.
• [70] Anbumani S, Kakkar P. Ecotoxicological effects of microplastics on biota: a review. Environmental Science and Pollution Research. 2018;25(15):14373-96.
• [71] Bada M, Stevens R, Goble C, Gil Y, Ashburner M, Blake JA, vd. A short study on the success of the Gene Ontology. Journal of web semantics. 2004;1(2):235-40.
• [72] Gene Ontology Resource [Internet]. Gene Ontology Resource. [a.yer 13 Şubat 2020]. Erişim adresi: http://geneontology.org/
• [73] Ebrahimie E, Fruzangohar M, Moussavi Nik SH, Newman M. Gene ontology-based analysis of zebrafish omics data using the web tool comparative gene ontology. Zebrafish. 2017;14(5):492-4.
• [74] Ruzicka L, Howe DG, Ramachandran S, Toro S, Van Slyke CE, Bradford YM, vd. The Zebrafish Information Network: new support for non-coding genes, richer Gene Ontology annotations and the Alliance of Genome Resources. Nucleic acids research. 2019;47(D1):D867-73.
• [75] Newman M, Hin N, Pederson S, Lardelli M. Brain transcriptome analysis of a familial Alzheimer’s disease-like mutation in the zebrafish presenilin 1 gene implies effects on energy production. Molecular brain. 2019;12(1):43.
• [76] Howe DG, Bradford YM, Eagle A, Fashena D, Frazer K, Kalita P, vd. The Zebrafish Model Organism Database: new support for human disease models, mutation details, gene expression phenotypes and searching. Nucleic acids research. 2017;45(D1):D758-68.
• [77] Larkin P, Villeneuve DL, Knoebl I, Miracle AL, Carter BJ, Liu L, vd. Development and validation of a 2,000‐gene microarray for the fathead minnow (Pimephales promelas). Environmental Toxicology and Chemistry: An International Journal. 2007;26(7):1497-506.
• [78] KEGG: Kyoto Encyclopedia of Genes and Genomes [Internet]. [a.yer 13 Şubat 2020]. Erişim adresi: https://www.genome.jp/kegg/
• [79] GenMAPP - Download Area [Internet]. [a.yer 17 Şubat 2020]. Erişim adresi: http://www.genmapp.org/
• [80] Villeneuve DL, Larkin P, Knoebl I, Miracle AL, Kahl MD, Jensen KM, vd. A graphical systems model to facilitate hypothesis-driven ecotoxicogenomics research on the teleost brain− pituitary− gonadal axis. Environmental science & technology. 2007;41(1):321-30.
• [81] Xu Z, Liu J, Wu X, Huang B, Pan X. Nonmonotonic responses to low doses of xenoestrogens: a review. Environmental research. 2017;155:199-207.
• [82] Liu Z, Huang R, Roberts R, Tong W. Toxicogenomics: A 2020 Vision. Trends in pharmacological sciences. 2019;40(2):92-103.
• [83] Vahle JL, Anderson U, Blomme EA, Hoflack J-C, Stiehl DP. Use of toxicogenomics in drug safety evaluation: Current status and an industry perspective. Regulatory Toxicology and Pharmacology. 2018;96:18-29.
• [84] Santos EM, Paull GC, Van Look KJ, Workman VL, Holt WV, Van Aerle R, vd. Gonadal transcriptome responses and physiological consequences of exposure to oestrogen in breeding zebrafish (Danio rerio). Aquatic toxicology. 2007;83(2):134-42.
• [85] Wilkinson J. Environmental Epigenetics: The Enviro-genomic Interface. 2018;
• [86] Patisaul HB, Fenton SE, Aylor D. Animal models of endocrine disruption. Best Practice & Research Clinical Endocrinology & Metabolism. 2018;32(3):283-97.
• [87] Fedorenkova A, Vonk JA, Lenders HR, Ouborg NJ, Breure AM, Hendriks AJ. Ecotoxicogenomics: Bridging the gap between genes and populations. Environmental science & technology. 2010;44(11):4328-33.
• [88] Amiard-Triquet C. How to improve toxicity assessment? From single-species tests to mesocosms and field studies. Içinde: Aquatic Ecotoxicology. Elsevier; 2015. s. 127-51.
• [89] Wang Y, Na G, Zong H, Ma X, Yang X, Mu J, vd. Applying adverse outcome pathways and species sensitivity–weighted distribution to predicted‐no‐effect concentration derivation and quantitative ecological risk assessment for bisphenol A and 4‐nonylphenol in aquatic environments: A case study on Tianjin City, China. Environmental toxicology and chemistry. 2018;37(2):551-62.
• [90] Scognamiglio V, Antonacci A, Patrolecco L, Lambreva MD, Litescu SC, Ghuge SA, vd. Analytical tools monitoring endocrine disrupting chemicals. TrAC Trends in Analytical Chemistry. 2016;80:555-67.
• [91] McMullen PD, Pendse S, Adeleye Y, Carmichael PL, Andersen ME, Clewell RA. Using Transcriptomics to Evaluate Thresholds in Genotoxicity Dose–Response. Içinde: Toxicogenomics in Predictive Carcinogenicity. Royal Society of Chemistry; 2016. s. 185-208.
• [92] Haggard D. Classifying Chemical Bioactivity by Coupling High-throughput Phenotypic Anchoring and Transcriptome Profiling in Zebrafish. 2016;
• [93] Mahaye N, Thwala M, Cowan DA, Musee N. Genotoxicity of metal based engineered nanoparticles in aquatic organisms: A review. Mutation Research/Reviews in Mutation Research. 2017;773:134-60.
• [94] Kuhn RM, Karolchik D, Zweig AS, Wang T, Smith KE, Rosenbloom KR, vd. The UCSC genome browser database: update 2009. Nucleic acids research. 2009;37(suppl_1):D755-61.
• [95] Grondin CJ, Davis AP, Wiegers TC, Wiegers JA, Mattingly CJ. Accessing an expanded exposure science module at the Comparative Toxicogenomics Database. Environmental health perspectives. 2018;126(1):014501.
• [96] Saito F. Mechanism-Based Evaluation System for Hepato-and Nephrotoxicity or Carcinogenicity Using Omics Technology. Içinde: Alternatives to Animal Testing. Springer; 2019. s. 91-104.
• [97] Baker TK, Engle SK, Halstead BW, Paisley BM, Searfoss GH, Willy JA. Discover Toxicology: An Early Safety Assessment Approach. Içinde: Translating Molecules into Medicines. Springer; 2017. s. 119-62.
• [98] Wu J-Q, Zhang S-S, Gao H, Qi Z, Zhou C-J, Ji W-W, vd. Experimental and theoretical studies on rhodium-catalyzed coupling of benzamides with 2, 2-difluorovinyl tosylate: diverse synthesis of fluorinated heterocycles. Journal of the American Chemical Society. 2017;139(9):3537-45.
• [99] Taboureau O, Audouze K, Brunak S. 3 REACH and Environmental. Computational Methods for Reproductive and Developmental Toxicology. 2015;23.
• [100] Broeckaert F, Rossi LH. Regulatory needs for the assessment of respiratory sensitisation under REACH and CLP. Toxicology Letters. 2017; 280:S60.
• [101] Maggi L, Zalacain A, Mazzoleni V, Alonso GL, Salinas MR. Comparison of stir bar sorptive extraction and solid-phase microextraction to determine halophenols and haloanisoles by gas chromatography–ion trap tandem mass spectrometry. Talanta. 2008;75(3):753-9.
• [102] Shamim N, Gupta A, Paul V, Vida E. Nutritional genomics: A review. The Pharma Innovation. 2017;6(4, Part A):17: 167-191.
• [103] Gao Y, Chen J. Informatics for Nutritional Genetics and Genomics. Içinde: Translational Informatics in Smart Healthcare. Springer; 2017. 143-66.