Publication Details |
| Category | Text Publication |
| Reference Category | Qualification assignments |
| Document | publication document |
| Title (Primary) | Modeling and predicting toxicogenomic effect profiles of environmental chemicals and their mixtures : towards non-target bioanalytics for environmental monitoring |
| Author | Schüttler, A. |
| Source Titel | PhD Dissertation |
| Year | 2019 |
| Department | BIOTOX |
| Volume | 1/2019 |
| Page To | XX, 200 |
| Language | englisch |
| Keywords | Umwelttoxikologie; Exposition; Chemikalie; Gewässer; Transkriptomanalyse; Toxikologische Bewertung; Genomik; Umweltüberwachung; Umweltchemikalie |
| UFZ inventory | Leipzig, Bibliothek, Reportsammlung, 00530743, 19-0193 F/E |
| Abstract | While many water bodies are found to be polluted by a mixture of numerous chemicals, suitable tools which allow a comprehensive diagnosis of the resulting biological effects are lacking. However, such effect information would be needed in water body management to facilitate measures which counteract decreasing ecological quality. Toxicogenomic methods (i.e., the application of omics technology in toxicology) could fill this gap by providing non-target bioanalytical approaches. Therefore, this dissertation aims at advancing the applicability of toxicogenomics in environmental monitoring. It has been shown that exposing organisms to chemicals may inducecompound specific changes on the transcriptome, i.e. the entire composition of RNA transcripts in a cell or tissue. Transcripts are copies of genes on the DNA, which may have regulatory functions or encode the assembly of proteins. The analysis of transcriptome profiles, which can be conducted with the help of cDNA-microarrays, may indicate specific compound exposure, and at the same time provide insights about the cellular or physiological responses in the organism (e.g., biotransformation, proliferation, cell death). These properties could be used to apply transcriptomics for comprehensive diagnoses of biological effects and the respective responsible substances in environmental samples. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=21836 |
| Schüttler, A. (2019): Modeling and predicting toxicogenomic effect profiles of environmental chemicals and their mixtures : towards non-target bioanalytics for environmental monitoring Dissertation, Rheinisch-Westfälische Technische Hochschule (RWTH), Fakultät für Mathematik, Informatik und Naturwissenschaften PhD Dissertation 1/2019 Helmholtz-Zentrum für Umweltforschung - UFZ, Leipzig, XX, 200 pp. |
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