Traditional water monitoring encounter limitations due to the large number of contaminants present in our waters possible giving raise to mixture effects. This thesis aimed to investigate how the emerging omics approaches (transcriptomics, proteomics and metabolomics) can be used as an effect-based monitoring approach to assess and predict adverse effects in the freshwater environment. Moreover, this thesis analysed challenges and barrier with omics. A systematic literature search was conducted using Scopus and Web of Science to find case-studies using omics in field studies and reviews regarding challenges and barriers. The results in this thesis suggest that the use of fish species (either collected in the wild or in situ set-ups), transcriptomics and investigations of WWTP recipient was the most common way to apply omics. In order to interpret omics-data multiple studies conducted chemical monitoring in conjunction, investigated additional traditional biomarkers and/or used omics to identify altered biological or functional pathways that possible could lead to adverse effects at higher levels. According to the challenges and barriers identified in this thesis, the future of omics in environmental monitoring rely on the possibility to characterise and quantify natural variability, define appropriate critical effect sizes (i.e. thresholds of critical effects) and define baseline data. Moreover, it is necessary to develop frameworks and standardisations for omics-approaches (e.g. study-designs) to promote the interpretation of the results. Future research is also needed to develop and increase the understanding of how the proteomics and metabolomics can be applied. By improving the use of omics a more holistic water monitoring can be achieved including screenings for biological responses and the ability to detect early warnings which will enhance the prioritisation and site management of polluted water bodies, including those with limited prior knowledge regarding potential contaminants.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-87517 |
| Date | January 2019 |
| Creators | Sahlin, Sara |
| Publisher | Linnéuniversitetet, Institutionen för biologi och miljö (BOM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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