A Systems Biology approach to understanding and monitoring chemical toxicity in the environment



Basili, D ORCID: 0000-0003-4830-7848
(2018) A Systems Biology approach to understanding and monitoring chemical toxicity in the environment. PhD thesis, University of Liverpool.

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Abstract

Chemicals pose every day a continuous hazard to both human health and environment. Unfortunately, Information about chemicals Mode of Action (MoA) for most of these compounds is limited. Development of approaches able to elucidate chemicals mechanisms of action is needed in order to improve risk assessment. Environmental omics aims to provide tools and methodologies to address these goals. Omics technologies in combination with system biology approaches have the potential to provide a powerful toolbox for understanding chemicals mode of action and consequently the outcomes these compounds trigger. The work presented in this thesis demonstrates the effectiveness of such approach in the context of environmentally relevant species. More specifically I focused on characterization of single chemical and chemical class toxicity mechanism in zebrafish embryos (Danio rerio) and in a fish gill cell line (Rainbow trout) and I demonstrated that the transcriptional state of an in vitro system exposed to a panel of environmentally relevant chemicals can be used as a biosensor to predict toxicity in an in vivo system. I also developed a computational model of ovary development in Largemouth bass (Micropterus salmoides) and used this to successfully identify chemical compounds with the ability to affect reproduction. Lastly, I developed a method to identify novel endocrine disrupting compounds in Daphnia magna supporting the use of this species for rapid screening in risk assessment. My results demonstrated the potential of system biology and data-driven science in identifying novel mechanisms of environmental toxicity and to develop a set of biomarkers for monitoring purposes. Further development building on these findings could potentially lead to improvements in risk assessment.

Item Type: Thesis (PhD)
Divisions: Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 14 Dec 2018 15:29
Last Modified: 19 Jan 2023 01:26
DOI: 10.17638/03025584
Supervisors:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3025584