Dioxin exposure is linked to a range of toxic effects in humans including cancer and irreversible developmental effects. Exposure is primarily through the ingestion of animal-derived foods so the ability to detect and eliminate dioxin from the food chain is paramount to ensuring public health. This study was designed to investigate the potential of analytical profiling tools to detect and identify live animals which have been exposed to dioxin based upon patterns of changes in analytes present in accessible biofluids such as blood and urine. In vitro cell culture studies identified a range of additive and non-additive interactions between dioxin and non-dioxin like co-toxins across a spectrum of endpoints including EROD activity, reduction of Alamar Blue and SELDI-TOF peptidomic profiling. Rats were then exposed to dioxin in their diet as 2,3,7,8-TCDD, but also in the form of incinerator soot or the PCB oil Aroclor 1254. The plasma and urine were screened for metabolomic changes which resulted from exposure using liquid id chromatography-high resolution mass spectrometry methods. This data was processed using multivariate statistical analysis techniques to identify potential biomarkers and to look for predictive statistical models which may be able to identify exposure. Furthermore the level of expression of a range of proteins were determined by the use of 2-dimensional gel electrophoresis to help understand the pathways affected by dose to real-world dioxin exposure condition s. A predictive statistical model was validated based upon metabolomic profiling of the plasma of the exposed rats which was able to correctly identify the source of dioxin exposure with a >97.2% accuracy rate. A novel method for validation of the accuracy of OPLS-DA models was developed and tested. Patterns of changes to amino acid metabolism such as tyrosine and tryptophan were identified as being important in exposure, indicating novel modes-of-action not previously associated with dioxin exposure.

MENVM / Department of Ecology and Resource Management / Polychlorinated biphenyls (PCBs) are worldwide environmental pollutants which contaminate the environment through careless disposal practices and accidental spills or leakages from electrical transformers. These organic compounds are lipophilic chemicals soluble in fats, slightly soluble in water and readily bioaccumulated in the fatty tissues of fish, birds, animals and humans. The main objective of this study was to isolate and identify PCB degrading bacteria from PCB contaminated soils and test them for their degradation ability of PCBs in natural habitat conditions. Three bacteria species which comprise of Gram negative and Gram positive microorganisms were isolated and identified through biochemical tests, catalase tests, oxidase tests and morphological study and included Burkholderia cepacia, Pasteurella pneumotropica and Enterococcus faecalis. The results indicated that, there was an overall decrease of PCB concentration level and the readings ranged between -1.51 and -1.79 respectively for all the microorganisms. Enterococcus faecalis remove as much as 32% of PCBs in the contaminated soil samples. Whereas Pasteurella pneumotropica could remove 24% of PCBs, Burkholderia cepacia 21% of PCBs and the mixed culture removed 23%. Data showed that the 3 bacterial strains could tolerate high concentration of PCBs. The results provided the evidence that naturally occurring bacteria in soil contaminated with PCBs have the potential to degrade PCBs. Statistical analysis showed that there was a significant positive correlation between bacteria growth and treatment with a coefficient of (r) =0.1459 and p value <0.001.