Development & evaluation of chlorophyll a fluorescence as a bioanalytical tool for pollutant identification
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There is potential to improve water quality monitoring programs by generating pollution data that better represents the aquatic ecosystem being monitored. By incorporating rapid and cost-effective bioanalytical methods into water quality monitoring programs, risk associated with unrepresentative data can be reduced by increasing the number of samples collected without incurring additional costs. The rapid and cost-effective toxin-identification method presented here is based on quantifying patterns of change in chlorophyll a fluorescence (fluorescence fingerprints) associated with a toxicants mode of action (MoA). Chlorophyll a fluorescence yield is influenced by environmental factors and can be used to identify stress caused by light, nutrient status and the presence of pollutants. When the functional state of the photosynthetic apparatus changes, the yield of fluorescence emission also changes, generating a chlorophyll a fluorescence response that has previously been thought to be unique based on a toxicants mode of action. The toxin-identification method was developed as a bioanalytical system based on the chlorophyll a fluorescence responses of a microalgae (Dunaliella tertiolecta) to herbicide and nutrient impacts, measured using the Imaging-PAM fluorometer. The analysis of the fluorescence response was the novel method; a holistic approach was employed. Unlike previous approaches which measured one fluorescence parameter for toxicant identification, the method presented here assessed the temporal unity of change in energy dissipation, which was found to be unique depending on a chemical ' s mode of action (i.e. its physico-chemical properties and toxicokinetic relationship with the organism). The method was tested for two different uses: (1) as a non-specific biosensor able to identify herbicides (and their potency) in a water sample of unknown constituents, and (2) a method specific to the identification and potency of nutrients in a water sample. Seven herbicides were examined totaling three different MoAs; PSII inhibitors (DCMU, Irgarol, Bromacil and Simazine), uncoupling of phosphorylation (Dinoseb and PCP) and creation of reactive oxygen species (paraquat). By first generating a database of reference response patterns, the response patterns of laboratory derived test samples were then measured and quantitatively compared to the reference patterns. The unknown or test sample was compared to reference toxicants using a mean-square fit (MSF) software program. The MSF program tells the user how well the fingerprint of the test sample fits to each of the fingerprints of the reference chemicals. The method showed 93% accuracy in correctly identifying six herbicides, with false negative identifications occurring for only two toxicants, simazine (8% of samples) and Dinoseb (27% of samples). Phosphate induced fluorescence transients were also assessed to demonstrate that the toxin-identification method was versatile in its ability to also be used as a selective biomarker. By culturing P-limited D. tertiolecta cells, a unique fluorescence response was recorded upon additions of PO₄³⁻. The NIFT (nutrient induced fluorescent transient) response was specific to PO₄³⁻ additions compared to NH₄³⁺ and NO²⁻ additions. Quantification of the NIFT response showed high levels of precision and specificity for multiple fluorescence parameters. The toxin-identification method presented here is still in its preliminary stages and higher levels of validation are still necessary including testing environmental samples, and comparing results from the toxin-identification method to results from chemical analysis. However, this thesis presents the foundational work of a unique and powerful bioanalytical tool with the potential to greatly improve water quality management practices.
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