Biosensor-based Methods for Detection of Microcystins as Early Warning Systems
Abstract: Cyanobacteria blooms are a water menace since they produce potent toxins that have been implicated in poisonings and deaths of humans and animals after consumption or contact with cyanotoxin-contaminated water. Of particular concern are cyanotoxins called microcystins, which are hepatotoxic cyclic peptides known to promote development of liver tumors in humans and animals. The high toxicity and increased occurrence of microcystins in drinking and surface waters have stimulated worldwide investigations and prompted the design of analytical techniques for the early stages of detection in order to protect human exposure to these fatal toxins. The major challenge for the accurate determination of microcystins is the large number of naturally occurring variants. To date, there are more than 80 different microcystin variants, and depending on the substituted amino acids in the structure, the hydrophobicity varies making it difficult for a single assay determination. Another problem is the low concentrations of individual toxins, which often are below the detection limits of existing assays. In order to achieve low concentrations detection, there is a need for a sensitive assay platform that gives a fast, quantitative determination of the microcystins below the stipulated limit. Regulations set for the monitoring of allowable microcystins levels in water are also becoming more stringent for water authorities to meet. Also, the predication of the algal blooming patterns becomes increasingly complicated. Of recent, algal blooms have shown to appear unexpectedly or come as late blooms due to changing weather patterns. Increased awareness of microcystin intoxications to the public that relies on surface waters has led to the World Health Organization (WHO) setting a guideline with a concentration limit for microcystins in drinking water of 1µg/L (10-9 M). Since these toxins are not efficiently removed during the conventional water treatment process, emphasis on alternative analytical methods are indeed required the protection of drinking water supplies. In addition, the detection of cyanotoxins at very low concentrations is necessary for making a rapid intervention before the toxin concentrations reach harmful levels. In this thesis work, biosensor-based methods for ultra-sensitive detection of microcystins have been developed. Different biosensor configurations were investigated where the first study involved the development of a capacitive immunoassay using specific antibodies able to recognize a special part in microcystin structure called 3-amino-9-methoxy-2,6,8-trymethyl-10-phenyldeca-4,6-dienoic acid (Adda). The study showed that microcystins could be detected at very low concentrations (down to 10-14 moles per liter) within 37 minutes. The developed biosensor was further applied for total analysis of microcystins produced in a batch culture of microcystin, aided by mass spectrometry to identify the different microcystin variants. A flow-ELISA-amperometric biosensor was also developed and investigated and showed an apparent rapid assay of 16 minutes (limit of detection 10-11 M). Finally, a micro-contact based molecularly imprinted polymer technique was explored as a cost-effective alternative for the expensive antibodies as ligands in the capacitive biosensor assay. In all cases, the developed biosensors showed both high selectivity and sensitivity and met the allowable detection limit set by WHO. In conclusion, the studies presented in this thesis demonstrated that low toxin determination with minimal sample preparation can be achieved using the investigated biosensor technology, and that miniaturization of the system can allow for portability and can be helpful for in situ monitoring of microcystins where sophisticated infrastructure is lacking. Also, the studies emphasize the need for more development of biorecognition molecules that will be able to monitor the group of microcystins at the same sensitivity while being able to discriminate against other non-related molecules. Automated and integrated system configurations used in all the experiments facilitated the analysis process by decreasing time and eliminating possible manual sampling handling errors.
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