Novel split trehalase-based biosensors for the detection of biomarkers of infectious diseases
Date
2019-05-15
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Abstract
Infectious diseases remain a serious public health challenge in the field of human and veterinary medicine. For instance, infectious diseases were among the leading causes of mortality worldwide in 2016 according to the WHO. In veterinary medicine, infectious diseases have a significant negative impact on animal productivity and welfare leading to decreased profits and increased health-associated costs. Furthermore, the WHO estimates that 61% of diseases affecting the human population are zoonotic. Therefore, programs to control and eradicate these diseases are of crucial importance. Correct diagnosis, supported by robust diagnostic tests, is an essential first step in achieving these goals. An ideal diagnostic test needs to be accurate and robust while being easily accessible and widely-available. Although different studies over the years have aimed to develop such a diagnostic test, there have not been many that have managed to enter into clinical practice. The most successful class of biosensors currently on the market is the glucometer used to monitor blood glucose. Glucometer's sensitivity and specificity, as well as its performance in clinical samples, have been mainly perfected. Measuring devices have been miniaturized and their production costs optimized. In this thesis, we developed and characterized a novel biosensor able to detect antibodies and other infectious disease markers. The biosensor is based on the protein complementation principle and uses an E. coli glycolytic enzyme, trehalase (TreA), as a reporter. Trehalase converts trehalose to glucose, which can then be detected by a glucometer. TreA was split into two non-functional fragments, and each fragment was fused to the sensing element that was specific for the targeted analyte. In the presence of the analyte, the sensing elements bind to it and induce the dimerization of the TreA which then becomes active. In the second chapter, we demonstrated that conditional complementation of the trehalase fragments leading to trehalose hydrolysis and glucose production could be used to detect antibodies, bacterial cells, small molecule, protein-protein interaction, and protein aggregation. We also demonstrated the retention of activity of split TreA in undiluted clinical samples like blood or milk. In the third chapter, we attempted to increase the sensitivity and shorten the time for signal detection of the TreA biosensor by introducing split inteins. We placed the inteins within the previously developed biosensor, but we were not successful in achieving analyte-mediated dimerization of the two biosensor components. In the fourth chapter, we applied this TreA biosensor to develop and validate a new diagnostic tool for the quantification of the total amount of immunoglobulins in bovine colostrum and serum (named STIGA). We demonstrated that STIGA performs more efficiently in quantifying total immunoglobulins in colostrum and calf serum than other diagnostic tools (Colostrometer and Brix) that are used on a farm. Therefore, it is a suitable detection assay to establish colostrum quality and calf immune status in the field. We also proposed a modified format of STIGA for this on-farm application and demonstrated that its performance remained high. In the fifth chapter, we explored the applicability of a modified STIGA with the anticipation to detect immunoglobulins in different animal species. We analyzed 29 animal species and proved that the same detection protocol could be applied with success to the majority of animal species. In conclusion, we engineered a trehalase-based biosensor that requires minimal sample preparation and can be integrated with existing glucometers or sensors, which offers a versatile and convenient method for point-of-care applications.
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Keywords
trehalase-based biosensor, genetic engineering, diagnostics
Citation
Drikic, M. (2019). Novel split trehalase-based biosensors for the detection of biomarkers of infectious diseases (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.