Doctor of Philosophy (PhD)
Early diagnosis and the monitoring of diseases and infections is a crucial medical practice to avoid aggressive and malignant disease progression and to preserve the quality of health. However, difficulties exist for the patient to access these diagnostics, including lack of existing testing for certain ailments, tests with high-cost or not covered by insurance, inconvenience in frequent monitoring, and lack of testing access. Fortunately, these issues can be remedied by combining the low-cost and accessible nature of synthetic biology with the variety of illness detection and easy access of the microRNA biomarker. MicroRNA detection is still in its infancy, however, many of the current conventional and non-conventional sensing techniques either suffer from high costs or inaccuracies and unreliable data due to the way they purify the microRNA from the RISC complex, losing its native state and function. This dissertation describes a novel low-cost technology allowing gentle purification of miRNA retained in its protein complex, the RISC, from extracellular vesicles found in liquid biopsies, and a cell-based environment to allow it to perform as it would in its native state, retaining accuracy sculpted through evolution. Using the cell-free system, a complex genetic circuit was created to amplify the signal after the sensing module, retaining the accuracy of detection while increasing the signal to reach close to clinically relevant levels of miRNA detection. The cell-free system itself was also optimized for low-limit biosensing purposes. A housing device for the cell-free sensing reaction was designed and tested to extend the reaction time and decrease the limit of detection. With this research, early disease detection and personalized monitoring are possible, allowing the patient the option for gentle treatments and the preservation of quality of life throughout the aging process.
Copeland, Caroline Elizabeth, "The Design of a MicroRNA Sensor Using an Improved Cell-Free Protein Synthesis System for Low-Limit Biomarker Detection" (2023). LSU Doctoral Dissertations. 6127.
Available for download on Wednesday, April 03, 2030