Dr. Mark Styczynski (Georgia Institute of Technology, Chemical & Biomolecular Engineering)
Dr. Andreas Bommarius (Georgia Institute of Technology, Chemical & Biomolecular Engineering)
Dr. Brian Hammer (Georgia Institute of Technology, Biology)
Dr. Hang Lu (Georgia Institute of Technology, Chemical & Biomolecular Engineering)
Dr. Pamela Peralta-Yahya (Georgia Institute of Technology, Chemistry & Biochemistry)
Biosensor development for field-deployable diagnostics
Almost all current tests for biomarkers require venous blood draws, extensive sample processing, and analysis with complex equipment. Inexpensive, easy-to-use tests are critical for expanding healthcare to under-developed regions, but the requirement for reliable quantification in complex sample types (like blood) has been a critical roadblock in developing such diagnostics. Microbial-based biosensors have the potential to serve as a robust and generalizable platform for such diagnostics, as microbes can sense a wide variety of clinically relevant analytes and can produce colored outputs that are visible to the naked eye. Further, cell-free systems, which use bacterial protein extract to implement genetic networks, can be freeze-dried and rehydrated in the sample to be analyzed, enabling long-term storage at ambient temperatures and point-of-care test implementation and interpretation. This work describes the development of bacteria-based diagnostic assays that use bacterial sensing methods to control production of different colored readouts that are visible to the naked eye, yet quantitative and robust to the interference effects seen in complex samples. Using this platform, I develop a nearly field-deployable test for zinc deficiency (which is estimated to cause over 100,000 childhood deaths annually) that accurately measures clinically relevant zinc concentrations. The test requires just a finger-prick of blood, is robust to temperature variation, and can be freeze-dried for long term storage. I also use this approach to measure other classes of biomarkers, demonstrating a generalizable platform for low-cost quantitative diagnostics.