Karly Liebendorfer
BioE PhD Proposal Presentation
Tuesday, September 8th, 2026, at 2:00 pm
Location: EBB 5029
Advisor:
Dr. Mark Styczynski, School of Chemical and Biomolecular Engineering
Committee Members:
Dr. John Blazeck, School of Chemical & Biomolecular Engineering
Dr. Julie Champion, School of Chemical & Biomolecular Engineering
Dr. Brian Hammer, School of Biological Sciences
Dr. Tara Deans, Wallace H. Coulter Department of Biomedical Engineering
Engineering Cell-Free Biosensors for Membrane Protein Detection at the Point of Care
Membrane proteins regulate essential cellular processes and serve as valuable biomarkers for disease diagnosis, progression, and therapeutic response. However, quantitative measurement of membrane-associated biomarkers remains largely dependent on techniques such as flow cytometry, microscopy, and extraction-based protein analysis, limiting their use outside specialized laboratories. Point-of-care biosensors offer a promising alternative because they are programmable, inexpensive, and compatible with decentralized testing, yet existing platforms have primarily focused on soluble analytes and have not been adapted for membrane protein detection. The T7 RNA Polymerase-Linked ImmunoSensing Assay (TLISA) is a cell-free analyte sensing platform that converts target recognition into a transcriptionally amplified output, providing a promising foundation for addressing this unmet need. Thus, the work proposed for this thesis will focus on expanding TLISA into a quantitative platform for membrane protein detection to support point-of-care applications in low resource environments such as human space travel. To achieve this, I will first identify and address mechanistic limitations in the current assay design to improve signal fidelity, analytical sensitivity, and limit of detection. In parallel, I will develop a proof-of-concept system for membrane protein detection by displaying model proteins on the Escherichia coli cell surface and evaluating their detection and quantification using TLISA. The optimized platform will then be applied to the epidermal growth factor receptor, a disease-associated membrane biomarker, and evaluated in biologically complex matrices. Together, my work will establish the feasibility of TLISA-based membrane protein quantification and support the development of accessible point-of-care diagnostics for clinically relevant membrane proteins.