Immunoassay-based disease diagnostics typically employ surface-immobilized immunoglobulins as affinity agents for the capture of disease-relevant biomarkers from patient samples. However, these antibodies are prone to thermal denaturation and nonspecific binding events that can render test results unreliable, and their use is governed by a complicated intellectual property landscape that can increase costs to the end user. These characteristics make antibodies non-ideal for incorporation into diagnostics intended for use in point-of-care contexts, where financial resources are limited and cold chain storage may not be feasible. In order to better address these needs, we are developing robust, minimalist, non-IgG affinity agents based on thermostable protein scaffolds, using yeast surface display and flow cytometric analysis. We are currently focusing on secreted infectious disease biomarkers found in peripheral fluid samples, but future efforts will also focus upon the development of binding molecules targeting pathogen-specific membrane proteins.
Eric A. Miller, Yara Jabbour Al Maalouf, Hadley D. Sikes. “Design principles for enhancing sensitivity in paper-based diagnostics via large-volume processing,” Analytical Chemistry, 2018. DOI: 10.1021/acs.analchem.8b02113.
Eric A. Miller, Subha Baniya, Daniel Osorio, Yara Jabbour Al Maalouf, and Hadley D. Sikes. “Paper-based diagnostics in the antigen-depletion regime: high density immobilization of rcSso7d-cellulose binding domain fusion proteins for efficient target capture,” Biosensors and Bioelectronics, 2018, 102: 456-463.
Eric A. Miller, Michael W. Traxylmeyer, Jacqueline Shen, and Hadley D. Sikes. “Activity-based assessment of an engineered hyperthermophilic protein as a capture agent in paper-based diagnostic tests,” Molecular Systems Design & Engineering, 2016, 1: 377-381. DOI: 10.1039/C6ME00032K.
Eric Miller and Hadley D. Sikes. “Addressing barriers to the development and adoption of rapid diagnostic tests in global health,” Nanobiomedicine, 2015, 2(6). DOI: 10.5772/61114.