Project Summary
The goal of the proposed work is to create a new synthetic biology-based platform for protein
diagnostics. The specific context motivating this challenge is the need to measure protein
biomarkers indicative of micronutrient deficiencies in a minimal-equipment fashion. Current
diagnostics for nutritional deficiencies are infeasible at the required population scale due to cost
and logistical constraints, and so a point-of-care, minimal-equipment, field-deployable approach
is needed to help nutritional epidemiologists get the information they need to better allocate limited
intervention resources. However, the impact of such a technology would go well beyond nutritional
epidemiology and diagnostics, as proteins are common biomarkers for many other diseases and
conditions. Thus, the same technology could be translated to global health applications and
screening for other diseases in resource-poor locations. In addition, it could also enable better
diagnostic monitoring for neonatal intensive care unit patients by overcoming limitations on daily
allowable blood draw volumes.
The use of a split protein reporter system coupled with a cell-free protein expression system is
proposed to accomplish this goal. In the presence of a specific protein, the split reporter system
reassembles and the reaction undergoes a colorimetric change. The entire approach requires
minimal to no equipment and would be inexpensive, making it perfectly suited for use in the low-
resource regions that are most prominently affected by nutritional deficiencies. There is strong
preliminary data supporting the likelihood of success for this approach. To achieve these goals,
three aims are proposed. First, the existing proof of principle sensor will be advanced with a model
protein target and the impact of sensor design choices on sensor functionality and performance
will be characterized. The second aim entails demonstrating the approach’s generalizability by
developing at least three sensors for clinically relevant proteins. The third aim involves advancing
the assay towards a truly field-deployable state by testing it for functionality in a human serum
matrix, implementing a calibration approach, demonstrating functionality after lyophilization, and
developing a companion smartphone app to support output interpretation.
This project will yield the underlying technology that can be used for the first-ever synthetic
biology-based, quantitative protein detection assay for low-resource settings. By being low-cost,
essentially point-of-care, and easily generalizable to other protein targets, such a long-term result
would potentially improve the health of millions of people worldwide.