Low-Cost, Flexible Protein Detection Platform for Global Health

Chemical and biomolecular engineers at Georgia Tech have developed a plug-and-play platform for detecting disease-related protein biomarkers. This system is designed to be simple, adaptable, and user-friendly, eliminating the need for costly laboratory equipment.

This innovation has the potential to usher in a new era of at-home diagnostic testing and improve healthcare accessibility in resource-limited regions.

The platform addresses a significant gap in the use of cell-free synthetic biology for disease detection. While existing cell-free tools have been effective in measuring DNA, RNA, and small molecules, they have not been successful in detecting proteins—until now.

This breakthrough is critical because proteins in viruses or bacteria tend to be more stable and less variable than the DNA or RNA sequences that encode them. Additionally, proteins are often easier to detect, as they can be found on cell surfaces or freely circulating in biofluids.

"Diagnosing disease and making medical care more accessible has the potential to create a major impact. I often think about its implications for the developing world, but also within the U.S., where healthcare inequality is a real issue. Studies show that ZIP codes can determine life expectancy. People in sub-Saharan Africa and rural Appalachia alike could benefit from increased access to low-cost diagnostic tools," said Mark Styczynski, William R. McLain Endowed Professor at Georgia Tech.

Styczynski, along with a team led by former Ph.D. student Megan McSweeney, introduced this testing method in late February in Science Advances. They describe it as a modular, cell-free protein biosensor platform. "Cell-free" refers to utilizing cellular components engineered in the lab rather than within living cells, while "modular" highlights the ease with which the platform can be adapted to detect different proteins.

The test provides results either as a visual color change, similar to a swimming pool pH test strip, or as precise data for clinical and research applications.

"Flexibility was a top priority because we know how valuable that is to synthetic biologists and engineers developing biosensors, particularly for proteins. The level of adaptability we achieved is remarkable," said McSweeney, now a postdoctoral scholar at Stanford University.

In their study, the team successfully detected a malnutrition biomarker and a protein from SARS-CoV-2, demonstrating the platform’s broad potential. The test performed effectively in pooled human blood serum and saliva, and researchers believe it will be applicable to a wide range of biofluids.

"It can take years and millions of dollars to develop a single lateral flow test, like the at-home COVID-19 test. What makes our platform so powerful is that swapping the target protein is as simple as changing a few ingredients—without reengineering the entire system," Styczynski explained.

The researchers leveraged RNA polymerases, enzymes that control gene activity, attaching segments of these polymerases to basic antibodies designed to bind specific proteins. When the antibodies successfully bind to their target, the polymerase segments connect, triggering an enzyme that produces a visible color change.

Depending on the concentration of the target protein, the color shift ranges from yellow to deep purple. In laboratory settings, the test can also produce fluorescent readouts for more detailed analysis.

"We designed this technology to be versatile—usable both by individuals with advanced lab equipment and those with limited resources. The platform's flexibility could enhance testing efficiency, consistency, and data quality across different settings," McSweeney noted.

The test’s modularity also makes it valuable for emergency response and military applications. Styczynski suggested it could serve as a field kit, allowing minimally trained technicians to mix test components on-site to detect pathogens or biomarkers. The kit would include raw materials and a set of customizable "recipes."

Alongside former Georgia Tech Ph.D. student Monica McNerney, McSweeney and Styczynski have applied for a patent for their approach. Their research team also included Ph.D. students Alexandra Patterson and Kathryn Loeffler, undergraduate researcher Regina Cuella Lelo de Larrea, and Garry Betty/V Foundation Chair and Professor Ravi Kane.

Moving forward, the researchers aim to refine the tool to detect even lower protein concentrations and improve ease of use. Preliminary findings suggest the test remains functional after lyophilization, which would eliminate the need for refrigeration. However, further work is needed to ensure long-term stability under real-world conditions.