Chemist Receives $1.95M for Research on AI-Powered Pathogen Detection, Precision Therapeutics

A man with dark hair and a gray blazer and glasses speaks animatedly in a brightly lit classroom.
MIRA recipient Mehmet Yigit, associate professor in the Department of Chemistry and the RNA Institute. (Photo by Patrick Dodson)

By Erin Frick

ALBANY, N.Y. (Feb. 27, 2025)—University at Albany’s Mehmet Yigit, associate professor in the Department of Chemistry and the RNA Institute at the College of Arts and Sciences, has received $1.95 million from the National Institute of General Medical Sciences, part of the National Institutes of Health, to advance his transdisciplinary research program focused on AI-powered biosensing and precision therapeutics. 

Yigit’s work leverages DNA and RNA nanotechnology, together with synthetic biology, to develop biomedical technologies with applications ranging from fast-acting pathogen detection in food products to differentiating diseased tissues from healthy ones using precision nanosensor arrays.

This new funding takes the form of a "Maximizing Investigators' Research Award," a special type of grant designed to support the full scope of the grantee’s research program, rather than one specific project. The award is a testament to the Yigit lab’s scientific rigor and record of developing promising biomedical techniques.

"My lab’s work is truly interdisciplinary, integrating chemistry, nanotechnology, biology, and advanced computational methodologies—essential for advancing biomedical tools, from disease detection to targeted drug delivery," said Yigit. "We are also contributing to the momentum in precision medicine, which is accelerating with advances in AI, machine learning, and RNA science, while uniting expertise across scientific fields. The technologies that my team and I are developing have applications ranging from public health to targeted therapeutics, and this award will propel each avenue forward."

Yigit directs several distinct research tracks that will benefit from this funding. These existing projects include:

  • Developing highly sensitive, paper-based detection methods to test for pathogens that threaten health, including common foodborne bacteria and human viruses
  • Strengthening the technology underpinning DNA nanoreceptor arrays for tissue analysis and for detecting dysregulations of biomarkers in human diseases
  • Advancing a new tool for drug delivery that employs a "DNA hydrogel" casing, which releases its contents upon encountering a specific biological target 

Paper-based pathogen detection

Being able to quickly detect pathogens is critical to containing viruses and harmful bacteria that make people sick. Yigit’s method employs a series of chemical reactions triggered by a target DNA or RNA which yield a visible positive or negative result, indicated by a color change on a paper test strip, similar to the types of tests used to detect COVID.

"We have already developed this technology to quickly detect salmonella," Yigit said. "We are now looking to expand the technology to detect other common foodborne bacterial pathogens like listeria and campylobacter, as well as human viruses such as West Nile, Zika, Dengue and Ebola."

The method is uniquely sensitive and is designed to yield results faster than other similar tests. For example, the team’s salmonella test only takes several hours to complete, whereas conventional microbial culturing methods take days. Reducing the time it takes to determine whether a sample contains a harmful pathogen can allow for faster containment and fewer people affected. 

The team also aims to develop data interpretation methods that can analyze photos captured with a phone camera. Using machine learning techniques, this proposed companion technology will analyze visual data from the paper tests to help users interpret their results. 

Machine learning and DNA nanotech for tissue analysis

In diseased tissues, the balance of metabolites, RNAs and proteins differs from that of healthy tissues. Rather than focusing on a single biological marker, which may be challenging to identify, analyzing a comprehensive panel of metabolic changes and RNA/protein expression provides a more accurate and informative assessment of disease states.

Yigit’s team is developing a diagnostic technology that uses nanoscale sensors to create a unique "fluorescence fingerprint" based on these changes. This fingerprint can help distinguish diseased tissues from healthy ones using tissue biopsies or body fluids. The team has demonstrated this approach in breast cancer cell analysis and plans to expand it to other diseases, including Alzheimer’s disease and other cancer types.

Drug delivery via DNA hydrogels

The third research track focuses on developing a new form of highly targeted drug delivery. The method employs a DNA hydrogel casing which degrades when it encounters a specific disease biomarker or a pathogen, releasing the drug at the desired site in the body. In addition to small molecule drugs, the DNA hydrogel could contain therapeutic RNAs or even imaging agents to be used for diagnosing disease. 

"Over the coming years, we are excited to advance these biotechnologies to inform new tools for pathogen and disease detection, as well as precision therapeutics," Yigit said. "Together, these methods are poised to address challenges that extend beyond the model systems. We hope these developments will generate knowledge and tools that will benefit the broader scientific community."