Nonspecific DNA Sensors for Scalable Pathogen Diagnostics

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The rapid identification of pathogens is essential for clinical diagnostics and biodefense. Given timely information, clinicians can prescribe better treatments and slow the rise of drug resistant bacteria, and U.S. biosurveillance efforts can track the emergence and spread of both existing and newly evolved pathogens. While most rapid diagnostic tests have sensors that are each specialized to detect only one kind of pathogen, this research effort is developing new DNA sensing techniques to efficiently detect large numbers of pathogens with just a few sensors. By minimizing the number of necessary sensors, new pathogen surveillance devices could be portable and inexpensive for routine use. The technology additionally provides an approach to detecting emerging novel pathogens without the need to create and deploy new test kits. In addition to furthering development of new pathogen identification technologies, the project develops a hands-on experimental module exploring this methodology and implements it in a biosensing and imaging course serving undergraduate and graduate engineering students at Rice University. This research effort applies compressed sensing which allows just a few DNA probes to (1) give each species a fingerprint response and (2) unmix these fingerprint signals when a few pathogens are in the same sample. Compressed sensing assumes that the sample is sparse. Sparsity occurs because although there may be dozens or hundreds of possible species to account for, any single sample from a patient or the environment will have only a few pathogens of interest for relevant applications. For pathogen detection, DNA probes each bind multiple times to microbial species. The number of binding events between a few probes and the microbes gives each of hundreds of species a “fingerprint” response, much like how 10 digits can give everyone in the U.S. a unique phone number. The first aim of this project is to develop a new DNA signal amplification technique that allows fewer binding events to be detectable. This amplification strategy also lets signals be positive or negative, effectively allowing fingerprint signals to spread further apart. The enhanced incoherence of the sensors is known to be very helpful for compressed sensing. The second aim is to use new technologies in microfluidics to capture individual pathogen cells in very small droplets and acquire fingerprint signals from each droplet separately. By analyzing every droplet, this project pushes towards single-cell resolution which would enable its broader application in any task that demands the characterization of unknown microbes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.