Intelligent biosensing system for automated real-time monitoring of airborne pathogens for safe indoor environments - PROJECT SUMMARY The increasing frequency of respiratory infectious diseases, such as influenza and COVID-19, which can spread rapidly and lead to severe outbreaks, necessitates that we re-envision our approaches to monitor pathogen exposures in the indoor environments. Current surveillance methods mostly depend on syndromic data from hospital admissions, clinic visits, and school absenteeism rates. However, these approaches can lead to underestimation and delay in disease surveillance due to no reporting of mild or asymptomatic cases, lack of access to healthcare, and time-consuming lab and diagnostic processes. A proactive approach in combating airborne diseases requires early detection of target pathogens. Here, we propose to innovate an intelligent system capable of real-time, efficient, and cost-effective monitoring of airborne pathogens in the environment. We will build upon our preliminary success in automated bioaerosol sampling and pathogen detection, to create an Airborne Pathogen Sensing (APS) system. This goal will be achieved by focusing on two specific aims. First, we will create a novel class of modular whole-cell biosensors for sensitive, rapid, and robust detection of multiple critical airborne pathogens. The pathogen detection will be achieved by creating quenchbody (Q-body) display biosensors, where target specific quenchbody is expressed and displayed on the surface of microbial host cells. When the Q-body binds to its antigen (target pathogen), the fluorescence intensity substantially increases via the antigen-dependent removal of the quenching effect on the fluorophore. Second, we will design and build a portable and automated bioaerosol sampling device that can be coupled to the biosensing and signal detection systems. To this end, we will evaluate and optimize two sampling devices: mist chamber and biosampler, and choose the device with the highest bioaerosol capture efficiency. Finally, we will integrate the biosensing component with the bioaerosol sampling device and an automated flow-through fluorescence detection system to achieve automated real-time monitoring of airborne pathogens.
