Yelleswarapu, Venkata Ravitheja
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PublicationMiniaturizing High Throughput Droplet Assays For Ultrasensitive Molecular Detection On A Portable Platform(2019-01-01) Yelleswarapu, Venkata RavithejaDigital droplet assays – in which biological samples are compartmentalized into millions of femtoliter-volume droplets and interrogated individually – have generated enormous enthusiasm for their ability to detect biomarkers with single-molecule sensitivity. These assays have untapped potential for point-of-care diagnostics but are mainly confined to laboratory settings due to the instrumentation necessary to serially generate, control, and measure millions of compartments. To address this challenge, we developed an optofluidic platform that miniaturizes digital assays into a mobile format by parallelizing their operation. This technology has three key innovations: 1. the integration and parallel operation of hundred droplet generators onto a single chip that operates >100x faster than a single droplet generator. 2. the fluorescence detection of droplets at >100x faster than conventional in-flow detection using time-domain encoded mobile-phone imaging, and 3. the integration of on-chip delay lines and sample processing to allow serum-to-answer device operation. By using this time-domain modulation with cloud computing, we overcome the low framerate of digital imaging, and achieve throughputs of one million droplets per second. To demonstrate the power of this approach, we performed a duplex digital enzyme-linked immunosorbent assay (ELISA) in serum to show a 1000x improvement over standard ELISA and matching that of the existing laboratory-based gold standard digital ELISA system. This work has broad potential for ultrasensitive, highly multiplexed detection, in a mobile format. Building on our initial demonstration, we explored the following: (i) we demonstrated that the platform can be extended to >100x multiplexing by using time-domain encoded light sources to detect color-coded beads that each correspond to a unique assay, (ii) we demonstrated that the platform can be extended to the detection of nucleic acid by implementing polymerase chain reaction, and (iii) we demonstrated that sensitivity can be improved with a nanoparticle-enhanced ELISA. Clinical applications can be expanded to measure numerous biomarkers simultaneously such as surface markers, proteins, and nucleic acids. Ultimately, by building a robust device, suitable for low-cost implementation with ultrasensitive capabilities, this platform can be used as a tool to quantify numerous medical conditions and help physicians choose optimal treatment strategies to enable personalized medicine in a cost-effective manner.