Dissertation Defense: Zhen Xiong "High-Speed Lens-Free Holographic Microscopy for Quantitative Large-Area Binding Sensors"

    Friday, August 7, 2020 - 9:00am - 12:00pm

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    The ongoing COVID-19 pandemic reminds us of the importance of biosensors. Accurate measurements of protein biomarker levels are important for disease diagnostics. Cost-effective, easy-to-use, field-portable, and sensitive point-of-care sensors could provide faster, cheaper, and/or more accurate measurements than existing methods.

    Lens-free holographic microscopy (LFHM) offers submicron resolution over an ultra-large field-of-view >20 mm2 with simple hardware, making it a great candidate for biosensing applications. However, there are a few challenges in applying LFHM to current sensing tasks. Firstly, we investigate the performance of various pixel super-resolution and regularized optimization algorithms for small-target sensing in LFHM. We find that a novel sparsity-promoting regularization algorithm enhances the signal to noise ratio (SNR) by ~8 dB compared to the other methods when imaging micron-scale beads with surface coverages up to ~4%. Secondly, we create a LFHM device based on a high-speed and high-power LED array to image >104 2-μm microsphere beads undergoing Brownian motion in solution. These beads are coated with biological capture agents, causing them to bind together in the presence of a specific target protein molecule. Automated image processing routines enable the counting of individual beads and clusters, providing a quantitative sensor readout that depends on both bead and analyte concentration. We call this system a quantitative large-area binding (QLAB) sensor.

    Here, we sense interferon-gamma (an immune system biomarker) and NeutrAvidin (a common biosensor benchmark). Fits to chemical binding theory are provided. For NeutrAvidin, we find a limit of detection (LOD) of <27 ng/mL (450 pM) and a dynamic range of 2-4 orders of magnitude. For mouse interferon-gamma, the LOD is <3 ng/mL (200 pM) and the dynamic range is at least 4 orders of magnitude. The QLAB sensor holds promise for point-of-care applications in low-resource communities and where protocol simplicity is important.​