Sub-picomolar lateral flow antigen detection with two-wavelength imaging of composite nanoparticles.

Lateral flow tests, commonly based on metal plasmonic nanoparticles, are rapid, robust, and low-cost. However, improvements in analytical sensitivity are required to allow detection of low-abundance biomarkers, for example detection of low antigen concentrations for earlier or asymptomatic diagnosis of infectious diseases. Efforts to improve sensitivity often require changes to the assay. Here, we developed optical methods to improve the sensitivity of absorption-based lateral flow tests, requiring no assay modifications to existing tests. We experimentally compared five different lock-in and subtraction-based methods, exploiting the narrow plasmonic peak of gold nanoparticles for background removal by imaging at different light wavelengths. A statistical framework and three fitting models were used to compare limits of detection, giving a 2.0-5.4-fold improvement. We then demonstrated the broad applicability of the method to an ultrasensitive assay, designing 530 nm composite nanoparticles to increase the particle volume, and therefore light absorption per particle, whilst retaining the plasmonic peak to allow background removal and without adding any assay steps. This multifaceted, modular approach gave a combined 58-fold improvement in the fundamental limit of detection using a biotin-avidin model over 50 nm gold nanoparticles with single-wavelength imaging. Applying to a sandwich assay for the detection of HIV capsid protein gave a limit of detection of 170 fM. Additionally, we developed an open-source software tool for performing the detection limit analysis used in this work.

Point-of-Care Serodiagnostic Test for Early-Stage Lyme Disease Using a Multiplexed Paper-Based Immunoassay and Machine Learning.

Caused by the tick-borne spirochete Borrelia burgdorferi, Lyme disease (LD) is the most common vector-borne infectious disease in North America and Europe. Though timely diagnosis and treatment are effective in preventing disease progression, current tests are insensitive in early stage LD, with a sensitivity of <50%. Additionally, the serological testing currently recommended by the U.S. Center for Disease Control has high costs (>$400/test) and extended sample-to-answer timelines (>24 h). To address these challenges, we created a cost-effective and rapid point-of-care (POC) test for early-stage LD that assays for antibodies specific to seven Borrelia antigens and a synthetic peptide in a paper-based multiplexed vertical flow assay (xVFA). We trained a deep-learning-based diagnostic algorithm to select an optimal subset of antigen/peptide targets and then blindly tested our xVFA using human samples (N(+) = 42, N(-) = 54), achieving an area-under-the-curve (AUC), sensitivity, and specificity of 0.950, 90.5%, and 87.0%, respectively, outperforming previous LD POC tests. With batch-specific standardization and threshold tuning, the specificity of our blind-testing performance improved to 96.3%, with an AUC and sensitivity of 0.963 and 85.7%, respectively.

Paper-based multiplexed vertical flow assay for point-of-care testing.

We developed a multiplexed point-of-care immunodiagnostic assay for antibody detection in human sera made through the vertical stacking of functional paper layers. In this multiplexed vertical flow immunodiagnostic assay (xVFA), a colorimetric signal is generated by gold nanoparticles captured on a spatially-multiplexed sensing membrane containing specific antigens. The assay is completed in 20 minutes, following which the sensing membrane is imaged by a cost-effective mobile-phone reader. The images are sent to a server, where the results are rapidly analyzed and relayed back to the user. The performance of the assay was evaluated by measuring Lyme-specific antibodies in human sera as model target antibodies. The presented platform is rapid, simple, inexpensive, and allows for simultaneous and quantitative measurement of multiple antibodies and/or antigens making it a suitable point-of-care platform for disease diagnostics.

Lensfree holographic imaging for on-chip cytometry and diagnostics.

We experimentally illustrate a lensfree holographic imaging platform to perform on-chip cytometry. By controlling the spatial coherence of the illumination source, we record a 2D holographic diffraction pattern of each cell or micro-particle on a chip using a high resolution sensor array that has approximately 2 microm pixel size. The recorded holographic image is then processed by using a custom developed decision algorithm for matching the detected hologram texture to existing library images for on-chip characterization and counting of a heterogeneous solution of interest. The holographic diffraction signature of any microscopic object is significantly different from the classical diffraction pattern of the same object. It improves the signal to noise ratio and the signature uniformity of the cell patterns; and also exhibits much better sensitivity for on-chip imaging of weakly scattering phase objects such as small bacteria or cells. We verify significantly improved performance of this holographic on-chip cytometry approach by automatically characterizing heterogeneous solutions of red blood cells, yeast cells, E. coli and various sized micro-particles without the use of any lenses or microscope objectives. This lensless on-chip holography platform will especially be useful for point-of-care cytometry and diagnostics applications involving e.g., infectious diseases such as HIV or malaria.