| dc.description.abstract | Over the past decade, developing affordable home-based tests to diagnose infectious diseases has become a pressing need. The lateral flow immunoassay (LFIA) is the most successfully commercialized point-of-care immunoassay. However, it suffers from poor sensitivity compared to conventional laboratory techniques such as enzyme-linked immunosorbent assay (ELISA). Consequently, traditional LFIAs fail to deliver on the promise of bedside diagnostic testing for many applications. Paper-based microfluidic devices provide an alternative platform for performing molecular diagnosis at a low cost and have become popular for their simplicity.
My research aimed to develop a portable paper-based signal-enhanced immunoassay device that satisfies WHO’s ASSURED (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free and deliverable to end-users) criteria. Using the malarial antigen, PfHRP2, as a model analyte, we developed a gold nanoparticle-based LFIA to determine a baseline limit of detection (LOD). To improve upon the baseline LOD, we ported the ELISA assay into a paper microfluidic device using HRP and poly-HRP enzymes. In addition, we also explored the gold-based enhancement of the signal generated in gold nanoparticle-based LFIAs. Finally, we compared all the colorimetric signal enhancement techniques. While we observed a 4-fold improvement in LOD using the gold enhancement technique, the HRP and the poly-HRP based enhancement did not improve the LOD as expected. This was contrary to the popular belief that enzyme-based signal amplification would produce an improved LOD compared to gold nanoparticle-based LFIAs (despite the fact that a direct comparison was never performed). Using time-lapse imaging, we elucidated that the poor sensitivity in the paper-based ELISA platform is because of the kinetic limitations of the enzymatic amplification system. Finally, we built a 3D printed device housing Arduino-controlled electromagnets to automate the multiple steps of signal-enhanced immunoassays, with the goal of making the device POC-compatible.
In a related area of research, we addressed the ‘hook effect’ in LFIAs. Analyte quantification in a sandwich LFIA is limited by the ‘hook effect’, according to which test line signal intensities reduce with increasing analyte concentration beyond a threshold analyte concentration. Using human chorionic gonadotropin (hCG) as a model analyte, we developed a transport-reaction model to understand the effect of analyte concentration on the kinetics of signal generation at the test and control lines. Guided by the model, we developed a method to expand the dynamic range of unmodified commercial LFIAs. The method involves time-lapse imaging of LFIA strips using a smartphone app and fitting the ratio of intensities at the test and control line (T/C ratio) to empirical equations. The fitting parameters thus obtained are calibrated against the analyte concentration. The dynamic range for the detection of human chorionic gonadotropin (hCG) of an unmodified commercially available pregnancy strip was expanded to 3 orders of magnitude (0.5–500 IU/mL), compared to ~2 orders of magnitude (0.5–40 IU/mL) achieved by end-point detection. Given the ubiquity of smartphones, this new quantitative method promises to significantly enhance the utility of LFIAs in point-of-care diagnostics.
Overall, using paper microfluidics and computational tools, we attempted to improve the sensitivity and the dynamic range of point-of-care immunoassays. | en_US |
