Functional comparison of paper-based immunoassays based on antibodies and engineered binding proteins

Significance of the antibody orientation for the lateral flow immunoassays: A mini-review

Lateral flow immunoassays (LFIAs) are well-established and broadly commercialized tools in the field of point-of-care testing due to their simplicity, rapidity, cost-effectiveness, and low requirements for users and equipment. However, the insensitivity and the possibility of producing inaccurate results associated with conventional LFIAs have impeded their wide-ranging implementation, especially for monitoring ultra-trace level of analytes. Moreover, the heterogeneous distribution of amino acids on the surface of antibody (Ab) results in a lack of precise control over their orientation, which ultimately leads to unsatisfactory detection performance. To address those concerns, herein we provide an overview of the emerging efforts to prepare well-established LFIAs from the perspective of orientation manipulation of immobilized Abs on the nanoprobes or membranes. The preparation of excellent nanoprobes with Abs being oriented immobilized, consisting of the nanoprobe types, Ab types, and their conjugation chemistries, are reviewed. Followed by the introduction of efforts highlight the importance of directionally immobilized Ab on the membrane. The effects of Ab orientation on the analytical performance of LFIA platforms in terms of sensitivity, specificity, rapidity, reliability, cost-effectiveness, and stability are also summarized. Finally, the future development and challenges of Ab-oriented immobilization-assisted LFIAs are also discussed.

Accelerating the optimization of vertical flow assay performance guided by a rational systematic model-based approach

Rapid diagnostic tests (RDTs) have shown to be instrumental in healthcare and disease control. However, they have been plagued by many inefficiencies in the laborious empirical development and optimization process for the attainment of clinically relevant sensitivity. While various studies have sought to model paper-based RDTs, most have relied on continuum-based models that are not necessarily applicable to all operation regimes, and have solely focused on predicting the specific interactions between the antigen and binders. It is also unclear how the model predictions may be utilized for optimizing assay performance. Here, we propose a streamlined and simplified model-based framework, only relying on calibration with a minimal experimental dataset, for the acceleration of assay optimization. We show that our models are capable of recapitulating experimental data across different formats and antigen-binder-matrix combinations. By predicting signals due to both specific and background interactions, our facile approach enables the estimation of several pertinent assay performance metrics such as limit-of-detection, sensitivity, signal-to-noise ratio and difference. We believe that our proposed workflow would be a valuable addition to the toolset of any assay developer, regardless of the amount of resources they have in their arsenal, and aid assay optimization at any stage in their assay development process.

Automated liquid handling robot for rapid lateral flow assay development

The lateral flow assay (LFA) is one of the most popular technologies on the point-of-care diagnostics market due to its low cost and ease of use, with applications ranging from pregnancy to environmental toxins to infectious disease. While the use of these tests is relatively straightforward, significant development time and effort are required to create tests that are both sensitive and specific. Workflows to guide the LFA development process exist but moving from target selection to an LFA that is ready for field testing can be labor intensive, resource heavy, and time consuming. To reduce the cost and the duration of the LFA development process, we introduce a novel development platform centered on the flexibility, speed, and throughput of an automated robotic liquid handling system. The system comprises LFA-specific hardware and software that enable large optimization experiments with discrete and continuous variables such as antibody pair selection or reagent concentration. Initial validation of the platform was demonstrated during development of a malaria LFA but was readily expanded to encompass development of SARS-CoV-2 and Mycobacterium tuberculosis LFAs. The validity of the platform, where optimization experiments are run directly on LFAs rather than in solution, was based on a direct comparison between the robotic system and a more traditional ELISA-like method. By minimizing hands-on time, maximizing experiment size, and enabling improved reproducibility, the robotic system improved the quality and quantity of LFA assay development efforts.

Graphical abstract

Antibody affinity as a driver of signal generation in a paper-based immunoassay for Ebola virus surveillance

During epidemics, such as the frequent and devastating Ebola virus outbreaks that have historically plagued regions of Africa, serological surveillance efforts are critical for viral containment and the development of effective antiviral therapeutics. Antibody serology can also be used retrospectively for population-level surveillance to provide a more complete estimate of total infections. Ebola surveillance efforts rely on enzyme-linked immunosorbent assays (ELISAs), which restrict testing to laboratories and are not adaptable for use in resource-limited settings. In this manuscript, we describe a paper-based immunoassay capable of detecting anti-Ebola IgG using Ebola virus envelope glycoprotein ectodomain (GP) as the affinity reagent. We evaluated seven monoclonal antibodies (mAbs) against GP—KZ52, 13C6, 4G7, 2G4, c6D8, 13F6, and 4F3—to elucidate the impact of binding affinity and binding epitope on assay performance and, ultimately, result interpretation. We used biolayer interferometry to characterize the binding of each antibody to GP before assessing their performance in our paper-based device. Binding affinity (K_D) and on rate (k_on) were major factors influencing the sensitivity of the paper-based immunoassay. mAbs with the best K_D (3–25 nM) exhibited the lowest limits of detection (ca. μg mL⁻¹), while mAbs with K_D > 25 nM were undetectable in our device. Additionally, and most surprisingly, we determined that observed signals in paper devices were directly proportional to k_on. These results highlight the importance of ensuring that the quality of recognition reagents is sufficient to support desired assay performance and suggest that the strength of an individual’s immune response can impact the interpretation of assay results.

Experimental validation of eosin-mediated photo-redox polymerization mechanism and implications for signal amplification applications

When eosin-mediated, photo-redox polymerization is used to amplify signals in biosensing, oxygen has dual, opposing roles.

Emerging Telemedicine Tools for Remote COVID-19 Diagnosis, Monitoring, and Management

The management of the COVID-19 pandemic has relied on cautious contact tracing, quarantine, and sterilization protocols while we await a vaccine to be made widely available. Telemedicine or mobile health (mHealth) is well-positioned during this time to reduce potential disease spread and prevent overloading of the healthcare system through at-home COVID-19 screening, diagnosis, and monitoring. With the rise of mass-fabricated electronics for wearable and portable sensors, emerging telemedicine tools have been developed to address shortcomings in COVID-19 diagnostics, monitoring, and management. In this Perspective, we summarize current implementations of mHealth sensors for COVID-19, highlight recent technological advances, and provide an overview on how these tools may be utilized to better control the COVID-19 pandemic.