Net-Shaped DNA Nanostructure-Based Lateral Flow Assays for Rapid and Sensitive SARS-CoV-2 Detection.

Lateral flow assay (LFA)-based rapid antigen tests are experiencing extensive global uptake as an expeditious and highly effective modality for the screening of viral infections during the COVID-19 pandemic. While these devices have played a significant role in alleviating the burden on the public healthcare system, their specificity and sensitivity fall short compared with molecular tests. In this study, we endeavor to address both limitations through the utilization of DNA nanotechnology in LFA format, wherein we substitute the target-specific antibody with designer DNA nanostructure-based molecular probes for recognizing the SARS-CoV-2 virus via multivalent, pattern-matching interactions. We meticulously designed a Net-shaped DNA nanostructure and strategically arranged trimeric clusters of aptamers that specifically recognize the spike proteins of SARS-CoV-2. This approach has proven instrumental in bolstering virus-binding affinity on the LFAs. Our findings indicate high LFA sensitivity, enabling the detection of viral loads ranging from 103 to 108 viral copies/mL. This notable sensitivity is maintained across various SARS-CoV-2 viral strains, obviating the need for intricate sample preparation protocols. The significance of this heightened sensitivity lies in the crucial role played by the designer DNA nanostructure, which facilitates the detection of extremely low levels of viral loads. This not only enhances the overall reliability of self-testing but also reduces the likelihood of false-negative results, especially in cases of low viral load within patient samples.

APIPred: An XGBoost-Based Method for Predicting Aptamer-Protein Interactions.

Aptamers are single-stranded DNA or RNA oligos that can bind to a variety of targets with high specificity and selectivity and thus are widely used in the field of biosensing and disease therapies. Aptamers are generated by SELEX, which is a time-consuming procedure. In this study, using in silico and computational tools, we attempt to predict whether an aptamer can interact with a specific protein target. We present multiple data representations of protein and aptamer pairs and multiple machine-learning-based models to predict aptamer-protein interactions with a fair degree of selectivity. One of our models showed 96.5% accuracy and 97% precision, which are significantly better than those of the previously reported models. Additionally, we used molecular docking and SPR binding assays for two aptamers and the predicted targets as examples to exhibit the robustness of the APIPred algorithm. This reported model can be used for the high throughput screening of aptamer-protein pairs for targeting cancer and rapidly evolving viral epidemics.

Review of HIV Self Testing Technologies and Promising Approaches for the Next Generation.

The ability to self-test for HIV is vital to preventing transmission, particularly when used in concert with HIV biomedical prevention modalities, such as pre-exposure prophylaxis (PrEP). In this paper, we review recent developments in HIV self-testing and self-sampling methods, and the potential future impact of novel materials and methods that emerged through efforts to develop more effective point-of-care (POC) SARS-CoV-2 diagnostics. We address the gaps in existing HIV self-testing technologies, where improvements in test sensitivity, sample-to-answer time, simplicity, and cost are needed to enhance diagnostic accuracy and widespread accessibility. We discuss potential paths toward the next generation of HIV self-testing through sample collection materials, biosensing assay techniques, and miniaturized instrumentation. We discuss the implications for other applications, such as self-monitoring of HIV viral load and other infectious diseases.

Single-molecule Diffusion and Assembly on Polymer-crowded Lipid Membranes.

Cellular membranes are highly crowded environments for biomolecular reactions and signaling. Yet, most in vitro experiments probing protein interaction with lipids employ naked bilayer membranes. Such systems lack the complexities of crowding by membrane-embedded proteins and glycans and exclude the associated volume effects encountered on cellular membrane surfaces. Also, the negatively charged glass surface onto which the lipid bilayers are formed prevents the free diffusion of transmembrane biomolecules. Here, we present a well-characterized polymer-lipid membrane as a mimic for crowded lipid membranes. This protocol utilizes polyethylene glycol (PEG)-conjugated lipids as a generalized approach for incorporating crowders into the supported lipid bilayer (SLB). First, a cleaning procedure of the microscopic slides and coverslips for performing single-molecule experiments is presented. Next, methods for characterizing the PEG-SLBs and performing single-molecule experiments of the binding, diffusion, and assembly of biomolecules using single-molecule tracking and photobleaching are discussed. Finally, this protocol demonstrates how to monitor the nanopore assembly of bacterial pore-forming toxin Cytolysin A (ClyA) on crowded lipid membranes with single-molecule photobleaching analysis. MATLAB codes with example datasets are also included to perform some of the common analyses such as particle tracking, extracting diffusive behavior, and subunit counting.

Smartphone-based kanamycin sensing with ratiometric FRET.

Smartphone-based fluorescence detection is a promising avenue for biosensing that can aid on-site analysis. However, quantitative detection with fluorescence in the field has been limited due to challenges with robust excitation and calibration requirements. Here, we show that ratiometric analysis with Förster resonance energy transfer (FRET) between dye pairs on DNA aptamers can enable rapid and sensitive kanamycin detection. Since our detection scheme relies on ligand binding-induced changes in the aptamer tertiary structure, it is limited only by the kinetics of ligand binding to the aptamer. Our FRET-based kanamycin binding aptamer (KBA) sensor displays two linear ranges of 0.05-5 nM (detection limit of 0.18 nM) and 50-900 nM of kanamycin. The aptamer displays high specificity even in the presence of the 'natural' background from milk. By immobilizing the aptamer in the flow cell, our KBA sensor design is also suitable for repeated kanamycin detection. Finally, we show that the ratiometric FRET-based analysis can be implemented on a cheap custom-built smartphone setup. This smartphone-based FRET aptamer scheme detects kanamycin in a linear range of 50-500 nM with a limit of detection (LOD) of 28 nM.