Highly Flexible Deep-Learning-Based Automatic Analysis for Graphically Encoded Hydrogel Microparticles

Tyramide signal amplification for a highly sensitive multiplex immunoassay based on encoded hydrogel microparticles

Proteins play a crucial role as mediators of immune regulation, homeostasis, and metabolism, making their quantification essential for understanding disease mechanisms in biomedical research and clinical diagnostics. However, conventional methods when used to detect proteins in clinical samples exhibit difficulty in terms of sensitivity, dynamic range, and multiplex capacity. In this study, we developed a highly sensitive multiplex immunoassay based on encoded hydrogel microparticles (MPs) utilizing tyramide signal amplification (TSA). The combination of the large multiplexing capacity of encoded hydrogel microparticles and the signal amplification of tyramide enables a highly sensitive multiplex immunoassay. By employing TSA, we are able to achieve larger detection signals with higher specificity. We effectively decreased the non-specific binding in the hydrogel network by blocking the unreacted acrylate double bonds remaining after the capture antibody-conjugation step and acquired a 3-fold increase in the signal-to-noise ratio. Also, we optimized three parameters mainly affecting the assay sensitivity: the detection antibody concentration, the biotinyl tyramide concentration, and the TSA reaction time. This approach leads to a significant improvement in assay sensitivity, achieving a limit of detection as low as 58 fg mL-1. Compared to the previous method, the assay sensitivity is enhanced 10-fold. In addition, the multiplex capability of the assay is validated by detecting cytokines IL-4, IL-5, IL-6, IL-9, and IL-17, with no observed cross-reactivity. Finally, with enhanced sensitivity, we demonstrate the clinical applicability of our platform by successfully multiplexing these cytokines at concentrations down to several hundreds of fg mL-1 within human serum, which could not be detected using previous methods.

Fibrosis Drug Efficacy Assessment Based on Microfluidic Mechanical Property Evaluation of Spheroid Models

Fibrotic diseases, such as pulmonary fibrosis, pose significant challenges in both research and treatment. To address the limitations of existing systems, a novel collision-based spheroid mechanical property assessment system is developed. The system utilizes inertial fluid dynamics to induce controlled collisions through uniformly sized spheroids, allowing strain to be measured via high-speed cameras. In this study, the system is first validated using HEK293T spheroids to optimize flow velocity, followed by an analysis of deformability differences between two cell types related to pulmonary fibrosis (Calu-1 and MRC-5). A co-culture spheroid model comprising two types of lung cells, endothelial and fibroblast cells, in different rations is further developed, and significant differences in deformability depending on the cell composition is observed. Finally, spheroids are treated with TGF-β1(Transforming Growth Factor-β1), a factor known to activate fibroblast cells and induce excessive extra cellular matrix (ECM) accumulation, and Nintedanib, an anti-fibrotic drug, to assess changes in mechanical properties. These results effectively reflect the mechanical properties driven by cell-cell and cell-ECM interactions and highlight the correlation between spheroid mechanics and the progression of fibrotic disease. This system not only contributes to a deeper understanding of fibrosis progression but also serves as a powerful platform for accelerating the development of anti-fibrotic therapies.

Hydrogel-Based In Situ DNA Extension Assay for Multiplexed and Rapid Detection of MicroRNA

MicroRNAs (miRNAs) are important biomarkers for liquid biopsy, with extensive applicability to diverse diseases. Among diverse miRNA sensing platforms, graphically encoded hydrogel-based miRNA detection technology is a highly promising diagnostic tool, in terms of sensitivity, specificity, and multiplexing capability. However, the conventional hydrogel-based miRNA detection process suffers from a long assay time (more than 3 h) and redundant assay steps, limiting the practical applicability to actual clinical fields. In this study, we develop a hydrogel-based in situ DNA extension assay for rapid, simple, and multiplexed miRNA detection. Unlike typical hydrogel-based assays, the target hybridization and biotinylation for fluorophore labeling are integrated into a single step via target miRNA-primed DNA extension in hydrogel microparticles. Therefore, multiple microRNA targets can be quantitatively detected within 45 min by two assay steps composed of (1) target capture/biotinylation and (2) fluorophore labeling via streptavidin-biotin interaction. We validate robust sensitivities (down to the low picomolar level) and specificities (single-nucleotide level) by conducting singleplex assays for breast cancer-related miRNA markers (miR-16, miR-92a, and let-7a). Furthermore, multiplexed detection of these miRNA markers is conducted to validate robust multiplexing capacity with negligible nonspecific signal expression. Finally, multiple types of miRNAs in the lysate of breast cancer cells (MCF-7) are successfully detected using the developed assay. We expect the developed hydrogel-based assay can contribute to biomedical and omic fields, enabling high-throughput profiling of multiple miRNAs.

Efficient isolation of encoded microparticles in a degassed micromold for highly sensitive and multiplex immunoassay with signal amplification

Multiplex detection of low-abundance protein biomarkers in biofluids can contribute to diverse biomedical fields such as early diagnosis and precision medicine. However, conventional techniques such as digital ELISA, microarray, and hydrogel-based assay still face limitations in terms of efficient protein detection due to issues with multiplexing capability, sensitivity, or complicated assay procedures. In this study, we present the degassed micromold-based particle isolation technique for highly sensitive and multiplex immunoassay with enzymatic signal amplification. Using degassing treatment of nanoporous polydimethylsiloxane (PDMS) micromold, the encoded particles are isolated in the mold within 5 min absorbing trapped air bubbles into the mold by air suction capability. Through 10 min of signal amplification in the isolated spaces by fluorogenic substrate and horseradish peroxidase labeled in the particle, the assay signal is amplified with one order of magnitude compared to that of the standard hydrogel-based assay. Using the signal amplification assay, vascular endothelial growth factor (VEGF) and chorionic gonadotropin beta (CG beta), the preeclampsia-related protein biomarkers, are quantitatively detected with a limit of detection (LoD) of 249 fg/mL and 476 fg/mL in phosphate buffer saline. The multiplex immunoassay is conducted to validate negligible non-specific detection signals and robust recovery rates in the multiplex assay. Finally, the VEGF and CG beta in real urine samples are simultaneously and quantitatively detected by the developed assay. Given the high sensitivity, multiplexing capability, and process simplicity, the presented particle isolation-based signal amplification assay holds significant potential in biomedical and proteomic fields.

Real-Time Signal Analysis with Wider Dynamic Range and Enhanced Sensitivity in Multiplex Colorimetric Immunoassays Using Encoded Hydrogel Microparticles

The simultaneous quantification of multiple proteins is crucial for accurate medical diagnostics. A promising technology, the multiplex colorimetric immunoassay using encoded hydrogel microparticles, has garnered attention, due to its simplicity and multiplex capabilities. However, it encounters challenges related to its dynamic range, as it relies solely on the colorimetric signal analysis of encoded hydrogel microparticles at the specific time point (i.e., end-point analysis). This necessitates the precise determination of the optimal time point for the termination of the colorimetric reaction. In this study, we introduce real-time signal analysis to quantify proteins by observing the continuous colorimetric signal change within the encoded hydrogel microparticles. Real-time signal analysis measures the "slope", the rate of the colorimetric signal generation, by focusing on the kinetics of the accumulation of colorimetric products instead of the colorimetric signal that appears at the end point. By developing a deep learning-based automatic analysis program that automatically reads the code of the graphically encoded hydrogel microparticles and obtains the slope by continuously tracking the colorimetric signal, we achieved high accuracy and high throughput analysis. This technology has secured a dynamic range more than twice as wide as that of the conventional end-point signal analysis, simultaneously achieving a sensitivity that is 4-10 times higher. Finally, as a demonstration of application, we performed multiplex colorimetric immunoassays using real-time signal analysis covering a wide concentration range of protein targets associated with pre-eclampsia.