Enhanced Label-Free Nanoplasmonic Cytokine Detection in SARS-CoV-2 Induced Inflammation Using Rationally Designed Peptide Aptamer.

Rapid and precise serum cytokine quantification provides immense clinical significance in monitoring the immune status of patients in rapidly evolving infectious/inflammatory disorders, examplified by the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. However, real-time information on predictive cytokine biomarkers to guide targetable immune pathways in pathogenic inflammation is critically lacking, because of the insufficient detection range and detection limit in current label-free cytokine immunoassays. In this work, we report a highly sensitive localized surface plasmon resonance imaging (LSPRi) immunoassay for label-free Interleukin 6 (IL-6) detection utilizing rationally designed peptide aptamers as the capture interface. Benefiting from its characteristically smaller dimension and direct functionalization on the sensing surface via Au-S bonding, the peptide-aptamer-based LSPRi immunoassay achieved enhanced label-free serum IL-6 detection with a record-breaking limit of detection down to 4.6 pg/mL, and a wide dynamic range of ∼6 orders of magnitude (values from 4.6 to 1 × 106 pg/mL were observed). The immunoassay was validated in vitro for label-free analysis of SARS-CoV-2 induced inflammation, and further applied in rapid quantification of serum IL-6 profiles in COVID-19 patients. Our peptide aptamer LSPRi immunoassay demonstrates great potency in label-free cytokine detection with unprecedented sensing capability to provide accurate and timely interpretation of the inflammatory status and disease progression, and determination of prognosis.

Machine-Learning-Assisted Microfluidic Nanoplasmonic Digital Immunoassay for Cytokine Storm Profiling in COVID-19 Patients.

Cytokine storm, known as an exaggerated hyperactive immune response characterized by elevated release of cytokines, has been described as a feature associated with life-threatening complications in COVID-19 patients. A critical evaluation of a cytokine storm and its mechanistic linkage to COVID-19 requires innovative immunoassay technology capable of rapid, sensitive, selective detection of multiple cytokines across a wide dynamic range at high-throughput. In this study, we report a machine-learning-assisted microfluidic nanoplasmonic digital immunoassay to meet the rising demand for cytokine storm monitoring in COVID-19 patients. Specifically, the assay was carried out using a facile one-step sandwich immunoassay format with three notable features: (i) a microfluidic microarray patterning technique for high-throughput, multiantibody-arrayed biosensing chip fabrication; (ii) an ultrasensitive nanoplasmonic digital imaging technology utilizing 100 nm silver nanocubes (AgNCs) for signal transduction; (iii) a rapid and accurate machine-learning-based image processing method for digital signal analysis. The developed immunoassay allows simultaneous detection of six cytokines in a single run with wide working ranges of 1-10,000 pg mL^-1 and ultralow detection limits down to 0.46-1.36 pg mL^-1 using a minimum of 3 µL serum samples. The whole chip can afford a 6-plex assay of 8 different samples with 6 repeats in each sample for a total of 288 sensing spots in less than 100 min. The image processing method enhanced by convolutional neural network (CNN) dramatically shortens the processing time ∼6,000 fold with a much simpler procedure while maintaining high statistical accuracy compared to the conventional manual counting approach. The immunoassay was validated by the gold-standard enzyme-linked immunosorbent assay (ELISA) and utilized for serum cytokine profiling of COVID-19 positive patients. Our results demonstrate the nanoplasmonic digital immunoassay as a promising practical tool for comprehensive characterization of cytokine storm in patients that holds great promise as an intelligent immunoassay for next generation immune monitoring.