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◆ Nature Methods2025-11-01· Computational biology

nELISA: a high-throughput, high-plex platform enables quantitative profiling of the inflammatory secretome

Milad Dagher, Grant Ongo, Nathaniel Robichaud, Jinglin Kong, Woojong Rho, Ivan Teahulos, Arya Tavakoli, Samantha Bovaird, Shahem Merjaneh, Andrew Tan, Kiran Edwardson, Christelle Scheepers, Andy Ng, Andy Hajjar, Baly Sow, Michael Vrouvides, Andy Lee, Philippe DeCorwin‐Martin, Shafqat Rasool, Jian-Yuan Huang, Timothy Erps, Spencer Coffin, Narges Rashidi, Yu Han, Srinivas Niranj Chandrasekaran, Lisa Miller, Maria Kost‐Alimova, Adam Skepner, Shantanu Singh, Anne E. Carpenter, Jeffrey D. Munzar, David Juncker

原始摘要(英文原文)· Original abstract
Existing high-plex protein measurement tools compromise on quantification, precision and cost efficiency. Here, to address this, we present nELISA, a platform that combines a DNA-mediated, bead-based sandwich immunoassay with advanced multicolor bead barcoding. Antibody pairs are preassembled on target-specific, barcoded beads, which ensures spatial separation between noncognate assays. Detection antibodies are tethered via flexible single-stranded DNA to enable efficient ternary sandwich formation. Detection is achieved through toehold-mediated strand displacement, where fluorescently labeled DNA oligos simultaneously untether and label detection antibodies. nELISA delivers sub-picogram-per-milliliter sensitivity across seven orders of magnitude. Using a 191-plex inflammation panel, we profiled cytokine responses in 7,392 peripheral blood mononuclear cell samples, generating ~1.4 million protein measurements and revealing over 440 robust cytokine responses, including previously unreported effects. nELISA thus provides a simple, scalable and cost-efficient solution for large-scale, high-fidelity phenotypic screening.
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