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Sequential Protein Capture in Multiplex Single Molecule Arrays: A Strategy for Eliminating Assay Cross‐Reactivity
Author(s) -
Gilboa Tal,
Maley Adam M.,
Ogata Alana F.,
Wu Connie,
Walt David R.
Publication year - 2021
Publication title -
advanced healthcare materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.288
H-Index - 90
eISSN - 2192-2659
pISSN - 2192-2640
DOI - 10.1002/adhm.202001111
Subject(s) - multiplex , analyte , chemistry , biomolecule , computational biology , covid-19 , combinatorial chemistry , chromatography , bioinformatics , biochemistry , biology , medicine , disease , pathology , infectious disease (medical specialty)
Measurements of multiple biomolecules within the same biological sample are important for many clinical applications to enable accurate disease diagnosis or classification. These disease‐related biomarkers often exist at very low levels in biological fluids, necessitating ultrasensitive measurement methods. Single‐molecule arrays (Simoa), a bead‐based digital enzyme‐linked immunosorbent assay, is the current state of the art for ultrasensitive protein detection and can detect sub‐femtomolar protein concentrations, but its ability to achieve high‐order multiplexing without cross‐reactivity remains a challenge. Here, a sequential protein capture approach for multiplex Simoa assays is implemented to eliminate cross‐reactivity between binding reagents by sequentially capturing each protein analyte and then incubating each capture bead with only its corresponding detection antibody. This strategy not only reduces cross‐reactivity to background levels and significantly improves measurement accuracies, but also enables higher‐order multiplexing. As a proof of concept, the sequential multiplex Simoa assay is used to measure five different cytokines in plasma samples from Coronavirus Disease 2019 (COVID‐19) patients. The ultrasensitive sequential multiplex Simoa assays will enable the simultaneous measurements of multiple low‐abundance analytes in a time‐ and cost‐effective manner and will prove especially critical in many cases where sample volumes are limited.