Josselyn Mata Calidonio, Arianna I. Maddox and Kimberly Hamad-Schifferli
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引用次数: 0
Abstract
Rapid diagnostics are critical infectious disease tools that are designed to detect a known biomarker using antibodies specific to that biomarker. However, a way to detect unknown disease variants has not yet been achieved in a paper test format. We describe here a route to make an adaptable paper immunoassay that can detect an unknown biomarker, demonstrating it on SARS-CoV-2 variants. The immunoassay repurposes cross reactive antibodies raised against the alpha variant. Gold nanoparticles of two different colors conjugated to two different antibodies create a colorimetric signal, and machine learning of the resulting colorimetric pattern is used to train the assay to discriminate between variants of alpha and Omicron BA.5. By using principal component analysis, the colorimetric test patterns can pick up and discriminate an unknown variant that it has not encountered before, Omicron BA.1. The test has an accuracy of 100% and a potential calculated discriminatory power of 900. We show that it can be used adaptively and that it can be used to pick up emerging variants without the need to raise new antibodies.
期刊介绍:
Lab on a Chip is the premiere journal that publishes cutting-edge research in the field of miniaturization. By their very nature, microfluidic/nanofluidic/miniaturized systems are at the intersection of disciplines, spanning fundamental research to high-end application, which is reflected by the broad readership of the journal. Lab on a Chip publishes two types of papers on original research: full-length research papers and communications. Papers should demonstrate innovations, which can come from technical advancements or applications addressing pressing needs in globally important areas. The journal also publishes Comments, Reviews, and Perspectives.