DNA origami signal amplification in lateral flow immunoassays

Lateral flow immunoassays (LFIAs) enable a rapid detection of analytes in a simple, paper-based test format. Despite their multiple advantages, such as low cost and ease of use, their low sensitivity compared to laboratory-based testing limits their use in e.g. many critical point-of-care applications. Here, we present a DNA origami-based signal amplification technology for LFIAs. DNA origami is used as a structurally precise adapter to connect detection antibodies to tailored numbers of signal-generating labels. As a proof of concept, we apply the DNA origami signal amplification in a sandwich-based LFIA for the detection of cardiac troponin I (cTnI) in human serum. We show a 55-fold improvement of the assay sensitivity with 40 nm gold nanoparticle labels and an adjustable signal amplification of up to 125-fold with fluorescent dyes. The technology is compatible with a wide range of existing analytes, labels, and sample matrices, and presents a modular approach for improving the sen..., , , # **DNA Origami Signal Amplification in Lateral Flow Immunoassays**

[https://doi.org/10.5061/dryad.k6djh9wh](https://doi.org/10.5061/dryad.k6djh9wh)

This folder contains the dataset supporting the findings of our research paper, i.e., the data for all figures presented in the manuscript. We have used transmission electron microscopy (TEM) imaging and agarose gel electrophoresis (AGE) for characterizing DNA origami nanostructures as well as DNA origami nanostructures combined with antibodies, gold nanoparticles, and fluorescent dyes. The DNA origami nanostructures have then been applied in various types of lateral flow immunoassays (LFIAs). The results of the LFIAs are presented as images of assay strips, including conventional photographs and fluorescence images, as well as numerical data of test line intensity values from image analysis.

## Description of the data and file structure

The data provided in this folder includes both raw and processed data. The presented raw data includ...,