ArticleACS sensors2023
Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT.
Article in ACS sensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Urinary Cell-Free DNA detection platform for bacterial cystitis diagnosis via spot-based machine learning.Journal of advanced research · 2026Article
- Stoichiometrically Defined Antibody-DNA Conjugates for Quantitative Super-Resolution Imaging.Nano letters · 2026Article
- Revealing Spatial Molecular Heterogeneity of High-Density Biofunctionalized Surfaces Using DNA-PAINT.ACS applied materials & interfaces · 2024Article
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6 authors.
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Abstract
Characterization of the number and distribution of biological molecules on 2D surfaces is of foremost importance in biology and biomedicine. Synthetic surfaces bearing recognition motifs are a cornerstone of biosensors, while receptors on the cell surface are critical/vital targets for the treatment of diseases. However, the techniques used to quantify their abundance are qualitative or semi-quantitative and usually lack sensitivity, accuracy, or precision. Detailed herein a simple and versatile workflow based on super-resolution microscopy (DNA-PAINT) was standardized to improve the quantification of the density and distribution of molecules on synthetic substrates and cell membranes. A detailed analysis of accuracy and precision of receptor quantification is presented, based on simulated and experimental data. We demonstrate enhanced accuracy and sensitivity by filtering out non-specific interactions and artifacts. While optimizing the workflow to provide faithful counting over a broad range of receptor densities. We validated the workflow by specifically quantifying the density of docking strands on a synthetic sensor surface and the densities of PD1 and EGF receptors (EGFR) on two cellular models.
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