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• W4317434191 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." @default.
• W4317434191 created "2023-01-19" @default.
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• W4317434191 date "2023-01-19" @default.
• W4317434191 modified "2023-10-12" @default.
• W4317434191 title "Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT" @default.
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• W4317434191 doi "https://doi.org/10.1021/acssensors.2c01736" @default.
• W4317434191 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36655822" @default.
• W4317434191 hasPublicationYear "2023" @default.
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