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Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT

[Image: see text] 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...

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Autores principales: Riera, Roger, Archontakis, Emmanouil, Cremers, Glenn, de Greef, Tom, Zijlstra, Peter, Albertazzi, Lorenzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887648/
https://www.ncbi.nlm.nih.gov/pubmed/36655822
http://dx.doi.org/10.1021/acssensors.2c01736
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author Riera, Roger
Archontakis, Emmanouil
Cremers, Glenn
de Greef, Tom
Zijlstra, Peter
Albertazzi, Lorenzo
author_facet Riera, Roger
Archontakis, Emmanouil
Cremers, Glenn
de Greef, Tom
Zijlstra, Peter
Albertazzi, Lorenzo
author_sort Riera, Roger
collection PubMed
description [Image: see text] 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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spelling pubmed-98876482023-02-01 Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT Riera, Roger Archontakis, Emmanouil Cremers, Glenn de Greef, Tom Zijlstra, Peter Albertazzi, Lorenzo ACS Sens [Image: see text] 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. American Chemical Society 2023-01-19 /pmc/articles/PMC9887648/ /pubmed/36655822 http://dx.doi.org/10.1021/acssensors.2c01736 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Riera, Roger
Archontakis, Emmanouil
Cremers, Glenn
de Greef, Tom
Zijlstra, Peter
Albertazzi, Lorenzo
Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT
title Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT
title_full Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT
title_fullStr Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT
title_full_unstemmed Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT
title_short Precision and Accuracy of Receptor Quantification on Synthetic and Biological Surfaces Using DNA-PAINT
title_sort precision and accuracy of receptor quantification on synthetic and biological surfaces using dna-paint
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887648/
https://www.ncbi.nlm.nih.gov/pubmed/36655822
http://dx.doi.org/10.1021/acssensors.2c01736
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