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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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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. |
format | Online Article Text |
id | pubmed-9887648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
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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