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Quantitative Super-Resolution Microscopy to Assess Adhesion of Neuronal Cells on Single-Layer Graphene Substrates
Single Layer Graphene (SLG) has emerged as a critically important nanomaterial due to its unique optical and electrical properties and has become a potential candidate for biomedical applications, biosensors, and tissue engineering. Due to its intrinsic 2D nature, SLG is an ideal surface for the dev...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8621106/ https://www.ncbi.nlm.nih.gov/pubmed/34832107 http://dx.doi.org/10.3390/membranes11110878 |
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author | Scalisi, Silvia Pennacchietti, Francesca Keshavan, Sandeep Derr, Nathan D. Diaspro, Alberto Pisignano, Dario Pierzynska-Mach, Agnieszka Dante, Silvia Cella Zanacchi, Francesca |
author_facet | Scalisi, Silvia Pennacchietti, Francesca Keshavan, Sandeep Derr, Nathan D. Diaspro, Alberto Pisignano, Dario Pierzynska-Mach, Agnieszka Dante, Silvia Cella Zanacchi, Francesca |
author_sort | Scalisi, Silvia |
collection | PubMed |
description | Single Layer Graphene (SLG) has emerged as a critically important nanomaterial due to its unique optical and electrical properties and has become a potential candidate for biomedical applications, biosensors, and tissue engineering. Due to its intrinsic 2D nature, SLG is an ideal surface for the development of large-area biosensors and, due to its biocompatibility, can be easily exploited as a substrate for cell growth. The cellular response to SLG has been addressed in different studies with high cellular affinity for graphene often detected. Still, little is known about the molecular mechanism that drives/regulates the cellular adhesion and migration on SLG and SLG-coated interfaces with respect to other substrates. Within this scenario, we used quantitative super-resolution microscopy based on single-molecule localization to study the molecular distribution of adhesion proteins at the nanoscale level in cells growing on SLG and glass. In order to reveal the molecular mechanisms underlying the higher affinity of biological samples on SLG, we exploited stochastic optical reconstruction microscopy (STORM) imaging and cluster analysis, quantifying the super-resolution localization of the adhesion protein vinculin in neurons and clearly highlighting substrate-related correlations. Additionally, a comparison with an epithelial cell line (Chinese Hamster Ovary) revealed a cell dependent mechanism of interaction with SLG. |
format | Online Article Text |
id | pubmed-8621106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86211062021-11-27 Quantitative Super-Resolution Microscopy to Assess Adhesion of Neuronal Cells on Single-Layer Graphene Substrates Scalisi, Silvia Pennacchietti, Francesca Keshavan, Sandeep Derr, Nathan D. Diaspro, Alberto Pisignano, Dario Pierzynska-Mach, Agnieszka Dante, Silvia Cella Zanacchi, Francesca Membranes (Basel) Article Single Layer Graphene (SLG) has emerged as a critically important nanomaterial due to its unique optical and electrical properties and has become a potential candidate for biomedical applications, biosensors, and tissue engineering. Due to its intrinsic 2D nature, SLG is an ideal surface for the development of large-area biosensors and, due to its biocompatibility, can be easily exploited as a substrate for cell growth. The cellular response to SLG has been addressed in different studies with high cellular affinity for graphene often detected. Still, little is known about the molecular mechanism that drives/regulates the cellular adhesion and migration on SLG and SLG-coated interfaces with respect to other substrates. Within this scenario, we used quantitative super-resolution microscopy based on single-molecule localization to study the molecular distribution of adhesion proteins at the nanoscale level in cells growing on SLG and glass. In order to reveal the molecular mechanisms underlying the higher affinity of biological samples on SLG, we exploited stochastic optical reconstruction microscopy (STORM) imaging and cluster analysis, quantifying the super-resolution localization of the adhesion protein vinculin in neurons and clearly highlighting substrate-related correlations. Additionally, a comparison with an epithelial cell line (Chinese Hamster Ovary) revealed a cell dependent mechanism of interaction with SLG. MDPI 2021-11-15 /pmc/articles/PMC8621106/ /pubmed/34832107 http://dx.doi.org/10.3390/membranes11110878 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Scalisi, Silvia Pennacchietti, Francesca Keshavan, Sandeep Derr, Nathan D. Diaspro, Alberto Pisignano, Dario Pierzynska-Mach, Agnieszka Dante, Silvia Cella Zanacchi, Francesca Quantitative Super-Resolution Microscopy to Assess Adhesion of Neuronal Cells on Single-Layer Graphene Substrates |
title | Quantitative Super-Resolution Microscopy to Assess Adhesion of Neuronal Cells on Single-Layer Graphene Substrates |
title_full | Quantitative Super-Resolution Microscopy to Assess Adhesion of Neuronal Cells on Single-Layer Graphene Substrates |
title_fullStr | Quantitative Super-Resolution Microscopy to Assess Adhesion of Neuronal Cells on Single-Layer Graphene Substrates |
title_full_unstemmed | Quantitative Super-Resolution Microscopy to Assess Adhesion of Neuronal Cells on Single-Layer Graphene Substrates |
title_short | Quantitative Super-Resolution Microscopy to Assess Adhesion of Neuronal Cells on Single-Layer Graphene Substrates |
title_sort | quantitative super-resolution microscopy to assess adhesion of neuronal cells on single-layer graphene substrates |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8621106/ https://www.ncbi.nlm.nih.gov/pubmed/34832107 http://dx.doi.org/10.3390/membranes11110878 |
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