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Image-Based Method to Quantify Decellularization of Tissue Sections

Tissue decellularization is typically assessed through absorbance-based DNA quantification after tissue digestion. This method has several disadvantages, namely its destructive nature and inadequacy in experimental situations where tissue is scarce. Here, we present an image processing algorithm for...

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Detalles Bibliográficos
Autores principales: Narciso, Maria, Otero, Jorge, Navajas, Daniel, Farré, Ramon, Almendros, Isaac, Gavara, Núria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8395145/
https://www.ncbi.nlm.nih.gov/pubmed/34445106
http://dx.doi.org/10.3390/ijms22168399
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author Narciso, Maria
Otero, Jorge
Navajas, Daniel
Farré, Ramon
Almendros, Isaac
Gavara, Núria
author_facet Narciso, Maria
Otero, Jorge
Navajas, Daniel
Farré, Ramon
Almendros, Isaac
Gavara, Núria
author_sort Narciso, Maria
collection PubMed
description Tissue decellularization is typically assessed through absorbance-based DNA quantification after tissue digestion. This method has several disadvantages, namely its destructive nature and inadequacy in experimental situations where tissue is scarce. Here, we present an image processing algorithm for quantitative analysis of DNA content in (de)cellularized tissues as a faster, simpler and more comprehensive alternative. Our method uses local entropy measurements of a phase contrast image to create a mask, which is then applied to corresponding nuclei labelled (UV) images to extract average fluorescence intensities as an estimate of DNA content. The method can be used on native or decellularized tissue to quantify DNA content, thus allowing quantitative assessment of decellularization procedures. We confirm that our new method yields results in line with those obtained using the standard DNA quantification method and that it is successful for both lung and heart tissues. We are also able to accurately obtain a timeline of decreasing DNA content with increased incubation time with a decellularizing agent. Finally, the identified masks can also be applied to additional fluorescence images of immunostained proteins such as collagen or elastin, thus allowing further image-based tissue characterization.
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spelling pubmed-83951452021-08-28 Image-Based Method to Quantify Decellularization of Tissue Sections Narciso, Maria Otero, Jorge Navajas, Daniel Farré, Ramon Almendros, Isaac Gavara, Núria Int J Mol Sci Article Tissue decellularization is typically assessed through absorbance-based DNA quantification after tissue digestion. This method has several disadvantages, namely its destructive nature and inadequacy in experimental situations where tissue is scarce. Here, we present an image processing algorithm for quantitative analysis of DNA content in (de)cellularized tissues as a faster, simpler and more comprehensive alternative. Our method uses local entropy measurements of a phase contrast image to create a mask, which is then applied to corresponding nuclei labelled (UV) images to extract average fluorescence intensities as an estimate of DNA content. The method can be used on native or decellularized tissue to quantify DNA content, thus allowing quantitative assessment of decellularization procedures. We confirm that our new method yields results in line with those obtained using the standard DNA quantification method and that it is successful for both lung and heart tissues. We are also able to accurately obtain a timeline of decreasing DNA content with increased incubation time with a decellularizing agent. Finally, the identified masks can also be applied to additional fluorescence images of immunostained proteins such as collagen or elastin, thus allowing further image-based tissue characterization. MDPI 2021-08-05 /pmc/articles/PMC8395145/ /pubmed/34445106 http://dx.doi.org/10.3390/ijms22168399 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
Narciso, Maria
Otero, Jorge
Navajas, Daniel
Farré, Ramon
Almendros, Isaac
Gavara, Núria
Image-Based Method to Quantify Decellularization of Tissue Sections
title Image-Based Method to Quantify Decellularization of Tissue Sections
title_full Image-Based Method to Quantify Decellularization of Tissue Sections
title_fullStr Image-Based Method to Quantify Decellularization of Tissue Sections
title_full_unstemmed Image-Based Method to Quantify Decellularization of Tissue Sections
title_short Image-Based Method to Quantify Decellularization of Tissue Sections
title_sort image-based method to quantify decellularization of tissue sections
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8395145/
https://www.ncbi.nlm.nih.gov/pubmed/34445106
http://dx.doi.org/10.3390/ijms22168399
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