Cargando…

Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates

Today, we are fully immersed into the era of 3D biology. It has been extensively demonstrated that 3D models: (a) better mimic the physiology of human tissues; (b) can effectively replace animal models; (c) often provide more reliable results than 2D ones. Accordingly, anti-cancer drug screenings an...

Descripción completa

Detalles Bibliográficos
Autores principales: Piccinini, Filippo, Balassa, Tamas, Carbonaro, Antonella, Diosdi, Akos, Toth, Timea, Moshkov, Nikita, Tasnadi, Ervin A., Horvath, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303562/
https://www.ncbi.nlm.nih.gov/pubmed/32612752
http://dx.doi.org/10.1016/j.csbj.2020.05.022
_version_ 1783548084435812352
author Piccinini, Filippo
Balassa, Tamas
Carbonaro, Antonella
Diosdi, Akos
Toth, Timea
Moshkov, Nikita
Tasnadi, Ervin A.
Horvath, Peter
author_facet Piccinini, Filippo
Balassa, Tamas
Carbonaro, Antonella
Diosdi, Akos
Toth, Timea
Moshkov, Nikita
Tasnadi, Ervin A.
Horvath, Peter
author_sort Piccinini, Filippo
collection PubMed
description Today, we are fully immersed into the era of 3D biology. It has been extensively demonstrated that 3D models: (a) better mimic the physiology of human tissues; (b) can effectively replace animal models; (c) often provide more reliable results than 2D ones. Accordingly, anti-cancer drug screenings and toxicology studies based on multicellular 3D biological models, the so-called “-oids” (e.g. spheroids, tumoroids, organoids), are blooming in the literature. However, the complex nature of these systems limit the manual quantitative analyses of single cells’ behaviour in the culture. Accordingly, the demand for advanced software tools that are able to perform phenotypic analysis is fundamental. In this work, we describe the freely accessible tools that are currently available for biologists and researchers interested in analysing the effects of drugs/treatments on 3D multicellular -oids at a single-cell resolution level. In addition, using publicly available nuclear stained datasets we quantitatively compare the segmentation performance of 9 specific tools.
format Online
Article
Text
id pubmed-7303562
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Research Network of Computational and Structural Biotechnology
record_format MEDLINE/PubMed
spelling pubmed-73035622020-06-30 Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates Piccinini, Filippo Balassa, Tamas Carbonaro, Antonella Diosdi, Akos Toth, Timea Moshkov, Nikita Tasnadi, Ervin A. Horvath, Peter Comput Struct Biotechnol J Review Article Today, we are fully immersed into the era of 3D biology. It has been extensively demonstrated that 3D models: (a) better mimic the physiology of human tissues; (b) can effectively replace animal models; (c) often provide more reliable results than 2D ones. Accordingly, anti-cancer drug screenings and toxicology studies based on multicellular 3D biological models, the so-called “-oids” (e.g. spheroids, tumoroids, organoids), are blooming in the literature. However, the complex nature of these systems limit the manual quantitative analyses of single cells’ behaviour in the culture. Accordingly, the demand for advanced software tools that are able to perform phenotypic analysis is fundamental. In this work, we describe the freely accessible tools that are currently available for biologists and researchers interested in analysing the effects of drugs/treatments on 3D multicellular -oids at a single-cell resolution level. In addition, using publicly available nuclear stained datasets we quantitatively compare the segmentation performance of 9 specific tools. Research Network of Computational and Structural Biotechnology 2020-06-03 /pmc/articles/PMC7303562/ /pubmed/32612752 http://dx.doi.org/10.1016/j.csbj.2020.05.022 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review Article
Piccinini, Filippo
Balassa, Tamas
Carbonaro, Antonella
Diosdi, Akos
Toth, Timea
Moshkov, Nikita
Tasnadi, Ervin A.
Horvath, Peter
Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates
title Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates
title_full Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates
title_fullStr Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates
title_full_unstemmed Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates
title_short Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates
title_sort software tools for 3d nuclei segmentation and quantitative analysis in multicellular aggregates
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303562/
https://www.ncbi.nlm.nih.gov/pubmed/32612752
http://dx.doi.org/10.1016/j.csbj.2020.05.022
work_keys_str_mv AT piccininifilippo softwaretoolsfor3dnucleisegmentationandquantitativeanalysisinmulticellularaggregates
AT balassatamas softwaretoolsfor3dnucleisegmentationandquantitativeanalysisinmulticellularaggregates
AT carbonaroantonella softwaretoolsfor3dnucleisegmentationandquantitativeanalysisinmulticellularaggregates
AT diosdiakos softwaretoolsfor3dnucleisegmentationandquantitativeanalysisinmulticellularaggregates
AT tothtimea softwaretoolsfor3dnucleisegmentationandquantitativeanalysisinmulticellularaggregates
AT moshkovnikita softwaretoolsfor3dnucleisegmentationandquantitativeanalysisinmulticellularaggregates
AT tasnadiervina softwaretoolsfor3dnucleisegmentationandquantitativeanalysisinmulticellularaggregates
AT horvathpeter softwaretoolsfor3dnucleisegmentationandquantitativeanalysisinmulticellularaggregates