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Automated Identification and Location Analysis of Marked Stem Cells Colonies in Optical Microscopy Images
Embryonic stem cells (ESCs) are characterized by two remarkable peculiarities: the capacity to propagate as undifferentiated cells (self-renewal) and the ability to differentiate in ectoderm, endoderm, and mesoderm derivatives (pluripotency). Although the majority of ESCs divide without losing the p...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3857180/ https://www.ncbi.nlm.nih.gov/pubmed/24349016 http://dx.doi.org/10.1371/journal.pone.0080776 |
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author | Paduano, Vincenzo Tagliaferri, Daniela Falco, Geppino Ceccarelli, Michele |
author_facet | Paduano, Vincenzo Tagliaferri, Daniela Falco, Geppino Ceccarelli, Michele |
author_sort | Paduano, Vincenzo |
collection | PubMed |
description | Embryonic stem cells (ESCs) are characterized by two remarkable peculiarities: the capacity to propagate as undifferentiated cells (self-renewal) and the ability to differentiate in ectoderm, endoderm, and mesoderm derivatives (pluripotency). Although the majority of ESCs divide without losing the pluripotency, it has become evident that ESC cultures consists of multiple cell populations highlighted by the expression of early germ lineage markers during spontaneous differentiation. Hence, the identification and characterization of ESCs subpopulations represents an efficient approach to improve the comprehension of correlation between gene expression and cell specification status. To study markers of ESCs heterogeneity, we developed an analysis pipeline which can automatically process images of stem cell colonies in optical microscopy. The question we try to address is to find out the statistically significant preferred locations of the marked cells. We tested our algorithm on a set of images of stem cell colonies to analyze the expression pattern of the Zscan4 gene, which was an elite candidate gene to be studied because it is specifically expressed in subpopulation of ESCs. To validate the proposed method we analyzed the behavior of control genes whose pattern had been associated to biological status such as differentiation (EndoA), pluripotency (Pou5f1), and pluripotency fluctuation (Nanog). We found that Zscan4 is not uniformly expressed inside a stem cell colony, and that it tends to be expressed towards the center of the colony, moreover cells expressing Zscan4 cluster each other. This is of significant importance because it allows us to hypothesize a biological status where the cells expressing Zscan4 are preferably associated to the inner of colonies suggesting pluripotent cell status features, and the clustering between themselves suggests either a colony paracrine effect or an early phase of cell specification through proliferation. Also, the analysis on the control genes showed that they behave as expected. |
format | Online Article Text |
id | pubmed-3857180 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-38571802013-12-13 Automated Identification and Location Analysis of Marked Stem Cells Colonies in Optical Microscopy Images Paduano, Vincenzo Tagliaferri, Daniela Falco, Geppino Ceccarelli, Michele PLoS One Research Article Embryonic stem cells (ESCs) are characterized by two remarkable peculiarities: the capacity to propagate as undifferentiated cells (self-renewal) and the ability to differentiate in ectoderm, endoderm, and mesoderm derivatives (pluripotency). Although the majority of ESCs divide without losing the pluripotency, it has become evident that ESC cultures consists of multiple cell populations highlighted by the expression of early germ lineage markers during spontaneous differentiation. Hence, the identification and characterization of ESCs subpopulations represents an efficient approach to improve the comprehension of correlation between gene expression and cell specification status. To study markers of ESCs heterogeneity, we developed an analysis pipeline which can automatically process images of stem cell colonies in optical microscopy. The question we try to address is to find out the statistically significant preferred locations of the marked cells. We tested our algorithm on a set of images of stem cell colonies to analyze the expression pattern of the Zscan4 gene, which was an elite candidate gene to be studied because it is specifically expressed in subpopulation of ESCs. To validate the proposed method we analyzed the behavior of control genes whose pattern had been associated to biological status such as differentiation (EndoA), pluripotency (Pou5f1), and pluripotency fluctuation (Nanog). We found that Zscan4 is not uniformly expressed inside a stem cell colony, and that it tends to be expressed towards the center of the colony, moreover cells expressing Zscan4 cluster each other. This is of significant importance because it allows us to hypothesize a biological status where the cells expressing Zscan4 are preferably associated to the inner of colonies suggesting pluripotent cell status features, and the clustering between themselves suggests either a colony paracrine effect or an early phase of cell specification through proliferation. Also, the analysis on the control genes showed that they behave as expected. Public Library of Science 2013-12-09 /pmc/articles/PMC3857180/ /pubmed/24349016 http://dx.doi.org/10.1371/journal.pone.0080776 Text en © 2013 Paduano et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Paduano, Vincenzo Tagliaferri, Daniela Falco, Geppino Ceccarelli, Michele Automated Identification and Location Analysis of Marked Stem Cells Colonies in Optical Microscopy Images |
title | Automated Identification and Location Analysis of Marked Stem Cells Colonies in Optical Microscopy Images |
title_full | Automated Identification and Location Analysis of Marked Stem Cells Colonies in Optical Microscopy Images |
title_fullStr | Automated Identification and Location Analysis of Marked Stem Cells Colonies in Optical Microscopy Images |
title_full_unstemmed | Automated Identification and Location Analysis of Marked Stem Cells Colonies in Optical Microscopy Images |
title_short | Automated Identification and Location Analysis of Marked Stem Cells Colonies in Optical Microscopy Images |
title_sort | automated identification and location analysis of marked stem cells colonies in optical microscopy images |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3857180/ https://www.ncbi.nlm.nih.gov/pubmed/24349016 http://dx.doi.org/10.1371/journal.pone.0080776 |
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