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A Computational Model for Understanding Stem Cell, Trophectoderm and Endoderm Lineage Determination

BACKGROUND: Recent studies have associated the transcription factors, Oct4, Sox2 and Nanog as parts of a self-regulating network which is responsible for maintaining embryonic stem cell properties: self renewal and pluripotency. In addition, mutual antagonism between two of these and other master re...

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Autores principales: Chickarmane, Vijay, Peterson, Carsten
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2566811/
https://www.ncbi.nlm.nih.gov/pubmed/18941526
http://dx.doi.org/10.1371/journal.pone.0003478
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author Chickarmane, Vijay
Peterson, Carsten
author_facet Chickarmane, Vijay
Peterson, Carsten
author_sort Chickarmane, Vijay
collection PubMed
description BACKGROUND: Recent studies have associated the transcription factors, Oct4, Sox2 and Nanog as parts of a self-regulating network which is responsible for maintaining embryonic stem cell properties: self renewal and pluripotency. In addition, mutual antagonism between two of these and other master regulators have been shown to regulate lineage determination. In particular, an excess of Cdx2 over Oct4 determines the trophectoderm lineage whereas an excess of Gata-6 over Nanog determines differentiation into the endoderm lineage. Also, under/over-expression studies of the master regulator Oct4 have revealed that some self-renewal/pluripotency as well as differentiation genes are expressed in a biphasic manner with respect to the concentration of Oct4. METHODOLOGY/PRINCIPAL FINDINGS: We construct a dynamical model of a minimalistic network, extracted from ChIP-on-chip and microarray data as well as literature studies. The model is based upon differential equations and makes two plausible assumptions; activation of Gata-6 by Oct4 and repression of Nanog by an Oct4–Gata-6 heterodimer. With these assumptions, the results of simulations successfully describe the biphasic behavior as well as lineage commitment. The model also predicts that reprogramming the network from a differentiated state, in particular the endoderm state, into a stem cell state, is best achieved by over-expressing Nanog, rather than by suppression of differentiation genes such as Gata-6. CONCLUSIONS: The computational model provides a mechanistic understanding of how different lineages arise from the dynamics of the underlying regulatory network. It provides a framework to explore strategies of reprogramming a cell from a differentiated state to a stem cell state through directed perturbations. Such an approach is highly relevant to regenerative medicine since it allows for a rapid search over the host of possibilities for reprogramming to a stem cell state.
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spelling pubmed-25668112008-10-22 A Computational Model for Understanding Stem Cell, Trophectoderm and Endoderm Lineage Determination Chickarmane, Vijay Peterson, Carsten PLoS One Research Article BACKGROUND: Recent studies have associated the transcription factors, Oct4, Sox2 and Nanog as parts of a self-regulating network which is responsible for maintaining embryonic stem cell properties: self renewal and pluripotency. In addition, mutual antagonism between two of these and other master regulators have been shown to regulate lineage determination. In particular, an excess of Cdx2 over Oct4 determines the trophectoderm lineage whereas an excess of Gata-6 over Nanog determines differentiation into the endoderm lineage. Also, under/over-expression studies of the master regulator Oct4 have revealed that some self-renewal/pluripotency as well as differentiation genes are expressed in a biphasic manner with respect to the concentration of Oct4. METHODOLOGY/PRINCIPAL FINDINGS: We construct a dynamical model of a minimalistic network, extracted from ChIP-on-chip and microarray data as well as literature studies. The model is based upon differential equations and makes two plausible assumptions; activation of Gata-6 by Oct4 and repression of Nanog by an Oct4–Gata-6 heterodimer. With these assumptions, the results of simulations successfully describe the biphasic behavior as well as lineage commitment. The model also predicts that reprogramming the network from a differentiated state, in particular the endoderm state, into a stem cell state, is best achieved by over-expressing Nanog, rather than by suppression of differentiation genes such as Gata-6. CONCLUSIONS: The computational model provides a mechanistic understanding of how different lineages arise from the dynamics of the underlying regulatory network. It provides a framework to explore strategies of reprogramming a cell from a differentiated state to a stem cell state through directed perturbations. Such an approach is highly relevant to regenerative medicine since it allows for a rapid search over the host of possibilities for reprogramming to a stem cell state. Public Library of Science 2008-10-22 /pmc/articles/PMC2566811/ /pubmed/18941526 http://dx.doi.org/10.1371/journal.pone.0003478 Text en Chickarmane 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
Chickarmane, Vijay
Peterson, Carsten
A Computational Model for Understanding Stem Cell, Trophectoderm and Endoderm Lineage Determination
title A Computational Model for Understanding Stem Cell, Trophectoderm and Endoderm Lineage Determination
title_full A Computational Model for Understanding Stem Cell, Trophectoderm and Endoderm Lineage Determination
title_fullStr A Computational Model for Understanding Stem Cell, Trophectoderm and Endoderm Lineage Determination
title_full_unstemmed A Computational Model for Understanding Stem Cell, Trophectoderm and Endoderm Lineage Determination
title_short A Computational Model for Understanding Stem Cell, Trophectoderm and Endoderm Lineage Determination
title_sort computational model for understanding stem cell, trophectoderm and endoderm lineage determination
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2566811/
https://www.ncbi.nlm.nih.gov/pubmed/18941526
http://dx.doi.org/10.1371/journal.pone.0003478
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