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Mathematical Analysis of Cytokine-Induced Differentiation of Granulocyte-Monocyte Progenitor Cells
Granulocyte-monocyte progenitor (GMP) cells play a vital role in the immune system by maturing into a variety of white blood cells, including neutrophils and macrophages, depending on exposure to cytokines such as various types of colony stimulating factors (CSF). Granulocyte-CSF (G-CSF) induces gra...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153365/ https://www.ncbi.nlm.nih.gov/pubmed/30279691 http://dx.doi.org/10.3389/fimmu.2018.02048 |
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author | Weston, Bronson R. Li, Liwu Tyson, John J. |
author_facet | Weston, Bronson R. Li, Liwu Tyson, John J. |
author_sort | Weston, Bronson R. |
collection | PubMed |
description | Granulocyte-monocyte progenitor (GMP) cells play a vital role in the immune system by maturing into a variety of white blood cells, including neutrophils and macrophages, depending on exposure to cytokines such as various types of colony stimulating factors (CSF). Granulocyte-CSF (G-CSF) induces granulopoiesis and macrophage-CSF (M-CSF) induces monopoiesis, while granulocyte/macrophage-CSF (GM-CSF) favors monocytic and granulocytic differentiation at low and high concentrations, respectively. Although these differentiation pathways are well documented, the mechanisms behind the diverse behavioral responses of GMP cells to CSFs are not well understood. In this paper, we propose a mechanism of interacting CSF-receptors and transcription factors that control GMP differentiation, convert the mechanism into a set of differential equations, and explore the properties of this mathematical model using dynamical systems theory. Our model reproduces numerous experimental observations of GMP cell differentiation in response to varying dosages of G-CSF, M-CSF, and GM-CSF. In particular, we are able to reproduce the concentration-dependent behavior of GM-CSF induced differentiation, and propose a mechanism driving this behavior. In addition, we explore the differentiation of a fourth phenotype, monocytic myeloid-derived suppressor cells (M-MDSC), showing how they might fit into the classical pathways of GMP differentiation and how progenitor cells can be primed for M-MDSC differentiation. Finally, we use the model to make novel predictions that can be explored by future experimental studies. |
format | Online Article Text |
id | pubmed-6153365 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61533652018-10-02 Mathematical Analysis of Cytokine-Induced Differentiation of Granulocyte-Monocyte Progenitor Cells Weston, Bronson R. Li, Liwu Tyson, John J. Front Immunol Immunology Granulocyte-monocyte progenitor (GMP) cells play a vital role in the immune system by maturing into a variety of white blood cells, including neutrophils and macrophages, depending on exposure to cytokines such as various types of colony stimulating factors (CSF). Granulocyte-CSF (G-CSF) induces granulopoiesis and macrophage-CSF (M-CSF) induces monopoiesis, while granulocyte/macrophage-CSF (GM-CSF) favors monocytic and granulocytic differentiation at low and high concentrations, respectively. Although these differentiation pathways are well documented, the mechanisms behind the diverse behavioral responses of GMP cells to CSFs are not well understood. In this paper, we propose a mechanism of interacting CSF-receptors and transcription factors that control GMP differentiation, convert the mechanism into a set of differential equations, and explore the properties of this mathematical model using dynamical systems theory. Our model reproduces numerous experimental observations of GMP cell differentiation in response to varying dosages of G-CSF, M-CSF, and GM-CSF. In particular, we are able to reproduce the concentration-dependent behavior of GM-CSF induced differentiation, and propose a mechanism driving this behavior. In addition, we explore the differentiation of a fourth phenotype, monocytic myeloid-derived suppressor cells (M-MDSC), showing how they might fit into the classical pathways of GMP differentiation and how progenitor cells can be primed for M-MDSC differentiation. Finally, we use the model to make novel predictions that can be explored by future experimental studies. Frontiers Media S.A. 2018-09-18 /pmc/articles/PMC6153365/ /pubmed/30279691 http://dx.doi.org/10.3389/fimmu.2018.02048 Text en Copyright © 2018 Weston, Li and Tyson. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Weston, Bronson R. Li, Liwu Tyson, John J. Mathematical Analysis of Cytokine-Induced Differentiation of Granulocyte-Monocyte Progenitor Cells |
title | Mathematical Analysis of Cytokine-Induced Differentiation of Granulocyte-Monocyte Progenitor Cells |
title_full | Mathematical Analysis of Cytokine-Induced Differentiation of Granulocyte-Monocyte Progenitor Cells |
title_fullStr | Mathematical Analysis of Cytokine-Induced Differentiation of Granulocyte-Monocyte Progenitor Cells |
title_full_unstemmed | Mathematical Analysis of Cytokine-Induced Differentiation of Granulocyte-Monocyte Progenitor Cells |
title_short | Mathematical Analysis of Cytokine-Induced Differentiation of Granulocyte-Monocyte Progenitor Cells |
title_sort | mathematical analysis of cytokine-induced differentiation of granulocyte-monocyte progenitor cells |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153365/ https://www.ncbi.nlm.nih.gov/pubmed/30279691 http://dx.doi.org/10.3389/fimmu.2018.02048 |
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