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Data-Driven Mathematical Model of Apoptosis Regulation in Memory Plasma Cells
Memory plasma cells constitutively produce copious amounts of antibodies, imposing a critical risk factor for autoimmune disease. We previously found that plasma cell survival requires secreted factors such as APRIL and direct contact to stromal cells, which act in concert to activate NF-κB- and PI3...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9102437/ https://www.ncbi.nlm.nih.gov/pubmed/35563853 http://dx.doi.org/10.3390/cells11091547 |
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author | Burt, Philipp Cornelis, Rebecca Geißler, Gustav Hahne, Stefanie Radbruch, Andreas Chang, Hyun-Dong Thurley, Kevin |
author_facet | Burt, Philipp Cornelis, Rebecca Geißler, Gustav Hahne, Stefanie Radbruch, Andreas Chang, Hyun-Dong Thurley, Kevin |
author_sort | Burt, Philipp |
collection | PubMed |
description | Memory plasma cells constitutively produce copious amounts of antibodies, imposing a critical risk factor for autoimmune disease. We previously found that plasma cell survival requires secreted factors such as APRIL and direct contact to stromal cells, which act in concert to activate NF-κB- and PI3K-dependent signaling pathways to prevent cell death. However, the regulatory properties of the underlying biochemical network are confounded by the complexity of potential interaction and cross-regulation pathways. Here, based on flow-cytometric quantification of key signaling proteins in the presence or absence of the survival signals APRIL and contact to the stromal cell line ST2, we generated a quantitative model of plasma cell survival. Our model emphasizes the non-redundant nature of the two plasma cell survival signals APRIL and stromal cell contact, and highlights a requirement for differential regulation of individual caspases. The modeling approach allowed us to unify distinct data sets and derive a consistent picture of the intertwined signaling and apoptosis pathways regulating plasma cell survival. |
format | Online Article Text |
id | pubmed-9102437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91024372022-05-14 Data-Driven Mathematical Model of Apoptosis Regulation in Memory Plasma Cells Burt, Philipp Cornelis, Rebecca Geißler, Gustav Hahne, Stefanie Radbruch, Andreas Chang, Hyun-Dong Thurley, Kevin Cells Article Memory plasma cells constitutively produce copious amounts of antibodies, imposing a critical risk factor for autoimmune disease. We previously found that plasma cell survival requires secreted factors such as APRIL and direct contact to stromal cells, which act in concert to activate NF-κB- and PI3K-dependent signaling pathways to prevent cell death. However, the regulatory properties of the underlying biochemical network are confounded by the complexity of potential interaction and cross-regulation pathways. Here, based on flow-cytometric quantification of key signaling proteins in the presence or absence of the survival signals APRIL and contact to the stromal cell line ST2, we generated a quantitative model of plasma cell survival. Our model emphasizes the non-redundant nature of the two plasma cell survival signals APRIL and stromal cell contact, and highlights a requirement for differential regulation of individual caspases. The modeling approach allowed us to unify distinct data sets and derive a consistent picture of the intertwined signaling and apoptosis pathways regulating plasma cell survival. MDPI 2022-05-05 /pmc/articles/PMC9102437/ /pubmed/35563853 http://dx.doi.org/10.3390/cells11091547 Text en © 2022 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 Burt, Philipp Cornelis, Rebecca Geißler, Gustav Hahne, Stefanie Radbruch, Andreas Chang, Hyun-Dong Thurley, Kevin Data-Driven Mathematical Model of Apoptosis Regulation in Memory Plasma Cells |
title | Data-Driven Mathematical Model of Apoptosis Regulation in Memory Plasma Cells |
title_full | Data-Driven Mathematical Model of Apoptosis Regulation in Memory Plasma Cells |
title_fullStr | Data-Driven Mathematical Model of Apoptosis Regulation in Memory Plasma Cells |
title_full_unstemmed | Data-Driven Mathematical Model of Apoptosis Regulation in Memory Plasma Cells |
title_short | Data-Driven Mathematical Model of Apoptosis Regulation in Memory Plasma Cells |
title_sort | data-driven mathematical model of apoptosis regulation in memory plasma cells |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9102437/ https://www.ncbi.nlm.nih.gov/pubmed/35563853 http://dx.doi.org/10.3390/cells11091547 |
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