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Disentangling juxtacrine from paracrine signalling in dynamic tissue
Prolactin is a major hormone product of the pituitary gland, the central endocrine regulator. Despite its physiological importance, the cell-level mechanisms of prolactin production are not well understood. Having significantly improved the resolution of real-time-single-cell-GFP-imaging, the author...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592563/ https://www.ncbi.nlm.nih.gov/pubmed/31194728 http://dx.doi.org/10.1371/journal.pcbi.1007030 |
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author | Momiji, Hiroshi Hassall, Kirsty L. Featherstone, Karen McNamara, Anne V. Patist, Amanda L. Spiller, David G. Christian, Helen C. White, Michael R. H. Davis, Julian R. E. Finkenstädt, Bärbel F. Rand, David A. |
author_facet | Momiji, Hiroshi Hassall, Kirsty L. Featherstone, Karen McNamara, Anne V. Patist, Amanda L. Spiller, David G. Christian, Helen C. White, Michael R. H. Davis, Julian R. E. Finkenstädt, Bärbel F. Rand, David A. |
author_sort | Momiji, Hiroshi |
collection | PubMed |
description | Prolactin is a major hormone product of the pituitary gland, the central endocrine regulator. Despite its physiological importance, the cell-level mechanisms of prolactin production are not well understood. Having significantly improved the resolution of real-time-single-cell-GFP-imaging, the authors recently revealed that prolactin gene transcription is highly dynamic and stochastic yet shows space-time coordination in an intact tissue slice. However, it still remains an open question as to what kind of cellular communication mediates the observed space-time organization. To determine the type of interaction between cells we developed a statistical model. The degree of similarity between two expression time series was studied in terms of two distance measures, Euclidean and geodesic, the latter being a network-theoretic distance defined to be the minimal number of edges between nodes, and this was used to discriminate between juxtacrine from paracrine signalling. The analysis presented here suggests that juxtacrine signalling dominates. To further determine whether the coupling is coordinating transcription or post-transcriptional activities we used stochastic switch modelling to infer the transcriptional profiles of cells and estimated their similarity measures to deduce that their spatial cellular coordination involves coupling of transcription via juxtacrine signalling. We developed a computational model that involves an inter-cell juxtacrine coupling, yielding simulation results that show space-time coordination in the transcription level that is in agreement with the above analysis. The developed model is expected to serve as the prototype for the further study of tissue-level organised gene expression for epigenetically regulated genes, such as prolactin. |
format | Online Article Text |
id | pubmed-6592563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65925632019-07-05 Disentangling juxtacrine from paracrine signalling in dynamic tissue Momiji, Hiroshi Hassall, Kirsty L. Featherstone, Karen McNamara, Anne V. Patist, Amanda L. Spiller, David G. Christian, Helen C. White, Michael R. H. Davis, Julian R. E. Finkenstädt, Bärbel F. Rand, David A. PLoS Comput Biol Research Article Prolactin is a major hormone product of the pituitary gland, the central endocrine regulator. Despite its physiological importance, the cell-level mechanisms of prolactin production are not well understood. Having significantly improved the resolution of real-time-single-cell-GFP-imaging, the authors recently revealed that prolactin gene transcription is highly dynamic and stochastic yet shows space-time coordination in an intact tissue slice. However, it still remains an open question as to what kind of cellular communication mediates the observed space-time organization. To determine the type of interaction between cells we developed a statistical model. The degree of similarity between two expression time series was studied in terms of two distance measures, Euclidean and geodesic, the latter being a network-theoretic distance defined to be the minimal number of edges between nodes, and this was used to discriminate between juxtacrine from paracrine signalling. The analysis presented here suggests that juxtacrine signalling dominates. To further determine whether the coupling is coordinating transcription or post-transcriptional activities we used stochastic switch modelling to infer the transcriptional profiles of cells and estimated their similarity measures to deduce that their spatial cellular coordination involves coupling of transcription via juxtacrine signalling. We developed a computational model that involves an inter-cell juxtacrine coupling, yielding simulation results that show space-time coordination in the transcription level that is in agreement with the above analysis. The developed model is expected to serve as the prototype for the further study of tissue-level organised gene expression for epigenetically regulated genes, such as prolactin. Public Library of Science 2019-06-13 /pmc/articles/PMC6592563/ /pubmed/31194728 http://dx.doi.org/10.1371/journal.pcbi.1007030 Text en © 2019 Momiji 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Momiji, Hiroshi Hassall, Kirsty L. Featherstone, Karen McNamara, Anne V. Patist, Amanda L. Spiller, David G. Christian, Helen C. White, Michael R. H. Davis, Julian R. E. Finkenstädt, Bärbel F. Rand, David A. Disentangling juxtacrine from paracrine signalling in dynamic tissue |
title | Disentangling juxtacrine from paracrine signalling in dynamic tissue |
title_full | Disentangling juxtacrine from paracrine signalling in dynamic tissue |
title_fullStr | Disentangling juxtacrine from paracrine signalling in dynamic tissue |
title_full_unstemmed | Disentangling juxtacrine from paracrine signalling in dynamic tissue |
title_short | Disentangling juxtacrine from paracrine signalling in dynamic tissue |
title_sort | disentangling juxtacrine from paracrine signalling in dynamic tissue |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592563/ https://www.ncbi.nlm.nih.gov/pubmed/31194728 http://dx.doi.org/10.1371/journal.pcbi.1007030 |
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