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Digital cell quantification identifies global immune cell dynamics during influenza infection
Hundreds of immune cell types work in coordination to maintain tissue homeostasis. Upon infection, dramatic changes occur with the localization, migration, and proliferation of the immune cells to first alert the body of the danger, confine it to limit spreading, and finally extinguish the threat an...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
European Molecular Biology Organization
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4023392/ https://www.ncbi.nlm.nih.gov/pubmed/24586061 http://dx.doi.org/10.1002/msb.134947 |
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author | Altboum, Zeev Steuerman, Yael David, Eyal Barnett‐Itzhaki, Zohar Valadarsky, Liran Keren‐Shaul, Hadas Meningher, Tal Mendelson, Ella Mandelboim, Michal Gat‐Viks, Irit Amit, Ido |
author_facet | Altboum, Zeev Steuerman, Yael David, Eyal Barnett‐Itzhaki, Zohar Valadarsky, Liran Keren‐Shaul, Hadas Meningher, Tal Mendelson, Ella Mandelboim, Michal Gat‐Viks, Irit Amit, Ido |
author_sort | Altboum, Zeev |
collection | PubMed |
description | Hundreds of immune cell types work in coordination to maintain tissue homeostasis. Upon infection, dramatic changes occur with the localization, migration, and proliferation of the immune cells to first alert the body of the danger, confine it to limit spreading, and finally extinguish the threat and bring the tissue back to homeostasis. Since current technologies can follow the dynamics of only a limited number of cell types, we have yet to grasp the full complexity of global in vivo cell dynamics in normal developmental processes and disease. Here, we devise a computational method, digital cell quantification (DCQ), which combines genome‐wide gene expression data with an immune cell compendium to infer in vivo changes in the quantities of 213 immune cell subpopulations. DCQ was applied to study global immune cell dynamics in mice lungs at ten time points during 7 days of flu infection. We find dramatic changes in quantities of 70 immune cell types, including various innate, adaptive, and progenitor immune cells. We focus on the previously unreported dynamics of four immune dendritic cell subtypes and suggest a specific role for CD103(+) CD11b(−) DCs in early stages of disease and CD8(+) pDC in late stages of flu infection. |
format | Online Article Text |
id | pubmed-4023392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | European Molecular Biology Organization |
record_format | MEDLINE/PubMed |
spelling | pubmed-40233922014-05-16 Digital cell quantification identifies global immune cell dynamics during influenza infection Altboum, Zeev Steuerman, Yael David, Eyal Barnett‐Itzhaki, Zohar Valadarsky, Liran Keren‐Shaul, Hadas Meningher, Tal Mendelson, Ella Mandelboim, Michal Gat‐Viks, Irit Amit, Ido Mol Syst Biol Articles Hundreds of immune cell types work in coordination to maintain tissue homeostasis. Upon infection, dramatic changes occur with the localization, migration, and proliferation of the immune cells to first alert the body of the danger, confine it to limit spreading, and finally extinguish the threat and bring the tissue back to homeostasis. Since current technologies can follow the dynamics of only a limited number of cell types, we have yet to grasp the full complexity of global in vivo cell dynamics in normal developmental processes and disease. Here, we devise a computational method, digital cell quantification (DCQ), which combines genome‐wide gene expression data with an immune cell compendium to infer in vivo changes in the quantities of 213 immune cell subpopulations. DCQ was applied to study global immune cell dynamics in mice lungs at ten time points during 7 days of flu infection. We find dramatic changes in quantities of 70 immune cell types, including various innate, adaptive, and progenitor immune cells. We focus on the previously unreported dynamics of four immune dendritic cell subtypes and suggest a specific role for CD103(+) CD11b(−) DCs in early stages of disease and CD8(+) pDC in late stages of flu infection. European Molecular Biology Organization 2014-02-28 /pmc/articles/PMC4023392/ /pubmed/24586061 http://dx.doi.org/10.1002/msb.134947 Text en © 2014 EMBO This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/3.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Altboum, Zeev Steuerman, Yael David, Eyal Barnett‐Itzhaki, Zohar Valadarsky, Liran Keren‐Shaul, Hadas Meningher, Tal Mendelson, Ella Mandelboim, Michal Gat‐Viks, Irit Amit, Ido Digital cell quantification identifies global immune cell dynamics during influenza infection |
title | Digital cell quantification identifies global immune cell dynamics during influenza infection |
title_full | Digital cell quantification identifies global immune cell dynamics during influenza infection |
title_fullStr | Digital cell quantification identifies global immune cell dynamics during influenza infection |
title_full_unstemmed | Digital cell quantification identifies global immune cell dynamics during influenza infection |
title_short | Digital cell quantification identifies global immune cell dynamics during influenza infection |
title_sort | digital cell quantification identifies global immune cell dynamics during influenza infection |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4023392/ https://www.ncbi.nlm.nih.gov/pubmed/24586061 http://dx.doi.org/10.1002/msb.134947 |
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