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Transcriptomic profiles of aging in naïve and memory CD4(+) cells from mice

BACKGROUND: CD4+ T cells can be broadly divided into naïve and memory subsets, each of which are differentially impaired by the aging process. It is unclear if and how these differences are reflected at the transcriptomic level. We performed microarray profiling on RNA derived from naïve (CD44(low))...

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Autores principales: Taylor, Jackson, Reynolds, Lindsay, Hou, Li, Lohman, Kurt, Cui, Wei, Kritchevsky, Stephen, McCall, Charles, Liu, Yongmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5477126/
https://www.ncbi.nlm.nih.gov/pubmed/28642803
http://dx.doi.org/10.1186/s12979-017-0092-5
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author Taylor, Jackson
Reynolds, Lindsay
Hou, Li
Lohman, Kurt
Cui, Wei
Kritchevsky, Stephen
McCall, Charles
Liu, Yongmei
author_facet Taylor, Jackson
Reynolds, Lindsay
Hou, Li
Lohman, Kurt
Cui, Wei
Kritchevsky, Stephen
McCall, Charles
Liu, Yongmei
author_sort Taylor, Jackson
collection PubMed
description BACKGROUND: CD4+ T cells can be broadly divided into naïve and memory subsets, each of which are differentially impaired by the aging process. It is unclear if and how these differences are reflected at the transcriptomic level. We performed microarray profiling on RNA derived from naïve (CD44(low)) and memory (CD44(high)) CD4+ T cells derived from young (2–3 month) and old (28 month) mice, in order to better understand the mechanisms of age-related functional alterations in both subsets. We also performed follow-up bioinformatic analyses in order to determine the functional consequences of gene expression changes in both of these subsets, and identify regulatory factors potentially responsible for these changes. RESULTS: We found 185 and 328 genes differentially expressed (FDR ≤ 0.05) in young vs. old naïve and memory cells, respectively, with 50 genes differentially expressed in both subsets. Functional annotation analyses highlighted an increase in genes involved in apoptosis specific to aged naïve cells. Both subsets shared age-related increases in inflammatory signaling genes, along with a decrease in oxidative phosphorylation genes. Cis-regulatory analyses revealed enrichment of multiple transcription factor binding sites near genes with age-associated expression, in particular NF-κB and several forkhead box transcription factors. Enhancer associated histone modifications were enriched near genes down-regulated in naïve cells. Comparison of our results with previous mouse and human datasets indicates few overlapping genes overall, but suggest consistent up-regulation of Casp1 and Il1r2, and down-regulation of Foxp1 in both mouse and human CD4+ T cells. CONCLUSIONS: The transcriptomes of naïve and memory CD4+ T cells are distinctly affected by the aging process. However, both subsets exhibit a common increase inflammatory genes and decrease in oxidative phosphorylation genes. NF-κB, forkhead box, and Myc transcription factors are implicated as upstream regulators of these gene expression changes in both subsets, with enhancer histone modifications potentially driving unique changes unique to naïve cells. Finally we conclude that there is little overlap in age-related gene expression changes between humans and mice; however, age-related alterations in a small subset of genes may be conserved. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12979-017-0092-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-54771262017-06-22 Transcriptomic profiles of aging in naïve and memory CD4(+) cells from mice Taylor, Jackson Reynolds, Lindsay Hou, Li Lohman, Kurt Cui, Wei Kritchevsky, Stephen McCall, Charles Liu, Yongmei Immun Ageing Research BACKGROUND: CD4+ T cells can be broadly divided into naïve and memory subsets, each of which are differentially impaired by the aging process. It is unclear if and how these differences are reflected at the transcriptomic level. We performed microarray profiling on RNA derived from naïve (CD44(low)) and memory (CD44(high)) CD4+ T cells derived from young (2–3 month) and old (28 month) mice, in order to better understand the mechanisms of age-related functional alterations in both subsets. We also performed follow-up bioinformatic analyses in order to determine the functional consequences of gene expression changes in both of these subsets, and identify regulatory factors potentially responsible for these changes. RESULTS: We found 185 and 328 genes differentially expressed (FDR ≤ 0.05) in young vs. old naïve and memory cells, respectively, with 50 genes differentially expressed in both subsets. Functional annotation analyses highlighted an increase in genes involved in apoptosis specific to aged naïve cells. Both subsets shared age-related increases in inflammatory signaling genes, along with a decrease in oxidative phosphorylation genes. Cis-regulatory analyses revealed enrichment of multiple transcription factor binding sites near genes with age-associated expression, in particular NF-κB and several forkhead box transcription factors. Enhancer associated histone modifications were enriched near genes down-regulated in naïve cells. Comparison of our results with previous mouse and human datasets indicates few overlapping genes overall, but suggest consistent up-regulation of Casp1 and Il1r2, and down-regulation of Foxp1 in both mouse and human CD4+ T cells. CONCLUSIONS: The transcriptomes of naïve and memory CD4+ T cells are distinctly affected by the aging process. However, both subsets exhibit a common increase inflammatory genes and decrease in oxidative phosphorylation genes. NF-κB, forkhead box, and Myc transcription factors are implicated as upstream regulators of these gene expression changes in both subsets, with enhancer histone modifications potentially driving unique changes unique to naïve cells. Finally we conclude that there is little overlap in age-related gene expression changes between humans and mice; however, age-related alterations in a small subset of genes may be conserved. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12979-017-0092-5) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-20 /pmc/articles/PMC5477126/ /pubmed/28642803 http://dx.doi.org/10.1186/s12979-017-0092-5 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Taylor, Jackson
Reynolds, Lindsay
Hou, Li
Lohman, Kurt
Cui, Wei
Kritchevsky, Stephen
McCall, Charles
Liu, Yongmei
Transcriptomic profiles of aging in naïve and memory CD4(+) cells from mice
title Transcriptomic profiles of aging in naïve and memory CD4(+) cells from mice
title_full Transcriptomic profiles of aging in naïve and memory CD4(+) cells from mice
title_fullStr Transcriptomic profiles of aging in naïve and memory CD4(+) cells from mice
title_full_unstemmed Transcriptomic profiles of aging in naïve and memory CD4(+) cells from mice
title_short Transcriptomic profiles of aging in naïve and memory CD4(+) cells from mice
title_sort transcriptomic profiles of aging in naïve and memory cd4(+) cells from mice
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5477126/
https://www.ncbi.nlm.nih.gov/pubmed/28642803
http://dx.doi.org/10.1186/s12979-017-0092-5
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