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A theoretical framework of immune cell phenotypic classification and discovery

Immune cells are highly heterogeneous and show diverse phenotypes, but the underlying mechanism remains to be elucidated. In this study, we proposed a theoretical framework for immune cell phenotypic classification based on gene plasticity, which herein refers to expressional change or variability i...

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Detalles Bibliográficos
Autores principales: Hu, Yuzhe, Liu, Chen, Han, Wenling, Wang, Pingzhang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018129/
https://www.ncbi.nlm.nih.gov/pubmed/36936975
http://dx.doi.org/10.3389/fimmu.2023.1128423
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author Hu, Yuzhe
Liu, Chen
Han, Wenling
Wang, Pingzhang
author_facet Hu, Yuzhe
Liu, Chen
Han, Wenling
Wang, Pingzhang
author_sort Hu, Yuzhe
collection PubMed
description Immune cells are highly heterogeneous and show diverse phenotypes, but the underlying mechanism remains to be elucidated. In this study, we proposed a theoretical framework for immune cell phenotypic classification based on gene plasticity, which herein refers to expressional change or variability in response to conditions. The system contains two core points. One is that the functional subsets of immune cells can be further divided into subdivisions based on their highly plastic genes, and the other is that loss of phenotype accompanies gain of phenotype during phenotypic conversion. The first point suggests phenotypic stratification or layerability according to gene plasticity, while the second point reveals expressional compatibility and mutual exclusion during the change in gene plasticity states. Abundant transcriptome data analysis in this study from both microarray and RNA sequencing in human CD4 and CD8 single-positive T cells, B cells, natural killer cells and monocytes supports the logical rationality and generality, as well as expansibility, across immune cells. A collection of thousands of known immunophenotypes reported in the literature further supports that highly plastic genes play an important role in maintaining immune cell phenotypes and reveals that the current classification model is compatible with the traditionally defined functional subsets. The system provides a new perspective to understand the characteristics of dynamic, diversified immune cell phenotypes and intrinsic regulation in the immune system. Moreover, the current substantial results based on plasticitomics analysis of bulk and single-cell sequencing data provide a useful resource for big-data–driven experimental studies and knowledge discoveries.
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spelling pubmed-100181292023-03-17 A theoretical framework of immune cell phenotypic classification and discovery Hu, Yuzhe Liu, Chen Han, Wenling Wang, Pingzhang Front Immunol Immunology Immune cells are highly heterogeneous and show diverse phenotypes, but the underlying mechanism remains to be elucidated. In this study, we proposed a theoretical framework for immune cell phenotypic classification based on gene plasticity, which herein refers to expressional change or variability in response to conditions. The system contains two core points. One is that the functional subsets of immune cells can be further divided into subdivisions based on their highly plastic genes, and the other is that loss of phenotype accompanies gain of phenotype during phenotypic conversion. The first point suggests phenotypic stratification or layerability according to gene plasticity, while the second point reveals expressional compatibility and mutual exclusion during the change in gene plasticity states. Abundant transcriptome data analysis in this study from both microarray and RNA sequencing in human CD4 and CD8 single-positive T cells, B cells, natural killer cells and monocytes supports the logical rationality and generality, as well as expansibility, across immune cells. A collection of thousands of known immunophenotypes reported in the literature further supports that highly plastic genes play an important role in maintaining immune cell phenotypes and reveals that the current classification model is compatible with the traditionally defined functional subsets. The system provides a new perspective to understand the characteristics of dynamic, diversified immune cell phenotypes and intrinsic regulation in the immune system. Moreover, the current substantial results based on plasticitomics analysis of bulk and single-cell sequencing data provide a useful resource for big-data–driven experimental studies and knowledge discoveries. Frontiers Media S.A. 2023-03-02 /pmc/articles/PMC10018129/ /pubmed/36936975 http://dx.doi.org/10.3389/fimmu.2023.1128423 Text en Copyright © 2023 Hu, Liu, Han and Wang https://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
Hu, Yuzhe
Liu, Chen
Han, Wenling
Wang, Pingzhang
A theoretical framework of immune cell phenotypic classification and discovery
title A theoretical framework of immune cell phenotypic classification and discovery
title_full A theoretical framework of immune cell phenotypic classification and discovery
title_fullStr A theoretical framework of immune cell phenotypic classification and discovery
title_full_unstemmed A theoretical framework of immune cell phenotypic classification and discovery
title_short A theoretical framework of immune cell phenotypic classification and discovery
title_sort theoretical framework of immune cell phenotypic classification and discovery
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018129/
https://www.ncbi.nlm.nih.gov/pubmed/36936975
http://dx.doi.org/10.3389/fimmu.2023.1128423
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