OMIP-104: A 30-color spectral flow cytometry panel for comprehensive analysis of immune cell composition and macrophage subsets in mouse metabolic organs

IF 2.5 4区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS
Joost M. Lambooij, Tamar Tak, Arnaud Zaldumbide, Bruno Guigas
{"title":"OMIP-104: A 30-color spectral flow cytometry panel for comprehensive analysis of immune cell composition and macrophage subsets in mouse metabolic organs","authors":"Joost M. Lambooij,&nbsp;Tamar Tak,&nbsp;Arnaud Zaldumbide,&nbsp;Bruno Guigas","doi":"10.1002/cyto.a.24845","DOIUrl":null,"url":null,"abstract":"<p>Obesity-induced chronic low-grade inflammation, also known as metaflammation, results from alterations of the immune response in metabolic organs and contributes to the development of fatty liver diseases and type 2 diabetes. The diversity of tissue-resident leukocytes involved in these metabolic dysfunctions warrants an in-depth immunophenotyping in order to elucidate disease etiology. Here, we present a 30-color, full spectrum flow cytometry panel, designed to (i) identify the major innate and adaptive immune cell subsets in murine liver and white adipose tissues and (ii) discriminate various tissue-specific myeloid subsets known to contribute to the development of metabolic dysfunctions. This panel notably allows for distinguishing embryonically-derived liver-resident Kupffer cells from newly recruited monocyte-derived macrophages and KCs. Furthermore, several adipose tissue macrophage (ATM) subsets, including perivascular macrophages, lipid-associated macrophages, and pro-inflammatory CD11c<sup>+</sup> ATMs, can also be identified. Finally, the panel includes cell-surface markers that have been associated with metabolic activation of different macrophage and dendritic cell subsets. Altogether, our spectral flow cytometry panel allows for an extensive immunophenotyping of murine metabolic tissues, with a particular focus on metabolically-relevant myeloid cell subsets, and can easily be adjusted to include various new markers if needed.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24845","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cytometry Part A","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cyto.a.24845","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Obesity-induced chronic low-grade inflammation, also known as metaflammation, results from alterations of the immune response in metabolic organs and contributes to the development of fatty liver diseases and type 2 diabetes. The diversity of tissue-resident leukocytes involved in these metabolic dysfunctions warrants an in-depth immunophenotyping in order to elucidate disease etiology. Here, we present a 30-color, full spectrum flow cytometry panel, designed to (i) identify the major innate and adaptive immune cell subsets in murine liver and white adipose tissues and (ii) discriminate various tissue-specific myeloid subsets known to contribute to the development of metabolic dysfunctions. This panel notably allows for distinguishing embryonically-derived liver-resident Kupffer cells from newly recruited monocyte-derived macrophages and KCs. Furthermore, several adipose tissue macrophage (ATM) subsets, including perivascular macrophages, lipid-associated macrophages, and pro-inflammatory CD11c+ ATMs, can also be identified. Finally, the panel includes cell-surface markers that have been associated with metabolic activation of different macrophage and dendritic cell subsets. Altogether, our spectral flow cytometry panel allows for an extensive immunophenotyping of murine metabolic tissues, with a particular focus on metabolically-relevant myeloid cell subsets, and can easily be adjusted to include various new markers if needed.

Abstract Image

用于全面分析小鼠代谢器官中免疫细胞组成和巨噬细胞亚群的 30 色光谱流式细胞仪面板
肥胖诱发的慢性低度炎症(又称变态反应性炎症)是代谢器官免疫反应改变的结果,也是脂肪肝和 2 型糖尿病的诱因。参与这些代谢功能障碍的组织驻留白细胞多种多样,因此需要进行深入的免疫分型,以阐明疾病的病因。在这里,我们展示了一种 30 色全光谱流式细胞仪面板,旨在(i)识别小鼠肝脏和白色脂肪组织中的主要先天性和适应性免疫细胞亚群;(ii)区分已知会导致代谢功能障碍发生的各种组织特异性髓系细胞亚群。该面板可将胚胎衍生的肝脏驻留 Kupffer 细胞与新招募的单核细胞衍生巨噬细胞和 KC 区分开来。此外,还能识别几个脂肪组织巨噬细胞(ATM)亚群,包括血管周围巨噬细胞、脂质相关巨噬细胞和促炎性 CD11c+ ATMs。最后,该面板还包括与不同巨噬细胞和树突状细胞亚群的代谢活化相关的细胞表面标记。总之,我们的光谱流式细胞仪面板可以对小鼠的代谢组织进行广泛的免疫分型,尤其侧重于与代谢相关的髓样细胞亚群,并可根据需要轻松调整以纳入各种新的标记物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Cytometry Part A
Cytometry Part A 生物-生化研究方法
CiteScore
8.10
自引率
13.50%
发文量
183
审稿时长
4-8 weeks
期刊介绍: Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques. The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome: Biomedical Instrumentation Engineering Biophotonics Bioinformatics Cell Biology Computational Biology Data Science Immunology Parasitology Microbiology Neuroscience Cancer Stem Cells Tissue Regeneration.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信