用于小鼠肺部深度免疫分型的全谱流式细胞仪优化面板。

IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Cell Reports Methods Pub Date : 2024-10-24 DOI:10.1016/j.crmeth.2024.100885
Zora Baumann, Carsten Wiethe, Cinja M Vecchi, Veronica Richina, Telma Lopes, Mohamed Bentires-Alj
{"title":"用于小鼠肺部深度免疫分型的全谱流式细胞仪优化面板。","authors":"Zora Baumann, Carsten Wiethe, Cinja M Vecchi, Veronica Richina, Telma Lopes, Mohamed Bentires-Alj","doi":"10.1016/j.crmeth.2024.100885","DOIUrl":null,"url":null,"abstract":"<p><p>The lung immune system consists of both resident and circulating immune cells that communicate intricately. The immune system is activated by exposure to bacteria and viruses, when cancer initiates in the lung (primary lung cancer), or when metastases of other cancer types, including breast cancer, spread to and develop in the lung (secondary lung cancer). Thus, in these pathological situations, a comprehensive and quantitative assessment of changes in the lung immune system is of paramount importance for understanding mechanisms of infectious diseases, lung cancer, and metastasis but also for developing efficacious treatments. Unfortunately, lung tissue exhibits high autofluorescence, and this high background signal makes high-parameter flow cytometry analysis complicated. Here, we provide an optimized 30-parameter antibody panel for the analysis of all major immune cell types and states in normal and metastatic murine lungs using spectral flow cytometry.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimized full-spectrum flow cytometry panel for deep immunophenotyping of murine lungs.\",\"authors\":\"Zora Baumann, Carsten Wiethe, Cinja M Vecchi, Veronica Richina, Telma Lopes, Mohamed Bentires-Alj\",\"doi\":\"10.1016/j.crmeth.2024.100885\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The lung immune system consists of both resident and circulating immune cells that communicate intricately. The immune system is activated by exposure to bacteria and viruses, when cancer initiates in the lung (primary lung cancer), or when metastases of other cancer types, including breast cancer, spread to and develop in the lung (secondary lung cancer). Thus, in these pathological situations, a comprehensive and quantitative assessment of changes in the lung immune system is of paramount importance for understanding mechanisms of infectious diseases, lung cancer, and metastasis but also for developing efficacious treatments. Unfortunately, lung tissue exhibits high autofluorescence, and this high background signal makes high-parameter flow cytometry analysis complicated. Here, we provide an optimized 30-parameter antibody panel for the analysis of all major immune cell types and states in normal and metastatic murine lungs using spectral flow cytometry.</p>\",\"PeriodicalId\":29773,\"journal\":{\"name\":\"Cell Reports Methods\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell Reports Methods\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.crmeth.2024.100885\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell Reports Methods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.crmeth.2024.100885","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

摘要

肺部免疫系统由常驻免疫细胞和循环免疫细胞组成,两者之间存在着错综复杂的联系。接触细菌和病毒、肺部发生癌症(原发性肺癌)或包括乳腺癌在内的其他癌症转移到肺部并在肺部发展(继发性肺癌)时,免疫系统都会被激活。因此,在这些病理情况下,全面、定量地评估肺部免疫系统的变化对于了解感染性疾病、肺癌和转移的机制以及开发有效的治疗方法至关重要。遗憾的是,肺组织具有很高的自发荧光,这种高背景信号使得高参数流式细胞术分析变得复杂。在这里,我们提供了一个优化的 30 参数抗体面板,利用光谱流式细胞仪分析正常和转移性小鼠肺部的所有主要免疫细胞类型和状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Optimized full-spectrum flow cytometry panel for deep immunophenotyping of murine lungs.

The lung immune system consists of both resident and circulating immune cells that communicate intricately. The immune system is activated by exposure to bacteria and viruses, when cancer initiates in the lung (primary lung cancer), or when metastases of other cancer types, including breast cancer, spread to and develop in the lung (secondary lung cancer). Thus, in these pathological situations, a comprehensive and quantitative assessment of changes in the lung immune system is of paramount importance for understanding mechanisms of infectious diseases, lung cancer, and metastasis but also for developing efficacious treatments. Unfortunately, lung tissue exhibits high autofluorescence, and this high background signal makes high-parameter flow cytometry analysis complicated. Here, we provide an optimized 30-parameter antibody panel for the analysis of all major immune cell types and states in normal and metastatic murine lungs using spectral flow cytometry.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Cell Reports Methods
Cell Reports Methods Chemistry (General), Biochemistry, Genetics and Molecular Biology (General), Immunology and Microbiology (General)
CiteScore
3.80
自引率
0.00%
发文量
0
审稿时长
111 days
期刊最新文献
Optimized full-spectrum flow cytometry panel for deep immunophenotyping of murine lungs. A deep learning framework combining molecular image and protein structural representations identifies candidate drugs for pain. Adult zebrafish can learn Morris water maze-like tasks in a two-dimensional virtual reality system. Recovering single-cell expression profiles from spatial transcriptomics with scResolve. Mimicking and analyzing the tumor microenvironment.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1