单细胞时间序列分析揭示了 HSPC 对炎症反应的动态变化。

IF 3.3 2区 生物学 Q1 BIOLOGY
Brigitte J Bouman, Yasmin Demerdash, Shubhankar Sood, Florian Grünschläger, Franziska Pilz, Abdul R Itani, Andrea Kuck, Valérie Marot-Lassauzaie, Simon Haas, Laleh Haghverdi, Marieke Ag Essers
{"title":"单细胞时间序列分析揭示了 HSPC 对炎症反应的动态变化。","authors":"Brigitte J Bouman, Yasmin Demerdash, Shubhankar Sood, Florian Grünschläger, Franziska Pilz, Abdul R Itani, Andrea Kuck, Valérie Marot-Lassauzaie, Simon Haas, Laleh Haghverdi, Marieke Ag Essers","doi":"10.26508/lsa.202302309","DOIUrl":null,"url":null,"abstract":"Hematopoietic stem and progenitor cells (HSPCs) are known to respond to acute inflammation; however, little is understood about the dynamics and heterogeneity of these stress responses in HSPCs. Here, we performed single-cell sequencing during the sensing, response, and recovery phases of the inflammatory response of HSPCs to treatment (a total of 10,046 cells from four time points spanning the first 72 h of response) with the pro-inflammatory cytokine IFNα to investigate the HSPCs' dynamic changes during acute inflammation. We developed the essential novel computational approaches to process and analyze the resulting single-cell time series dataset. This includes an unbiased cell type annotation and abundance analysis post inflammation, tools for identification of global and cell type-specific responding genes, and a semi-supervised linear regression approach for response pseudotime reconstruction. We discovered a variety of different gene responses of the HSPCs to the treatment. Interestingly, we were able to associate a global reduced myeloid differentiation program and a locally enhanced pyroptosis activity with reduced myeloid progenitor and differentiated cells after IFNα treatment. Altogether, the single-cell time series analyses have allowed us to unbiasedly study the heterogeneous and dynamic impact of IFNα on the HSPCs.","PeriodicalId":18081,"journal":{"name":"Life Science Alliance","volume":"22 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Single-cell time series analysis reveals the dynamics of HSPC response to inflammation.\",\"authors\":\"Brigitte J Bouman, Yasmin Demerdash, Shubhankar Sood, Florian Grünschläger, Franziska Pilz, Abdul R Itani, Andrea Kuck, Valérie Marot-Lassauzaie, Simon Haas, Laleh Haghverdi, Marieke Ag Essers\",\"doi\":\"10.26508/lsa.202302309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hematopoietic stem and progenitor cells (HSPCs) are known to respond to acute inflammation; however, little is understood about the dynamics and heterogeneity of these stress responses in HSPCs. Here, we performed single-cell sequencing during the sensing, response, and recovery phases of the inflammatory response of HSPCs to treatment (a total of 10,046 cells from four time points spanning the first 72 h of response) with the pro-inflammatory cytokine IFNα to investigate the HSPCs' dynamic changes during acute inflammation. We developed the essential novel computational approaches to process and analyze the resulting single-cell time series dataset. This includes an unbiased cell type annotation and abundance analysis post inflammation, tools for identification of global and cell type-specific responding genes, and a semi-supervised linear regression approach for response pseudotime reconstruction. We discovered a variety of different gene responses of the HSPCs to the treatment. Interestingly, we were able to associate a global reduced myeloid differentiation program and a locally enhanced pyroptosis activity with reduced myeloid progenitor and differentiated cells after IFNα treatment. Altogether, the single-cell time series analyses have allowed us to unbiasedly study the heterogeneous and dynamic impact of IFNα on the HSPCs.\",\"PeriodicalId\":18081,\"journal\":{\"name\":\"Life Science Alliance\",\"volume\":\"22 1\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2023-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Life Science Alliance\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.26508/lsa.202302309\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Life Science Alliance","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.26508/lsa.202302309","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

众所周知,造血干细胞和祖细胞(HSPCs)会对急性炎症做出反应;然而,人们对HSPCs中这些应激反应的动态性和异质性知之甚少。在这里,我们在促炎细胞因子 IFNα 处理 HSPCs 炎症反应的感应、反应和恢复阶段(共 10,046 个细胞,来自四个时间点,跨越反应的前 72 小时)进行了单细胞测序,以研究 HSPCs 在急性炎症期间的动态变化。我们开发了重要的新型计算方法来处理和分析由此产生的单细胞时间序列数据集。这包括炎症后无偏见的细胞类型注释和丰度分析、识别全局和细胞类型特异性反应基因的工具,以及用于反应伪时间重建的半监督线性回归方法。我们发现了 HSPCs 对治疗的各种不同基因反应。有趣的是,我们发现 IFNα 处理后,髓系分化程序的整体减少和局部热休克活性的增强与髓系祖细胞和分化细胞的减少有关。总之,单细胞时间序列分析使我们能够公正地研究 IFNα 对 HSPCs 的异质性动态影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-cell time series analysis reveals the dynamics of HSPC response to inflammation.
Hematopoietic stem and progenitor cells (HSPCs) are known to respond to acute inflammation; however, little is understood about the dynamics and heterogeneity of these stress responses in HSPCs. Here, we performed single-cell sequencing during the sensing, response, and recovery phases of the inflammatory response of HSPCs to treatment (a total of 10,046 cells from four time points spanning the first 72 h of response) with the pro-inflammatory cytokine IFNα to investigate the HSPCs' dynamic changes during acute inflammation. We developed the essential novel computational approaches to process and analyze the resulting single-cell time series dataset. This includes an unbiased cell type annotation and abundance analysis post inflammation, tools for identification of global and cell type-specific responding genes, and a semi-supervised linear regression approach for response pseudotime reconstruction. We discovered a variety of different gene responses of the HSPCs to the treatment. Interestingly, we were able to associate a global reduced myeloid differentiation program and a locally enhanced pyroptosis activity with reduced myeloid progenitor and differentiated cells after IFNα treatment. Altogether, the single-cell time series analyses have allowed us to unbiasedly study the heterogeneous and dynamic impact of IFNα on the HSPCs.
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
Life Science Alliance
Life Science Alliance Agricultural and Biological Sciences-Plant Science
CiteScore
5.80
自引率
2.30%
发文量
241
审稿时长
10 weeks
期刊介绍: Life Science Alliance is a global, open-access, editorially independent, and peer-reviewed journal launched by an alliance of EMBO Press, Rockefeller University Press, and Cold Spring Harbor Laboratory Press. Life Science Alliance is committed to rapid, fair, and transparent publication of valuable research from across all areas in the life sciences.
×
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