Integrative analysis of spatial transcriptome with single-cell transcriptome and single-cell epigenome in mouse lungs after immunization.
Integrative analysis of spatial transcriptome with single-cell transcriptome and single-cell epigenome in mouse lungs after immunization.
复制标题
DOI：
10.1016/j.isci.2022.104900
复制
发表时间：
2022-09-16
期刊：
影响因子：
5.8
通讯作者：
Chen, Kong
中科院分区：
文献类型：
--
作者：
Xu, Zhongli;Wang, Xinjun;Fan, Li;Wang, Fujing;Lin, Becky;Wang, Jiebiao;Trevejo-Nunez, Giraldina;Chen, Wei;Chen, Kong
了解肺免疫需要对组织驻留T细胞在肺内的精确解剖位置进行公正的分析，但这些信息尚未在免疫小鼠模型中得到表征。在这项初步研究中，我们使用10x Genomics Chromium and Visium平台，利用一种完善的肺炎克雷伯菌感染模型，对免疫后小鼠肺细胞的空间转录组进行了单细胞RNA-seq和单细胞ATAC-seq的综合分析。我们建立了一个优化的反卷积管道，以准确地破译特定的细胞类型组成的解剖位置。我们发现，结合scATAC-seq和scRNA-seq数据可以提供更可靠的细胞类型鉴定，特别是对谱系特异性T辅助细胞。结合这三种方式，我们观察到辅助性T细胞及其相应的趋化因子位置的动态变化。总之，我们的原理验证研究证明了单细胞多组学分析在揭示肺免疫的空间和细胞类型依赖机制方面的力量和潜力。通过整合scRNA-seq和scATAC-seq数据确定了肺细胞类型，在肺炎克雷伯菌再次攻击时，发现Th17细胞比Th1细胞更靠近气道，气道中有大量免疫应答被激活。免疫学;组学;转录组
Understanding lung immunity requires an unbiased profiling of tissue-resident T cells at their precise anatomical locations within the lung, but such information has not been characterized in the immunized mouse model. In this pilot study, using 10x Genomics Chromium and Visium platform, we performed an integrative analysis of spatial transcriptome with single-cell RNA-seq and single-cell ATAC-seq on lung cells from mice after immunization using a well-established Klebsiella pneumoniae infection model. We built an optimized deconvolution pipeline to accurately decipher specific cell-type compositions by anatomic location. We discovered that combining scATAC-seq and scRNA-seq data may provide more robust cell-type identification, especially for lineage-specific T helper cells. Combining all three modalities, we observed a dynamic change in the location of T helper cells as well as their corresponding chemokines. In summary, our proof-of-principle study demonstrated the power and potential of single-cell multi-omics analysis to uncover spatial- and cell-type-dependent mechanisms of lung immunity. Deconvolution workflow was verified to study lung immunity using ST 15 lung cell types were identified by integrating scRNA-seq and scATAC-seq data Th17 cells were found proximal to airways than Th1 upon Klebsiella pneumoniae re-challenge Massive immune responses were activated in airways upon K. pneumoniae re-challenge Biological sciences; Immunology; Omics; Transcriptomics
登录
查看更多内容
影响因子：
64.8
作者：
Boyd DF;Allen EK;Randolph AG;Guo XJ;Weng Y;Sanders CJ;Bajracharya R;Lee NK;Guy CS;Vogel P;Guan W;Li Y;Liu X;Novak T;Newhams MM;Fabrizio TP;Wohlgemuth N;Mourani PM;PALISI Pediatric Intensive Care Influenza (PICFLU) Investigators;Wight TN;Schultz-Cherry S;Cormier SA;Shaw-Saliba K;Pekosz A;Rothman RE;Chen KF;Yang Z;Webby RJ;Zhong N;Crawford JC;Thomas PG
通讯作者：
Thomas PG
影响因子：
14.9
作者：
Gene Ontology Consortium
通讯作者：
Gene Ontology Consortium
影响因子：
4.6
作者：
Bankhead P;Loughrey MB;Fernández JA;Dombrowski Y;McArt DG;Dunne PD;McQuaid S;Gray RT;Murray LJ;Coleman HG;James JA;Salto-Tellez M;Hamilton PW
通讯作者：
Hamilton PW
影响因子：
14.9
作者：
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者：
Smyth GK
DOI：
10.1093/bioinformatics/btaa1009
发表时间：
2021-04-05
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Ahlmann-Eltze C;Huber W
通讯作者：
Huber W