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题名

Single-cell transcriptomics of blood reveals a natural killer cell subset depletion in tuberculosis

作者
通讯作者Chen,Xinchun
发表日期
2020-03-01
DOI
发表期刊
ISSN
2352-3964
EISSN
2352-3964
卷号53
摘要
Background: Tuberculosis (TB) continues to be a critical global health problem, which killed millions of lives each year. Certain circulating cell subsets are thought to differentially modulate the host immune response towards Mycobacterium tuberculosis (Mtb) infection, but the nature and function of these subsets is unclear. Methods: Peripheral blood mononuclear cells (PBMC) were isolated from healthy controls (HC), latent tuberculosis infection (LTBI) and active tuberculosis (TB) and then subjected to single-cell RNA sequencing (scRNA-seq) using 10 × Genomics platform. Unsupervised clustering of the cells based on the gene expression profiles using the Seurat package and passed to tSNE for clustering visualization. Flow cytometry was used to validate the subsets identified by scRNA-Seq. Findings: Cluster analysis based on differential gene expression revealed both known and novel markers for all main PBMC cell types and delineated 29 cell subsets. By comparing the scRNA-seq datasets from HC, LTBI and TB, we found that infection changes the frequency of immune-cell subsets in TB. Specifically, we observed gradual depletion of a natural killer (NK) cell subset (CD3-CD7+GZMB+) from HC, to LTBI and TB. We further verified that the depletion of CD3-CD7+GZMB+ subset in TB and found an increase in this subset frequency after anti-TB treatment. Finally, we confirmed that changes in this subset frequency can distinguish patients with TB from LTBI and HC. Interpretation: We propose that the frequency of CD3-CD7+GZMB+ in peripheral blood could be used as a novel biomarker for distinguishing TB from LTBI and HC. Fund: The study was supported by Natural Science Foundation of China (81770013, 81525016, 81772145, 81871255 and 91942315), National Science and Technology Major Project (2017ZX10201301), Science and Technology Project of Shenzhen (JCYJ20170412101048337) and Guangdong Provincial Key Laboratory of Regional Immunity and Diseases (2019B030301009). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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相关链接[Scopus记录]
收录类别
语种
英语
学校署名
其他
WOS研究方向
General & Internal Medicine ; Research & Experimental Medicine
WOS类目
Medicine, General & Internal ; Medicine, Research & Experimental
WOS记录号
WOS:000523581700031
出版者
Scopus记录号
2-s2.0-85080084259
来源库
Scopus
引用统计
被引频次[WOS]:85
成果类型期刊论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/106372
专题南方科技大学第二附属医院
作者单位
1.Guangdong Key Laboratory of Regional Immunity and Diseases,Department of Pathogen Biology,Shenzhen University School of Medicine,Shenzhen,518000,China
2.Research Institute of Infectious Diseases,Guangzhou Eighth People's Hospital,Guangzhou Medical University,Guangzhou,510000,China
3.Guangdong Key Lab for Diagnosis &Treatment of Emerging Infectious Diseases,Shenzhen Third People's Hospital,Southern University of Science and Technology,Shenzhen,518000,China
4.Shenzhen University General Hospital,Shenzhen University School of Medicine,Shenzhen,518000,China
5.Yuebei Second People's Hospital,Shaoguan,512000,China
6.The MOH Key Laboratory of Systems Biology of Pathogens,Institute of Pathogen Biology,Centre for Tuberculosis,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing,100176,China
7.Department of Infectious Diseases and Immunology,Sydney Medical School,the University of Sydney,Sydney,2006,Australia
推荐引用方式
GB/T 7714
Cai,Yi,Dai,Youchao,Wang,Yejun,et al. Single-cell transcriptomics of blood reveals a natural killer cell subset depletion in tuberculosis[J]. EBioMedicine,2020,53.
APA
Cai,Yi.,Dai,Youchao.,Wang,Yejun.,Yang,Qianqing.,Guo,Jiubiao.,...&Chen,Xinchun.(2020).Single-cell transcriptomics of blood reveals a natural killer cell subset depletion in tuberculosis.EBioMedicine,53.
MLA
Cai,Yi,et al."Single-cell transcriptomics of blood reveals a natural killer cell subset depletion in tuberculosis".EBioMedicine 53(2020).
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