014-多组学分析肺结核队列的记忆T细胞状态

刘小泽写于2021.5.25

速览

  • 题目:Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease

  • 作者:哈佛医学院 Soumya Raychaudhuri 团队

    首先感觉他们实验室主页做的很不错:https://immunogenomics.hms.harvard.edu/lab

  • 链接:https://www.nature.com/articles/s41590-021-00933-1

  • 发表在:Nature Immunology (2021-05-24)

  • 数据是公开的: GSE158769 ,采用CITE-seq

    Platforms	GPL11154	Illumina HiSeq 2000 (Homo sapiens)
    Samples 	 GSM4810298	Memory_T_cell_CITE-seq
      
    GSE158769_exprs_norm.tsv.gz	3.0 Gb	(ftp)(http)	TSV
    GSE158769_exprs_raw.tsv.gz	747.0 Mb	(ftp)(http)	TSV
    GSE158769_meta_data.txt.gz	19.8 Mb	(ftp)(http)	TXT
    

    Genotype data: phs002025.v1.p1

  • 分析代码:https://github.com/immunogenomics/TB_Tcell_CITEseq

  • 还发开了一个网页:https://immunogenomics.io/tbru/

摘要

  • 分析了来自秘鲁的259个肺结核(tuberculosis , TB)病人的500,089个记忆T细胞,得到31种细胞状态

  • 在排除年龄、性别、季节、遗传等因素影响后,发现了一种多能型type 17 helper T (TH17) 细胞状态,在结核杆菌发展成肺结核病的过程中丰度和功能都有所下降

方法

数据准备

  • PBMC sample preparation
  • Flow cytometry of total PBMCs
  • CITE-seq of isolated memory T cells
  • Bulk RNA sequencing
  • Genotyping and genetic data processing

数据分析

  • scRNA比对+定量
  • scRNA数据拆分
  • scRNA数据质控
  • 降维
  • 聚类+注释
  • bulk RNA-seq 比对+定量
  • 利用MASC(modeling of associations of single cells )评价不同细胞状态与疾病的关系

先用CITE-seq测了>500,000个T细胞

  • 在秘鲁首都利马进行了一次大型的流行病学调查(n= 18,544),从其中招募了264个人,采样了外周血单核细胞进行CITE-seq测定,同时还加入了基因表型数据和蛋白数据
  • 图b是进行了6次QC,每一次过滤掉一些细胞,最后得到了500K
  • 大部分样本的细胞数量在2k左右

得到记忆T细胞的31种不同状态

利用canonical correlation analysis (CCA) 进行降维,选择top20 canonical variates (CVs)进行批次校正和聚类,根据基因和蛋白marker得到31个细胞状态

  • 23/31 were CD4+; five were CD8+; one (C-24) was a mixture; Two clusters (C-30 and C-31) were CD4−CD8−
  • C-20: contained a subset of CD4−CD8− and CD8+ cells expressing innate-like T cell markers, including ZBTB16 and CD161 and CD26 surface proteins
  • one central memory cluster (C-25) and distinct GZMK+ (C-28) and GZMB+ (C-29) effector subsets, reflecting different cytotoxicities
  • high expression of HLA-DR and CD38 surface protein and proliferation-associated MKI67 (C-15 and C-27) represent chronically activated cells
  • TH17 cells (C-12, CCR6+ and RORC)
  • type 1 helper T cells (TH1; C-17, CXCR3+ and IFNG and TBX21)
  • heterogeneous continuum of intermediate TH1/TH17 states (C-13, C-16 and C-19) with varying degrees of CXCR3, CCR6, CCR5 and CD161 surface protein expression and RORC and TBX21 expression
  • CD161+ subset of type 2 helper T (TH2) cells (C-14), described as pathogenic, with higher expression of allergy-associated HPGDS and IL17RB
  • a subset of FOXP3+ Treg cells (C-5) expressing higher CCR6 surface protein and CTLA4 and RORC than other Treg cells

记忆T细胞的状态因人口特征和环境而异

发现: 年龄因素的影响最大;性别因素与T细胞状态也高度相关; type 2 helper T (TH2) 细胞状态在冬天(季节因素)搜集的样本中最为丰富

之后发现一个感兴趣的C-12状态

探索每个细胞状态和肺结核病情进展的关系,同时校正其他可能存在影响的因素(年龄、性别、季节、遗传以及其他技术因素),发现:

病人在肺结核发展时期,C-12显著降低了20%,并且在年龄因素和男性因素下也会下降,而季节因素(冬季)会上升

又找到了C-12 surface markers:CD4+CD26+CD161+CCR6+ ,这些marker已经被证明了以下功能:

  • IL-17-producing TH17 state
  • CD26 is a co-stimulatory molecule that promotes cytotoxicity
  • CD161 is associated with innate-like function
  • CCR6 is a homing marker that directs migration to inflamed sites

那么C-12的下降是疾病的原因还是结果呢?

利用外部数据进行验证,发现这种变化可能早于疾病发展

  • predicted C-12 abundance was 9% lower in cases before progression compared to latent controls

Yunze Liu
Yunze Liu
Bioinformatics Sharer

Co-founder of Bioinfoplanet(生信星球)

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