新冠疫情期间，关于COVID-19病毒感染病人的单细胞研究很多，我看到《单细胞天地》解读了：COVID-19病人支气管免疫细胞单细胞测序分析，文章信息如下：
- 题目：Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19
- 投稿日期：2020年2月24日
- 接收日期：2020年4月23日
- 发表日期：2020年5月12日
- 杂志：Nature Medicine
- 文章在：https://www.nature.com/articles/s41591-020-0901-9
让我想起来了另外一个COVID-19病毒感染病人的单细胞研究，发表在Cell Discov. 2020 May ,标题是：Immune Cell Profiling of COVID-19 Patients in the Recovery Stage by Single-Cell Sequencing，差不多是同一时间发表的哦！
毕竟Cell Discov杂志和 Nature Medicine差别还是蛮大的，不知道是不是研究者特别想把研究写在祖国大地上。
文章实验设计
很清晰的实验设计，如下：
- 15个人
- 5个early recovery stage (ERS)
- 5个late recovery stage (LRS)
- 5个heathy controls (HCs)
- 单细胞数量
- 10个COVID-19 病人，共计 (70,858 PBMCs)
- 5个正常人，共计 (57,238 cells)
第一次分群
使用 t-distributed stochastic neighbor embedding (t-SNE) 方法降维
- 全部15个人的 128,096 scRNA-seq profiles
- 36,442 myeloid cells,
- 64,247 NK and T cells,
- 10,177 B cells
- 标记基因是：
- CD14, CD1C, and FCGR3A for myeloid cells;
- CD3E, CD4, CD8A, and NCAM1 for NK and T cells;
- CD19 for B cells
第二次分群
使用 Uniform manifold approximation and projection (UMAP) 方法降维
- 36,442 myeloid cells 分成6群
- Classical CD14 monocytes (M1),
- non-classical CD16 (FCGR3A) CD14−/ monocytes (M2),
- intermediate CD14 CD16 monocytes (M3),
- CD1C cDC2 (M4),
- CLEC9A cDC1 (M5),
- pDC (CLEC4C CD123 ) (M6)
- 64,247 NK and T cells 分成10群
- naïve CD8 T cells (T5), which expressed high levels of CCR7, LEF1, and TCF7, similar to naïve CD4 T cells;
- effector memory CD8 T cells (T6, CD8 Tm), which expressed high levels of GZMK;
- cytotoxic CD8 lymphocytes (CD8 CTL) (T7), which expressed high levels of GZMB, GNLY, and PRF1. Proliferating T cells (T8, Tprol) were TYMS MKI67 cells.
- naïve CD4 T cells (T1), which expressed high levels ofCCR7, LEF1, and TCF7;
- central memory CD4 T cells (T2, CD4 Tcm), which expressed high levels of CCR7, but more AQP3 andCD69 compared to naïve CD4 T cells;
- effector memory CD4 T cells (T3, CD4 Tem), which expressed high levels of CCR6, CXCR6, CCL5, and PRDM1;
- regulatory T cells (T4, Treg), which expressed FOXP3.
- C56−CD16 NK cells (NK2), which expressed high levels of CD16 and low levels of CD56.
- CD56 CD16− NK cells (NK1), which expressed high levels of CD56 and low levels of CD16;
- NK cells highly expressed NCAM1, KLRF1, KLRC1, andKLRD1; then, we sub-divided the NK cells into
- CD4 T cells expressed CD3E and CD4; then, we sub-divided these cells into four clusters:
- CD8 T cells expressed CD8A and CD8B and were sub-divided into three clusters:
- 10,177 B cells 分成 4群
- naïve B cells (B1) expressing CD19, CD20 (MS4A1), IGHD, IGHM, IL4R, and TCL1A;
- memory B cells (B2) expressing CD27, CD38, andIGHG;
- immature B cells (B3) only expressing CD19 and CD20 (MS4A1);
- plasma cells (B4) expressing high levels ofXBP1 and MZB1
分析层面的细节，都展现在分群以及细胞亚群的定义上面了。
主要分析
文章的图表很清晰，都是显而易见的分析，读起来很友好反正：
- 3群细胞（myeloid, NK and T, and B cells），在3组人（five HCs, five ERS patients, and five LRS patients.）的比例
- myeloid的6个亚群，NK和T细胞的10亚群，以及4个B细胞亚群在3组人的比例情况
- Classical CD14 monocytes (M1) 的差异分析，全套（火山图，热图，GO/KEGG数据库注释）
- CD4 T cells 的差异分析，全套（火山图，热图，GO/KEGG数据库注释）
- Memory B cells and plasma cells (MPB) 的差异分析，全套（火山图，热图，GO/KEGG数据库注释）
也有一点点高级分析，包括sc-BCR, and sc-TCR 数据分析
- 主要是 (IgA IgG IgE) to (IgD IgM) 比例情况
以及 Cell-to-cell communication ，这些分析可以在：单细胞转录组数据的个性化分析汇总全部找到。
