Summary

全骨髓的制备,用于中性粒系细胞的大规模细胞测定分析

Published: June 19, 2019
doi:

Summary

在这里,我们提出一个协议,处理从小鼠或人类分离的新鲜骨髓(BM),用于对中性粒细胞的超维质量细胞测定(飞行时间,CyTOF)的细胞测定。

Abstract

在本文中,我们提出了一个协议,经过优化,以保存新BM中的中性粒细胞,用于整个BM CyTOF分析。我们使用骨髓偏置的39抗体CyTOF面板,利用该协议对造血系统进行评价,重点是中性粒细胞系细胞。利用开放资源维还原算法viSNE对CyTOF结果进行了分析,并给出了数据,以证明该协议的结果。我们根据这个协议发现了新的嗜中性粒细胞群。这种新鲜全BM制剂的协议可用于1),CyTOF分析,发现来自整个BM的不明细胞群,2),调查整个BM缺陷的血液疾病患者,如白血病,3,协助优化荧光激活流式细胞仪协议,利用新鲜的全BM。

Introduction

在过去的几十年中,细胞学方法一直是研究BM造血系统的有力工具。这些方法包括荧光活化流细胞测定法和采用重金属标记抗体的CyTOF新方法。通过鉴定其独特的表面标记表达特征,它们在异质生物标本中发现了许多细胞类型。增加的频谱重叠与更多的通道相关,导致荧光激活流细胞学应用中的数据误差更高。因此,为了丰富荧光激活流细胞学分析感兴趣的细胞群,通常会去除不需要的细胞。例如,Ly6G(或Gr-1)和CD11b被视为成熟的骨髓细胞标记,Ly6G= (或Gr-1+) 和CD11b+细胞在流式细胞测定分析之前,通常使用磁性浓缩试剂盒从BM样品中取出。造血干细胞和祖细胞(HSPCs)或将这些标记物组合在一个转储鸡尾酒通道1,2,3。另一个例子是,中性粒细胞经常从人类血液标本中取出,以丰富外周血单核细胞(PBMC),用于免疫学研究。然而,从小鼠或人类分离出的整个骨髓很少被完整地研究为细胞学分析。

最近,CyTOF已成为研究造血系统4,5,6的革命性工具。使用CyTOF,荧光度标记抗体被重元素报告标记抗体所取代。此方法允许同时测量 40 多个标记,而不必担心频谱重叠。它使完整的生物标本能够进行分析,无需预消耗步骤或转储通道。因此,我们可以从传统的二维流式细胞学图中,以高含量的维数全面地观察造血系统。过去在消耗或浇注过程中省略的细胞群现在可以使用CyTOF4,5生成的高维数据来揭示。我们设计了一个抗体面板,同时测量造血系统中的39个参数,重点是骨髓性linage7。与传统流式细胞测量数据相比,CyTOF生成的前所未有的单细胞高维数据的解释和可视化具有挑战性。计算科学家已经开发了用于高维数据集可视化的维数缩减技术。在本文中,我们使用使用 t 分布随机邻域嵌入 (t-SNE) 技术的算法 viSNE 来分析 CyTOF 数据,并在二维地图上显示高维结果,同时保护高维结构数据8,9,10。在 tSNE 图中,类似的单元格被聚入子集,颜色用于突出显示单元格的特征。例如,在图1中,骨髓细胞根据CyTOF(图1)4产生的33个表面标记的表达模式的相似性,分布到多个细胞集中。在这里,我们研究了小鼠骨髓与我们之前报告的39标记CyTOF面板通过viSNE分析7。viSNE分析我们的CyTOF数据显示一个不明的细胞群,显示HSPC (CD117+)和嗜中性粒细胞 (Ly6G+) 特性 (图2)7

最后,我们提出了一个方案,用于CyTOF分析处理新鲜的全骨髓。在本文中,我们以小鼠骨髓为例,而此协议也可用于处理人类骨髓样本。协议中也注明了人类骨髓样本的细节。该协议的优点是,它包含一些细节,如孵育时间和温度,经过优化,以保存整个骨髓中的嗜中性粒细胞,以便对完整的整个骨髓进行调查。对于荧光激活流式细胞学应用,此协议也可轻松修改。

Protocol

所有实验均遵循拉霍亚过敏和免疫学研究所动物护理和使用委员会批准的准则,并根据国家卫生研究院的《实验室动物护理和使用指南》。 1. 收获小鼠骨髓 (BM) 从商业供应商处购买 C57BL/6J 鼠标。在无病原体的设施中,在微型隔离器笼中喂养标准的啮齿动物食物,并饲养房屋。 使用6-10周大的雄性小鼠进行实验。通过CO2吸入安乐死,然后是宫颈脱位。 ?…

Representative Results

图1作为CyTOF实验的一个示例。在此 tSNE 图中,跨多个小鼠组织的细胞根据 33 参数 CyTOF 面板测量的表面标记表达式配置文件的相似性聚集到子中。具有更多相似属性的细胞根据每个细胞上的 33 个标记的表达式自动聚集在一起,如嗜中性粒细胞、巨噬细胞或 DC。 图2是使用本研究提出的协议进行的小鼠BM CyTOF实验的一个示例结果。该协议…

Discussion

在过去的几十年里,荧光流细胞学被用作研究细胞谱系和异质性1、2、3的主要方法。虽然流式细胞学提供了多维数据,但这种方法受到参数选择和光谱重叠的限制。为了克服流式细胞学的弱点,我们利用了CyTOF,它使用重金属同位素代替荧光水,来标记抗体,消除检测通道之间的串扰或细胞的自荧光,因此,可以测量许多在单细胞水平上?…

Offenlegungen

The authors have nothing to disclose.

Acknowledgements

我们要感谢LJI流式细胞学核心协助进行大规模细胞测量程序。这项工作得到了NIH授予R01HL134236、P01HL136275和R01CA202987(全部授予C.C.H)和ADA7-12-MN-31(04)(C.C.H.和Y.P.Z)的支持。

Materials

CyTOF Antibodies (mouse)
Anti-Mouse CD45 (Clone 30-F11) -89Y Fluidigm Cat# 3089005B
Anti-Human/Mouse CD45R/B220 (Clone RA36B2)-176Yb Fluidigm Cat# 3176002B
Anti-mouse CD105 (Clone MJ7/18)-Purified Biolegend Cat# 120402; RRID:AB_961070
Anti-mouse CD115 (CSF-1R) (Clone AFS98)-Purified Biolegend Cat# 135502; RRID:AB_1937293
Anti-Mouse CD117/c-kit (Clone 2B8)-166Er Fluidigm Cat# 3166004B
Anti-mouse CD11a (Clone M17/4)-Purified Biolegend Cat# 101101; RRID:AB_312774
Anti-Mouse CD11b (Clone M1/70)-148Nd Fluidigm Cat# 3148003B
Anti-Mouse CD11c (Clone N418)-142Nd Fluidigm Cat# 3142003B
Anti-mouse CD127 (IL-7Rα) (Clone A7R34)-MaxPar Ready Biolegend Cat# 133919; RRID:AB_2565433
Anti-Mouse CD150 (Clone TC1512F12.2)-167Er Fluidigm Cat# 3167004B
Anti-mouse CD16.2 (FcγRIV) (Clone 9E9)-Purified Biolegend Cat# 149502; RRID:AB_2565302
Anti-Mouse CD162 (Clone 4RA10 (RUO))-Purified BD Biosciences Cat# 557787; RRID:AB_647340
Anti-mouse CD169 (Siglec-1) (Clone 3D6.112)-Purified Biolegend Cat# 142402; RRID:AB_10916523
Anti-mouse CD182 (CXCR2) (Clone SA044G4)-Purified Biolegend Cat# 149302; RRID:AB_2565277
Anti-mouse CD183 (Clone CXCR3-173)-Purified Biolegend Cat# 126502; RRID:AB_1027635
Anti-mouse CD335 (NKp46) (Clone 29A1.4)-MaxPar Ready Biolegend Cat# 137625; RRID:AB_2563744
Anti-mouse CD34 (Clone MEC14.7)-Purified Biolegend Cat# 119302; RRID:AB_345280
Anti-mouse CD41 (Clone MWReg30)-MaxPar Ready Biolegend Cat# 133919; RRID:AB_2565433
Anti-Mouse CD43 (Clone S11)-146Nd Fluidigm Cat# 3146009B
Anti-Mouse CD48 (Clone HM48.1)-156Gd Fluidigm Cat# 3156012B
Anti-mouse CD62L (Clone MEL-14)-MaxPar Ready ThermoFisher Cat# 14-1351-82; RRID:AB_467481
Anti-mouse CD71 (Clone RI7217)-Purified Biolegend Cat# 113802; RRID:AB_313563
Anti-mouse CD90 (Clone G7)-Purified Biolegend Cat# 105202; RRID:AB_313169
Anti-Mouse F4/80 (Clone BM8)-159Tb Fluidigm Cat# 3159009B
Anti-mouse FcεRIα (Clone MAR-1)-MaxPar Ready Biolegend Cat# 134321; RRID:AB_2563768
Anti-mouse GM-CSF (MP1-22E9 (RUO))-Purified BD Biosciences Cat# 554404; RRID:AB_395370
Anti-Mouse I-A/I-E (Clone M5/114.15.2)-174Yb Fluidigm Cat# 3174003B
Anti-Mouse Ki67 (Clone B56 (RUO))-Purified BD Biosciences Cat# 556003; RRID:AB_396287
Anti-Mouse Ly-6A/E (Sca-1) (Clone D7)-169Tm Fluidigm Cat# 3169015B
Anti-Mouse Ly6B (Clone 7/4)-Purified abcam Cat# ab53457; RRID:AB_881409
Anti-mouse Ly-6G (Clone 1A8)-MaxPar Ready Biolegend Cat# 127637; RRID:AB_2563784
Anti-Mouse NK1.1 (Clone PK136)-165Ho Fluidigm Cat# 3165018B
Anti-Mouse Siglec-F (Clone E50-2440 (RUO))-Purified BD Biosciences Cat# 552125; RRID:AB_394340
Anti-Mouse TCRβ (Clone H57-597)-143Nd Fluidigm (Clone H57-597)-143Nd
Anti-mouse TER-119/Erythroid Cells (Clone TER-119)-MaxPar Ready Biolegend Cat# 116241; RRID:AB_2563789
Chemicals, Peptides and Recombinant Proteins
Antibody Stabilizer CANDOR Bioscience Cat# 130050
Bovine Serum Albumin Sigma-Aldrich Cat# A4503
Cisplatin-194Pt Fluidigm Cat# 201194
eBioscience 1X RBC Lysis Buffer ThermoFisher Cat# 00-4333-57
eBioscience Foxp3 / Transcription Factor Staining Buffer Set ThermoFisher Cat# 00-4333-57
EQ Four Element Calibration Beads Fluidigm Cat# 201078
Ethylenediaminetetraacetic acid (EDTA) ThermoFisher Cat# AM9260G
Fetal Bovine Serum Omega Scientific Cat# FB-02
HyClone Phosphate Buffered Saline solution GE Lifesciences Cat#SH30256.01
Intercalator-Ir Fluidigm Cat# 201192B
MAXPAR Antibody Labeling Kits Fluidigm http://www.dvssciences.com/product-catalog-maxpar.php
Paraformaldehyde Sigma-Aldrich Cat# 158127
Sodium azide Sigma-Aldrich Cat# S2002
Triton X-100 Sigma-Aldrich Cat# X100
Trypsin EDTA 1X Corning Cat# 25-053-Cl
Experimental Model: Organism/Strains
Mouse: C57BL/6J The Jackson Laboratory Stock No: 000664
Software Alogrithm
Bead-based Normalizer Finck et al., 2013 https://med.virginia.edu/flow-cytometry-facility/wp-content/uploads/sites/170/2015/10/3_Finck-Rachel_CUGM_May2013.pdf
Cytobank Cytobank https://www.cytobank.org/
Cytofkit v1.r.0 Chen et al., 2016 https://bioconductor.org/packages/release/bioc/html/cytofkit.html
t-SNE van der Maaten and Hinton, 2008 https://cran.r-project.org/web/packages/Rtsne/index.html

Referenzen

  1. Akashi, K., Traver, D., Miyamoto, T., Weissman, I. L. A clonogenic common myeloid progenitor that gives rise to all myeloid lineages. Nature. 404, 193-197 (2000).
  2. Iwasaki, H., Akashi, K. Myeloid lineage commitment from the hematopoietic stem cell. Immunity. 26, 726-740 (2007).
  3. Manz, M. G., Miyamoto, T., Akashi, K., Weissman, I. L. Prospective isolation of human clonogenic common myeloid progenitors. Proceedings of the National Academy of Sciences. 99, 11872-11877 (2002).
  4. Becher, B., et al. High-dimensional analysis of the murine myeloid cell system. Nature Immunology. 15, 1181-1189 (2014).
  5. Bendall, S. C., et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science. 332, 687-696 (2011).
  6. Samusik, N., Good, Z., Spitzer, M. H., Davis, K. L., Nolan, G. P. Automated mapping of phenotype space with single-cell data. Nature Methods. 13, 493-496 (2016).
  7. Zhu, Y. P., et al. Identification of an Early Unipotent Neutrophil Progenitor with Pro-tumoral Activity in Mouse and Human Bone Marrow. Cell Reports. 24, 2329-2341 (2018).
  8. Van der Maaten, L. J. P., Hinton, G. E. Visualizing High-Dimensional Data Using t-SNE. Journal of Machine Learning Research. 9, 2579-2605 (2008).
  9. Amir, E. A. D., et al. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nature Biotechnology. 31, 545-552 (2013).
  10. van der Maaten, L., Hinton, G. Visualizing data using t-SNE. Journal of Machine Learning Research. 9 (85), 2579-2065 (2008).
  11. Cloos, J., et al. Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia. Journal of Visualized Experiment. 133, 56386 (2018).
  12. Bendall, S. C., Nolan, G. P., Roederer, M., Chattopadhyay, P. K. A deep profiler’s guide to cytometry. Trends in Immunology. 33, 323-332 (2012).
  13. Ley, K., et al. Neutrophils: New insights and open questions. Science Immunology. 3 (30), 4579 (2018).
  14. Ng, L. G., Ostuni, R., Hidalgo, A. Heterogeneity of neutrophils. Nature Reviews in Immunology. , (2019).

Play Video

Diesen Artikel zitieren
Zhu, Y. P., Padgett, L., Dinh, H. Q., Marcovecchio, P., Wu, R., Hinz, D., Kim, C., Hedrick, C. C. Preparation of Whole Bone Marrow for Mass Cytometry Analysis of Neutrophil-lineage Cells. J. Vis. Exp. (148), e59617, doi:10.3791/59617 (2019).

View Video