大鼠外周全血细胞免疫表型和因子生成的单细胞分析
Summary
在这里, 我们描述了一个单细胞蛋白质组学方法, 以评估免疫表型和功能 (细胞因子诱导) 改变周围全血标本, 分析通过大规模细胞术。
Abstract
细胞因子在自身免疫性疾病的发病机制中起着举足轻重的作用。因此, 对细胞因子水平的测量一直是多项研究的重点, 试图了解导致自我耐受和随后的自身免疫性崩溃的精确机制。迄今为止的方法都是基于对免疫系统的一个特定方面 (单个或少数细胞类型或细胞因子) 的研究, 并且不提供对复杂自身免疫性疾病的全球评估。虽然以血清为基础的研究为自身免疫提供了重要的洞察力, 但它们并没有给出失调细胞因子的特定细胞来源。本文介绍了在 “固有” 患者特定血浆循环因子的背景下, 综合评价多种免疫细胞亚群细胞因子生成的综合性单细胞方法。这种方法可以监测患者特定的免疫表型 (表面标记) 和功能 (细胞因子), 无论是在其本机 “固有致病性” 疾病状态, 或在存在的治疗药物 (在体内或体内).
Introduction
自身免疫性疾病是影响3-8% 人口发病率和死亡率的主要原因。在美国, 自体免疫性疾病是青年和中年妇女死亡的主要原因 (年龄 < 65 岁)1,2。自身免疫性疾病的特点是异质临床表现和多种基础免疫学过程。非均质谱在不同的疾病中有很好的表现, 如联合参与类风湿关节炎 (RA) 和多发性硬化症 (MS) 的神经系统疾病。然而, 这一水平的异质性也表现在单一的紊乱, 如系统性红斑狼疮 (SLE): 一些病人可能出现肾脏病理, 而其他人患有血液或联合介入3。
自身免疫性疾病的潜在发病反映了临床异质性, 包括多先天和自适应免疫细胞亚群的自动和超活化, 以及伴随失调细胞因子的产生。虽然细胞因子在自身免疫性疾病的发病机制中起着举足轻重的作用, 但了解其在疾病机理中的具体作用已证明是具有挑战性的。细胞因子的特点是多效性 (一个细胞因子可以对不同的细胞类型有多种影响), 冗余 (多个细胞因子可以有相同的效果), 二元性 (一个细胞因子可以有亲或抗炎作用在不同的条件下),和可塑性 (细胞因子可以塑造成一个角色不同于它的 “原物” 一, 取决于环境)4,5,6。因此, 人口水平的方法不能区分异质细胞对同一 “细胞因子环境” 的反应。同样, 研究的设计, 专注于免疫系统的一个特定方面 (单一细胞类型或细胞因子), 不提供全球评估所有的因素涉及复杂的自身免疫性疾病。虽然以血清为基础的研究为自身免疫提供了重要的洞察力, 但它们并没有给出失调细胞因子的特定细胞来源。
最近, 我们开发了单细胞蛋白质组学方法, 同时评估多种免疫细胞类型, 并检测其在特定的 “致病性” 外周血血浆循环因子的环境中的各种细胞因子扰动。这里描述的工作流的特点是使用完整的周围全血样本, 而不是孤立的外周血单个核细胞 (PBMCs)。外周全血代表最生理相关的车辆, 以研究系统性免疫介导的疾病, 包括 1) 非单核血细胞经常参与自身免疫性疾病 (即中性粒细胞, 血小板) 和 2) 血浆诸如核酸、免疫复合物和细胞因子等循环因子, 具有免疫激活作用。为了捕捉 “内在致病性” 失调细胞因子的产生, 外周血标本立即处理后, 血液提取 (T0, 时间零), 并在6小时的孵化后37°c (生理体温) 与蛋白质运输抑制剂在没有任何外源刺激条件 (T6, 时间6小时), 以检测细胞因子的生产 (积累, T6-T0), 这将反映 “内在” 疾病状态 (图 1)。为了研究反应信号通路在与疾病相关的免疫应答中的失调过程, 外周血样本被治疗 (6 小时孵化37°c 与蛋白质转运抑制剂) 与外源刺激的条件, 反映疾病的发病机制, 例如, 在 SLE (T6 + R848, 时间6小时与1µg/毫升 R848) 的情况下类似的像样受体 (TLR) 激动剂, 以检测细胞因子的产生, 反映对核酸的反应 (比较 T0 和 T6 vs T6 +R848,图 1)。为了研究可用疗法的免疫调节作用, 因为它们与特定患者的精确免疫失调过程有关, 所以在相关治疗中用 JAK 抑制剂治疗外周血标本。集中 (这里, 5 uM ruxolitinib;T6 + 5R, 时间6小时与 5 uM ruxolitinib), 以检测 “内在” 疾病状态的变化反应的药物 (T0 vs T6 vs T6 + 5R,图 1)。为这项研究选择了 JAK 抑制剂, 因为 JAK 抑制剂已证明是成功的治疗自身免疫性疾病, 如 RA。
为了同时评价上述在多免疫细胞亚群中的失调过程, 对 SLE 患者的外周血样本和健康控制进行了处理, 并通过质细胞术进行了分析。质细胞术, 也称为细胞术-飞行时间, 提供了40多个参数的单细胞分析, 没有光谱重叠7,8,9的问题。这种技术利用稀土金属同位素的形式, 可溶性金属离子作为标签绑定到抗体, 而不是显影10。关于质量细胞术技术平台的其他细节 (即调谐和校准, 样品采集) 可以在 Leipold 等和麦卡锡等中找到 。11,12高维度的大规模细胞术能够同时测量的多种细胞因子整个先天和自适应免疫细胞亚群与单细胞粒度 (材料表)。
目前的常规临床和实验室参数往往不敏感或具体到足以检测正在进行的疾病活动或对特定的免疫调节剂13的反应, 反映了需要更好地描绘潜在的免疫驱动 flare 的更改。鉴于细胞因子失调在自身免疫性疾病中的普遍存在, 大量的治疗方法使用的抗体或小分子抑制剂靶向细胞因子或信号蛋白参与调控细胞因子的生产有最近出现。在它的基本格式, 这里描述的外周血分析方法提供了一个平台, 以确定病人特定的失调细胞亚群和他们的异常细胞因子产生的自身免疫性疾病的系统性表现。这种方法允许个性化的治疗选择, 因为具体的失调细胞因子可以确定, 和特定的治疗方案, 可以测试在体内, 以评估他们的能力 immunomodulate 病人特定的疾病过程。
Protocol
Representative Results
Discussion
在这里, 我们描述了一个新的, 单细胞, 蛋白质组学方法, 同时评估多种免疫细胞类型和检测其各种细胞因子扰动的环境中的患者特异性 “致病性” 外周血血浆循环因素。该方法采用外周全血作为分析载体, 以质细胞仪作为评价免疫细胞表型和功能异常的工具。该方法易于应用于人体和小鼠的研究21, 并与其他免疫功能分析 (如检测信号异常14) 兼容。
<p class="jove_co…Disclosures
The authors have nothing to disclose.
Acknowledgements
我们要感谢艾米 Pugh-伯纳德对她的智力投入和有益的评论。这项工作得到了 Boettcher 基金会韦伯-华林生物医学研究奖和 K23-1K23AR070897 从 NIH 到埃琳娜 W.Y. 谢的奖励数字的支持。她还得到了来自尤尼斯肯尼迪K12-HD000850 国家儿童健康和人类发展研究所以及露塞尔儿童健康基金会、斯坦福 CTSA UL1 TR001085 和儿童健康研究协会颁发的奖项编号的支持。斯坦福大学研究所。
Materials
| Ruxolitinib | Santa Cruz | SC-364729A | Stock Conc: 10 mM; Final Conc: 5 μM |
| R848 | Invivogen | tlrl-r848-5 | Stock Conc: 1 μg/μL; Final Conc: 1 μg/mL |
| LPS-EK | Invivogen | tlrl-eklps | Stock Conc: 1 μg/μL; Final Conc: 0.1 μg/mL |
| Sterile PBS | Lonza | 17-516F | |
| Lyse/Fix Buffer | BD biosciences | 558049 | Stock Conc: 5X; Final Conc: 1X (dilute in ddH2O) |
| BD Phosflow perm/wash buffer I | BD biosciences | 557885 | Stock Conc: 10X; Final Conc: 1:10 (dilute in ddH2O) |
| RPMI | Gibco | 21870-076 | |
| Sodium Azide (NaN3) | Sigma-Aldrich | S-8032 | Stock Conc: >99.9%; Final Conc: 0.0002 |
| Protein Transport Inhibitor (PTI) | eBiosciences | 00-4980-93 | Stock Conc: 500X; Final Conc: 1X |
| DNA Intercalator | Fluidigm | 201192B | Stock Conc: 500 μM; Final Conc: 0.1 μM |
| Cell Staining Media (CSM) | PBS + 0.5% BSA, 0.02% NaN3 | ||
| MaxPar Barcode Perm Buffer | Fluidigm | 201057 | Stock Conc: 10X; Final Conc: 1X |
| 20-plex Pd Barcode Set | Fluidigm | S0014 | Stock Conc: n/a; Final Conc: n/a |
| EQ TM Four Element Calibration Beads | Fluidigm | 201078 | Stock Conc: 10X; Final Conc: 1X |
| 16% MeOH-free Formaldehyde Solution | Thermo | 28908 | Stock Conc: 16% (w/v); Final Conc: 1.6% (w/v) |
| Sterile round bottom polystyrene tubes | VWR | 60818-496 | Stock Conc: n/a; Final Conc: n/a |
| Polypropylene cluster tubes | Light Labs | A-9001 | Stock Conc: n/a; Final Conc: n/a |
| Helios CyTOF instrument | Fluidigm | Helios | All solutions to be used in CyTOF analysis need to be free of metal contamination. ddH2O is used in the preparation of any solutions should have a resistivity of at least 18.0 MΩ.cm. ddH2O and any self-prepared solutions should be stored in new plastic or glass bottles that have never been autoclaved. |
| Name | Company | Catalog Number | Comments |
| Antibodies used for Mass Cytometry | |||
| Surface markers | |||
| CD1c | Biolegend | L161 | Mass: 161 |
| CD3 | BD | UCHT1 | Mass: 144 |
| CD4 | Biolegend | SK3 | Mass: 174 |
| CD7 | BD | M-T701 | Mass: 149 |
| CD8 | Biolegend | SK1 | Mass: 142 |
| CD11b | Fluidigm | ICRF44 | Mass: 209 |
| CD11c | BD | B-ly6 | Mass: 152 |
| CD15 | BD | HI98 | Mass: 115 |
| CD14 | Biolegend | M5E2 | Mass: 154 |
| CD16 | eBioscience/Thermo | B73.1 | Mass: 165 |
| CD19 | Santa Cruz | SJ25C1 | Mass: 163 |
| CD21 | Biolegend | Bu32 | Mass: 141 |
| CD27 | BD | L128 | Mass: 155 |
| CD38 | Fluidigm | HIT2 | Mass: 172 |
| CD45 total | Biolegend | HI30 | Mass: 89 |
| CD45RA | Biolegend | HI100 | Mass: 153 |
| CD56 | Miltenyi | REA196 | Mass: 168 |
| CD66 | BD | B1.1/CD66 | Mass: 113 |
| CD86 | Fluidigm | IT2.2 | Mass: 150 |
| CD123 | Fluidigm | 6H6 | Mass: 143 |
| CD278/ICOS | Biolegend | C398.4A | Mass: 156 |
| CD179/PD1 | Biolegend | EH12.2H7 | Mass: 162 |
| IgD | Biolegend | IA6-2 | Mass: 146 |
| IgM | Biolegend | MHM-88 | Mass: 151 |
| CXCR5 | BD | RF8B2 | Mass: 173 |
| HLADR | Biolegend | L243 | Mass: 167 |
| Cytokines | |||
| IL-1α | Biolegend | 364-3B3-14 | Mass: 147 |
| IL-1β | Biolegend | H1b-98 | Mass: 169 |
| IL-1RA | Santa Cruz | AS17 | Mass: 157 |
| IL-6 | Biolegend | MQ2-13A5 | Mass: 164 |
| IL-8 | BD | E8N1 | Mass: 160 |
| IL-12/IL-23p40 | Biolegend | C8.6 | Mass: 171 |
| IL-17A | Biolegend | BL168 | Mass: 148 |
| IL23p19 | eBioscience/Thermo | 23dcdp | Mass: 176 |
| MIP1β | BD | D21-1351 | Mass: 158 |
| MCP1 | BD | 5D3-F7 | Mass: 170 |
| IFNα | Miltenyi | LT27:295 | Mass: 175 |
| IFNγ | Biolegend | 4S.B3 | Mass: 165 |
| PTEN | BD | A2B1 | Mass: 159 |
| TNFα | Biolegend | Mab11 | Mass: 166 |
| Note: If the manufacturer is stated as Fluidigm, this antibody was purchased from Fluidigm with metal pre-conjugated. If the manufacturer is stated as other than Fluidigm, this antibody was self-conjugated using the MaxPar Multi-Metal Labeling Kit (Fluidigm Cat: 201300) according to manufacturer protocol. |
References
- Walsh, S. J., Rau, L. M. Autoimmune diseases: a leading cause of death among young and middle-aged women in the United States. American journal of public health. 90 (9), 1463-1466 (2000).
- Mak, A., Cheung, M. W. -. L., Chiew, H. J., Liu, Y., Ho, R. C. -. M. Global trend of survival and damage of systemic lupus erythematosus: meta-analysis and meta-regression of observational studies from the 1950s to 2000s. Seminars in arthritis and rheumatism. 41 (6), 830-839 (2012).
- Kaul, A., Gordon, C., et al. Systemic lupus erythematosus. Nature reviews. Disease primers. 2, 16039 (2016).
- Annunziato, F., Romagnani, S. Heterogeneity of human effector CD4+ T cells. Arthritis Research & Therapy. 11 (6), 257 (2009).
- Peck, A., Mellins, E. D. Plasticity of T-cell phenotype and function: the T helper type 17 example. Immunology. 129 (2), 147-153 (2010).
- Basso, A. S., Cheroutre, H., Mucida, D. More stories on Th17 cells. Cell research. 19 (4), 399-411 (2009).
- Ornatsky, O., Bandura, D., Baranov, V., Nitz, M., Winnik, M. A., Tanner, S. Highly multiparametric analysis by mass cytometry. Journal of Immunological Methods. 361 (1-2), 1-20 (2010).
- Ornatsky, O., Baranov, V. I., Bandura, D. R., Tanner, S. D., Dick, J. Multiple cellular antigen detection by ICP-MS. Journal of Immunological Methods. 308 (1-2), 68-76 (2006).
- Bendall, S. C., Simonds, E. F., et al. Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum. Science. 332 (6030), 687-696 (2011).
- Bandura, D. R., Baranov, V. I., et al. Mass Cytometry: Technique for Real Time Single Cell Multitarget Immunoassay Based on Inductively Coupled Plasma Time-of-Flight Mass Spectrometry. Analytical Chemistry. 81 (16), 6813-6822 (2009).
- Leipold, M. D., Maecker, H. T. Mass cytometry: protocol for daily tuning and running cell samples on a CyTOF mass cytometer. Journal of visualized experiments : JoVE. (69), e4398 (2012).
- McCarthy, R. L., Duncan, A. D., Barton, M. C. Sample Preparation for Mass Cytometry Analysis. Journal of visualized experiments : JoVE. (122), (2017).
- Rahman, A., Isenberg, D. A. Systemic lupus erythematosus. The New England journal of medicine. 358 (9), 929-939 (2008).
- O’Gorman, W. E., Hsieh, E. W. Y., et al. Single-cell systems-level analysis of human Toll-like receptor activation defines a chemokine signature in patients with systemic lupus erythematosus. The Journal of allergy and clinical immunology. 136 (5), 1326-1336 (2015).
- O’Gorman, W. E., Kong, D. S., et al. Mass cytometry identifies a distinct monocyte cytokine signature shared by clinically heterogeneous pediatric SLE patients. Journal of Autoimmunity. 81, 74-89 (2017).
- Simonds, E. F., Bendall, S. C., et al. Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nature Biotechnology. , 1-8 (2011).
- Amir, E. -. A. D., Davis, K. L., et al. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nature Biotechnology. 31 (6), 545-552 (2013).
- Bruggner, R. V., Bodenmiller, B., Dill, D. L., Tibshirani, R. J., Nolan, G. P. Automated identification of stratifying signatures in cellular subpopulations. Proceedings of the National Academy of Sciences of the United States of America. 111 (26), E2770-E2777 (2014).
- Levine, J. H., Simonds, E. F., et al. Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis. Cell. 162 (1), 184-197 (2015).
- Samusik, N., Good, Z., Spitzer, M. H., Davis, K. L., Nolan, G. P. Automated mapping of phenotype space with single-cell data. Nature Publishing Group. 13 (6), 493-496 (2016).
- Spitzer, M. H., Gherardini, P. F., et al. IMMUNOLOGY. An interactive reference framework for modeling a dynamic immune system. Science. 349 (6244), 1259425 (2015).
- Fienberg, H. G., Simonds, E. F., Fantl, W. J., Nolan, G. P., Bodenmiller, B. A platinum-based covalent viability reagent for single-cell mass cytometry. Cytometry Part A. 81 (6), 467-475 (2012).
- Jansen, K., Blimkie, D., et al. Polychromatic flow cytometric high-throughput assay to analyze the innate immune response to Toll-like receptor stimulation. Journal of Immunological Methods. 336 (2), 183-192 (2008).
- Zunder, E. R., Finck, R., et al. Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm. Nature Protocols. 10 (2), 316-333 (2015).
- Lai, L., Ong, R., Li, J., Albani, S. A CD45-based barcoding approach to multiplex mass-cytometry (CyTOF). Cytometry Part A. , (2015).
- Mei, H. E., Leipold, M. D., Schulz, A. R., Chester, C., Maecker, H. T. Barcoding of live human peripheral blood mononuclear cells for multiplexed mass cytometry. The Journal of Immunology. 194 (4), 2022-2031 (2015).
- Finck, R., Simonds, E. F., et al. Normalization of mass cytometry data with bead standards. Cytometry Part A. 83 (5), 483-494 (2013).
- Takahashi, C., Au-Yeung, A., et al. Mass cytometry panel optimization through the designed distribution of signal interference. Cytometry. Part A : the journal of the International Society for Analytical Cytology. 91 (1), 39-47 (2017).
