细胞内染色和流式细胞仪识别鼠主动脉，肾脏和淋巴结内淋巴细胞亚群的高血压模型
Summary
本文提供了详细的方法来识别和量化细胞内染色鼠肾，主动脉和淋巴结中存在功能性T淋巴细胞亚群和流式细胞仪。被选中的血管紧张素II诱导高血压模型来解释，一步一步的程序和流式细胞仪的基本原则和细胞内染色。
Abstract
It is now well known that T lymphocytes play a critical role in the development of several cardiovascular diseases1,2,3,4,5. For example, studies from our group have shown that hypertension is associated with an excessive accumulation of T cells in the vessels and kidney during the development of experimental hypertension6. Once in these tissues, T cells produce several cytokines that affect both vascular and renal function leading to vasoconstriction and sodium and water retention1,2. To fully understand how T cells cause cardiovascular and renal diseases, it is important to be able to identify and quantify the specific T cell subsets present in these tissues. T cell subsets are defined by a combination of surface markers, the cytokines they secrete, and the transcription factors they express. The complexity of the T cell population makes flow cytometry and intracellular staining an invaluable technique to dissect the phenotypes of the lymphocytes present in tissues. Here, we provide a detailed protocol to identify the surface and intracellular markers (cytokines and transcription factors) in T cells isolated from murine kidney, aorta and aortic draining lymph nodes in a model of angiotensin II induced hypertension. The following steps are described in detail: isolation of the tissues, generation of the single cell suspensions, ex vivo stimulation, fixation, permeabilization and staining. In addition, several fundamental principles of flow cytometric analyses including choosing the proper controls and appropriate gating strategies are discussed.
Introduction
最近的证据表明，适应性免疫系统，特别是T淋巴细胞，在几个心血管疾病1,2,3,4,5的发展中发挥了关键作用。例如，在血管紧张肽II引起的高血压模型中，T细胞在血管和小鼠的肾脏的累积已经描述6。血管积累主要是在外膜和血管周围的脂肪。在肾脏中，T细胞堆积在髓质和肾皮质两者。取决于哪个子集参与，这些T细胞产生不同的细胞因子，可以影响血管和肾功能，并导致病理的发展（由麦克马斯特等 6中综述）。
CD4 + T辅助淋巴细胞可分为几个子集：根据其职能和签名CYTO T辅助1（Th1细胞），Th2细胞，TH9，Th17细胞，TH22，调节性T（Treg细胞）细胞和T滤泡辅助（Tfh发挥细胞）基恩斯7。同样，CD8 +细胞毒性T细胞可以被分类为TC1，TC2，TC17或TC9 8。也有（不表达的CD4或CD8 T细胞的标志物即细胞）双阴性T细胞。这些细胞的一个子集具有一个备用的γδT细胞受体（而不是经典α和β受体），因此，被称为的γδT细胞。通过表面标记，细胞因子和转录因子的流式细胞仪的多参数分析构成，以确定这些细胞中的最好的方法。虽然这种方法是在免疫学领域广泛使用，这是不那么在实体器官和在心血管疾病的设置说明。
从历史上看，在组织中的淋巴细胞的识别仅限于免疫组化或RT-PCR的方法。虽然免疫组织化学和免疫功能强大的方法来确定一个int抗原的组织分布erest，他们是不足以表型鉴定所涉及的子集。此外，虽然RT-PCR分析是检测抗原，细胞因子或转录因子的mRNA表达是有用的，它不允许在单个细胞水平同时多种蛋白质的检测。
流的出现术，特别是当与细胞内染色组合以检测细胞因子和转录因子，提供了强大的技术，其允许鉴定和定量在固体器官的免疫细胞亚群的单个细胞水平的调查。我们已经优化了细胞内染色法，流式细胞仪鼠肾，主动脉和主动脉淋巴结内出现在血管紧张素II诱发的高血压模型中的主要T细胞亚群鉴别。在一个高度重新组织消化， 离体活化，透化，并且表面和细胞内染色结果：每一步的优化可生产测定可应用于其他心血管和肾脏疾病模型。
Protocol
Representative Results
Discussion
The protocol described herein has been optimized to properly identify T cell subsets present within murine kidneys, aorta and lymph nodes. This protocol can be easily adapted to examine other immune cell subsets such as B lymphocytes and innate immune cells and can be modified to include other tissue types. The digestion step is critical and has to be modified and optimized for each tissue9. A prolonged digestion step or the use of an inappropriate enzyme can affect the stability of antigen expression. Similar…
Disclosures
The authors have nothing to disclose.
Acknowledgements
这项工作是由美国心脏协会奖学金奖（16POST29950007）到FL，从健康（NIH T32 HL069765），以BLD，美国心脏协会奖学金奖（14POST20420025）至MA萨利赫全国学院培训津贴，以及美国国立卫生研究院支持K08奖（HL121671），男男性接触者。 MSM也由吉利德科学公司研究基金支持
Materials
| Collagenase D | ROCHE | 11088882001 | |
| Collagenase A | ROCHE | 10103586001 | |
| Collagenase B | ROCHE | 11088815001 | |
| Dnase | ROCHE | 10104159001 | |
| 1X Red blood cell lysis buffer | eBioscience | 00-4333-57 | |
| RPMI Medium 1614 1X | Gibco | 11835-030 | |
| DPBS without calcium and magnesium | Gibco | 14190-144 | |
| Percoll | GE Healthcare | 17-5445-02 | For density gradient centrifugation |
| GentleMACS ™ C tube | Miltenyi Biotec | 130-096-334 | |
| GentleMACS dissociator device | Miltenyi Biotec | 130-093-235 | Use the program SPLEEN_04 |
| Cell activation cocktail (with Brefeldin A) | Biolegend | 423303 | |
| anti-CD16/32 | eBioscience | 14-0161-81 | dilute 1:100 |
| LIVE/DEAD fixable violet dead cell stain kit | Life Technologies | L34955 | |
| Transcription factor buffer set | BD Pharmingen | 562725 | |
| OneComp eBeads | eBioscience | 01-1111-42 | |
| 123 count eBeads | eBioscience | 01-1234-42 | |
| CD45 AmCyan (clone 30-F11) | BioLegend | 103138 | |
| CD3 PerCP-Cy5.5 (clone 17A2) | BioLegend | 100218 | |
| IL-17A FITC (clone TC11-18H10.1) | BioLegend | 506910 | |
| IL-17F APC (clone 9D3.1C8) | BioLegend | 517004 | |
| CD4 APC-Cy7 (clone GK1.5) | BD Biosciences | 560181 | |
| CD8 APC (clone 53-67) | eBioscience | 17-0081-82 | |
| T-bet PE-Cy7 (clone 4B10) | BioLegend | 644823 | |
| IFNγ FITC (clone XMG1.2) | BD Biosciences | 557724 |
References
- Saleh, M. A., McMaster, W. G., Wu, J., et al. Lymphocyte adaptor protein LNK deficiency exacerbates hypertension and end-organ inflammation. J Clin Invest. 125 (3), 1189-1202 (2015).
- Madhur, M. S., Lob, H. E., McCann, L. A., et al. Interleukin 17 promotes angiotensin II-induced hypertension and vascular dysfunction. Hypertension. 55 (2), 500-507 (2010).
- Laroumanie, F., Douin-Echinard, V., Pozzo, J., et al. CD4+ T Cells Promote the Transition From Hypertrophy to Heart Failure During Chronic Pressure Overload. Circulation. 129 (21), 2111-2124 (2014).
- Guzik, T. J., Hoch, N. E., Brown, K. A., et al. Role of the T cell in the genesis of angiotensin II induced hypertension and vascular dysfunction. J Exp Med. 204 (10), 2449-2460 (2007).
- Ketelhuth, D. F. J., Hansson, G. K. Adaptive Response of T and B Cells in Atherosclerosis. Circ Res. 118 (4), 668-678 (2016).
- McMaster, W. G., Kirabo, A., Madhur, M. S., Harrison, D. G. Inflammation, Immunity, and Hypertensive End-Organ Damage. Circ Res. (6), 1022-1033 (2015).
- Luckheeram, R. V., Zhou, R., Verma, A. D., et al. CD4+T Cells: Differentiation and Functions. Clin Dev Immunol. 2012, 1-12 (2012).
- Mittrücker, H. -. W., Visekruna, A., Huber, M. Heterogeneity in the differentiation and function of CD8+ T cells. Arch Immunol Ther Exp (Warsz). 62 (6), 449-458 (2014).
- Autengruber, A., Gereke, M., Hansen, G., Hennig, C., Bruder, D. Impact of enzymatic tissue disintegration on the level of surface molecule expression and immune cell function. Eur J Microbiol Immunol (Bp). 2 (2), 112-120 (2012).
- Finak, G., Langweiler, M., Jaimes, M., et al. Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium. Sci Rep. 6, 20686 (2016).
- Herzenberg, L. A., Parks, D., Sahaf, B., Perez, O., Roederer, M., Herzenberg, L. A. The history and future of the fluorescence activated cell sorter and flow cytometry: a view from Stanford. Clin Chem. 48 (10), 1819-1827 (2002).
- Hrvatin, S., Deng, F., O’Donnell, C. W., Gifford, D. K., Melton, D. A. MARIS: method for analyzing RNA following intracellular sorting. PLoS One. 9 (3), 89459 (2014).
- Kalisky, T., Quake, S. R. Single-cell genomics. Nat Methods. 8 (4), 311-314 (2011).
- Chattopadhyay, P. K., Roederer, M. Cytometry: Today’s technology and tomorrow’s horizons. Methods. 57 (3), 251-258 (2012).
- Jiang, L., Tixeira, R., Caruso, S., et al. Monitoring the progression of cell death and the disassembly of dying cells by flow cytometry. Nat Protoc. 11 (4), 655-663 (2016).
- Lemoine, S., Jaron, B., Tabka, S., et al. Dectin-1 activation unlocks IL12A expression and reveals the TH1 potency of neonatal dendritic cells. J Allergy Clin Immunol. 136 (5), 1355-1368 (2015).
- Gaublomme, J. T., Yosef, N., Lee, Y., et al. Single-Cell Genomics Unveils Critical Regulators of Th17 Cell Pathogenicity. Cell. 163 (6), 1400-1412 (2015).
