This article provides detailed methodology to identify and quantify functional T lymphocyte subsets present within murine kidney, aorta and lymph nodes by intracellular staining and flow cytometry. The model of angiotensin II induced hypertension was chosen to explain, step-by-step, the procedures and fundamental principles of flow cytometry and intracellular staining.
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.
Recent evidence demonstrates that the adaptive immune system, particularly T lymphocytes, play a critical role in the development of several cardiovascular diseases1,2,3,4,5. For example, in the model of angiotensin II induced hypertension, an accumulation of T cells in the vessels and kidneys of mice has been described6. The vascular accumulation is predominantly in the adventitia and the perivascular fat. In the kidney, T cells accumulate in both the medulla and renal cortex. Depending on which subset is involved, these T cells give rise to different cytokines that can affect vascular and renal function and lead to the development of pathology (reviewed by McMaster et al.6).
CD4+ T helper lymphocytes can be divided into several subsets: T helper 1 (Th1), Th2, Th9, Th17, Th22, T regulatory (Treg) cells, and T follicular helper (Tfh) cells based on their functions and signature cytokines7. Similarly, CD8+ cytotoxic T cells can be classified as Tc1, Tc2, Tc17 or Tc98. There are also double negative T cells (i.e. cells that do not express the CD4 or CD8 T cell markers). A subset of these cells possess an alternate gamma delta T cell receptor (instead of the classical alpha and beta receptors) and are therefore referred to as gamma delta T cells. The multi-parameter analysis by flow cytometry of surface marker, cytokine and transcription factor constitutes the best approach to identify these cells. Although this method is extensively used in the field of immunology, it is less well described in solid organs and in the setting of cardiovascular diseases.
Historically, the identification of lymphocytes in tissues was limited to immunohistochemistry or RT-PCR approaches. Although immunohistochemistry and immunofluorescence are powerful methods to determine the tissue distribution of an antigen of interest, they are inadequate to phenotypically identify the subsets involved. In addition, while RT-PCR analysis is useful to detect mRNA expression of antigens, cytokines or transcription factors, it doesn't allow the detection of multiple proteins simultaneously at the level of individual cells.
The advent of flow cytometry, especially when combined with intracellular staining to detect cytokines and transcription factors, provides investigators with a powerful technique that allows identification and quantification at the single cell level of immune cell subsets in solid organs. We have optimized an intracellular staining assay to identify by flow cytometry the major T cell subsets present within murine kidney, aorta and aortic draining lymph nodes in a model of angiotensin II induced hypertension. The optimization of each step: tissue digestion, ex vivo activation, permeabilization, and surface and intracellular staining results in a highly reproducible assay that can be applied to other cardiovascular and renal disease models.
Vanderbilt University's Institutional Animal Care and Use Committee has approved the procedures described herein. Mice are housed and cared for in accordance with the Guide for the Care and Use of Laboratory Animals (National Academies Press. Revised 2010).
1. Isolation of the Aortic Draining Lymph Nodes, Kidney and Aorta from Mice
2. Generation of Single Cell Suspensions from Each Tissue
3. Ex Vivo Stimulation for Cytokine Detection by Flow Cytometry
4. Surface Staining
5. Fixation, Permeabilization and Intracellular Staining
6. Compensation, Gating, Normalization, and Tips
The protocol described permits the identification of surface and intracellular markers in T cells isolated from murine kidney, aorta and aortic draining lymph nodes in a model of angiotensin II induced hypertension. Representative results are presented below.
Figure 1 demonstrates the gating strategy used to identify the T cell population in a single cell suspension prepared from the aorta of a WT mouse infused with angiotensin II to induce hypertension. A similar strategy is used in the kidney and lymph nodes. The Forward Scatter Area (FSC-A) and Side Scatter Area (SSC-A) voltage was adjusted to detect the leukocyte population (G1) and to exclude debris. The live cells (G2) are negative for the viability marker conjugated with Pacific blue. Live cells were then gated on Forward Scatter Height (FSC-H) and Forward Scatter Area (FSC-A) to gate only on the singlet population (G3). Leukocytes were then selected by gating on SSC-A and CD45 (G4). CD45 is conjugated with AmCyan in this example. Finally, T cells are gated as the CD45+CD3+ population (G5). CD3 is conjugated with PerCP-Cy5.5 in this example.
To determine the presence of IL-17A and IL-17F producing T cells within murine kidney and aorta in this model, single cell suspensions were stained for IL-17A and IL-17F. Figure 2 illustrates fluorescence minus one controls (FMOs) for IL-17A and IL-17F staining in a kidney sample (conjugated with FITC and APC, respectively). FMO controls are samples that contain all the antibodies in a panel except for one. As expected, very few cells are positive for IL-17A (Figure 2A) or IL-17F (Figure 2B) in the FMO controls. These controls permit accurate discrimination of positive versus negative signals to properly adjust the gates to identify the cells positive for IL-17A or IL-17F in the experimental samples.
Figure 3 provides an example of intracellular staining of T cells isolated from kidney (Figure 3A) and aorta (Figure 3B) of WT mice infused with vehicle (Sham) or angiotensin II (Ang II). Indeed, a subset of T cells that express IL-17A or IL-17F can be detected in both tissues in this model.
Figure 4 illustrates intracellular staining of T cells within the aortic draining lymph nodes in this model (Figure 4A). CD8+ T cells were first gated (Figure 4B). Then, the expression of two Tc1 markers, the cytokine IFNγ or the transcription factor T-bet, were quantified from the CD8+ T cell subset. Figure 4C illustrates the FMOs for IFNγ and T-bet staining in the lymph node samples (conjugated with FITC and PE-Cy7, respectively). Figure 4D shows that in the aortic draining lymph nodes of WT mice infused with angiotensin II, a population of CD8+IFNγ+ and CD8+T-bet+ cells can be identified.
Figure 1: Flow cytometry gating strategy to identify T cells. Leukocytes are first gated on a forward scatter/side scatter (FSC-A/SSC-A) dot plot (G1), and live cells are selected (G2). The cells are then gated on singlets (FSC-A/FSC-H) (G3). Cells from G3 are further characterized by the expression of CD45 (G4). Finally, T cells are gated on CD45+CD3+ double positive cells (G5). This single cell suspension was prepared from the whole aorta isolated from a wild type (WT) mouse infused with angiotensin II to induce hypertension. Please click here to view a larger version of this figure.
Figure 2: Fluorescence minus one controls (FMO) for IL-17A and IL-17F. (A) A single cell suspension isolated from an angiotensin II treated murine kidney sample was stained using a fixable viability marker (Pacific Blue), CD45 (AmCyan), CD3 (PerCP-Cy5.5) and IL-17F (APC). The antibody for IL-17A was omitted to determine the proper gating for IL-17A. (B) A single cell suspension isolated from an angiotensin II treated murine kidney sample was stained using a fixable viability marker (Pacific Blue), CD45 (AmCyan), CD3 (PerCP-Cy5.5) and IL-17A (FITC). In this case, the antibody for IL-17F was omitted. Please click here to view a larger version of this figure.
Figure 3: Intracellular staining of T cells isolated from murine kidney and aorta for IL-17A and IL-17F. Flow cytometry dot plots showing IL-17A and IL-17F expression in T cells from kidney (A) and aorta (B) from WT mice infused with vehicle (Sham) or angiotensin II (Ang II) and previously gated on CD45+CD3+ cells. Please click here to view a larger version of this figure.
Figure 4: Intracellular staining of T cells isolated from murine aortic draining lymph nodes. (A) Macroscopic appearances of two lumbar aortic draining lymph nodes in a WT mouse. (B) Representative flow cytometry dot plots of CD4+ and CD8+ T cells isolated from four aortic draining lymph nodes isolated from a WT mouse infused with angiotensin II and previously gated on CD45+CD3+ cells. (C) A single cell suspension isolated from lymph nodes was stained using a viability marker (Pacific Blue), CD3 (PerCP-Cy5.5), CD4 (APC-Cy7), and CD8 (APC). FMO controls are shown in which the antibody for IFNγ (FITC) or T-bet (PE-Cy7) was omitted to determine the proper gating. (D) Flow cytometry dot plots demonstrating positive IFNγ and T-bet expression within CD8+ lymph node T cells using the gates determined by the FMO controls. Please click here to view a larger version of this figure.
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. Similarly, an incomplete digestion can affect the results leading to a lower number of positive cells. Furthermore, the time of ex vivo stimulation needs to be carefully adjusted for each cell type/cytokine to allow for optimal stimulation with minimal cell toxicity.
Although intracellular staining coupled with flow cytometry analysis is one of the most powerful methods to analyze immune processes at a cellular level in blood and tissues, this technique has its limitations. These limitations include the relatively low number of immune cells in cardiovascular and renal tissues. Thus, depending on the cell type examined, it may be necessary to pool organs from several mice to obtain one sample. Furthermore, the instability of markers is another limitation as the expression of markers can be affected by several steps during the process. For this reason, it is advisable to perform histology in parallel to confirm the results obtained by flow cytometry. There are also special considerations regarding the use of the flow cytometer and the interpretation of the results. The flow cytometer is a sophisticated instrument and requires highly trained operators. Importantly, despite the use of compensation controls, there is still an issue of spectral overlap that limits experiments to 8-12 markers (usually 8) per sample.
Moreover, this technique is very sensitive and subject to several experimental manipulations which can lead to slight day-to-day variation in the quantification of results. Thus, if performing this technique across multiple days for a given study, it is important to include control and experimental groups each day to determine relative changes. Finally, another limitation/source of variation is the choice of the markers used to identify a population10. Each study tends to use different combinations of markers and fluorochromes to define a population, which can lead to slight differences in quantification.
Despite these limitations, this is a powerful experimental technique that allows the identification and quantification of T cell subsets in solid organs. In fact, while other techniques measure either the expression of surface markers, cytokines or transcription factors separately, this method permits the measurement of several markers simultaneously at the single cell level. Furthermore, once the cells are identified, several other parameters can then be determined11,12,13,14. For example, one can evaluate for markers of apoptosis, protein phosphorylation or the proliferation of a specific T cell subset15. In addition, there are newer proprietary methods to detect mRNAs in cells using flow cytometry16,17.
In conclusion, we have outlined a detailed and reproducible protocol to identify T cell subsets using surface and intracellular markers (cytokines and transcription factors) in murine kidney, aorta and aortic draining lymph nodes in a model of angiotensin II induced hypertension. This protocol can be applied to other tissues (with slight modification) and to other models of disease.
The authors have nothing to disclose.
This work was supported by an American Heart Association Fellowship Award (16POST29950007) to FL, a training grant from the National Institutes of Health (NIH T32 HL069765) to BLD, an American Heart Association Fellowship Award (14POST20420025) to MA Saleh, and an NIH K08 award (HL121671) to MSM. MSM is also supported by a research grant from Gilead Sciences, Inc.
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 |