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High-dimensional, single-cell characterization of the brain's immune compartment

Nature Neuroscience volume 20, pages 1300–1309 (2017)Cite this article

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Abstract

The brain and its borders create a highly dynamic microenvironment populated with immune cells. Yet characterization of immune cells within the naive brain compartment remains limited. In this study, we used CyTOF mass cytometry to characterize the immune populations of the naive mouse brain using 44 cell surface markers. By comparing immune cell composition and cell profiles between the brain compartment and blood, we were able to characterize previously undescribed cell subsets of CD8 T cells, B cells, NK cells and dendritic cells in the naive brain. Using flow cytometry, we show differential distributions of immune populations between meninges, choroid plexus and parenchyma. We demonstrate the phenotypic ranges of resident myeloid cells and identify CD44 as a marker for infiltrating immune populations. This study provides an approach for a system-wide view of immune populations in the brain and is expected to serve as a resource for understanding brain immunity.

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Figure 1: Characterization of the brain's resident and infiltrating immune cell populations by mass cytometry.
Figure 2: Differential abundances of infiltrating immune cell populations (CD45high) in the brain compared to in peripheral blood.
Figure 3: Functional marker expression of immune cells in the brain and blood.
Figure 4: Comparison of specific immune cell subsets between the brain and peripheral blood.
Figure 5: High-dimensional characterization of resident myeloid cells (CD45lowCX3CR1+CD11b+).
Figure 6: Identification of resident and infiltrating immune cells using CD44.

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Acknowledgements

We thank S. Schwarzbaum and N. Green for editing the paper; M. Schwartz, S. Shen-Orr, I. Strominger and H. Elyahu for their discussions and advice; G. Vildebaum and L. Saadaa for their help with the experiments; and A. Grau, Y. Sakuory, S. Blumenfeld and the Biomedical core facility at the Technion Faculty of Medicine for technical support and remarks. This study was supported by the Israeli Ministry of Science, Technology & Space (MOST; 3-12070), Prince Center for Neurodegenerative Diseases, Israeli Society for Science (ISF; 1862/15), the FP-7-CIG grant (618654) and the Adelis Foundation.

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Authors and Affiliations

  1. Department of Immunology, Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel

    Ben Korin, Tamar L Ben-Shaanan, Maya Schiller, Tania Dubovik, Hilla Azulay-Debby, Nadia T Boshnak, Tamar Koren & Asya Rolls

  2. Department of Neuroscience, Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel

    Ben Korin, Tamar L Ben-Shaanan, Maya Schiller, Hilla Azulay-Debby, Nadia T Boshnak, Tamar Koren & Asya Rolls

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Contributions

B.K. designed and carried out the experiments, analyzed and interpreted the results and wrote the manuscript; T.L.B.-S. and M.S. contributed to the execution and design of the experiments and the analysis of the results and revised the manuscript; T.D. ran the CyTOF samples and contributed to CyTOF analyses and to the manuscript; H.A.-D. carried out the RT-PCR experiments and revised the manuscript; N.T.B. designed the website to present the data and helped with the experiments; T.K. helped with the experiments; and A.R. led the experimental design and interpretation of results and wrote the manuscript.

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Integrated supplementary information

Supplementary Figure 1 SPADE population bubbles in dot plots.

(a) Illustration of gating strategy for identification of resident and infiltrating myeloid cells. For each cell population, as indicated in the SPADE plot, a histogram of CD45 expression and a dot plot of the markers relevant for cell characterization are presented. Of note, only the selected population is depicted in the dot plots. The relative expression of these markers compared to the entire population is shown in Figure 1. (b) Histograms indicating the expression levels of the selected cell surface markers among the “undefined cells” population.

Supplementary Figure 2 Expression of F4/80 in naive mouse brain immune populations.

Histogram indicating the differential expression of F4/80 on immune cells in the brain compartment (blue) and blood (red). Our analysis indicated very low levels of F4/80 on immune cells in naïve mouse brains. Positive staining (dashed black rectangle) of the antibody is valid according to the blood taken from the same mouse. Representative image of six experiments.

Supplementary Figure 3 Evaluation of cell granularity.

Flow cytometry characterization of granularity in CD11b+/Ly6Clow/Ly6Ghigh cells (granulocytes) compared to CD11b+/Ly6Chigh/Ly6Glow cells (monocytes). Cells are indicated on the left panel. The side scatter (SSC) distribution of these cells, indicative of cell granularity, is shown on the right panel. Representative image of six mice.

Supplementary Figure 4 Identification of CD45+ cells in the brain compartment that were present in the blood circulation at time of mouse perfusion (perfusion validation).

(a) Mice were injected with PE-conjugated anti-mouse CD45 injection (intravenous; i.v.), and three minutes later, we sampled the blood and perfused the mice. (b) Pie chart representing the percentage of each immune population that was PE positive among the infiltrating immune populations in the brain compartments as determined using flow cytometry (mean ± sem; n=3; representative image of three experiments). (c) TER119 staining identified using flow cytometry detects red blood cells among CD45high cells in the brain compartment (mean ± sem; n=7).

Supplementary Figure 5 Characterization of cell subsets in the brain compartment.

Histograms demonstrating relevant cell surface markers expressed on each population of infiltrating immune cells: (a) DCs (CD11c, CD103, CD26, CD24, CD11b, CD64), (b) Gr-1+ myeloid cells (Gr-1, CD11b, CD24, CD62L), (c) Monocytes/Macrophages (Ly6C, CD11b, CD24, CD62L, CD64, CD115, CD26, CCR2), (d) CD4 T cells (CD4, CD44, CD62L, CD5, FR4, CD27, CD69), (e) CD8 T cells (CD8, CD44, CD62L, CD5, CD27, CD69, CD86), (f) B cells (CD19, IgD, IgM, CD5, CD24, CD69) (g) NK cells (CD49b, CD62L, CD27, IL-2R, CD69). FC; flow cytometry. Dashed line indicates the negative staining.

Supplementary Figure 6 Functional marker expression of resident and infiltrating immune cells in the naive mouse brain compartment.

(a-r) The expression of functional markers (antigen presentation and co-stimulation: MHC-II, CD80, CD86, CD27; cellular activation: CD115, TLR-2, CD14, CD44, CD69; migration: CCR5, CXCR4, CD62L; and cytokine receptors: IL-1R, IL-2R, IL-4R, IL-6R, TNF-αR and IFN-γR, respectively) is overlaid on top of annotated SPADE diagrams, enabling simultaneous visualization of each marker's expression in various cell populations. For each marker, the colored gradient range corresponds to the arcsinh transformed expression of the median marker expression level; node size correlates with the number of cells. Representative image of six experiments. Res. Myeloid cells, Resident Myeloid cells; Monocytes/Mϕs, Monocytes/Macrophages.

Supplementary Figure 7 Flow cytometry validation of CX3CR1 expression in brain versus blood populations.

Using flow cytometry, the percentage of CX3CR1+ cells in (a) DCs, (b) B cells, (c) NK cells, (d) CD8 T cells and (e) CD4 T cells was analyzed in the brain compartment and blood. Representative image of two experiments (mean ± sem; n=7; Student’s t-test; **** P<0.0001).

Supplementary Figure 8 TCR-β-like immunoreceptor expression on resident myeloid cells.

(a) Histogram indicating the expression levels of TCR-β or TCR-β-like immunoreceptor on a TCR-β negative population (B cells; orange), resident myeloid cells (blue) and a TCR-β positive population (T cells; red), representative image of five experiments. (b) The expression of TCR-β -like immunoreceptor on resident myeloid cells, overlaid on a CD11b/CX3CR1 dot plot, representative image of five experiments. (c) Flow cytometry overlay histograms, indicating the expression of TCR-β-like immunoreceptor on resident myeloid cells (blue) compared to unstained cells (green), representative image of ten mice. (d) Fold change of TCR-β-like immunoreceptor expression following inflammation. Mice were injected with heat-killed E. coli i.c.v and 48 hours later their brains were analyzed. One of three experiments (mean ± sem; n=4; Student’s t-test; *** P<0.001). (e) PCR analysis of mRNA expression of TCR-β (top) and β-actin (bottom) among splenic CD4 T cells (positive control; left), B cell-line (C38; negative control; middle) and resident myeloid cells (right). Res. M. cells, Resident Myeloid cells; Inflamm., Inflammation.

Supplementary Figure 9 Gating strategy for flow cytometry single-cell analysis: selection of resident and infiltrating myeloid cells.

Single-cell analysis was performed on live single cells, chosen according to their FSC and SSC parameters. Resident myeloid cells were selected as CD45low/CX3CR1+/CD11b+. Infiltrating myeloid cells were selected as CD45high/CD11b+. Representative image of seven mice.

Supplementary Figure 10 Real-time PCR validation of CD44 and Tmem119.

Infiltrating and resident immune cells were isolated from naïve mouse brains using FACS, and total RNA was extracted and reverse transcribed to cDNA. The expression levels of (a) CD44 and (b) Tmem119 were examined by Real Time PCR analysis and normalized by the relevant expression level of resident myeloid cells. Each dot represents a pool of four mice from an independent experiment (mean ± sem; n=3; Student’s t-test; ** P<0.01; ****P<0.0001).

Supplementary Figure 11 Gating strategy for mass cytometry single-cell analysis.

Single-cell analysis was performed on live single cells, chosen by the following gating strategy: cell length versus Iridium (Ir) 191/193 (choosing singlets), Ir191 versus Ir193 (choosing live cells), and Ir191/193 versus Rhodium (Rh; excluding dead cells). Representative image of six experiments.

Supplementary Figure 12 Full-length gel image of the PCR analysis of mRNA expression shown in Supplementary Figure 8.

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Korin, B., Ben-Shaanan, T., Schiller, M. et al. High-dimensional, single-cell characterization of the brain's immune compartment. Nat Neurosci 20, 1300–1309 (2017). https://doi.org/10.1038/nn.4610

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