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. 2017 Jan 17;46(1):148-161.
doi: 10.1016/j.immuni.2016.11.005. Epub 2016 Dec 13.

Human Innate Lymphoid Cell Subsets Possess Tissue-Type Based Heterogeneity in Phenotype and Frequency

Yannick Simoni  1 , Michael Fehlings  2 , Henrik N Kløverpris  3 , Naomi McGovern  2 , Si-Lin Koo  4 , Chiew Yee Loh  2 , Shawn Lim  2 , Ayako Kurioka  5 , Joannah R Fergusson  5 , Choong-Leong Tang  6 , Ming Hian Kam  6 , Koh Dennis  7 , Tony Kiat Hon Lim  8 , Alexander Chung Yaw Fui  9 , Chan Weng Hoong  10 , Jerry Kok Yen Chan  11 , Maria Curotto de Lafaille  12 , Sriram Narayanan  13 , Sonia Baig  14 , Muhammad Shabeer  14 , Sue-Anne Ee Shiow Toh  15 , Henry Kun Kiaang Tan  16 , Rosslyn Anicete  16 , Eng-Huat Tan  4 , Angela Takano  8 , Paul Klenerman  5 , Alasdair Leslie  17 , Daniel S W Tan  18 , Iain Beehuat Tan  19 , Florent Ginhoux  2 , Evan W Newell  20
Affiliations

Human Innate Lymphoid Cell Subsets Possess Tissue-Type Based Heterogeneity in Phenotype and Frequency

Yannick Simoni et al. Immunity. .

Erratum in

  • Human Innate Lymphoid Cell Subsets Possess Tissue-Type Based Heterogeneity in Phenotype and Frequency.
    Simoni Y, Fehlings M, Kløverpris HN, McGovern N, Koo SL, Loh CY, Lim S, Kurioka A, Fergusson JR, Tang CL, Kam MH, Dennis K, Lim TKH, Fui ACY, Hoong CW, Chan JKY, Curotto de Lafaille M, Narayanan S, Baig S, Shabeer M, Toh SES, Tan HKK, Anicete R, Tan EH, Takano A, Klenerman P, Leslie A, Tan DSW, Tan IB, Ginhoux F, Newell EW. Simoni Y, et al. Immunity. 2018 May 15;48(5):1060. doi: 10.1016/j.immuni.2018.04.028. Immunity. 2018. PMID: 29768165 No abstract available.

Abstract

Animal models have highlighted the importance of innate lymphoid cells (ILCs) in multiple immune responses. However, technical limitations have hampered adequate characterization of ILCs in humans. Here, we used mass cytometry including a broad range of surface markers and transcription factors to accurately identify and profile ILCs across healthy and inflamed tissue types. High dimensional analysis allowed for clear phenotypic delineation of ILC2 and ILC3 subsets. We were not able to detect ILC1 cells in any of the tissues assessed, however, we identified intra-epithelial (ie)ILC1-like cells that represent a broader category of NK cells in mucosal and non-mucosal pathological tissues. In addition, we have revealed the expression of phenotypic molecules that have not been previously described for ILCs. Our analysis shows that human ILCs are highly heterogeneous cell types between individuals and tissues. It also provides a global, comprehensive, and detailed description of ILC heterogeneity in humans across patients and tissues.

Keywords: CyTOF; ILC; ILC1; ILC2; ILC3; human; ieILC1.

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Figures

Graphic abstract
Graphic abstract
Figure 1
Figure 1. t-SNE Analysis Objectively Delineates ILCs Populations—with the Exception of ILC1 Cells
(A) Visualized t-SNE map of cells isolated from cord blood, tonsil, and colon tissue. t-SNE was performed after depleting B and T cells and gating on live CD45+ Lin− (FcεR1α− CD14− CD19− CD123−, see Figure S1A for gating strategy). Clusters (cells populations) were identified by manual gating. Data shown are representatives of one donor per tissue from 3 to 10 independent experiments. (B) Based on the clusters identified in (A), median intensities for each of the marker were calculated and plotted as a heatmap to identify the respective ILC populations. Data shown are from donor represented in (A). (C) Identification of putative ILC1 cells using standard bi-axial gating (CD45+ Lin− CD94− CD127− CRTH2− c-Kit− NKp44−) from tonsil. Data shown are from donor represented in (A). (D) Histogram of T-bet expression by putative ILC1 cells in tonsils. Cell clusters corresponding to ILC2, ILC3, and NK cells were used as controls. Data shown are from donor represented in (A). (E) Visualization of all different ILC subsets identified by standard bi-axial gating by t-SNE. Data shown are from donor represented in (A). Please also see Figures S1 and S2.
Figure 2
Figure 2. ieILC1-like Cells Are Present in Non-Mucosal Inflamed Tissues
(A) Visualized t-SNE map of cells from omentum adipose tissue (AT), lung tumor, and colorectal tumor. t-SNE was performed after depleting B and T cells and gating on live CD45+ Lin− (FcεR1α− CD14− CD19− CD123−). Cluster corresponding to NK cells is represented in orange. Data representative of one donor by tissue from 3 to 5 independent experiments. (B) Frequencies of cells positive for each marker molecule assessed. Based on the gates shown in (A), the frequencies of positive cells for each marker were calculated and represented as a heatmap. (C) Dot plots showing markers expressed by ieILC1-like cells. According to the clusters identified by t-SNE (A) ieILC1-like cells (red) were displayed on a biaxial dot plot. CD45+ Lin− (gray) cells were used as controls. Representative data from one donor (lung tumor) is shown from 3 to 5 independent experiments. (D) Top shows dot plots representing NKp44 expression by ieILC1 cells from three colorectal tumor samples (three donors). Data shown is gated on NK and ieILC1-like cells (see gating Figure S3B). Bottom shows expression of NKp44 by ieILC1 cells from tonsil, colon, omentum AT, lung, and colorectal tumor tissue (for gating see Figure S3B). Data shown are the mean values ± SD from at least 3 independent experiments. (E) Ex vivo expression of perforin and granzymeB by ieILC1 cells (red) and NK cells (orange) from omentum AT, lung, and colorectal tumor tissue. Helper type ILCs (gray) were used as controls (for gating see Figure S4A). Data shown are one representative from three different donors. (F) Dot plot representing expression of IL18Rα on ieILC1 (red) and CD103− NK cells (orange). Representative data from one individual from 3 independent experiments. (G) IL15RA mRNA expression of ieILC1 and CD103− NK cells (see sorting gating strategy Figure S3C), means ± SD, n = 4. (H and I) Frequencies of IFN-γ producing ieILC1-like or CD103– NK cells from PBMC, tonsil, colon, lung tumor, and colorectal tumor tissue following stimulation with IL-12 and IL-15 (H) or IL-12 and IL-18 (I). Data shown are the mean values ± SD from 3 independent experiments. n/a (data not available) (see Figure S3D for staining). Please also see Figure S3.
Figure 3
Figure 3. t-SNE Analysis Objectively Delineates Helper-Type ILC Populations
(A) Visualized t-SNE map of cells from tonsil tissue. t-SNE was performed after depleting B and T cells and gating on live CD45+ Lin− (FcεR1α− CD14− CD19− CD123−). Manual gating identified three clusters corresponding to ILC2 (green), NKp44− ILC3 (light blue), and NKp44+ ILC3 (dark blue) cells. Data shown is from three donors. (B) A second round of t-SNE analysis (t-SNE #2) was applied to zoom-in exclusively on ILC2 and ILC3 cells cluster (black circle, A). Normalized expression intensities of each marker were calculated and overlayed on the t-SNE plot (see Figure S4A for others markers). (C) Representation of marker expression by standard bi-axial gating according to the gates shown in (A). (D) Expression of T-bet, GATA3, and RORγt by each ILC population. HSC (CD34+) were used as negative control. Representative data from one donor (tonsil) is shown. (E) Normalized mean signal intensities (MSI) of T-bet, GATA3, or RORγt of each ILC population. Data from >5 independent experiments, n = 17 tonsil tissue, paired t test, ns, non significant, *p ≤ 0.05, **p ≤ 0.01, ****p ≤ 0.0001. (F) mRNA expression of TBX21, GATA3, and RORC of each ILC population. Data from one experiment, n = 3 tonsil tissue, unpaired t test, ns, non significant, *p ≤ 0.05, **p ≤ 0.01. (G) Flow cytometry based gating strategy for the identification of each helper-type ILC population from PBMCs and tonsil. Lineage markers: CD14, CD5, CD19, FcεR1α, CD123, CD11c.
Figure 4
Figure 4. Frequencies of ILC Populations in Human Tissues
(A) Pie charts displaying the frequencies of NK (orange), ieILC1-like (red), ILC2 (green), NKp44− ILC3 (light blue), and NKp44+ ILC3 (dark blue) cells in human tissues. Data shown are the mean values from at least 9 independent experiments, Non-pathological tissues included PBMC (n = 15), cord blood (n = 3), bone marrow (n = 4), spleen (n = 6), lung (n = 6), skin (n = 4), tonsil (n = 9), adenoid (n = 4), and colon (n = 9) tissue. Pathological tissues included omentum AT (n = 4), lung tumor (n = 6), and colorectal tumor (n = 7) (Table S1). (B) Heatmap displaying the frequencies of positive cells for markers expressed by ILC2 and NKp44− ILC3 cells. Data shown are PBMCs (n = 10) from 4 independent experiments. (C) Histograms displaying the percentages of ILC2 and NKp44− ILC3 cells expressing markers. Data shown are PBMCs from 3 different healthy donors from 4 independent experiments. Please also see Figure S4.
Figure 5
Figure 5. Heterogeneity of Helper-Type ILC between Tissues and Donors
Heatmap displaying the frequencies of ILC2 and ILC3 cells positive for 32 different marker molecules. Data shown are from at least 13 independent experiments, n/a (data not available).
Figure 6
Figure 6. Heterogeneity of Helper-Type ILCs
(A) Expression of CD69, ICOS, and HLA-DR by ILC populations in non-mucosal (blood), mucosal (tonsil), and pathological tissue (lung tumor). Data shown is one representative from 3 different donors. (B) Comparison of NKp30, ICOS, and CD103 expression by ILC2 cells derived from adult PBMCs and cord blood. Data shown are the mean values ± SD from at least 6 independent experiments (n = 14 for PBMCs, and n = 3 for cord blood). n/a (data not available). (C) Expression of IL-4, IL-5, IL-9, and IL-13 by sorted ILC2 cells from blood (white) or cord blood (gray) after culture with or without IL-33. Data shown are the mean values ± SD from 2 independent experiments. n = 4, Mann-Whitney test, ns: non-significant, *p ≤ 0.05, **p ≤ 0.01. (D) Expression of CD25 and CD122 by ILC population in non-pathological (PBMCs) and pathological tissue (lung tumor). Data shown is one representative from two different donors from at least 6 independent experiments. (E) Frequencies of proliferating ILCs (Ki67+) in all tissues analyzed. Data shown are the mean values ± SD from at least 9 independent experiments (see Figure S5A for staining). (F) Expression of CD49a and CD39 by ILC2 and ILC3 cell populations in tonsils. Data shown are the mean values ± SD from at least 6 independent experiments. (G) Expression of IL-18Rα by NK (orange), ILC2 (green), and ILC3 (blue) cells. Representative dot plot from one donor (PBMC) from at least 6 independent experiments. (H) Expression of GM-CSF, IL-8, IL-17A, TNFα, and IL-13 by sorted ILC3 cells from PBMCs after culture with or without IL-18 and IL-23. Data shown are the mean values ± SD from 2 independent experiments, n = 5, Mann-Whitney test, ns: non significant, *p ≤ 0.05, **p ≤ 0.01. (I) Expression of IL-4, IL-5, IL-9, IL-13, GM-CSF, IL-8, and IL-6 by sorted ILC2 cells from PBMCs after culture with or without IL-18 and IL-23. Data shown are the mean values ± SD from 2 independent experiments, n = 4, Mann-Whitney test, ns: non significant, *p ≤ 0.05, **p ≤ 0.01 (see Figure S5D for sorting strategy). Please also see Figure S5.
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