Design of a Robust Flow Cytometric Approach for Phenotypical and Functional Analysis of Human Monocyte Subsets in Health and Disease

Abstract

Human monocytes can be subdivided into phenotypically and functionally different classical, intermediate and non-classical monocytes according to the cell surface expression of CD14 and CD16. A precise identification and characterisation of monocyte subsets is necessary to unravel their role in inflammatory diseases. Here, we compared three different flow cytometric strategies (A-C) and found that strategy C, which included staining against CD11b, HLA-DR, CD14 and CD16, followed by several gating steps, most reliably identified monocyte subtypes in blood samples from healthy volunteers and from patients with stable coronary heart disease (CHD) or ST-elevation myocardial infarction (STEMI). Additionally, we established a fixation and permeabilisation protocol to enable the analysis of intracellular markers. We investigated the phagocytosis of lipid nanoparticles, the uptake of 2-NBD-glucose and the intracellular levels of CD74 and HLA-DM. This revealed that classical and intermediate monocytes from patients with STEMI showed the highest uptake of 2-NBD-glucose, whereas classical and intermediate monocytes from patients with CHD took up the largest amounts of lipid nanoparticles. Interestingly, intermediate monocytes had the highest expression level of HLA-DM. Taken together, we present a robust flow cytometric approach for the identification and functional characterisation of monocyte subtypes in healthy humans and patients with diseases.

Keywords: MHC class II pathway; coronary heart disease; flow cytometry; gating; glucose uptake; monocyte subsets; myocardial infarction; phagocytosis.

Figure 1

Antibody staining and gating strategies for identification of monocyte subsets. Human whole blood was obtained from healthy volunteers, erythrocytes were lysed and cells were stained with (A) CD11b-APC, CD14-PE.Cy7, CD16-APC.Cy7 (strategy A; ST-A); (B) CD11b-APC, CD14-PE.Cy7, CD16-APC.Cy7 and CD3-FITC, CD19-FITC, CD209-FITC (strategy B; ST-B); (C) CD11b-APC, CD14-PE.Cy7, CD16-APC.Cy7, HLA-DR-PerCP.Cy5.5 (strategy C; ST-C). Blood cells were additionally stained with DAPI (4′,6-Diamidin-2-phenylindol) to exclude dead cells (DAPI⁺) from the analysis (Figure S2). Displayed are pseudo-colour plots that indicate the gating strategy for the identification of monocyte subtypes based on the expression levels of CD14 and CD16. CM—classical monocytes, IM—intermediate monocytes, NC—non-classical monocytes. (D) Quantitative analysis of monocyte subset (% of monocytes for each subset and the CD16⁺/CD14⁻ contamination of the monocyte population; marked by red arrows). Mean ± SD are shown; n = 9–10. Normality was tested using the Shapiro–Wilk test and variability with Levene’s test. Differences between the groups were analysed by a one-way ANOVA followed by Tukey’s multiple comparisons test. Statistical significance: ns— not significant, * p < 0.05, **** p < 0.0001. There were 12 healthy volunteers (2 × male, 10 × female; 22–28 years, median: 23 years). The complete gating for identification of monocyte subsets by strategies A–C is shown in Supplementary Figure S2.

Figure 2

Analysis of monocyte subsets in CHD and STEMI patients. Blood samples derived from healthy volunteers (A, blue), patients with stable coronary heart disease (CHD, red) (B) and patients with ST-elevation myocardial infarction (STEMI, green) (C) were stained for CD11b, CD14, CD16 and HLA-DR to identify monocyte subsets. Displayed are pseudo-colour plots that show the gating strategy (strategy C) and the identification of the monocyte subtypes based on the expression of CD14 and CD16. (D) Quantitative analysis of the relative amount of monocyte subsets (CM—classical, IM—intermediate, NC—non-classical) in varying conditions. Data are mean values ± SD of n = 10–15. Normality was tested using the Shapiro–Wilk Test and variability with Levene’s test. Differences between the groups were analysed by a one-way ANOVA followed by Tukey’s multiple comparisons test. Statistical significance: ns—not significant, * p < 0.05, ** p < 0.01. There were 15 healthy controls (3 × male, 12 × female; 22–33 years, median: 24 years), 10 patients with CHD (5 × female, 5 × male; 52–86 years, median: 64 years) and 12 patients with STEMI (1 × female, 11 × male; 40–78 years, median: 60.5 years). (The complete gating strategy for the identification of monocyte subsets is shown in Supplementary Figure S6).

Figure 3

Cell surface expression of CCR2 and CX3CR1 in monocyte subsets. Blood samples were derived from healthy volunteers and from patients one day after ST-elevation myocardial infarction (STEMI). Cells were stained with antibodies against CD11b, CD14, CD16 and HLA-DR (strategy C) to identify monocyte subsets. Cells were then additionally incubated with either anti-CCR2 or anti-CX3CR1 antibodies. Quantitative analysis of CCR2 (A) or CX3CR1 (B) expression in monocyte subsets of healthy donors (blue) and patients with STEMI (green). Data are mean values ± SD of n = 5 individual experiments. Normality was tested using the Shapiro–Wilk test. Differences between the groups were analysed by an unpaired two-tailed t-test with or without Welch correction or a Mann–Whitney test. Statistical significance: ns— not significant, ** p < 0.01. There were 5 healthy controls (4 × female, 1 × male; 22–27 years, median: 24 years) and 5 patients with STEMI (5 × male; 59–68 years, median: 63 years).

Figure 4

Identification of monocyte subsets after fixation and permeabilisation. Blood was derived from healthy volunteers and cells were stained with antibodies against CD11b, CD14, CD16 and HLA-DR for monocyte identification. Afterwards, cells were left untreated ((A), upper panel), fixed at room temperature for 25 min ((B), middle panel) or fixed and permeabilised (20 min at room temperature) ((C), lower panel). (D) Quantitative analysis of the relative amount of monocyte subsets (CM—classical, IM—intermediate, NC—non-classical) after fixation (Fix) and permeabilisation (Perm) of untreated control cells (Con). Normality was tested using a Shapiro–Wilk test and variability with Levene’s test. Differences between the groups were analysed by a one-way ANOVA followed by Tukey’s multiple comparisons test. Data are mean values ± SD of n = 9–11 (9 × female, 2 × male; 22–27 years, median: 24 years). Statistical significance: ns—not significant, * p < 0.05.

Figure 5

Assessment of phagocytosis and glucose uptake in monocyte subsets. Blood samples were derived from healthy volunteers (blue), patients with stable coronary heart disease (CHD, red) and patients with ST- elevation myocardial infarction (STEMI, green). After lysis of erythrocytes, cells were either incubated with fluorescently labelled perfluorocarbon nanoemulsions (^A488PFCs) (A), or the glucose analogue 2-NBDG [2-(7-Nitro-2,1,3-benzoxadiazol-4-yl)-D-glucosamine] (B). Cells were then stained for CD11b, HLA-DR, CD14 and CD16 to determine the uptake of ^A488PFCs or 2-NBDG in classical (CM), intermediate (IM) and non-classical monocytes (NC) by flow cytometry. Displayed is the quantification of the mean fluorescence intensity of the ^A488PFCs (A) or the 2-NBDG (B) signals in CM, IM and NC of healthy volunteers and patients with CHD and STEMI. Data are mean values ± SD of n = 9–12. Normality was tested using the Shapiro–Wilk test and variability with Levene’s test. Differences between the groups were analysed by a one-way ANOVA followed by Tukey’s multiple comparisons test. Statistical significance: ns—not significant, * p < 0.05, ** p < 0.01, **** p < 0.0001. (A) There were 10 healthy controls (5 × male, 5 × female; 22–45 years, median: 23 years), 10 patients with CHD (5 × male, 5 × female; 52–86 years, median: 64 years) and 10 patients with STEMI (2 × female, 8 × male; 41–80 years, median: 59.5 years). (B) There were 12 healthy controls (10 × female, 2 × male; 22–33 years, median: 25 years), 10 patients with CHD (5 × female, 5 × male; 52–86 years, median: 64 years) and 9 patients with STEMI (1 × female, 8 × male; 40–78 years, median: 57 years).

Figure 6

Intracellular staining of HLA-DM and CD74 in monocyte subsets. Blood samples were derived from young healthy volunteers. Cells were first stained with antibodies against CD11b, CD14, CD16 and HLA-DR to identify classical (CM, blue), intermediate (IM, red) and non-classical monocytes (NC, green). Subsequently, the samples were additionally stained for CD74 (A) or HLA-DM (B) to determine the surface expression (CS). Alternatively, immune cells were fixed and permeabilised and treated with anti-CD74 and HLA-DM antibodies to detect intracellular (IC) expression levels. Light colours represent the expression of CD74 and HLA-DM on the cell surface, darker colours depict intracellular expression. (C) Quantitative analysis of the mean fluorescence intensities (MFI) of intracellular CD74 (left) and HLA-DM (right). Data are mean values ± SD, n = 5–6 (4 × female, 2 × male; 22–33 years, median: 25 years). Normality was tested using a Shapiro–Wilk test and variability with Levene’s test. Differences between the groups were analysed by a one-way ANOVA followed by Tukey’s multiple comparisons test. Statistical significance: ns—not significant, *** p < 0.0001, **** p < 0.0001.