Thomas Graham D, Hamers Anouk A J, Nakao Catherine, Marcovecchio Paola, Taylor Angela M, McSkimming Chantel, Nguyen Anh Tram, McNamara Coleen A, Hedrick Catherine C
From the Division of Inflammation Biology, La Jolla Institute for Allergy and Immunology, CA (G.D.T., A.A.J.H., C.N., P.M., C.C.H.); and Division of Cardiology and Robert M. Berne Cardiovascular Center, University of Virginia, Charlottesville (A.M.T., C.M., A.T.N., C.A.M.).
Arterioscler Thromb Vasc Biol. 2017 Aug;37(8):1548-1558. doi: 10.1161/ATVBAHA.117.309145. Epub 2017 Jun 8.
Human monocyte subsets are defined as classical (CD14CD16), intermediate (CD14CD16), and nonclassical (CD14CD16). Alterations in monocyte subset frequencies are associated with clinical outcomes, including cardiovascular disease, in which circulating intermediate monocytes independently predict cardiovascular events. However, delineating mechanisms of monocyte function is hampered by inconsistent results among studies.
We use cytometry by time-of-flight mass cytometry to profile human monocytes using a panel of 36 cell surface markers. Using the dimensionality reduction approach visual interactive stochastic neighbor embedding (viSNE), we define monocytes by incorporating all cell surface markers simultaneously. Using viSNE, we find that although classical monocytes are defined with high purity using CD14 and CD16, intermediate and nonclassical monocytes defined using CD14 and CD16 alone are frequently contaminated, with average intermediate and nonclassical monocyte purity of ≈86.0% and 87.2%, respectively. To improve the monocyte purity, we devised a new gating scheme that takes advantage of the shared coexpression of cell surface markers on each subset. In addition to CD14 and CD16, CCR2, CD36, HLA-DR, and CD11c are the most informative markers that discriminate among the 3 monocyte populations. Using these additional markers as filters, our revised gating scheme increases the purity of both intermediate and nonclassical monocyte subsets to 98.8% and 99.1%, respectively. We demonstrate the use of this new gating scheme using conventional flow cytometry of peripheral blood mononuclear cells from subjects with cardiovascular disease.
Using cytometry by time-of-flight mass cytometry, we have identified a small panel of surface markers that can significantly improve monocyte subset identification and purity in flow cytometry. Such a revised gating scheme will be useful for clinical studies of monocyte function in human cardiovascular disease.
人类单核细胞亚群被定义为经典型(CD14⁺CD16⁻)、中间型(CD14⁺CD16⁺)和非经典型(CD14⁻CD16⁺)。单核细胞亚群频率的改变与包括心血管疾病在内的临床结局相关,在心血管疾病中,循环中的中间型单核细胞可独立预测心血管事件。然而,研究结果的不一致阻碍了对单核细胞功能机制的描述。
我们使用飞行时间质谱流式细胞术,通过一组36种细胞表面标志物对人类单核细胞进行分析。使用降维方法视觉交互式随机邻域嵌入(viSNE),我们通过同时纳入所有细胞表面标志物来定义单核细胞。使用viSNE,我们发现虽然使用CD14和CD16可以高纯度地定义经典单核细胞,但仅使用CD14和CD16定义的中间型和非经典型单核细胞经常受到污染,中间型和非经典型单核细胞的平均纯度分别约为86.0%和87.2%。为了提高单核细胞的纯度,我们设计了一种新的设门方案,该方案利用了每个亚群细胞表面标志物的共同共表达。除了CD14和CD16外,CCR2、CD36、HLA-DR和CD11c是区分这3种单核细胞群体最具信息性的标志物。使用这些额外的标志物作为筛选条件,我们修订后的设门方案将中间型和非经典型单核细胞亚群的纯度分别提高到了98.8%和99.1%。我们使用来自心血管疾病患者外周血单个核细胞的传统流式细胞术展示了这种新设门方案的应用。
通过飞行时间质谱流式细胞术,我们确定了一小组表面标志物,它们可以显著提高流式细胞术中单核细胞亚群的识别和纯度。这种修订后的设门方案将有助于人类心血管疾病中单核细胞功能的临床研究。