Single-cell transcriptome analyses reveal microglia types associated with proliferative retinopathy
Zhiping Liu, Huidong Shi, Jiean Xu, Qiuhua Yang, Qian Ma, Xiaoxiao Mao, Zhimin Xu, Yaqi Zhou, Qingen Da, Yongfeng Cai, David J.R. Fulton, Zheng Dong, Akrit Sodhi, Ruth B. Caldwell, Yuqing Huo
Zhiping Liu, Huidong Shi, Jiean Xu, Qiuhua Yang, Qian Ma, Xiaoxiao Mao, Zhimin Xu, Yaqi Zhou, Qingen Da, Yongfeng Cai, David J.R. Fulton, Zheng Dong, Akrit Sodhi, Ruth B. Caldwell, Yuqing Huo
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Research Article Angiogenesis Ophthalmology

Single-cell transcriptome analyses reveal microglia types associated with proliferative retinopathy

Abstract

Pathological angiogenesis is a major cause of irreversible blindness in individuals of all age groups with proliferative retinopathy (PR). Mononuclear phagocytes (MPs) within neovascular areas contribute to aberrant retinal angiogenesis. Due to their cellular heterogeneity, defining the roles of MP subsets in PR onset and progression has been challenging. Here, we aimed to investigate the heterogeneity of microglia associated with neovascularization and to characterize the transcriptional profiles and metabolic pathways of proangiogenic microglia in a mouse model of oxygen-induced PR (OIR). Using transcriptional single-cell sorting, we comprehensively mapped all microglia populations in retinas of room air (RA) and OIR mice. We have unveiled several unique types of PR-associated microglia (PRAM) and identified markers, signaling pathways, and regulons associated with these cells. Among these microglia subpopulations, we found a highly proliferative microglia subset with high self-renewal capacity and a hypermetabolic microglia subset that expresses high levels of activating microglia markers, glycolytic enzymes, and proangiogenic Igf1. IHC staining shows that these PRAM were spatially located within or around neovascular tufts. These unique types of microglia have the potential to promote retinal angiogenesis, which may have important implications for future treatment of PR and other pathological ocular angiogenesis–related diseases.

Authors

Zhiping Liu, Huidong Shi, Jiean Xu, Qiuhua Yang, Qian Ma, Xiaoxiao Mao, Zhimin Xu, Yaqi Zhou, Qingen Da, Yongfeng Cai, David J.R. Fulton, Zheng Dong, Akrit Sodhi, Ruth B. Caldwell, Yuqing Huo

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Figure 5

scRNA-Seq revealed heterogeneity of inflammatory gene expression in resting and activated microglia.

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scRNA-Seq revealed heterogeneity of inflammatory gene expression in rest...
(A) tSNE plots colored for 4 inflammatory genes. (B) Violin plots of 4 inflammatory genes. P values were determined by the Wilcoxon rank-sum test in R. **P < 0. 01, ***P < 0. 001, ****P < 0.0001. Light blue dots indicate the mean. (C) tSNE plots showing cytokine and inflammatory pathway activity scores calculated using the AUCell package. (D) Violin plots showing cytokine and inflammatory pathway activity scores. P values were determined by the Wilcoxon rank-sum test in R. ****P < 0.0001. Light-blue dots indicate the mean. (E) Dot plot showing pathway enrichment results from 3 independent pathway databases. The lists of upregulated and downregulated genes in OIR versus RA resting microglia (clusters 0, 1, 2) and OIR versus RA-activated microglia (clusters 5, 9, and 10) are used as inputs for the analysis. The cutoff thresholds for gene inclusion are: absolute average log2 fold change > 0.585, adjusted P < 0.05, and expression in at least 15% of OIR or RA microglia. (F) qPCR analysis of inflammatory cytokine genes in negative control siRNA and Myc siRNA–transfected N9 microglial cells after LPS stimulation (10 ng/mL) for 6 hours (n = 4). Data are mean ± SEM. *P < 0.05 by 1-way ANOVA followed by Bonferroni test.