Convergence between Microglia and Peripheral Macrophages Phenotype during Development and Neuroinflammation

Abstract

Differently from other myeloid cells, microglia derive exclusively from precursors originating within the yolk sac and migrate to the CNS under development, without any contribution from fetal liver or postnatal hematopoiesis. Consistent with their unique ontology, microglia may express specific physiological markers, which have been partly described in recent years. Here we wondered whether profiles distinguishing microglia from peripheral macrophages vary with age and under pathology. To this goal, we profiled transcriptomes of microglia throughout the lifespan and included a parallel comparison with peripheral macrophages under physiological and neuroinflammatory settings using age- and sex-matched wild-type and bone marrow chimera mouse models. This comprehensive approach demonstrated that the phenotypic differentiation between microglia and peripheral macrophages is age-dependent and that peripheral macrophages do express some of the most commonly described microglia-specific markers early during development, such as Fcrls, P2ry12, Tmem119, and Trem2. Further, during chronic neuroinflammation CNS-infiltrating macrophages and not peripheral myeloid cells acquire microglial markers, indicating that the CNS niche may instruct peripheral myeloid cells to gain the phenotype and, presumably, the function of the microglia cell. In conclusion, our data provide further evidence about the plasticity of the myeloid cell and suggest caution in the strict definition and application of microglia-specific markers.SIGNIFICANCE STATEMENT Understanding the respective role of microglia and infiltrating monocytes in neuroinflammatory conditions has recently seemed possible by the identification of a specific microglia signature. Here instead we provide evidence that peripheral macrophages may express some of the most commonly described microglia markers at some developmental stages or pathological conditions, in particular during chronic neuroinflammation. Further, our data support the hypothesis about phenotypic plasticity and convergence among distinct myeloid cells so that they may act as a functional unit rather than as different entities, boosting their mutual functions in different phases of disease. This holds relevant implications in the view of the growing use of myeloid cell therapies to treat brain disease in humans.

Keywords: EAE; development; macrophages; microglia; plasticity; tissue-reprogramming.

Figure 1.

Transcriptional profiling of microglia and liver myeloid cells during development. Genome-wide expression analysis of microglia and liver macrophages sorted from naive C57BL6 E14 embryos and P1 pups. A, Raw data were subjected to background subtraction followed by cubic spline normalization. Filtering was performed for probes with detection p < 0.05 in at least three samples. The significance threshold was set to p < 0.05 for the intra-tissue comparison and p < 0.01 for inter-tissue comparison. Differentially expressed genes (DEGs) were defined by statistical significance and thresholds on fold-change (±1.7) and expression intensity (>100 in any 1 of the 2 compared groups). B, DEGs (4513 and 4060) were found comparing microglia and liver myeloid cells at E14 and P1, respectively, whereas only 387 and 894 DEGs were found between embryonic and postnatal microglia or liver myeloid cells, despite the less stringent statistical threshold (corrected p < 0.05). C, D, PCA plots of microglia versus liver macrophages at E14 (C) and P1 (D). E, Simultaneous expression of pan myeloid genes in microglia and liver myeloid cells at E14 and P1. F, Referred microglial-specific markers were expressed by both microglia and liver myeloid cells at E14 and P1. G, A well known microglia-specific marker (i.e., Slc2a5) was absent in liver myeloid cells at both time points but undetectable in microglia at E14 and barely expressed at P1. Each bar represents the average intensity signal ± SEM of three biological replicates per time point, resulting from a pool of 10 mice each.

Figure 2.

Identification of microglia-specific transcripts during development. A, Identification of tissue-specific transcripts [1321 E14 microglia (Figure 2-1); 1168 P1 microglia (Figure 2-2); 752 E14 liver myeloid cells (Figure 2-3); and 855 P1 liver myeloid cells (Figure 2-4)] expressed by microglia or liver myeloid cells at each time point with no expression in the other tissue and a fold-change ≥ 5. B, Top expressed transcripts in microglia-specific lists at E14 and P1. C, Well known microglia-specific markers were also detectable in liver myeloid cells and therefore eliminated from further analysis. Each bar represents the average intensity signal ± SEM of three biological replicates per time point, resulting from a pool of 10 mice each. D, Top significant biological processes enriched in each tissue-specific myeloid signature at E14 and P1. E, F, Identification of a core of 759 conserved transcripts, which are microglia-specific during development (Figure 2-5) and relative PCA plot (F). G, Top significant biological processes enriched in microglia-specific lists at E14 and P1.

Figure 3.

Identification of 65 homeostatic microglia-specific transcripts throughout life. A, B, Heatmap and hierarchical clustering of differentially expressed genes in microglia at E14, P1, and in adulthood. Each lane represents the average expression value of three biological replicates per time-point; relative PCA plot (B). C, Venn diagram displays unique and intersecting DEGs among microglia at E14, P1, and in adulthood. Ninety-four transcripts were shared at all time points (Figure 3-1). D, Venn diagram displaying homeostatic microglia-specific transcripts with no expression in adult peritoneal macrophages at steady state or after differentiation toward an M1 or M2 phenotype. Sixty-five transcripts were absent in all three macrophage populations (Figure 3-2). E, Heatmap and hierarchical clustering of the identified 65 microglia-specific transcripts in microglia at E14, P1, in adulthood, and in liver macrophages at E14 and P1, and peritoneal macrophages at steady state or after differentiation toward an M1 or M2 phenotype. Each lane represents the average expression value of three biological replicates per time point, in turn deriving from polls of 8–10 mice each. F, Average gene expression of the identified 65 microglia-specific transcripts at E14, P1, and adult phase.

Figure 4.

MoDMs express microglia-specific markers during EAE. A, EAE induction and expression. Red arrows indicate time points used for isolation of CNS myeloid cells (pre-onset, peak, and chronic phase). B, Exemplificative plots of the sorted populations at each time point: R1 (microglia), R2 (MoDMs). C, D, Heatmap reporting mRNA levels of 14 selected microglia-specific genes in sorted microglia and MoDMs during EAE in wild-type mice (C) and chimeric mice (D). Data represent two independent experiments and each sample results from a pool of 10 mice.

Figure 5.

Microglia-specific markers are acquired specifically by peripheral myeloid cells entering the CNS. A, Flow cytometry of CNS leukocytes from EAE mice, assessed at the chronic phase (38–40 dpi). Frequencies of microglia (CD11b+ CD45^low F4/80+ Ly6C^low cells) and MoDMs (CD11b+ CD45high F4/80+ Ly6C^high cells) are shown in the plots. B–D, Graphs show the frequency of Lag3+, Tnfrsf17+, and Siglech+ on microglia at E14, P1, P60, liver macrophages at E14 and P1, adult splenic macrophages in physiological conditions as well as on microglia, MoDMs, spleen macrophages, and blood monocytes in the acute phase and chronic phases of EAE (n = 5 mice per group). Data represent the mean ± SEM and are representative of two independent experiments. ***p ≤ 0.001, **p ≤ 0.01, unpaired t test. E, F, FACS analysis of Lag3+, Tnfrsf17+, and Siglech+ microglia (E) and MoDMs (F) at the chronic phase of EAE. Black lines represent isotype controls. Data are representative of three or more replicates.