Defining newly formed and tissue-resident bone marrow-derived macrophages in adult mice based on lysozyme expression

Tong Lei; Jiayu Zhang; Qian Zhang; Xinran Ma; Yanan Xu; Yang Zhao; Lianfeng Zhang; Zhongbing Lu; Yong Zhao

doi:10.1038/s41423-022-00936-4

. 2022 Nov 8;19(12):1333–1346. doi: 10.1038/s41423-022-00936-4

Defining newly formed and tissue-resident bone marrow-derived macrophages in adult mice based on lysozyme expression

Tong Lei ^1,^2,^#, Jiayu Zhang ^1,^3,^#, Qian Zhang ^1,^3,^#, Xinran Ma ^1,², Yanan Xu ¹, Yang Zhao ¹, Lianfeng Zhang ^4,^✉, Zhongbing Lu ^2,^✉, Yong Zhao ^1,^3,^5,^✉

PMCID: PMC9708686 PMID: 36348079

Abstract

Tissue-resident macrophages are derived from different precursor cells and display different phenotypes. Reconstitution of the tissue-resident macrophages of inflamed or damaged tissues in adults can be achieved by bone marrow-derived monocytes/macrophages. Using lysozyme (Lysm)-GFP-reporter mice, we found that alveolar macrophages (AMs), Kupffer cells, red pulp macrophages (RpMacs), and kidney-resident macrophages were Lysm-GFP⁻, whereas all monocytes in the fetal liver, adult bone marrow, and blood were Lysm-GFP⁺. Donor-derived Lysm-GFP⁺ resident macrophages gradually became Lysm-GFP⁻ in recipients and developed gene expression profiles characteristic of tissue-resident macrophages. Thus, Lysm may be used to distinguish newly formed and long-term surviving tissue-resident macrophages that were derived from bone marrow precursor cells in adult mice under pathological conditions. Furthermore, we found that Irf4 might be essential for resident macrophage differentiation in all tissues, while cytokine and receptor pathways, mTOR signaling pathways, and fatty acid metabolic processes predominantly regulated the differentiation of RpMacs, Kupffer cells, and kidney macrophages, respectively. Deficiencies in ST2, mechanistic target of rapamycin (mTOR) and fatty acid-binding protein 5 (FABP5) differentially impaired the differentiation of tissue-resident macrophages from bone marrow-derived monocytes/macrophages in the lungs, liver, and kidneys. These results indicate that a combination of shared and unique signaling pathways coordinately shape tissue-resident macrophage differentiation in various tissues.

Keywords: Tissue-resident macrophages, Kupffer cells, Lysozyme, Inflammation, Metabolism, Cytokine

Subject terms: Kupffer cells, Interleukins, Bone marrow transplantation, Imaging the immune system

Introduction

Tissue-resident macrophage heterogeneity underlies different macrophage functions across various tissues and organs under steady-state and disease conditions [1, 2]. Three major tissue-resident macrophage origins have been recognized; these include the yolk sac, fetal liver, and bone marrow [3–5]. Adult bone marrow-derived monocytes replace and maintain tissue-resident macrophage pools in various tissues and organs to different degrees and with different kinetics depending on age and physiological or pathological status [6, 7]. Therefore, tissue-resident macrophages in all organs (likely except the brain) consist of macrophages derived from various sources in adults [5, 8]. The phenotypes and functions of macrophages in different tissues are believed to be mainly shaped and regulated by local tissue microenvironments and niches [6, 8–10]. Granulocyte macrophage colony-stimulating factor (GM-CSF) and macrophage colony-stimulating factor (M-CSF) are important growth factors that induce macrophage maturation. For example, GM-CSF plays an important role in pulmonary alveolar macrophage (AM) development [11, 12], and TGF-β combined with GM-CSF induces an alveolar macrophage phenotype [13, 14]. Tissue-resident macrophages developed from the three distinct precursor cell types have distinctive gene expression profiles but eventually share similar gene profiles and functional phenotypes when residing in the same tissue [6, 8]. However, recruited bone marrow monocytes can develop into different monocyte-derived macrophage subsets in tissues under different stimulation conditions. For example, after lysolecithin injection, there are two major populations of injury-responsive microglial cells in the brain [15]. Additionally, two monocyte-derived Kupffer cell subtypes can be identified by differential Clec4f expression in the liver [6], and a single-cell sequencing analysis showed that multiple macrophage subsets developed from bone marrow monocytes in human and mouse lung cancers [16]. Unfortunately, there are limited biomarkers and mapping systems to define different tissue-resident macrophages derived from different sites, and determining transcriptional profile changes during adult bone marrow-derived monocyte differentiation into tissue-resident macrophages has been challenging. In the present study, we found that all fetal and adult bone marrow-derived monocytes highly expressed lysozyme (Lysm) but that tissue-resident macrophages did not express detectable Lysm in Lysm-GFP-reporter mice. Using RNA sequencing (RNA-seq) and adoptive transfer of adult mouse bone marrow-derived monocytes to reconstruct macrophage pools in various tissues in adult mice, we found that tissue-resident macrophages differentiated from Lysm-GFP⁺ bone marrow-derived monocytes were Lysm-GFP⁺ in the early transfer stage but became Lysm-GFP⁻ in the later stage. Therefore, we could use Lysm-GFP expression as a marker to distinguish newly immigrant or formed bone marrow-derived tissue-resident macrophages from long-term surviving tissue-resident macrophages in mice. This provides a useful research tool to study the differentiation kinetics and gene expression profiles of bone marrow-derived monocytes in tissues and organs.

Results

Tissue-resident macrophages did not express Lysm

To verify previously reported mouse tissue-resident macrophage fate mapping results, we used the following surface markers to define macrophage subpopulations in different tissues in the present study (Extended Data Fig. 1): lung macrophages were gated as CD45⁺CD64⁺Mertk⁺ cells, lung-resident AMs were CD11c⁺CD11b⁻, lung interstitial macrophages (IMs) were CD11c⁺CD11b⁺ [17], Kupffer cells from the liver were CD45⁺Gr-1⁻CD11b^lowF4/80^hi Tim4⁺ [18, 19], red pulp macrophages (RpMacs) from the spleen were CD45⁺Gr-1⁻CD11c⁻CD11b^lowF4/80^hi [20], macrophages from the kidneys were CD45⁺Gr-1⁻CD11b^lowF4/80^hi [21], and monocyte-derived macrophages (MDMacs) from the liver and kidneys and pre-red pulp macrophages (Pre-RpMacs) from the spleen were CD45⁺Gr-1⁻CD11b^hiF4/80^low [20, 21].

As expected, 100% of monocytes in the fetal liver (CD11b⁺Ly6C^hiF4/80^low), adult bone marrow (CD11b⁺Ly6C^hi and CD11b⁺Ly6C^low), and peripheral blood (CD11b⁺Ly6C^hi and CD11b⁺Ly6C^low) in Lysm-GFP-reporter mice were Lysm-GFP⁺, as detected by flow cytometry (Fig. 1a–c). These results suggest that all monocytes in fetal and adult mice express Lysm. We found that approximately 80% of lung CD64⁺Mertk⁺CD11b^lowCD11c^hi IMs were Lysm-GFP⁺; however, almost all CD64⁺Mertk⁺CD11b^hiCD11c^low AMs were Lysm-GFP⁻ (Fig. 1d). All CD11b^hiF4/80⁻ MDMacs in the liver were Lysm-GFP⁺, but in contrast, Lysm-GFP was undetectable in CD11b^lowF4/80^hi Kupffer cells (Fig. 1e). In the kidneys, 100% of CD11b^hiF4/80^low MDMacs expressed Lysm-GFP, and 40% of CD11b^lowF4/80^hi Macs expressed Lysm-GFP (Fig. 1f). In the spleen, 60% of CD11b^lowF4/80^hi Pre-RpMacs expressed Lysm, but almost no CD11b^hiF4/80^low RpMacs, which are derived from Pre-RpMacs [20], expressed Lysm-GFP (Fig. 1g). Consistent with our flow cytometry results, RNA-seq analysis showed that monocytes exhibited the highest expression of Lysm, while tissue-resident macrophages, especially macroglia, had notably lower Lysm expression levels (Fig. 1h). Furthermore, RpMacs and Kupffer cells expressed markedly less Lysm. These results indicated that all fetal liver and adult bone marrow-derived monocytes had high Lysm expression levels, but some tissue-resident macrophage subsets, including AMs in the lungs, Kupffer cells in the liver, and RpMacs in the spleen, did not exhibit detectable Lysm expression. However, the majority of IMs in the lungs, MDMacs in the liver and kidneys, and Pre-RpMacs in the spleen highly expressed Lysm.

Tissue-resident macrophages in the liver, lungs, kidneys, and spleen were *Lysm*-GFP⁻. *Lysm*-GFP expression in macrophage subsets from different tissues was gated as shown in Extended Data Fig. 1. a *Lysm*-GFP expression in fetal liver CD11b^hiF4/80^lowLy6C^hi monocytes from E14.5d embryonic mice. b *Lysm*-GFP expression in CD11b⁺Ly6C^hi and CD11b⁺Ly6C^low adult bone marrow monocytes from 6–8-week-old mice. c *Lysm*-GFP expression in CD11b⁺ Ly6C^hi and CD11b⁺Ly6C^low adult blood monocytes from 6–8-week-old mice. d *Lysm*-GFP expression in CD45⁺CD64⁺Mertk⁺CD11c⁺CD11b⁻ AMs and CD45⁺CD64⁺Mertk⁺CD11b⁺ IMs from the lungs and the percentage of GFP⁺ lung macrophages. e *Lysm*-GFP expression in CD45⁺Gr-1⁻CD11b^hiF4/80⁻ MDMacs and CD45⁺Gr-1⁻CD11b^lowF4/80^hi Tim4⁺ Kupffer cells from the liver and the percentage of GFP⁺ liver macrophages. f *Lysm*-GFP expression in CD45⁺Gr-1^-CD11b^hiF4/80⁻ MDMacs and CD45⁺Gr-1⁻CD11b^lowF4/80^hi macrophages from the kidneys and the percentage of GFP⁺ kidney macrophages. g *Lysm*-GFP expression in CD11c⁻Gr-1⁻CD11b⁺F4/80⁺ Pre-RpMacs and CD11c⁻Gr-1⁻CD11b⁻F4/80^hi RpMacs from the spleen and the percentage of GFP⁺ spleen macrophages. The flow cytometry data are presented as the means, and each scatterplot point represents one mouse (n = 5). h *Lysm* mRNA expression levels in monocytes, lung macrophages, liver Kupffer cells, spleen macrophages, and microglia, as detected by RNA-seq

Considering that yolk sac-, fetal liver-, and adult hematopoietic precursor-derived monocytes/macrophages contribute differently to tissue-resident macrophages in various organs [21] and that tissue-resident macrophages are gradually supplemented by adult hematopoietic monocytes in adult mice [17], we compared Lysm expression in tissue-resident macrophages from E8.5 until adult age in mice. The results showed that Lysm-GFP expression in primary erythromyeloid precursors (EMPs) of the E8.5 yolk sac was negative, but secondary EMPs and fetal liver monocytes were positive in the E8.5 yolk sac and E14.5 fetal liver, respectively (Extended Data Fig. 2a). Meanwhile, Lysm-GFP expression in tissue-resident macrophages from the lungs, liver, kidneys, and spleen was similar among embryonic, neonatal and adult mice (Extended Data Fig. 2b, c), supporting the finding that both fetal precursor- and adult monocyte-derived tissue-resident macrophages did not express Lysm, although both fetal liver- and bone marrow-derived monocytes were Lysm-GFP⁺ (Fig. 1a–c).

Lysm expression was downregulated during Lysm-GFP⁺ monocyte differentiation into tissue-resident macrophages

Because monocytes and Pre-RpMacs expressed high levels of Lysm-GFP, but the majority of tissue-resident macrophages in the lungs, spleen, and kidneys did not express Lysm-GFP, as detected by flow cytometry, we hypothesized that Lysm expression may be downregulated during monocyte differentiation into tissue-resident macrophages. To test this hypothesis, we constructed a bone marrow chimeric mouse model. We transplanted bone marrow cells from CD45.2⁺ Lysm-GFP transgenic mice into 6 Gy-irradiated CD45.1⁺ recipient mice (Fig. 2a). Four weeks after bone marrow transplantation, all donor-derived CD45.2⁺CD11b⁺Ly6C^hi bone marrow monocytes were Lysm-GFP⁺, and all host-derived CD45.1⁺ bone marrow monocytes were Lysm-GFP⁻ (Fig. 2b). Furthermore, the majority of donor-derived CD45.2⁺ AMs in the lungs, Kupffer cells in the liver, F4/80^hi macrophages in the kidneys, and RpMacs in the spleen were negative for Lysm-GFP expression, as detected by flow cytometry (Fig. 2c–f). However, the majority of donor-original IMs in the lungs, MDMac cells in the liver, CD11b⁺ macrophages in the kidneys, and Pre-RpMacs in the spleen still expressed Lysm-GFP (Fig. 2c–f). Thus, the majority of the bone marrow-derived tissue-resident macrophages in the lungs, liver, kidneys, and spleen displayed a Lysm-GFP⁻ phenotype.

Fig. 2 — *Lysm* expression was lost in BM-derived tissue-resident macrophages. CD45.2⁺ bone marrow cells from *Lysm*-GFP transgenic mice were transferred into CD45.1⁺ recipient mice via tail vein injection. CD45.2⁺ donor-derived cells and CD45.1⁺ host-derived cells were analyzed 4 weeks after transfer. a Schematic overview of the experiment. b Chimeric efficiency of bone marrow transplantation in CD45.1⁺ recipient mouse bone marrow. c–f Chimeric efficiency of tissue-resident macrophages in the lungs (c), liver (d), kidneys (e), and spleen (f). The flow cytometry data are presented as the means, and each scatterplot point represents one mouse (n = 6)

To determine the kinetics of Lysm downregulation during bone marrow monocyte differentiation into tissue-resident macrophages in mice, we analyzed donor-original macrophage Lysm-GFP expression in tissues at 2, 4, and 10 weeks after adoptive transplantation of sorted CD45.2⁺CD11b⁺Ly6C^hiLysm-GFP⁺ monocytes into syngeneic CD45.1⁺ recipients (Fig. 3a). We observed that approximately 85% of the donor-original CD45.2⁺ IMs were Lysm-GFP⁺ (Fig. 3b). Almost all of the donor-original CD45.2⁺ MDMacs in the liver and CD11b^hi macrophages in the kidneys were Lysm-GFP⁺ by 10 weeks after transplantation (Fig. 3b). The donor-original CD45.2⁺ Pre-RpMacs in the spleen continually lost Lysm expression, and only approximately 40% expressed Lysm-GFP (Fig. 3b), which is similar to the corresponding cells in Lysm-GFP-reporter mice. However, the percentages of donor-original Lysm-GFP⁻ CD45.2⁺ AMs in the lungs, CD45.2⁺ Kupffer cells in the liver, CD45.2⁺F4/80^hi macrophages in the kidneys, and CD45.2⁺ RpMacs in the spleen gradually increased and reached a plateau 4 weeks after transplantation (Fig. 3b, c). Lysm-GFP⁻ donor-original resident macrophage numbers gradually increased in the lungs, liver, kidneys, and spleen (Fig. 3d). Conversely, Lysm-GFP⁺ donor-original resident macrophage numbers decreased in the liver, kidneys, and spleen by 10 weeks after transplantation, while a fraction of Lysm-GFP⁺ donor-original alveolar macrophages consistently remained in the lungs (Fig. 3d). In addition, the ratios of Lysm-GFP⁻ donor-original resident macrophages to host-derived tissue-resident macrophages gradually increased (Extended Data Fig. 3a), while the ratios of Lysm-GFP⁺ donor-original resident macrophages to host-derived tissue-resident macrophages significantly decreased in the lungs, liver, kidneys, and spleen by 4 weeks after transplantation (Extended Data Fig. 3b). Importantly, we observed similar results when we adoptively transferred in vitro GM-CSF-induced CD45.2⁺ Lysm-GFP⁺ macrophages into syngeneic CD45.1⁺ recipient mice, demonstrating that the majority of donor-derived CD45.2⁺ AMs in the lungs, Kupffer cells in the liver, CD45.2⁺F4/80^hi macrophages in the kidneys, and RpMacs in the spleen displayed a level of Lysm expression similar to that of tissue-resident macrophages under steady-state conditions (Extended Data Fig. 4). On the other hand, we found that all macrophages derived from Lysm-GFP⁺ bone marrow cells in the in vitro M-CSF- or in vitro GM-CSF-induced macrophage differentiation system were Lysm-GFP⁺ (Extended Data Fig. 5). Thus, these data collectively indicated that newly formed bone marrow-derived macrophages expressed Lysm and likely developed a Lysm-GFP⁻ phenotype during their differentiation into lung AMs, liver Kupffer cells, kidney F4/80^hi macrophages, and spleen RpMacs in mice, although we could not fully exclude the possibility of direct Lysm-GFP⁺ monocyte development into Lysm-GFP⁻ macrophages in tissues after adoptive transfer of bone marrow-derived Lysm-GFP⁺ monocytes.

Fig. 3 — *Lysm*-GFP⁺ macrophages gradually transformed into *Lysm*-GFP⁻ macrophages in tissues. a CD45.2⁺CD11b⁺Ly6C^hiLysm⁺ bone marrow monocytes were transferred into CD45.1⁺ recipient mice. Mice were sacrificed 2, 4, or 10 weeks after transfer, and CD45.1⁺ host-derived cells were used as a control. We then analyzed *Lysm*-GFP expression in CD45.2⁺ donor-derived tissue-resident macrophages. b Flow cytometric analysis of donor-derived macrophage subsets, including IMs and AMs in the lungs, MDMacs and Kupffer cells in the liver, MDMacs and renal F4/80^high macrophages in the kidneys, and red pulp precursor macrophages and red pulp macrophages in the spleen, at 2, 4, and 10 weeks after transfer. c Percentages of *Lysm*-GFP⁻ and *Lysm*-GFP⁺ donor-derived macrophages in tissues at different time points. d Donor-derived tissue-resident macrophage cell numbers in tissues at different time points. e The autologous erythrocyte clearance experimental procedure. Autologous erythrocytes were stained with CellTracker red CMTPX (RBCs-Red-CF594) and transferred via tail vein injection into CD45.1⁺ recipient mice 4 weeks after CD45.2 *Lysm*-GFP⁺ monocytes were transferred. f, g Flow cytometric analysis of tissue-resident macrophage erythrocyte clearance in the liver and kidneys. Percentages of RBCs-Red-CF594⁺ Kupffer cells and renal tissue-resident macrophages. The flow cytometry data are presented as the means, and the histogram data are presented as the means ± SEMs (n = 3)

Furthermore, to evaluate whether the bone marrow-derived Lysm-GFP⁻ macrophages could act as tissue-resident macrophages in the liver and spleen, we examined the bone marrow-derived Lysm-GFP⁻ tissue-resident macrophage erythrocyte clearance capacity in a Lysm-GFP⁺ monocyte adoptive transfer mouse model (Fig. 3e). Host-original Kupffer cells and host-original RpMacs were 84.7% and 85% Red-CF594 positive, respectively, indicating that the host-original tissue-resident macrophages in the liver and spleen had an obvious erythrocyte clearance capacity (Fig. 3f, g). While only 1.2% of Lysm-GFP⁺ donor-original Kupffer cells and 0.2% of Lysm-GFP⁺ donor-original RpMacs individually were positive for Red-CF594, 68.9% of Lysm-GFP⁻ donor-original Kupffer cells and 53% of Lysm-GFP⁻ donor-original RpMacs were positive for Red-CF594 (Fig. 3f, g). Although the proportion of Red-CF594-positive donor-original macrophages was much lower than that of host-original tissue-resident macrophages, Lysm-GFP⁻ donor-original Kupffer cells and Lysm-GFP⁻ donor-original RpMacs contained Red-CF594-positive RBC levels similar to those of host-original RTMs, while Lysm-GFP⁺ donor-original macrophages contained few Red-CF594-positive RBCs. These data indicate that bone marrow-derived Lysm-GFP⁻ donor-original resident macrophages function similarly to host-original resident macrophages.

Monocyte-derived Lysm-GFP⁻ macrophages displayed phenotypes similar to embryo-derived resident macrophages

The kinetics of bone marrow monocyte-derived tissue-resident macrophage changes suggested that Lysm-GFP⁺ macrophages were differentiating into Lysm-GFP⁻ macrophages in adult mice. To determine whether the gene expression profiles of Lysm-GFP⁺ monocyte/macrophage-derived Lysm-GFP⁻ tissue-resident macrophages were similar to those of tissue-resident macrophages, which are mainly derived from embryonic precursor cells, we performed an RNA-seq analysis of sorted donor Lysm-GFP⁺ macrophages, donor Lysm-GFP⁻ macrophages, and host tissue-resident macrophages from the liver, kidneys, and spleen of host mice that had received an adoptive transfer of syngeneic Lysm-GFP⁺ monocytes. Four weeks after the adoptive transfer of CD45.2⁺Lysm-GFP⁺CD11b⁺Ly6C^hi monocytes into 6 Gy-irradiated CD45.1⁺ syngeneic recipient mice, we sorted donor Lysm-GFP⁺ and Lysm-GFP⁻ RpMacs (CD45.2⁺CD11b^lowF4/80^hi) from the spleen, donor Lysm-GFP⁺ and Lysm-GFP⁻ Kupffer cells (CD45.2⁺CD11b^lowF4/80^hi) from the liver, and donor Lysm-GFP⁺ and Lysm-GFP⁻ macrophages (CD45.2⁺CD11b^lowF4/80^hi) from the kidneys, as described in the Materials and Methods. We visualized the RNA-seq data by plotting the genes of three samples in a three-axis graph [8] (Extended Data Fig. 6). The three macrophage subpopulations from the liver, kidneys, and spleen were each divided into three quadrants (Extended Data Fig. 7), showing a gene set similar to those of Lysm-GFP⁺ macrophages and tissue-resident macrophages (blue rhombus, Extended Data Fig. 8a), a gene set similar to those of Lysm-GFP⁻ macrophages and tissue-resident macrophages (pink rhombus, Extended Data Fig. 8b), and a gene set similar to those of Lysm-GFP⁺ and Lysm-GFP⁻ macrophages (orange rhombus, Extended Data Fig. 8c). To rule out genes commonly altered during monocyte differentiation into macrophages and to show transcriptionally altered genes in donor Lysm-GFP⁺, Lysm-GFP⁻, and host tissue-resident macrophages in a relatively specific way, we assembled the gene sets by eliminating genes that were upregulated in both monocyte-derived Lysm-GFP⁺ and Lysm-GFP⁻ macrophages compared to host tissue-resident macrophages (log2FC > 1 in monocyte-derived Lysm-GFP⁺ and Lysm-GFP⁻ macrophages vs. tissue-resident macrophages from the spleen, liver, and kidneys, respectively, Extended Data Fig. 9). We found that donor Lysm-GFP⁺ and Lysm-GFP⁻ macrophages and host tissue-resident macrophages, including liver Kupffer cells (Fig. 4a), renal macrophages (Fig. 4b), and spleen RpMacs (Fig. 4c), shared the majority of transcriptionally expressed genes. The differentially expressed genes in the blue and pink quadrants suggest that both Lysm-GFP⁺ and Lysm-GFP⁻ macrophages had gene expression profiles similar to those of embryonic-derived tissue-resident macrophages from the same tissue (Fig. 4a–c). To analyze the relationship among Lysm-GFP⁺, Lysm-GFP⁻, and embryonic-derived tissue-resident macrophages from different tissues, we further enriched for gene sets that were highly specifically expressed in liver Kupffer cells, renal macrophages, or spleen RpMacs (Extended Data Fig. 10a). We then separately performed PCA in the context of the gene sets specifically expressed by liver Kupffer cells, renal macrophages, and spleen RpMacs to assess the relationship among Lysm-GFP⁺, Lysm-GFP⁻, and embryonic-derived tissue-resident macrophages from the liver, kidneys, and spleen (Extended Data Fig. 10b). Importantly, PCA showed the following route in the three tissues: Lysm-GFP⁺ monocytes → Lysm-GFP⁺ macrophages → Lysm-GFP⁻ macrophages → tissue-resident macrophages (Fig. 4d), which is in line with findings from the Scott and Lu teams [6, 20]. Based on the above results, Lysm-GFP⁻ macrophages seemed more like tissue-resident macrophages than Lysm-GFP⁺ macrophages, so we enriched for genes upregulated in Lysm-GFP⁻ macrophages in the context of the aforementioned tissue-specific gene expression sets. The results showed that Lysm-GFP⁻ macrophages in the three different tissues highly expressed genes characteristic of the corresponding tissue-resident macrophages compared with Lysm-GFP⁺ macrophages and monocytes, including recognized marker genes such as Timd4 and Clec4F in liver Kupffer cells, Mertk in renal tissue-resident macrophages, and Spic in spleen RpMacs [6, 20, 22] (Fig. 4e–g). Furthermore, we analyzed potential biomarker expression in tissue-resident donor Lysm-GFP⁺ macrophages and in Lysm-GFP⁻ macrophages from the liver, kidneys, and spleen 4 weeks after adoptive transfer. We found upregulated expression of tissue-resident macrophage biomarkers, including Tim4, Mertk, and CD169, in Lysm-GFP⁻ macrophages, supporting the hypothesis that Lysm-GFP⁻ macrophages were more similar to the corresponding tissue-resident macrophages than the Lysm-GFP⁺ macrophages in the same tissue (Fig. 4h). These bioinformatic analyses and functional assays collectively indicated that Lysm-GFP⁻ macrophages were much more similar to tissue-resident macrophages than Lysm-GFP⁺ macrophages with respect to gene expression profile and function.

Fig. 4 — *Lysm*-GFP⁻ macrophages displayed a phenotype similar to that of tissue-resident macrophages. For gene expression comparisons, we collected CD45.2⁺ donor-derived *Lysm*-GFP⁻ tissue-resident macrophages, CD45.2⁺ donor-derived *Lysm*-GFP⁺ tissue-resident macrophages, and CD45.1⁺ host-derived embryonic tissue-resident macrophages from the liver, kidneys, and spleen (gating strategies are shown in Fig. 3). a–c Gene sets without commonly shared genes expressed in macrophages from the liver, kidneys, and spleen are presented in hexagon and rose diagrams. d Transcriptional profile PCA of monocytes, CD45.2⁺ donor-derived *Lysm*-GFP⁻ tissue-resident macrophages, CD45.2⁺ donor-derived *Lysm*-GFP⁺ tissue-resident macrophages, and CD45.1⁺ host-derived embryonic tissue-resident macrophages from the liver, kidneys, and spleen. e Heatmap of the gene set specific to *Lysm*^- and *Lysm*⁺ Kupffer cells. Canonical DEGs between *Lysm*-GFP⁻ and *Lysm*-GFP⁺ Kupffer cells are shown in the orange box. f Heatmap of kidney macrophage-specific genes. Canonical DEGs between *Lysm*-GFP⁻ and *Lysm*-GFP⁺ macrophages are shown in the green box. g Heatmap of the spleen macrophage-specific gene set. Canonical DEGs between *Lysm*-GFP⁻ and *Lysm*-GFP⁺ RpMacs are shown in the blue box. h Flow cytometry profiles of tissue-resident macrophage marker gene expression on donor-derived tissue-resident macrophages from the lungs, liver, spleen, and kidneys. Donor-derived tissue-resident macrophages were analyzed 4 weeks after the adoptive transfer of *Lysm*-GFP⁺ monocytes. The heatmap value was calculated based on normalization between samples of the same tissue

Common pathways regulating Lysm⁺ macrophage differentiation into Lysm⁻ macrophages

To identify pathways regulating the differentiation of newly recruited or formed tissue-resident macrophages into long-term surviving resident macrophages in various tissue types, we first compared Lysm-GFP⁻ and Lysm-GFP⁺ macrophage gene expression profiles in three different tissues (Extended Data Fig. 11a). We found 1942, 566, and 2681 genes with at least a 2-fold difference (p < 0.01) between Lysm-GFP⁺ and Lysm-GFP⁻ macrophages in the liver, kidneys, and spleen, respectively (Fig. 5a). Among these altered genes, we observed 788 upregulated genes and 1154 downregulated genes in donor Lysm-GFP⁻ Kupffer cells compared to Lysm-GFP⁺ Kupffer cells from the liver, 316 upregulated genes and 250 downregulated genes in donor Lysm-GFP⁻ macrophages compared to Lysm-GFP⁺ macrophages from the kidneys, and 2237 upregulated and 444 downregulated genes in donor Lysm-GFP⁻ RpMacs compared to Lysm-GFP⁺ RpMacs from the spleen (Fig. 5a). These results suggested that Lysm-GFP⁻ and Lysm-GFP⁺ tissue-resident macrophages had very distinct gene expression profiles. KEGG analyses found that the top upregulated pathways in Lysm-GFP⁻ Kupffer cells, RpMacs, and kidney CD11b^lowF4/80^hi macrophages included ribosome, oxidative phosphorylation, thermogenesis, metabolism pathways, antigen processing/presentation, glutathione metabolism, vascular smooth muscle contraction, FcγR-mediated phagocytosis, RNA transport, and spliceosome pathways (Fig. 5b, Extended Data Fig. 11b). The top downregulated pathways in Lysm-GFP⁻ Kupffer cells, RpMacs, and renal CD11b^lowF4/80^hi macrophages included phagosomes, NOD-like receptor signaling pathways, cytokine-cytokine receptor interactions, IL-17 signaling pathways, TNF signaling pathways, complement and coagulation cascades, and lysosome pathways (Fig. 5b and Extended Data Fig. 11c). Interestingly, the differential signaling pathways were highly similar in tissue-resident macrophages from the three different tissues. The ribosome and metabolism pathways were enriched in Lysm-GFP⁻ Kupffer cells, RpMacs, and kidney CD11b^lowF4/80^hi macrophages, whereas oxidative phosphorylation was enriched in only Lysm-GFP⁻ Kupffer cells. Antigen processing/presentation and protein processing in the endoplasmic reticulum were enriched in Lysm-GFP⁻ Kupffer cells and RpMacs (Fig. 5b). However, phagosome, toll-like receptor pathways, cytokine and receptor interactions, lysosomes, and NF-KB pathways were enriched in Lysm-GFP⁻ Kupffer cells, RpMacs, and kidney CD11b^lowF4/80^hi macrophages (Fig. 5b). Lysm-GFP⁺ tissue-resident macrophages transformed into Lysm-GFP⁻ tissue-resident macrophages in different tissues by downregulating similar signaling pathways, mainly affecting the macrophage phagosome and inflammatory responses (Fig. 5b). In addition, we used GSEA to assess similarly regulated KEGG pathways in Lysm-GFP⁻ macrophages from the three different tissues (Extended Data Fig. 12). The results showed that the toll-like receptor pathway, lysosomes, and NF-κB pathways were all significantly downregulated in Lysm-GFP⁻ macrophages, whereas there was no significant difference in cytokine changes, which might be due to complicated signal regulatory networks, including both positive and negative cytokine expression regulatory pathways in macrophages (Fig. 5c). Among the enriched pathways, ribosome and antigen processing and presentation pathways were significantly upregulated in Lysm-GFP⁻ macrophages from the liver, kidneys, and spleen (Fig. 5d). The enrichment of these pathways in Lysm-GFP⁻ macrophages suggested that liver-, kidney-, and spleen-resident Lysm-GFP⁻ macrophages exhibited a weaker proinflammatory response and an enhanced antigen-presenting ability.

Fig. 5 — *Lysm*-GFP⁻ and *Lysm*-GFP⁺ tissue-resident macrophages had different gene expression profiles. a Differential gene expression between *Lysm*-GFP⁻ and *Lysm*-GFP⁺ macrophages. Each gene was plotted in the volcano plot. The blue dots indicate genes downregulated in *Lysm*-GFP⁻ macrophages, and the red dots indicate genes upregulated in *Lysm*-GFP⁻ macrophages. The bar graphs represent the number of specific genes upregulated and downregulated between *Lysm*-GFP⁻ and *Lysm*-GFP⁺ macrophages in each tissue. b Bubble plots showing the KEGG pathways enriched by GSEA for the DEGs in different tissues. The dot size represents the gene count, and the color gradient represents −Log10 (p value). c GSEA of common downregulated pathways in the liver, kidneys, and spleen. d GSEA of common upregulated pathways in the liver, kidneys, and spleen. Each set of samples contains three biological replicates

Lysm⁺ macrophage differentiation into Lysm⁻ macrophages via tissue-specific regulatory pathways

Metabolism plays a central role in regulating macrophage function and development [23]. We integrated all metabolism-related genes that were upregulated in Lysm-GFP⁻ macrophages from the liver, kidneys, and spleen compared them with the same genes in the corresponding Lysm-GFP⁺ macrophages. Using heatmap analysis of the upregulated metabolism-related genes in the three different tissues, we found that many genes were tissue-specific (Extended Data Fig. 13). Glutamate metabolism was specifically upregulated in spleen Lysm-GFP⁻ RpMacs, fatty acid metabolism was specifically upregulated in kidney Lysm-GFP⁻ macrophages, and oxidative phosphorylation was specifically upregulated in liver Lysm-GFP⁻ Kupffer cells (Fig. 6a). These results suggested that different metabolic shifts might be involved in regulating bone marrow-derived macrophage development into resident macrophages in different tissues. In addition, we analyzed the specifically upregulated genes using KEGG analysis (Extended Data Fig. 14a) and found that cytokine and receptor pathways, mTOR signaling pathways, and fatty acid metabolic processes were specifically upregulated in spleen Lysm-GFP⁻ RpMacs, liver Lysm-GFP⁻ Kupffer cells, and kidney Lysm-GFP⁻ macrophages, respectively (Fig. 6b). These results suggested that distinct metabolic and intracellular signaling pathways were differentially involved in regulating Lysm-GFP⁺ macrophage development into Lysm-GFP⁻ macrophages in the three different tissues. IL-33 is an important cytokine that regulates Pre-RpMac development into RpMacs [24], and the upregulated ST2/MAPK pathway in Lysm-GFP⁻ RpMacs also suggested that the IL-33-ST2 axis might be a main regulatory pathway promoting the differentiation of spleen Lysm-GFP⁺ macrophages into Lysm-GFP⁻ macrophages (Extended Data Fig. 14b, c). We observed similar changes in spleen CD11b⁻F4/80^hi RpMacs but no detectable changes in spleen Pre-RpMacs or tissue-resident macrophages in the liver or kidneys of myeloid-specific ST2-deleted mice (Fig. 6c). This is in line with a previous report showing that knockout of the IL-33 receptor ST2 (encoded by Il1rl1) reduced the proportion of CD11b⁻F4/80^hi RpMacs in the spleen [24]. To test whether the mTOR pathway controls liver Tim4⁺ Kupffer cell differentiation, we determined the levels of tissue-resident macrophages in myeloid-specific mTOR-deficient mice. Our results showed that the proportions of CD11b^lowF4/80^hi macrophages were identical in the livers of wild-type (WT) and mTOR-deficient mice, but the proportion of CD11b^lowF4/80^hiTim4⁺ Kupffer cells in the CD11b^lowF4/80^hi macrophage population was significantly reduced in mTOR-deleted mice compared with WT mice (p < 0.01, Fig. 6d). The proportions of tissue-resident macrophages in other tissues were not different after mTOR deletion (Fig. 6d). Then, we determined the efficiency of reconstituted tissue-resident macrophages in recipient mice by adoptively transferring mTOR-deficient monocytes. The results showed that mTOR deficiency significantly inhibited the proportion of CD11b^lowF4/80^hiTim4⁺ Kupffer cells in the liver but not that of CD11b^lowF4/80^hi macrophages in the kidneys or CD11b⁻F4/80^hi RpMacs in the spleen (Extended Data Fig. 15). These data collectively suggest that different metabolic and signaling pathways control resident macrophage differentiation in different tissues.

Fig. 6 — *Lysm*-GFP⁻ macrophages in different tissues displayed tissue-specific metabolic pathways. a Integrated metabolic network analysis of DEGs between *Lysm*-GFP⁻ and *Lysm*-GFP⁺ macrophages from the liver, kidneys, and spleen. The squares in the network diagram represent DEGs, and the circle represents a metabolite. The purple squares represent commonly upregulated genes in the three tissues, the blue squares represent spleen-specific upregulated genes, the pink squares represent liver-specific upregulated genes, and the green squares represent kidney-specific upregulated genes. Tissue-specific upregulated metabolic pathways are provided. b Heatmap presenting tissue-specific upregulated genes in macrophages from the spleen, liver, and kidneys. Gene expression is shown as the fold change compared to the reference expression. Canonical upregulated pathways related to tissue-specific upregulated genes are listed in the colored boxes. Each set of samples contains three biological replicates. c The percentages of tissue-resident macrophages from the liver, spleen, and kidneys in WT and *Lysm*-ST2 knockout mice detected via flow cytometry. d The percentages of tissue-resident macrophages from the liver, spleen, and kidneys in WT and *Lysm*-mTOR knockout mice detected via flow cytometry. The flow cytometry data are presented as the means, and the histogram data are presented as the means ± SEMs (n = 3)

FABP5 deficiency inhibits bone marrow-derived tissue-resident macrophage development

Fatty acid-binding protein 5 (FABP5), a member of the intracellular lipid-binding protein family that can reversibly bind intracellular hydrophobic ligands and traffic them among cellular compartments, plays an important regulatory role in many physiological processes, such as lipid metabolism [25, 26] and inflammation [26, 27]. Fabp5 expression was significantly upregulated in renal Lysm-GFP⁻ macrophages compared to Lysm-GFP⁺ macrophages, while the expression levels of other protein family members were low or downregulated (Extended Data Fig. 14d). To investigate whether FABP5 is involved in bone marrow-derived tissue-resident macrophage differentiation in mice, we evaluated tissue-resident macrophages from WT and myeloid-specific FABP5-deficient mice via flow cytometry. We found that FABP5 deficiency had no apparent effect on the percentages of liver CD11b^lowF4/80^hiTim4⁺ Kupffer cells or spleen CD11b^hiF4/80⁺ RpMacs, although we observed a reduced percentage of CD11b^lowF4/80^hi Pre-RpMacs in FABP5-deleted mice (Fig. 7a). However, kidney CD11b^lowF4/80^hi resident macrophages were significantly reduced after FABP5 deletion (p < 0.01, Fig. 7a). Tissue-resident macrophages from the liver, spleen, and kidneys are predominantly derived from fetal precursors, while a small fraction of these cells differentiate from bone marrow precursors during normal physiological aging. To clarify the intrinsic impact of FABP5 deficiency on bone marrow-derived resident macrophage development under pathological conditions, we examined tissue-resident macrophage differentiation from bone marrow-derived monocytes sorted from FABP5-deficient mice in an adoptive transfer mouse model (Fig. 7b). Our results showed that the proportions of donor Ly6C^hi and Ly6C^low monocytes in the recipient bone marrow were not affected by FABP5 deficiency (Fig. 7c). Interestingly, FABP5 deficiency inhibited donor bone marrow-derived macrophage reconstitution in recipient tissues (Fig. 7d). The proportion of donor-derived tissue-resident macrophages in the kidneys was significantly reduced in mice that received FABP5-deficient monocytes, while no effect was observed in the spleen (Fig. 7d, e). We further assessed the ability of donor monocytes to develop into tissue-resident macrophages by comparing the ratio of tissue-resident macrophages (Kupffer cells, Renal-F4/80^hi macrophages, and RpMacs) to MDMacs (CD11b^hiF4/80^low macrophages, CD11b^hiF4/80^low macrophages, and Pre-RpMacs). We found that the ratio of tissue-resident macrophages to MDMacs in the kidneys was significantly reduced in the presence of FABP5 deficiency, while the ratio of donor-derived RpMacs to Pre-RpMacs in the spleen was unchanged, and the ratio of donor-derived Kupffer cells to CD11b^hiF4/80^low cells in the liver was increased in mice that received FABP5-deficient monocytes (Fig. 7f). These results suggested that metabolic changes caused by FABP5 deficiency might be involved in bone marrow-derived monocyte development into resident macrophages in the kidneys.

Fig. 7 — FABP5 loss blocks bone marrow-derived monocyte development into tissue-resident macrophages. a Flow cytometric analysis of macrophage subsets from the liver, spleen, and kidneys in WT and FABP5-knockout mice showing percentages of Timd4⁺ Kupffer cells in the liver, renal F4/80^high macrophages in the kidneys, and red pulp precursor macrophages and red pulp macrophages in the spleen. b Schematic experimental overview of sorted *Lysm*-FABP5-knockout mouse monocyte transfer into CD45.1⁺ recipient mice. c Percentages of donor-derived Ly6C^low and Ly6C^hi monocytes in recipient mouse bone marrow. d Flow cytometric analysis of donor-derived macrophage subsets from the liver, kidneys, and spleen of recipient mice. e Proportions of donor-derived macrophage subsets from the liver, kidneys, and spleen. f Ratios of Kupffer cells and CD11b⁺F4/80^low macrophages in the liver, renal F4/80^hi macrophages and CD11b⁺F4/80^low macrophages in the kidneys, and RpMacs and pre-RpMacs in the spleen. The flow cytometry data are presented as the means, and the histogram data are presented as the means ± SEMs (n = 3)

GM-CSF-induced macrophages favorably colonize the tissue niche

Transcription factors (TFs) are key genes regulating cell differentiation and function. We compared differentially expressed TFs in all Lysm-GFP⁺ macrophages versus Lysm-GFP⁻ macrophages in the liver, spleen, and kidneys (Extended Data Fig. 16). Among all altered Lysm-GFP⁻ macrophage TFs, 131 TFs were upregulated, and 41 TFs were downregulated in all three tissues (Fig. 8a). Thirty-three TFs were upregulated specifically in liver Lysm-GFP⁻ Kupffer cells, and 85 TFs were upregulated specifically in spleen Lysm-GFP⁻ RpMacs (Fig. 8a). We separately analyzed the upregulated and downregulated TFs that were commonly detected in all Lysm-GFP⁻ tissue-resident macrophages and plotted TF interactions (Fig. 8b, c). We found potential key upregulated TFs, including IFN regulatory factor 4 (Irf4), Foxo1, Meis1, Hmga1, Ebf1, and Tcf12, and important downregulated TFs, including Nfe2l2, Prdm1, Bcl6, Maf, and Irf7, to be enriched during the differentiation of Lysm⁺ cells into Lysm⁻ tissue-resident macrophages (Fig. 8b, c). GM-CSF dramatically induced Irf4 expression, whereas M-CSF increased Irf5 expression in macrophages [28, 29]. Interestingly, the Irf5 level was decreased in Lysm-GFP⁻ macrophages in the liver, spleen, and kidneys (Fig. 8c). After obtaining the upregulated gene sets in either GM-CSF- or M-CSF-induced bone marrow-derived macrophages (Extended Data Fig. 17), we compared gene expression between Lysm-GFP⁺ and Lysm-GFP⁻ macrophages. The results showed that GM-CSF-upregulated genes were significantly upregulated in Lysm-GFP⁻ macrophages in all tissues, but M-CSF-upregulated genes were downregulated in Lysm-GFP⁻ macrophages compared with Lysm-GFP⁺ macrophages (Fig. 8d, e). Therefore, we speculated that M-CSF and GM-CSF have different effects on the development of monocyte-derived macrophages into tissue-resident macrophages.

Fig. 8 — GM-CSF-induced macrophages colonize the tissue niche more favorably than do M-CSF-induced macrophages. a Heatmap of the different transcription factors expressed in *Lysm*-GFP⁻ and *Lysm*-GFP⁺ tissue macrophages from the liver, kidneys, and spleen. b Network of the commonly upregulated transcription factors expressed in *Lysm*-GFP⁻ and *Lysm*-GFP⁺ tissue macrophages from the three different tissues. The color represents the node degree. c Network of commonly downregulated transcription factors expressed in *Lysm*-GFP⁻ and *Lysm*-GFP⁺ tissue macrophages from the three different tissues. The color represents the node degree. d Heatmap representing the genes differentially expressed between *Lysm*-GFP⁻ and *Lysm*-GFP⁺ tissue macrophages from the liver, kidneys, and spleen using the gene set upregulated after M-CSF stimulation. e Heatmap representing the genes differentially expressed between *Lysm*-GFP⁻ and *Lysm*-GFP⁺ tissue macrophages from the liver, kidneys, and spleen using the gene set upregulated after GM-CSF stimulation. A schematic overview of the following experiment is shown in Extended Data Fig. 17. f Chimeric efficiency flow cytometric analysis of donor-derived CD11b⁺ F4/80⁺ macrophages from the bone marrow of recipient mice with BMMOs, M-Macs, and GM-Macs. g The proportion of CD45.1⁻CD45.2⁺CD11b⁺F4/80⁺ macrophages among total CD11b⁺F4/80⁺ bone marrow macrophages. h Chimeric efficiency flow cytometric analysis of donor-derived tissue-resident macrophages from the lungs, liver, kidneys, and spleen. The identification of tissue-resident macrophages for flow cytometric analysis is presented in Fig. 1. i The ratios of CD45.2⁺ donor-derived tissue-resident macrophages and MDMacs in the lungs, liver, kidneys, and spleen of recipient mice. The flow cytometry data are presented as the means, and histogram data are presented as the means ± SEMs (n = 3)

We next performed in vivo experiments to determine how efficiently in vitro M-CSF- and in vitro GM-CSF-induced macrophages (GM-Macs and M-Macs, respectively) colonized the tissue niche in mice. We purified CD45.2⁺CD11b⁺F4/80⁺ GM-Macs and CD45.2⁺CD11b⁺F4/80⁺ M-Macs and then transplanted these cells into 6 Gy-irradiated CD45.1⁺ recipient mice (Extended Data Fig. 18a). We measured the proportion of donor-derived resident macrophages in recipient mice 4 weeks after cell transplantation. The proportions of CD45.2⁺CD11b⁺F4/80⁺ donor-derived macrophages in the bone marrow of recipient mice that received M-Macs or GM-Macs were similar (Fig. 8f, g). However, the levels of reconstituted lung CD11c⁺CD11b⁻ AMs, liver CD45⁺Gr-1⁻CD11b^lowF4/80^hiTim4⁺ Kupffer cells, kidney CD11b⁺F4/80^hi macrophages, and spleen Gr-1⁻CD11c⁻CD11b^lowF4/80^hi RpMacs in mice that underwent M-Mac transplantation were significantly lower than those in mice that underwent GM-Mac transplantation, while the proportions of MDMacs in the lungs, liver, kidneys, and spleen of recipient mice after M-Mac transplantation were higher than those in mice that underwent GM-Mac transplantation (p < 0.001, Fig. 8h, i). The ratios of tissue-resident macrophages to MDMacs in these tissues in mice that underwent GM-Mac transplantation were significantly higher than those in mice that underwent M-Mac transplantation (Extended Data Fig. 18b, c). Thus, these results showed that GM-Macs colonized the tissue niche more favorably than did M-Macs.

Discussion

In this study, we found that monocytes expressed high levels of Lysm, but Lysm expression was markedly decreased in tissue-resident macrophages, as detected by RNA-seq and flow cytometry assays. In Lysm-GFP-reporter mice, all fetal liver monocytes and adult bone marrow monocytes highly expressed Lysm-GFP, as detected by flow cytometry, but the majority of (if not all) lung CD11c⁺CD11b⁻ AMs, liver CD45⁺Gr-1 CD11b^lowF4/80^hiTim4⁺ Kupffer cells, kidney CD11b⁺F4/80^hi macrophages, and spleen Gr-1⁻CD11c⁻CD11b^lowF4/80^hi RpMacs were Lysm-GFP negative. Studies using adoptive transfer of sorted Lysm-GFP⁺ monocytes into irradiated syngeneic mice demonstrated that the tissue-resident macrophages in the lungs, liver, kidneys, and spleen that were reconstituted by bone marrow-derived monocytes gradually became Lysm-GFP⁻ and expressed tissue-resident macrophage gene transcription profiles. Thus, Lysm expression was gradually turned off during bone marrow-derived monocyte differentiation into tissue-resident macrophages. The lack of Lysm expression was a common characteristic of tissue-resident macrophages in the lungs, liver, kidneys, and spleen.

Tissue-resident macrophages are known to be derived from different precursors, including the yolk sac, fetal liver, and bone marrow, to different degrees, depending on age, tissue type, and physiological or pathological conditions [30]. Due to the lack of available markers to distinguish tissue-resident macrophages derived from the three different precursor cell types in adult mice, scientists have studied the phenotypes and gene expression profiles of tissue-resident macrophages as a mixture of these lineages. Taking advantage of the distinctive Lysm expression patterns and adoptive transfer mouse models, we studied mouse bone marrow-derived tissue-resident macrophage gene expression profiles by RNA-seq. After analyzing the differentially expressed gene sets in Lysm-GFP⁻ macrophages from three different tissues, we found that Lysm-GFP⁻ macrophages expressed higher levels of antigen presentation- and metabolism-associated genes, whereas Lysm-GFP⁺ macrophages expressed inflammation-related genes. The expression of glutamate metabolism-related genes was specifically upregulated in spleen Lysm-GFP⁻ RpMacs, while fatty acid metabolism-related gene expression was specifically upregulated in kidney Lysm-GFP⁻ macrophages, and oxidative phosphorylation-related gene expression was selectively upregulated in liver Lysm-GFP⁻ Kupffer cells. In addition to the distinct gene expression profiles of Lysm-GFP⁺ and Lysm-GFP⁻ Kupffer cells, Lysm-GFP⁻ Kupffer cells expressed core genes similar to those of embryonic-derived Kupffer cells, suggesting that Lysm-GFP⁻ Kupffer cells derived from bone marrow monocytes developed more tissue-resident macrophage characteristics. Lysm-GFP⁺ and Lysm-GFP⁻ RpMacs in the spleen and Lysm-GFP⁺ and Lysm-GFP⁻ macrophages in the kidneys showed similar patterns. The conclusion that Lysm-GFP⁻ macrophages in the liver and spleen were bone marrow-derived tissue-resident macrophage-like cells was also supported by our observation that Lysm-GFP⁻ macrophages from the liver and spleen, but not Lysm-GFP⁺ macrophages, efficiently cleared erythrocytes in an adoptive transfer mouse model. However, some genes were differentially expressed by bone marrow-derived tissue-resident macrophages and embryonic-derived tissue-resident macrophages in the liver, kidneys, and spleen, which might be due to differences in tissue-resident macrophage origins [6, 8].

Importantly, PCA revealed the developmental route from Lysm-GFP⁺ monocytes → Lysm-GFP⁺ macrophages → Lysm-GFP⁻ macrophages → tissue-resident macrophages in the liver, kidneys, and spleen. This hypothesis was supported by the early presence of Lysm-GFP⁺ tissue-resident macrophages that was followed by a gradual increase in Lysm-GFP⁻ tissue-resident macrophages in the lungs, liver, and kidneys after adoptive transfer of Lysm-GFP⁺ monocytes or macrophages. To understand the common molecular mechanisms orchestrating the differentiation of Lysm-GFP⁺ cells into Lysm-GFP⁻ tissue-resident macrophages in different tissues, we analyzed the commonly regulated TFs in Lysm-GFP⁻ macrophages from the lungs, liver, and kidneys. We identified key TFs, including Irf4, Foxo1, Meis1, Hmga1, Ebf1, and Tcf12, that were upregulated during the differentiation of Lysm⁺ cells into Lysm⁻ tissue-resident macrophages in the lungs, liver, and kidneys, whereas another set of TFs, including Nfe2l2, Prdm1, Bcl6, Irf5, Maf, and Irf7, was downregulated. Considering that the expression levels of Irf4 and Irf5 changed in opposite directions in Lysm⁻ macrophages and that GM-CSF and M-CSF are known to differentially regulate Irf4 and Irf5 expression in macrophages [28, 29], we speculated on the different roles of GM-CSF- and M-CSF-induced macrophages in maintaining the tissue-resident macrophage pool. Indeed, GM-Macs formed a higher proportion of tissue-resident macrophages after tissue colonization than did M-Macs, and M-Macs formed a higher proportion of monocyte-derived macrophages after tissue colonization than did GM-Macs. These observations indicated that GM-Macs more favorably reconstituted the tissue-resident macrophage pools in the lungs, kidneys, liver, and spleen after adoptive transfer. Thus, compared with M-Macs, GM-Macs might contribute more to the reconstituted tissue-resident macrophage pool in adult mice after pathological stress.

In addition to the common regulatory pathways for resident macrophage differentiation in tissues, distinctive metabolic and signaling pathways may regulate tissue-resident macrophage differentiation [1, 20, 22, 31–33]. We found that cytokine and receptor pathways, mTOR signaling pathways, and fatty acid metabolic processes were specifically upregulated in spleen Lysm-GFP⁻ RpMacs, liver Lysm-GFP⁻ Kupffer cells, and kidney Lysm-GFP⁻ macrophages, respectively. Indeed, our genetically modified mouse models showed that splenic RpMac development was significantly repressed in myeloid-specific ST2-deficient mice, as previously reported [24]. Hepatic CD11b^lowF4/80^hi Tim4⁺ Kupffer cell development was blocked in myeloid-specific mTOR-deficient mice, whereas kidney CD11b^lowF4/80^hi resident macrophages were significantly reduced in myeloid-specific FABP5-deleted mice. Notably, we did not examine changes in ST2-deficient monocyte development into tissue-resident macrophages in an adoptive transfer mouse model; thus, we could not rule out potential effects of ST2 deficiency in other myeloid lineage cells (such as neutrophils) on tissue-resident macrophage development, something that should be clarified in future studies. However, we determined how efficiently adoptively transferred FABP5-deficient and mTOR-deficient monocytes reconstituted tissue-resident macrophages in recipient mice and found that FABP5 deficiency significantly inhibited the ratio of tissue-resident macrophages to monocyte-derived macrophages in the kidneys and that mTOR deficiency significantly reduced the percentage of Tim4⁺ Kupffer cells in the liver. These findings indicated that FABP5 intrinsically controlled tissue-resident macrophages in the kidneys but not in the liver or spleen and that mTOR intrinsically controlled Tim4⁺ Kupffer cells in the liver but not resident macrophages in the kidneys or spleen. Thus, macrophages used different metabolic and signaling pathways to develop tissue-resident macrophage phenotypes in various tissues.

In summary, we developed a new research tool based on Lysm expression that could distinguish newly formed tissue-resident macrophages and long-term surviving tissue-resident macrophages in adult mice under pathological conditions. We found that GM-Macs contributed to the tissue-resident macrophage pool more efficiently than did M-Macs in adult mice when tissue-resident macrophage reconstitution was needed. High Irf4 expression might be essential for resident macrophage differentiation in all tissues, but cytokine and cytokine receptor pathways, mTOR signaling pathways, and fatty acid metabolic processes predominantly regulated spleen RpMacs, liver Kupffer cells, and kidney macrophages, respectively. Understanding tissue-resident macrophage molecular regulatory mechanisms could help us to identify novel therapeutic targets to treat macrophage-mediated diseases.

Methods

Mice

We obtained CD45.2⁺Lysm-GFP-reporter mice from Dr. Lianfeng Zhang, Key Laboratory of Human Diseases Comparative Medicine, Ministry of Health. We purchased C57BL/6 mice from Vital River Laboratories (Beijing, China). We used CD45.1⁺ mice purchased from the Beijing Laboratory Animal Research Center (Beijing, China) as bone marrow transplantation recipient mice. To obtain embryonic precursor cells, female mice and male mice were caged together in the afternoon, and then the female mice were separated the next morning. We obtained E8.5d embryonic mice and E14.5d embryonic mice on the eighth and fourteenth days after mouse separation, respectively. We purchased Lysm-Cre mice and mTOR^loxp/loxp mice from The Jackson Laboratory (Bar Harbor, ME). We obtained ST2^loxp/loxp mice and FABP5^loxp/loxp mice from Dr Lianfeng Zhang, Key Laboratory of Human Diseases Comparative Medicine, Ministry of Health. We crossed mTOR^loxp/loxp mice, ST2^loxp/loxp mice, and FABP5^loxp/loxp mice with Lysm-Cre mice to generate Lysm-Cre mTOR^loxp/loxp mice, Lysm-Cre ST2^loxp/loxp mice, and Lysm-Cre FABP5^loxp/loxp mice, respectively [34]. We used littermates (Lysm-Cre negative mTOR^loxp/loxp mice, Lysm-Cre negative ST2^loxp/loxp mice, and Lysm-Cre negative FABP5^loxp/loxp mice) or age-matched wild-type mice as controls to compare the effects of gene deficiency on tissue-resident macrophage development. All experimental animals were bred in the animal facility of the Institute of Zoology, Chinese Academy of Sciences. The breeding conditions were strictly in accordance with the following requirements: 5 mice were housed in a single ventilated cage under specific pathogen-free conditions, light conditions were set to a day-night cycle, and mice were given sufficient breeding feed and sterilized water. All feeding and experimental processes were carried out in accordance with the requirements of the Animal Ethics Committee of the Institute of Zoology (Beijing, China).

Cell preparation for flow cytometry and sorting

We collected peripheral blood cells from the mouse tail vein and then used a red blood cell lysis solution to remove the red blood cells [34]. To eliminate blood cell interference during flow cytometric analysis of tissue-resident immune cells, cardiac perfusion was performed before tissue removal. Depending on the difficulty in obtaining single cells from tissues, we used various grinding and digestion methods to prepare single-cell suspensions. We obtained bone marrow cells from the tibia, femur, and ilium of the hind limbs of mice using DMEM (HyClone Laboratories, SH30022.01B) and used a red blood cell lysis solution to remove the red blood cells. We mechanically dissociated spleen cells in DMEM to obtain single cells and used a red blood cell lysis solution to remove the red blood cells. We digested brain, lung, liver, and kidney tissues to obtain single-cell suspensions by mixing the tissues with 500 μg/mL Type IV Collagenase (Sigma‒Aldrich, C5138) and 20 units/mL DNase I (Sigma‒Aldrich, D5025) in DMEM supplemented with 2% fetal bovine serum (GIBCO, 16000-044). We incubated tissue samples at 37 °C for 30–60 min with 200 rpm shaking. To perform subsequent flow cytometric analysis, we passed the single-cell suspensions through a 75-μM mesh filter. We stained all single-cell suspensions with antibodies and then analyzed them using a flow cytometer (BD LSRFortessa X-20) or sorted them using a flow cytometer (BD Fusion).

Bone marrow chimeric mouse model

We exposed CD45.1⁺ C57BL/6 recipient mice to 6 Gy γ-irradiation before transplantation [35]. We cultured bone marrow cells from Lysm-GFP transgenic mice (C57BL/6, CD45.2⁺) to induce macrophages. We injected recipient mice with 10⁸ CD45.2⁺ bone marrow cells, 5 × 10⁵ CD45.2⁺ bone marrow monocytes, GM-CSF-induced bone marrow-derived macrophages (BMDMs), or M-CSF-induced BMDMs via tail vein injection in different experiments. We analyzed the subsequent distribution of CD45.2⁺CD45.1⁻ donor-derived tissue-resident macrophages 6 weeks after bone marrow cell transfer and 2, 4, and 10 weeks after the transfer of monocytes, GM-CSF-derived BMDMs, and M-CSF-derived BMDMs, respectively.

Erythrocyte clearance assay

Macrophage erythrocyte clearance capacity was evaluated in vivo. RBCs were separated from whole blood from CD45.2⁺ mice and then stained with CellTracker™ Red CMTPX Dye (Thermo Fisher Scientific) at 37 °C for 30 min. The ratio of CellTracker to RBCs was 1:1000. After the incubation with CellTracker, the labeled RBCs were washed three times with PBS and then resuspended in an equal volume. Three hundred microliters of labeled RBCs were transferred into CD45.1⁺ recipient mice and then analyzed 4 weeks after transplantation [36, 37].

Bone marrow-derived macrophage induction and treatment

We induced BMDMs from fresh bone marrow cells. We flushed cells from the bone marrow using sterile DMEM and then resuspended them in BMDM preparation medium (DMEM supplemented with 5% fetal bovine serum). We then resuspended the cells with 1 ml 0.2% NaCl buffer and 1 ml 1.6% NaCl buffer in sequence to lyse the red blood cells. We filtered cells through a 75-μM mesh filter, placed them in 10-cm culture dishes (Corning Brand) for 2 h and incubated them at 37 °C and 5% CO₂ atmosphere for adherent culture. We then obtained the nonadherent cells and suspended them in BMDM culture medium (DMEM supplemented with 5% fetal bovine serum, 25 ng/mL GM-CSF or 50 ng/mL M-CSF) at a concentration of 10⁷ cells per mL in a total of 10 mL of medium [38]. Four days after seeding, we discarded the medium, added 10 mL of fresh BMDM culture medium, and incubated the cells for 3 more days. We used BMDMs for bone marrow transplantation experiments and cytokine treatment experiments. All cytokines in the cytokine treatment experiments were used at a concentration of 20 ng/mL. Three days after cytokine stimulation, we added 5 mL of fresh BMDM culture medium with cytokines to each dish and cultured the cells for an additional 4 days.

Flow cytometry

We prepared single-cell suspension samples (10⁷ cells per mL) as described above and stained a 100-μL sample of cells with fluorophore-conjugated antibodies and 2.4G2 (Fc blocking) for 15 min at 4 °C. We diluted all fluorophore-conjugated antibodies in flow staining buffer (PBS with 1% BSA, 2 mM EDTA, and 0.01% NaN₃) and determined the fluorophore-conjugated antibody concentrations in advance through antibody titration experiments [39]. Fifteen minutes after staining, we mildly shook the stained single-cell suspensions for an additional 15 min. We then washed the samples with flow staining wash buffer (DMEM with 2% BSA) twice. We analyzed the cells using a flow cytometer (BD LSRFortessa X-20) and obtained flow plots using FlowJo V10 software. All fluorophore-conjugated antibodies and reagents used are listed below: PE-conjugated anti-mouse Tim4 (BioLegend 130005), PE-conjugated anti-mouse Mertk (BioLegend 151505), PE-conjugated anti-mouse Ly6C (BioLegend 128007), PE-conjugated anti-mouse F4/80 (BioLegend 157304), PE/Cy5-conjugated anti-mouse F4/80 (BioLegend 123112), PE/Cy5-conjugated anti-mouse CD11c (BioLegend 117316), PE/Cy5-conjugated anti-mouse Gr-1 (BioLegend 108410), PE/Cy5-conjugated anti-mouse CD11b (BioLegend 101210), PE/Cy7-conjugated anti-mouse CD45.1 (BioLegend 110730), APC-conjugated anti-mouse F4/80 (BioLegend 123116), APC-conjugated anti-mouse CD45.2 (BioLegend 109814), Brilliant Violet 510-conjugated anti-mouse CD11b (BioLegend 101263), eBioscience^TM Fixable Viability Dye eFluor^TM 780 (Thermo Fisher Scientific 65-0865-14), Brilliant Violet 711-conjugated anti-mouse CD64 (BioLegend 139311), and BUV395-conjugated rat anti-mouse CD45RA (BD Biosciences 740232).

RNA-sequencing analysis

Sample preparation

We performed two RNA-sequencing analyses. We sorted Lysm-GFP+ macrophage and Lysm-GFP⁻ macrophage samples from CD45.1⁺ recipient mice that had been transferred with CD45.2⁺Lysm-GFP⁺ bone marrow monocytes. Figure 2 shows the tissue macrophage identification strategy. We directly obtained Lysm-GFP⁻ GM-Mac samples from cytokine-stimulated BMDMs in vitro, resuspended RNA-sequencing samples in TRIzol lysis buffer, and stored them at −80 °C or used them immediately for RNA extraction and cDNA library preparation for RNA-sequencing analysis [40]. The RNA extraction and cDNA library preparation steps were performed and sequences were generated by CapitalBio Technology (Beijing, China).

Data processing

We used Trimgalore to filter low-quality reads (Q < 20) and the adaptor sequence. Processed reads were aligned to the mouse genome (mm10) via HISAT2 [41]. We calculated the RNA-seq TPM (transcripts per kilobase of exon model per million mapped reads) values by read count using StringTie [42]. We used DEGseq [43] to study differentially expressed genes (DEGs) meeting a threshold of p < 0.05 and |Fold change| > 1 and compared the number of DEGs between Lysm-GFP⁺ and Lysm-GFP⁻ in different tissues. We constructed hexagon and rose diagrams using the Triwise package [8] to compare the gene expression profiles of monocyte-derived macrophages (Lysm-GFP⁺ and Lysm-GFP⁻) with those of tissue-resident macrophages in the spleen, liver, and kidneys, separately. We performed a principal component analysis (PCA) using the top 15% of variable genes according to their expression. We calculated the heatmap scale based on normalization between samples from the same tissue.

Functional analysis and visualization

Functional differences between negative and positive cells were analyzed using Metascape, KOBAS 3.0 [44] (available online: http://kobas.cbi.pku.edu.cn/kobas3/), GSEA 4.3.0 [45], and GSVA [46] (R package, version 1.38.2) software. We used the KEGG and Reactome pathway databases to evaluate cell function. We selected all pathway terms with p < 0.05 as the cutoff criterion. We constructed a metabolic network using GAM [47] (available online: https://artyomovlab.wustl.edu/shiny/gam/) to represent the relationship between genes and their metabolites. We constructed a TF network using literature-curated comprehensive data from InnateDB in NetworkAnalyst [48] (available online: https://www.networkanalyst.ca) and used Cytoscape [49] to perform all network visualizations.

Statistical analysis

Analyzed flow cytometry data are presented as the means, and the histograms and scatterplots are presented as the means ± SEMs. We tested for significant differences using two-way ANOVA or a parametric two-tailed unpaired Student’s test.

Supplementary information

Supplement Data^{(11.2KB, xlsx)}

Extended Data Figures^{(3.1MB, pdf)}

Acknowledgements

We would like to acknowledge Mrs. Qing Meng and Mrs. Xiaoqiu Liu for their expert technical assistance, Mrs. Ling Li for her excellent laboratory management, and Mr. Yiming Jin for his assistance with the animal and cellular experiments. This work was supported by grants from the National Natural Science Foundation for Key Programs (31930041, Y.Z.), National Key Research and Development Program of China (2017YFA0105002, 2017YFA0104402, Y.Z.), and Knowledge Innovation Program of the Chinese Academy of Sciences (XDA16030301, Y.Z.).

Author contributions

T.L. and Y.Z. designed the methodology and investigation. T.L. and Q.Z. conducted experiments, collected results, and performed analyses. J.Y.Z. performed bioinformatic analysis. T.L., X.R.M., Y.N.X., and Y.Z. performed animal husbandry. T.L., J.Y.Z., and Y.Z. wrote the paper. Y.Z. supervised, directed, performed project administration, and acquired funding.

Data availability

We downloaded the microarray GM-CSF data and M-CSF-induced bone marrow-derived macrophage data from E-MTAB-791 [29]. The raw RNA-seq data generated in our study were deposited in the National Genomics Data Center (NCDC): BioProject PRJCA008365.

Material availability

Methods, including statements of data availability and any further information, are available in the online version of this paper.

Competing interests

The authors declare no competing interests.

Footnotes

These authors contributed equally: Tong Lei, Jiayu Zhang, Qian Zhang.

Contributor Information

Lianfeng Zhang, Email: zhanglf@cnilas.org.

Zhongbing Lu, Email: luzhongbing@ucas.ac.cn.

Yong Zhao, Email: zhaoy@ioz.ac.cn.

Supplementary information

The online version contains supplementary material available at 10.1038/s41423-022-00936-4.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement Data^{(11.2KB, xlsx)}

Extended Data Figures^{(3.1MB, pdf)}

Data Availability Statement

Methods, including statements of data availability and any further information, are available in the online version of this paper.

[CR1] 1.Bleriot C, Chakarov S, Ginhoux F. Determinants of resident tissue macrophage identity and function. Immunity. 2020;52:957–70. doi: 10.1016/j.immuni.2020.05.014. [DOI] [PubMed] [Google Scholar]

[CR2] 2.Knipper JA, Ding X, Eming SA. Diabetes impedes the epigenetic switch of macrophages into repair mode. Immunity. 2019;51:199–201. doi: 10.1016/j.immuni.2019.07.009. [DOI] [PubMed] [Google Scholar]

[CR3] 3.Ginhoux F, Guilliams M. Tissue-resident macrophage ontogeny and homeostasis. Immunity. 2016;44:439–49. doi: 10.1016/j.immuni.2016.02.024. [DOI] [PubMed] [Google Scholar]

[CR4] 4.Gomez Perdiguero E, Klapproth K, Schulz C, Busch K, Azzoni E, Crozet L, et al. Tissue-resident macrophages originate from yolk-sac-derived erythro-myeloid progenitors. Nature. 2015;518:547–51. doi: 10.1038/nature13989. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR5] 5.Zhao Y, Zou W, Du J, Zhao Y. The origins and homeostasis of monocytes and tissue-resident macrophages in physiological situation. J Cell Physiol. 2018;233:6425–39. doi: 10.1002/jcp.26461. [DOI] [PubMed] [Google Scholar]

[CR6] 6.Scott CL, Zheng F, De Baetselier P, Martens L, Saeys Y, De Prijck S, et al. Bone marrow-derived monocytes give rise to self-renewing and fully differentiated Kupffer cells. Nat Commun. 2016;7:10321. doi: 10.1038/ncomms10321. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR7] 7.Wynn TA, Vannella KM. Macrophages in tissue repair, regeneration, and fibrosis. Immunity. 2016;44:450–62. doi: 10.1016/j.immuni.2016.02.015. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.van de Laar L, Saelens W, De Prijck S, Martens L, Scott CL, Van Isterdael G, et al. Yolk Sac macrophages, fetal liver, and adult monocytes can colonize an empty niche and develop into functional tissue-resident macrophages. Immunity. 2016;44:755–68. doi: 10.1016/j.immuni.2016.02.017. [DOI] [PubMed] [Google Scholar]

[CR9] 9.Bonnardel J, T'Jonck W, Gaublomme D, Browaeys R, Scott CL, Martens L, et al. Stellate cells, hepatocytes, and endothelial cells imprint the Kupffer cell identity on monocytes colonizing the liver macrophage niche. Immunity. 2019;51:638–54.e9. doi: 10.1016/j.immuni.2019.08.017. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Seidman JS, Troutman TD, Sakai M, Gola A, Spann NJ, Bennett H, et al. Niche-specific reprogramming of epigenetic landscapes drives myeloid cell diversity in nonalcoholic steatohepatitis. Immunity. 2020;52:1057–74.e. doi: 10.1016/j.immuni.2020.04.001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR11] 11.Woo YD, Jeong D, Chung DH. Development and functions of alveolar macrophages. Mol Cells. 2021;44:292–300. doi: 10.14348/molcells.2021.0058. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR12] 12.Cheah FC, Presicce P, Tan TL, Carey BC, Kallapur SG. Studying the effects of granulocyte-macrophage colony-stimulating factor on fetal lung macrophages during the perinatal period using the mouse model. Front Pediatr. 2021;9:614209. doi: 10.3389/fped.2021.614209. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Lambrecht BN. TGF-beta gives an air of exclusivity to alveolar macrophages. Immunity. 2017;47:807–9. doi: 10.1016/j.immuni.2017.11.005. [DOI] [PubMed] [Google Scholar]

[CR14] 14.Yu X, Buttgereit A, Lelios I, Utz SG, Cansever D, Becher B, et al. The cytokine TGF-beta promotes the development and homeostasis of alveolar macrophages. Immunity. 2017;47:903–12.e4. doi: 10.1016/j.immuni.2017.10.007. [DOI] [PubMed] [Google Scholar]

[CR15] 15.Kucharova K, Stallcup WB. Distinct NG2 proteoglycan-dependent roles of resident microglia and bone marrow-derived macrophages during myelin damage and repair. PLoS ONE. 2017;12:e0187530. doi: 10.1371/journal.pone.0187530. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR16] 16.Zilionis R, Engblom C, Pfirschke C, Savova V, Zemmour D, Saatcioglu HD, et al. Single-cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations across individuals and species. Immunity. 2019;50:1317–34.e0. doi: 10.1016/j.immuni.2019.03.009. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Gibbings SL, Thomas SM, Atif SM, McCubbrey AL, Desch AN, Danhorn T, et al. Three unique interstitial macrophages in the murine lung at steady state. Am J Respir Cell Mol Biol. 2017;57:66–76. doi: 10.1165/rcmb.2016-0361OC. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR18] 18.Devisscher L, Scott CL, Lefere S, Raevens S, Bogaerts E, Paridaens A, et al. Non-alcoholic steatohepatitis induces transient changes within the liver macrophage pool. Cell Immunol. 2017;322:74–83. doi: 10.1016/j.cellimm.2017.10.006. [DOI] [PubMed] [Google Scholar]

[CR19] 19.Miyanishi M, Tada K, Koike M, Uchiyama Y, Kitamura T, Nagata S. Identification of Tim4 as a phosphatidylserine receptor. Nature. 2007;450:435–9. doi: 10.1038/nature06307. [DOI] [PubMed] [Google Scholar]

[CR20] 20.Lu Y, Basatemur G, Scott IC, Chiarugi D, Clement M, Harrison J, et al. Interleukin-33 signaling controls the development of iron-recycling macrophages. Immunity. 2020;52:782–93.e5. doi: 10.1016/j.immuni.2020.03.006. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.Sheng J, Ruedl C, Karjalainen K. Most tissue-resident macrophages except microglia are derived from fetal hematopoietic stem cells. Immunity. 2015;43:382–93. doi: 10.1016/j.immuni.2015.07.016. [DOI] [PubMed] [Google Scholar]

[CR22] 22.Gautier EL, Shay T, Miller J, Greter M, Jakubzick C, Ivanov S, et al. Gene-expression profiles and transcriptional regulatory pathways that underlie the identity and diversity of mouse tissue macrophages. Nat Immunol. 2012;13:1118–28. doi: 10.1038/ni.2419. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR23] 23.Zhu L, Zhao Q, Yang T, Ding W, Zhao Y. Cellular metabolism and macrophage functional polarization. Int Rev Immunol. 2015;34:82–100. doi: 10.3109/08830185.2014.969421. [DOI] [PubMed] [Google Scholar]

[CR24] 24.Xu D, Huang SK. IL-33: a key player in the development of iron-recycling red pulp macrophages. Cell Mol Immunol. 2020;17:1218–9. doi: 10.1038/s41423-020-0509-5. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR25] 25.Umbarawan Y, Enoura A, Ogura H, Sato T, Horikawa M, Ishii T, et al. FABP5 is a sensitive marker for lipid-rich macrophages in the luminal side of atherosclerotic lesions. Int Heart J. 2021;62:666–76. doi: 10.1536/ihj.20-676. [DOI] [PubMed] [Google Scholar]

[CR26] 26.Moore SM, Holt VV, Malpass LR, Hines IN, Wheeler MD. Fatty acid-binding protein 5 limits the anti-inflammatory response in murine macrophages. Mol Immunol. 2015;67:265–75. doi: 10.1016/j.molimm.2015.06.001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR27] 27.Guo Y, Liu Y, Zhao S, Xu W, Li Y, Zhao P, et al. Oxidative stress-induced FABP5 S-glutathionylation protects against acute lung injury by suppressing inflammation in macrophages. Nat Commun. 2021;12:7094. doi: 10.1038/s41467-021-27428-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR28] 28.Lee MC, Lacey DC, Fleetwood AJ, Achuthan A, Hamilton JA, Cook AD. GM-CSF- and IRF4-dependent signaling can regulate myeloid cell numbers and the macrophage phenotype during inflammation. J Immunol. 2019;202:3033–40. doi: 10.4049/jimmunol.1801549. [DOI] [PubMed] [Google Scholar]

[CR29] 29.Lacey DC, Achuthan A, Fleetwood AJ, Dinh H, Roiniotis J, Scholz MG, et al. Defining GM-CSF—and macrophage-CSF-dependent macrophage responses by in vitro models. J Immunol. 2012;188:5752–65. doi: 10.4049/jimmunol.1103426. [DOI] [PubMed] [Google Scholar]

[CR30] 30.Harjes U. Home advantage for tissue-resident macrophages. Nat Rev Cancer. 2021;21:539. doi: 10.1038/s41568-021-00393-7. [DOI] [PubMed] [Google Scholar]

[CR31] 31.Ma D, Doi Y, Jin S, Li E, Sonobe Y, Takeuchi H, et al. TGF-beta induced by interleukin-34-stimulated microglia regulates microglial proliferation and attenuates oligomeric amyloid beta neurotoxicity. Neurosci Lett. 2012;529:86–91. doi: 10.1016/j.neulet.2012.08.071. [DOI] [PubMed] [Google Scholar]

[CR32] 32.Sakai M, Troutman TD, Seidman JS, Ouyang Z, Spann NJ, Abe Y, et al. Liver-derived signals sequentially reprogram myeloid enhancers to initiate and maintain Kupffer cell identity. Immunity. 2019;51:655–70.e8. doi: 10.1016/j.immuni.2019.09.002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR33] 33.Dahik VD, Frisdal E, Le Goff W. Rewiring of lipid metabolism in adipose tissue macrophages in obesity: impact on insulin resistance and type 2 diabetes. Int J Mol Sci. 2020;21:5505. doi: 10.3390/ijms21155505. [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

Defining newly formed and tissue-resident bone marrow-derived macrophages in adult mice based on lysozyme expression

Tong Lei

Jiayu Zhang

Qian Zhang

Xinran Ma

Yanan Xu

Yang Zhao

Lianfeng Zhang

Zhongbing Lu

Yong Zhao

Abstract

Introduction

Results

Tissue-resident macrophages did not express Lysm

Fig. 1.

Lysm expression was downregulated during Lysm-GFP+ monocyte differentiation into tissue-resident macrophages

Fig. 2.

Fig. 3.

Monocyte-derived Lysm-GFP− macrophages displayed phenotypes similar to embryo-derived resident macrophages

Fig. 4.

Common pathways regulating Lysm+ macrophage differentiation into Lysm− macrophages

Fig. 5.

Lysm+ macrophage differentiation into Lysm− macrophages via tissue-specific regulatory pathways

Fig. 6.

FABP5 deficiency inhibits bone marrow-derived tissue-resident macrophage development

Fig. 7.

GM-CSF-induced macrophages favorably colonize the tissue niche

Fig. 8.

Discussion

Methods

Mice

Cell preparation for flow cytometry and sorting

Bone marrow chimeric mouse model

Erythrocyte clearance assay

Bone marrow-derived macrophage induction and treatment

Flow cytometry

RNA-sequencing analysis

Sample preparation

Data processing

Functional analysis and visualization

Statistical analysis

Supplementary information

Acknowledgements

Author contributions

Data availability

Material availability

Competing interests

Footnotes

Contributor Information

Supplementary information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

Lysm expression was downregulated during Lysm-GFP⁺ monocyte differentiation into tissue-resident macrophages

Monocyte-derived Lysm-GFP⁻ macrophages displayed phenotypes similar to embryo-derived resident macrophages

Common pathways regulating Lysm⁺ macrophage differentiation into Lysm⁻ macrophages

Lysm⁺ macrophage differentiation into Lysm⁻ macrophages via tissue-specific regulatory pathways