Host microbiota constantly control maturation and function of microglia in the CNS

Daniel Erny, Anna Lena Hrabě de Angelis, Diego Jaitin, Peter Wieghofer, Ori Staszewski, Eyal David, Hadas Keren-Shaul, Tanel Mahlakoiv, Kristin Jakobshagen, Thorsten Buch, Vera Schwierzeck, Olaf Utermöhlen, Eunyoung Chun, Wendy S Garrett, Kathy D McCoy, Andreas Diefenbach, Peter Staeheli, Bärbel Stecher, Ido Amit, Marco Prinz, Daniel Erny, Anna Lena Hrabě de Angelis, Diego Jaitin, Peter Wieghofer, Ori Staszewski, Eyal David, Hadas Keren-Shaul, Tanel Mahlakoiv, Kristin Jakobshagen, Thorsten Buch, Vera Schwierzeck, Olaf Utermöhlen, Eunyoung Chun, Wendy S Garrett, Kathy D McCoy, Andreas Diefenbach, Peter Staeheli, Bärbel Stecher, Ido Amit, Marco Prinz

Abstract

As the tissue macrophages of the CNS, microglia are critically involved in diseases of the CNS. However, it remains unknown what controls their maturation and activation under homeostatic conditions. We observed substantial contributions of the host microbiota to microglia homeostasis, as germ-free (GF) mice displayed global defects in microglia with altered cell proportions and an immature phenotype, leading to impaired innate immune responses. Temporal eradication of host microbiota severely changed microglia properties. Limited microbiota complexity also resulted in defective microglia. In contrast, recolonization with a complex microbiota partially restored microglia features. We determined that short-chain fatty acids (SCFA), microbiota-derived bacterial fermentation products, regulated microglia homeostasis. Accordingly, mice deficient for the SCFA receptor FFAR2 mirrored microglia defects found under GF conditions. These findings suggest that host bacteria vitally regulate microglia maturation and function, whereas microglia impairment can be rectified to some extent by complex microbiota.

Figures

Figure 1. Altered microglial gene profile and…
Figure 1. Altered microglial gene profile and immaturity in GF animals
(a) Left, photograph of caeca from SPF (control) and GF mice. Representative pictures are shown, with ruler for scaling. Right, relative cecal weight (to body weight) of SPF and GF mice. Symbols represent individual mice. 12 mice per group were examined. Data are representative of three independent experiments. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test, ***P = 0.0001. (b) RNA-seq analysis. Gene expression data shown was either induced or reduced by a factor of at least 2 (P < 0.01, unpaired t test) in microglia from SPF or GF mice. Representative genes are noted on the right. Each column represents microglia data from one individual mouse, with seven mice per group. Color code presents linear scale. (c) mRNA expression profile of genes that were at least 1.5-fold (P < 0.05, unpaired t test) downregulated in microglia from GF compared to SFP mice. Color code shows linear values. Representative genes are noted on the right. (d) Functional networks of genes that were downregulated (at least 1.5-fold, P < 0.05, unpaired t test) in microglia from GF compared to SPF mice. Blue framed genes were found to be downregulated whereas red framed genes were automatically predicted. (e) Expression profile of genes that were at least 1.5-fold (P < 0.05, unpaired t test) upregulated in microglia from GF compared with SFP mice. Representative genes are noted on the right. Color code presents linear scale. (f) Functional networks of upregulated genes (at least 1.5-fold, P < 0.05, unpaired t test). Blue-framed genes indicate upregulated molecules whereas red-framed genes were automatically predicted. (g) mRNA expression values (number of reads) of genes from microglia in GF (white bars) or SPF (black bars) mice were categorized according to the M0, M1 or M2 phenotypes, as described previously. Bars represent means ± s.e.m. with seven samples per group. Significant differences were determined by an unpaired t test (*P < 0.05, **P < 0.01, ***P < 0.001). P values: Gpr34, 0.0005; Serpine2, <0.0001; Slco2b1, 0.0078; Sparc, <0.0001; P2ry13, 0.0001; Atp8a2, 0.0239; P2ry12, <0.0001; Adamts16, 0.0105; Tmem119, 0.0002; Itgb5, 0.0052; Itga6, 0.0003; Golm1, 0.0125; Plxdc2, 0.006; Abi3, 0.0037; Cd34, 0.0001; Tgfbr1, 0.0035; Il-1α, 0.0002; Cd14, 0.0109; Cd86, 0.004; Fcgr1, 0.0281; Timp2, 0.0144; Tspan7, 0.0074; Ccnd1, 0.0378; X99384, 0.0077; Stab1, 0.0093; Mafb, 0.0257; C1qa, 0.0001.
Figure 2. Increased expression of maturation and…
Figure 2. Increased expression of maturation and activation marker in GF microglia
(a) Gating strategy for flow cytometric analysis of CD11 b+ CD45lo microglia from GF and SFP mice. Representative dot plots obtained from three independent experiments are shown. SSC, side scatter. (b) Representative cytometry graphs of the maturation and activation marker CSF1R, F4/80, CD31, CD44, CD62L and MHC class II on microglia from GF mice (red lines), SFP mice (blue lines) and isotype controls (gray lines). In addition, quantifications of the percentages (%) of positively labeled cells and MFIs are depicted. Each symbol represents data from one mouse, with six investigated mice per group. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (*P < 0.05, **P < 0.01, ***P < 0.001). Data are representative of three independent experiments. P values: CSF1R (percentage of positive cells), 0.0068; CSF1R (MFI), <0.0001; F4/80 (percentage of positive cells), 0.0134; F4/80 (MFI), 0.0047; CD31 (percentage of positive cells), 0.0103.
Figure 3. Lack of microbes impairs microglia…
Figure 3. Lack of microbes impairs microglia morphology and disturbs cellular network
(a) CNS histology of several brain regions that were stained with hematoxylin and eosin (H&E) or subjected to immunohistochemistry for Iba-1 to detect microglia. Scale bars represent 200 μm (H&E, cortex and corpus callosum), 500 μm (H&E, hippocampus and olfactory bulb), 1 mm (H&E, cerebellum) and 50 μm (Iba-1). Representative pictures from nine mice per group are displayed. (b) Number of Iba-1+ ramified parenchymal microglia in different localizations of the CNS. Each symbol represents data from one mouse, with nine mice per group. Three to four sections per mouse were examined. Data are presented as mean ± s.e.m. Data are representative of two independent experiments. Significant differences were determined by an unpaired t test (*P < 0.05, **P < 0.01, ***P < 0.001). P values: cortex, 0.0024; corpus callosum, 0.0008; hippocampus, 0.0073; olfactory bulb, 0.0092; cerebellum, 0.0246. (c) Expression of Ddit4 mRNA measured by qRT-PCR in microglia isolated from SPF (black bar) or GF (white bar) mice. Data are presented as mean ± s.e.m. with five samples in each group. Significant differences were determined by an unpaired t test (***P = 0.0002). Data are representative of two independent experiments. (d) Quantification of proliferating Iba-1+ Ki67+ double-positive parenchymal microglia was performed on cortical brain slices. Each symbol represents one mouse, with three mice per group. Three to four sections per mouse were examined. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (**P = 0.0033). (e) Fluorescence microscopy of Iba-1+ (red) microglia, the proliferation marker Ki67 (green) and DAPI (4′,6-diamidino-2-phenylindole, blue). Overview and magnification are shown. Scale bars represent 100 μm (overview) and 20 μm (inset). (f,g) Three-dimensional reconstruction (scale bars represent 15 μm, f) and Imaris-based automatic quantification of cell morphometry (g) of cortical Iba-1+ microglia. Each symbol represents one mouse with at least three measured cells per mouse. Five mice per group were analyzed. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (**P < 0.01). P values: dendrite length, 0.0035; number of segments, 0.0012; number of branch points, 0.0012; number of terminal points, 0.0012; volume, 0.0011.
Figure 4. Diminished microglia response to infection…
Figure 4. Diminished microglia response to infection under GF conditions
(a) Venn diagram depicting the different regulated and overlapping genes between sorted microglia from GF and SPF animals (P < 0.01) 6 h after LPS treatment compared with PBS-treated controls of the same housing conditions (GF/SPF). (b) Heat map of the mean centered and s.d. scaled expression values for genes that were significantly and at least twofold up- or downregulated in GF compared with SPF microglia 6 h after i.c. treatment with LPS. Only genes that were also significantly up- or downregulated by LPS treatment compared with PBS-treated controls of the same housing conditions (GF and SPF, respectively) were included to account for differences in basal gene regulation. Expression levels exceeding the mean value are colored in red and expression levels below the mean are colored in green (standardized and scaled to linear expression). Values close to the median are colored black. Random variance two-sample t test as implemented in BRB-Tools was performed to test significance at P < 0.01. (c) qRT-PCR in microglia 6 h after i.c. LPS exposure. Data are expressed as the ratio of the mRNA expression compared with endogenous Actb relative to SPF controls and are presented as mean ± s.e.m. At least three mice per group were analyzed. Data are representative of two independent experiments. Significant differences were examined by an unpaired t test (*P < 0.05, **P < 0.01, ***P < 0.001). ns, not significant. P values: PBS: Il-1β, 0.2324; Il-6, 0.6569; Il-12β, 0.0608; Tnfα, 0.7485; Marco, 0.2415; Ccl2, 0.8035; Ccl7, 0.1757; Cxcl10, 0.2138; Csf1, 0.1224; cyclin D2, 0.8405; S100a4, 0.1279; S100a6, 0.1169; S100a8, 0;1169; S100a9, 0.2677; S100a10, 0.8502. LPS: Il-1β, 0.0001; Il-6, 0.0005; Il-12β, 0.0001; Tnfα, 0.0050; Marco, 0.0001; Ccl2, 0.0001; Ccl7, 0.0003; Cxcl10, 0.0055; Csf1, 0.0028; cyclin D2, 0.0003; S100a4, 0.0033; S100a6, 0.0050; S100a8, 0.0425; S100a9, 0.2136; S100a10, 0.0028. (d,e) Three-dimensional reconstruction (scale bar represents 15 μm, d) and Imaris-based automatic quantification of cell morphometry (e) of cortical Iba-1+ microglia 6 h after i.c. treatment with LPS. Each symbol represents one mouse with at least three measured cells per mouse. Three SPF and four GF animals were investigated. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (*P < 0.05). P values: dendrite length, 0.0238; number of segments, 0.0238; number of branch points, 0.0209; number of terminal points, 0.027; volume, 0.0413.
Figure 5. Reduced microglia response to viral…
Figure 5. Reduced microglia response to viral infection under GF conditions
(a) Iba-1 immunhistochemistry depicting cortical microglia response 4 d after i.c. challenge with LCMV (left) and quantification (right). Each symbol represents one mouse, with nine PBS-treated control mice and ten LCMV-treated mice. Three to four sections per mouse were examined. Data are presented as mean ± s.e.m. Data are representative of two independent experiments. Significant differences were determined by an unpaired t test (*P < 0.05, **P < 0.01, ***P < 0.001). P values: SPF (PBS) versus GF (PBS): 0.0024; SPF (PBS) versus SPF (LCMV): 0.0001; GF (PBS) versus GF (LCMV): 0.0323; SPF (LCMV) versus GF (LCMV): 0.0222. Scale bars represent 50 μm. (b) Venn diagram illustrating the differences and overlaps between microglia from GF and SPF animals in significantly (P < 0.01) up- or down-regulated genes 4 d after LCMV treatment compared with PBS-treated controls of the same housing conditions (GF/SPF). (c) qRT-PCR in microglia 4 d after i.c. LCMV exposure. Data are expressed as the ratio of the mRNA expression compared with endogenous Actb relative to SPF controls and show mean ± s.e.m. Ten LCMV-treated and three PBS-control mice were analyzed for both housing conditions, respectively. Data are representative of two independent experiments. Significant differences were examined by an unpaired t test (*P < 0.05, **P < 0.01, ***P < 0.001). ns, not significant. P values: PBS: Tnfα, 0.5082; Il-1β, 0.5025; Ccl5, 0.7325; Cxcl10, 0.8510; Usp18, 0.8331; Irf3, 0.7942; Irf7, 0.4691; Isg15, 0.5344; Oas2, 0.0738; Msr1, 0.8069; c-Jun, 0.3162; c-Fos, 0.2778; FosB, 0.2491; Nox2, 0.3746; Csf1, 0.1224; cyclin B2, 0.1297; S100a4, 0.1463; S100a6, 0.1296; S100a8, 0.2677; S100a9, 0.4182; S100a10, 0.8502. LCMV: Tnfα, 0.0072; Il-1β, 0.0315; Ccl5, 0.9502; Cxcl10, 0.3839; Usp18, 0.0013; Irf3, 0.3887; Irf7, 0.2704; Isg15, 0.9575; Oas2, 0.9831; Msr1, 0.0579; c-Jun, 0.0042; c-Fos, 0.0016; FosB, 0.0008; Nox2, 0.0001; Csf1, 0.2828; cyclin B2, 0.0491; S100a4, 0.0415; S100a6, 0.0374; S100a8, 0.9149; S100a9, 0.9459; S100a10, 0.6775. (d,e) Three-dimensional reconstruction (scale bars represent 15 μm, d) and Imaris-based automatic quantification of cell morphometry (e) of cortical Iba-1+ microglia 4 d after i.c. LCMV exposure. Each symbol represents one mouse with at three measured cells per mouse. Six animals were analyzed per group. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (*P < 0.05, ***P < 0.001). P values: dendrite length, 0.0003; number of segments, 0.0009; number of branch points, 0.0008; number of terminal points, 0.0009; volume, 0.0234.
Figure 6. Antibiotic treatment induces immature and…
Figure 6. Antibiotic treatment induces immature and malformed microglia
(a) Left, gross morphology of cecum in untreated and antibiotic-treated (ABX) SPF mice. Ruler scale is shown. One representative picture of six investigated control and seven ABX-treated mice is shown. Right, relative cecum weight. Symbols represent individual mice. Data are presented as mean ± s.e.m. Data are representative of two independent experiments. Significant differences were determined by an unpaired t test (***P = 0.0001). (b) Immunhistochemistry for Iba-1+ parenchymal microglia (left) and quantification (right) in the cortex of seven ABX-treated and six untreated (control) SPF mice. Depicted symbols represent individual mice. Three to four sections per mouse were examined. Data are presented as mean ± s.e.m. Data are representative of two independent experiments. Scale bars represent 50 μm. (c) Expression of Ddit4 mRNA measured by qRT-PCR in microglia isolated from untreated SPF (black bar) or antibiotic-treated SPF (white bar) mice. Data are presented as mean ± s.e.m. with at six samples in each group are displayed. No significant differences were detectable by an unpaired t test. Data are representative of two independent experiments. (d,e) Three-dimensional reconstruction (scale bars represent 15 μm, d) and Imaris-based automatic quantification of cell morphometry (e) of cortical Iba-1+ microglia in five ABX-treated and six untreated mice. Each symbol represents one mouse per group with at least three measured cells per mouse. Data are presented as mean ± s.e.m. Significant differences were evaluated by an unpaired t test (*P < 0.05, ***P < 0.001). P values: dendrite length, 0.0001; number of segments, <0.0001; number of branch points, <0.0001; number of terminal points, 0.0001; volume, 0.0486. (f) Representative cytometry graphs of the maturation markers CSF1R, F4/80 and CD31 on microglia from ABX-treated mice (red lines), untreated SFP controls (blue lines) and isotype controls (gray lines). Data are representative of two independent experiments. (g) Percentages and MFI of CSF1R, F4/80 and CD31 on microglia. Each symbol represents one mouse, with six animals per group. Data are presented as mean ± s.e.m. Data are representative of two independent experiments. Significant differences were determined by an unpaired t test. F4/80 (percentage of positive cells), **P = 0.0021; F4/80 (MFI), ***P = 0.0008.
Figure 7. Only complex microbiota can restore…
Figure 7. Only complex microbiota can restore microglia insufficiency
(a) Left, macroscopical view on cecum from SFP animal (control) and an individual with altered Schaedler flora (ASF). Ruler scale is shown. Representative pictures are displayed. Right, relative cecum weight of ASF and control SPF mice. Symbols represent individual mice, with five examined mice per group. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (***P = 0.0001). Data are representative of two independent experiments. (b) Iba-1+ immunohistochemistry (left) in the cortex of ASF and control mice and quantification thereof (right). Every symbol represents one mouse. Five mice per group were investigated and three to four sections per mouse were examined. Data are presented as mean ± s.e.m. Significant differences were evaluated by an unpaired t test and marked with asterisks (*P = 0.0143). Data are representative of two independent experiments. Scale bars represent 50 μm. (c) Ddit4 mRNA measured by qRT-PCR in microglia from SPF (black bar) or ASF (white bar) mice. Data are presented as mean ± s.e.m. with at least five samples in each group. Significant differences were determined by an unpaired t test (***P = 0.0001). Data are representative of two independent experiments. (d,e) Three-dimensional reconstruction (d) of representative Iba-1+ parenchymal microglia from ASF or SPF control mice, respectively. Scale bars represent 15 μm. Automatic Imaris-based quantification of cortical microglia morphology (e) is shown. Each symbol represents one mouse per group with at least three measured cells per mouse. Five animals per group were analyzed. Data are presented as mean ± s.e.m. Significant differences were evaluated by an unpaired t test (**P < 0.01). P values: dendrite length, 0.0099; number of segments, 0.0025; number of branch points, 0.0031; number of terminal points, 0.0022. (f) Left, macroscopical view of cecum from SPF (control), ASF and recolonized ASF mice. Ruler scale is shown. Representative pictures are shown. Right, relative cecum weight of ASF, recolonized ASF and control SPF mice. Symbols represent individual mice, with five mice per group. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (*P < 0.05, ***P < 0.001). P values: SPF versus ASF, 0.0001; SPF versus ASF (recol.), 0.0008; ASF versus ASF (recol.), 0.0202. Data are representative of two independent experiments. (g) Top, immunohistochemistry for Iba-1+ in the cortex of recolonized ASF and control mice. Bottom, quantification. Three to four sections per mouse were examined. Every symbol represents one mouse, with five mice per group. Data are presented as mean ± s.e.m. (**P < 0.01). P values: SPF versus ASF, 0.0072; ASF versus ASF (recol.), 0.00250. Data are representative of two independent experiments. Scale bars represent 50 μm. (h) Quantitative measurement of Ddit4 mRNA by qRT-PCR in microglia from SPF (black bar), recolonized ASF (gray) and ASF (white bar) mice. Data are presented as mean ± s.e.m. with five samples in each group. Significant differences were determined by an unpaired t test (***P < 0.001). P values: SPF versus ASF, <0.0001; ASF versus ASF (recol.), 0.0001. Data are representative of two independent experiments. (i) Three-dimensional structure of a representative microglia cell of recolonized ASF or SPF control mice. Scale bars represent 15 μm. (j) Imaris-based morphometric measurements of cortical Iba-1+ microglia. Each symbol represents one mouse per group with three measured cells per mouse. Data are presented as mean ± s.e.m. Significant differences were evaluated by an unpaired t test (*P < 0.05, **P < 0.01). P values: dendrite length, SPF versus ASF, 0.0099; number of segments, SPF versus ASF, 0.0025; number of branch points, SPF versus ASF, 0.0031; number of terminal points, SPF versus ASF, 0.0022; ASF versus ASF (recol.), 0.0386.
Figure 8. SCFA restore microglia malformation and…
Figure 8. SCFA restore microglia malformation and immaturity in GF mice
(a) Relative cecal weight of six SPF (SPF contr.), six GF mice fed with sodium-matched water (GF contr.) or nine GF mice treated with SCFAs (GF SCFA) for 4 weeks. Symbols represent data from individual mice. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (***P < 0.001). P values: SPF (contr.) versus GF (contr.), 0.0001; SPF (contr.) versus GF (SCFA.), <0.0001. (b) CNS histology of the cerebral cortex that was subjected to immunohistochemistry for Iba-1 to detect microglia (left) and quantification (right). Scale bars represent 50 μm. Representative pictures of six examined control mice and nine SCFA-treated mice are displayed, respectively. Each symbol represents one mouse and three to four sections per mouse were examined. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (*P < 0.05). P values: SPF (contr.) versus GF (contr.), 0.0456; GF (contr.) versus GF (SCFA.), 0.0118. (c) Expression of Ddit4 mRNA measured by qRT-PCR in microglia isolated from SPF (contr.) (black bar), GF (contr.) (white bar) or GF mice treated with SCFA (gray bar). Data are presented as mean ± s.e.m. with six control samples and nine SCFA-treated samples. Significant differences were determined by an unpaired t test (*P < 0.05, **P < 0.01). P values: SPF (contr.) versus GF (contr.), 0.0064; GF (contr.) versus GF (SCFA.), 0.0306; SPF (contr.) versus GF (SCFA.), 0.0056. (d) Morphology of representative cortical microglia (scale bars represent 15 μm, d) and Imaris-based quantification of cellular parameters (e). Each symbol displays one mouse with three measured cells per animal. Six SPF and GF control animals and nine SCFA-treated GF animals were investigated. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (*P < 0.05, **P < 0.01, ***P < 0.001). P values: dendrite length SPF (contr.) versus GF (contr.), 0.0001; GF (contr.) versus GF (SCFA), 0.0008; SPF (contr.) versus GF (SCFA), 0.0247; number of segments SPF (contr.) versus GF (contr.), 0.0001; GF (contr.) versus GF (SCFA), 0.0021; number of branch points SPF (contr.) versus GF (contr.), 0.0001; GF (contr.) versus GF (SCFA), 0.0027; number of terminal points SPF (contr.) versus GF (contr.), 0.0001; GF (contr.) versus GF (SCFA), 0.0018; volume SPF (contr.) versus GF (contr.), 0.0001; GF (contr.) versus GF (SCFA), 0.0004. (f) Quantifications of the percentages of positively labeled cells and MFIs for CSF1R, F4/80 and CD31 on microglia from six SPF (contr.), six GF (contr.) and nine GF (SCFA) mice. Each symbol represents one mouse. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (*P < 0.05, **P < 0.01, ***P < 0.001). P values: CSF1R (percentage of positive cells) SPF (contr.) versus GF (contr.), 0.0094; GF (contr.) versus GF (SCFA), 0.0156; CSF1R (MFI) SPF (contr.) versus GF (contr.), 0.0076; GF (contr.) versus GF (SCFA), 0.0427; F4/80 (percentage of positive cells) SPF (contr.) versus GF (contr.), 0.0204; GF (contr.) versus GF (SCFA), 0.0367; SPF (contr.) versus GF (SCFA), 0.0002; F4/80 (MFI) SPF (contr.) versus GF (SCFA), 0.0194; CD31 (percentage of positive cells) SPF (contr.) versus GF (contr.), 0.0009; SPF (contr.) versus GF (SCFA), 0.0023. (g) Iba-1 immunhistochemistry (left) and quantification (right) of cortical sections from four FFAR2-deficient (SPF-FFAR2ko) or five competent (SPFwt) mice. Scale bars represent 50 μm. Representative pictures are displayed. Each symbol represents one mouse. Three to four sections per mouse were examined. Data are presented as mean ± s.e.m. (h,i) Imaris-based three-dimensional reconstruction of representative microglia from SPF-FFAR2ko and (SPFwt) mice (scale bars represent 15 μm) and quantification of the cellular parameters (i). Each symbol shows one mouse with at least three measured cells per animal. Four FFAR2-deficient (SPF-FFAR2ko) and five competent (SPFwt) mice were analyzed. Data are presented as mean ± s.e.m. Significant differences were determined by an unpaired t test (***P < 0.001). P values: dendrite length, 0.0007; number of segments, 0.0007; number of branch points, 0.0006; number of terminal points, 0.0008; volume, 0.0008. (j) Ffar2 mRNAs levels measured by qRT-PCR for the indicated cells and tissues, respectively. Data are expressed as ΔCT ratio of Ffar2 mRNA expression versus endogenous Actb and exhibited as mean ± s.e.m. Bar represents means ± s.e.m. with at least three samples in each group. n.d., not detectable. (k) Immunofluorescence images of FFAR2 (aqua green) on Iba-1+ (red) microglia or macrophages of wild-type mice. Asterisks indicate double-positive cells in the spleen (upper row) and FFAR2-negative microglia in the cortex (lower row) of wild-type mice. Arrows highlight FFAR2-negative endothelial cells. Nuclei were stained with DAPI (blue). Scale bars represent 50 μm.

References

    1. Ransohoff RM, Perry VH. Microglial physiology: unique stimuli, specialized responses. Annu Rev Immunol. 2009;27:119–145.
    1. Kettenmann H, Hanisch UK, Noda M, Verkhratsky A. Physiology of microglia. Physiol Rev. 2011;91:461–553.
    1. Prinz M, Priller J. Microglia and brain macrophages in the molecular age: from origin to neuropsychiatric disease. Nat Rev Neurosci. 2014;15:300–312.
    1. Schafer DP, Stevens B. Phagocytic glial cells: sculpting synaptic circuits in the developing nervous system. Curr Opin Neurobiol. 2013;23:1034–1040.
    1. Naj AC, et al. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease. Nat Genet. 2011;43:436–441.
    1. Hollingworth P, et al. Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease. Nat Genet. 2011;43:429–435.
    1. Guerreiro RJ, et al. Using exome sequencing to reveal mutations in TREM2 presenting as a frontotemporal dementia-like syndrome without bone involvement. JAMA Neurol. 2013;70:78–84.
    1. Rademakers R, et al. Mutations in the colony stimulating factor 1 receptor (CSF1R) gene cause hereditary diffuse leukoencephalopathy with spheroids. Nat Genet. 2012;44:200–205.
    1. Zhan Y, et al. Deficient neuron-microglia signaling results in impaired functional brain connectivity and social behavior. Nat Neurosci. 2014;17:400–406.
    1. Prinz M, Mildner A. Microglia in the CNS: immigrants from another world. Glia. 2011;59:177–187.
    1. Ginhoux F, et al. Fate mapping analysis reveals that adult microglia derive from primitive macrophages. Science. 2010;330:841–845.
    1. Schulz C, et al. A lineage of myeloid cells independent of Myb and hematopoietic stem cells. Science. 2012;336:86–90.
    1. Kierdorf K, et al. Microglia emerge from erythromyeloid precursors via Pu.1- and Irf8-dependent pathways. Nat Neurosci. 2013;16:273–280.
    1. Yona S, et al. Fate mapping reveals origins and dynamics of monocytes and tissue macrophages under homeostasis. Immunity. 2013;38:79–91.
    1. Goldmann T, et al. A new type of microglia gene targeting shows TAK1 to be pivotal in CNS autoimmune inflammation. Nat Neurosci. 2013;16:1618–1626.
    1. Prinz M, Tay TL, Wolf Y, Jung S. Microglia: unique and common features with other tissue macrophages. Acta Neuropathol. 2014;128:319–331.
    1. Grenham S, Clarke G, Cryan JF, Dinan TG. Brain-gut-microbe communication in health and disease. Front Physiol. 2011;2:94.
    1. Gaspar P, Cases O, Maroteaux L. The developmental role of serotonin: news from mouse molecular genetics. Nat Rev Neurosci. 2003;4:1002–1012.
    1. Diaz Heijtz R, et al. Normal gut microbiota modulates brain development and behavior. Proc Natl Acad Sci USA. 2011;108:3047–3052.
    1. Bercik P, et al. The intestinal microbiota affect central levels of brain-derived neurotropic factor and behavior in mice. Gastroenterology. 2011;141609:599–609.
    1. Dorrestein PC, Mazmanian SK, Knight R. Finding the missing links among metabolites, microbes, and the host. Immunity. 2014;40:824–832.
    1. Kamada N, Seo SU, Chen GY, Nunez G. Role of the gut microbiota in immunity and inflammatory disease. Nat Rev Immunol. 2013;13:321–335.
    1. Round JL, Mazmanian SK. The gut microbiota shapes intestinal immune responses during health and disease. Nat Rev Immunol. 2009;9:313–323.
    1. Markle JG, et al. gammadelta T cells are essential effectors of type 1 diabetes in the nonobese diabetic mouse model. J Immunol. 2013;190:5392–5401.
    1. Wu HJ, et al. Gut-residing segmented filamentous bacteria drive autoimmune arthritis via T helper 17 cells. Immunity. 2010;32:815–827.
    1. Berer K, et al. Commensal microbiota and myelin autoantigen cooperate to trigger autoimmune demyelination. Nature. 2011;479:538–541.
    1. Reikvam DH, et al. Depletion of murine intestinal microbiota: effects on gut mucosa and epithelial gene expression. PLoS ONE. 2011;6:e17996.
    1. Kierdorf K, Prinz M. Factors regulating microglia activation. Front Cell Neurosci. 2013;7:44.
    1. Sofer A, Lei K, Johannessen CM, Ellisen LW. Regulation of mTOR and cell growth in response to energy stress by REDD1. Mol Cell Biol. 2005;25:5834–5845.
    1. Hickman SE, et al. The microglial sensome revealed by direct RNA sequencing. Nat Neurosci. 2013;16:1896–1905.
    1. Chiu IM, et al. A neurodegeneration-specific gene-expression signature of acutely isolated microglia from an amyotrophic lateral sclerosis mouse model. Cell Reports. 2013;4:385–401.
    1. Butovsky O, et al. Identification of a unique TGF-beta–dependent molecular and functional signature in microglia. Nat Neurosci. 2014;17:131–143.
    1. Greter M, et al. Stroma-derived interleukin-34 controls the development and maintenance of langerhans cells and the maintenance of microglia. Immunity. 2012;37:1050–1060.
    1. Khosravi A, et al. Gut microbiota promote hematopoiesis to control bacterial infection. Cell Host Microbe. 2014;15:374–381.
    1. Prinz M, et al. Microglial activation by components of gram-positive and -negative bacteria: distinct and common routes to the induction of ion channels and cytokines. J Neuropathol Exp Neurol. 1999;58:1078–1089.
    1. Cunningham C, Wilcockson DC, Campion S, Lunnon K, Perry VH. Central and systemic endotoxin challenges exacerbate the local inflammatory response and increase neuronal death during chronic neurodegeneration. J Neurosci. 2005;25:9275–9284.
    1. Stecher B, et al. Like will to like: abundances of closely related species can predict susceptibility to intestinal colonization by pathogenic and commensal bacteria. PLoS Pathog. 2010;6:e1000711.
    1. Schaedler RW, Dubos RJ. The fecal flora of various strains of mice. Its bearing on their susceptibility to endotoxin. J Exp Med. 1962;115:1149–1160.
    1. Bindels LB, Dewulf EM, Delzenne NM. GPR43/FFA2: physiopathological relevance and therapeutic prospects. Trends Pharmacol Sci. 2013;34:226–232.
    1. Smith PM, et al. The microbial metabolites, short-chain fatty acids, regulate colonic Treg cell homeostasis. Science. 2013;341:569–573.
    1. Chu H, Mazmanian SK. Innate immune recognition of the microbiota promotes host-microbial symbiosis. Nat Immunol. 2013;14:668–675.
    1. Clarke G, et al. The microbiome-gut-brain axis during early life regulates the hippocampal serotonergic system in a sex-dependent manner. Mol Psychiatry. 2013;18:666–673.
    1. Fiedler K, Kokai E, Bresch S, Brunner C. MyD88 is involved in myeloid as well as lymphoid hematopoiesis independent of the presence of a pathogen. Am J Blood Res. 2013;3:124–140.
    1. Kawai T, Akira S. The roles of TLRs, RLRs and NLRs in pathogen recognition. Int Immunol. 2009;21:317–337.
    1. Deshmukh HS, et al. The microbiota regulates neutrophil homeostasis and host resistance to Escherichia coli K1 sepsis in neonatal mice. Nat Med. 2014;20:524–530.
    1. Borre YE, et al. Microbiota and neurodevelopmental windows: implications for brain disorders. Trends Mol Med. 2014;20:509–518.
    1. Braniste V, et al. The gut microbiota influences blood-brain barrier permeability in mice. Sci Transl Med. 2014;6:263ra158.
    1. Schéle E, et al. The gut microbiota reduces leptin sensitivity and the expression of the obesity-suppressing neuropeptides proglucagon (Gcg) and brain-derived neurotrophic factor (Bdnf) in the central nervous system. Endocrinology. 2013;154:3643–3651.
    1. Perez-Burgos A, et al. Psychoactive bacteria Lactobacillus rhamnosus (JB-1) elicits rapid frequency facilitation in vagal afferents. Am J Physiol Gastrointest Liver Physiol. 2013;304:G211–G220.
    1. Giovanoli S, et al. Stress in puberty unmasks latent neuropathological consequences of prenatal immune activation in mice. Science. 2013;339:1095–1099.
    1. Conrad ML, et al. Maternal TLR signaling is required for prenatal asthma protection by the nonpathogenic microbe Acinetobacter lwoffii F78. J Exp Med. 2009;206:2869–2877.
    1. Dann A, et al. Cytosolic RIG-I-like helicases act as negative regulators of sterile inflammation in the CNS. Nat Neurosci. 2012;15:98–106.
    1. Mildner A, et al. Microglia in the adult brain arise from Ly-6C(hi)CCR2(+) monocytes only under defined host conditions. Nat Neurosci. 2007;10:1544–1553.
    1. Raasch J, et al. I{kappa}B kinase 2 determines oligodendrocyte loss by non-cell-autonomous activation of NF-{kappa}B in the central nervous system. Brain. 2011;134:1184–1198.
    1. Jaitin DA, et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science. 2014;343:776–779.
    1. Cahenzli J, Koller Y, Wyss M, Geuking MB, McCoy KD. Intestinal microbial diversity during early-life colonization shapes long-term IgE levels. Cell Host Microbe. 2013;14:559–570.
    1. Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4:44–57.
    1. Eden E, Navon R, Steinfeld I, Lipson D, Yakhini Z. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics. 2009;10:48.
    1. Eden E, Lipson D, Yogev S, Yakhini Z. Discovering motifs in ranked lists of DNA sequences. PLoS Comput Biol. 2007;3:e39.
    1. Herz J, et al. Acid sphingomyelinase is a key regulator of cytotoxic granule secretion by primary T lymphocytes. Nat Immunol. 2009;10:761–768.

Source: PubMed

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