Abstract
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Dectin-1 limits autoimmune neuroinflammation and promotes myeloid cell-astrocyte crosstalk via Card9-independent expression of Oncostatin M
SUMMARY
Pathologic roles for innate immunity in neurologic disorders are well-described, but their beneficial aspects are less understood. Dectin-1, a C-type lectin receptor (CLR), is largely known to induce inflammation. Here we report that Dectin-1 limited experimental autoimmune encephalomyelitis (EAE), while its downstream signaling molecule, Card9, promoted the disease. Myeloid cells mediated the pro-resolution function of Dectin-1 in EAE with enhanced gene expression of the neuroprotective molecule, Oncostatin M (Osm), through a Card9-independent pathway, mediated by the transcription factor NFAT. Furthermore, we found that the Osm receptor (OsmR) functioned specifically in astrocytes to reduce EAE severity. Notably, Dectin-1 did not respond to heat-killed Mycobacteria, an adjuvant to induce EAE. Instead, endogenous Dectin-1 ligands, including galectin-9, in the central nervous system (CNS) were involved to limit EAE. Our study reveals a mechanism of beneficial myeloid cell-astrocyte crosstalk regulated by a Dectin-1 pathway and identifies potential therapeutic targets for autoimmune neuroinflammation.
eTOC BLURB
Pattern recognition receptor signaling can regulate neuroinflammation in animal model of Multiple Sclerosis (MS). Deerhake et al. now show that Dectin-1 promotes beneficial myeloid cell-astrocyte cross talk in EAE by upregulating Oncostatin M through a Card9-independent pathway.
INTRODUCTION
The innate immune response contributes to both damage and repair in central nervous system (CNS) autoimmunity, and pattern recognition receptors (PRRs) are key to orchestrating innate immune responses (Deerhake et al., 2019; Dendrou et al., 2015). Among PRRs, the C-type lectin receptor (CLR) family, including Dectin-1, has been studied mainly in fungal infections and remains less characterized in sterile inflammation and autoimmune disorders, including multiple sclerosis (MS) (Deerhake et al., 2019). Dectin-1 induces interleukin-1β (IL-1β) and resulting T helper-17 (Th17) cell responses during fungal infections via Card9/− and NFκB signaling (Gross et al., 2006; LeibundGut-Landmann et al., 2007). Although Dectin-1 is known as a receptor for fungal β-glucans (Taylor et al., 2007), some studies have identified host-derived endogenous ligands for Dectin-1, as well as functions of Dectin-1 signaling beyond the setting of fungal infections (Bode et al., 2019; Daley et al., 2017; Roesner et al., 2019; Shan et al., 2013; Thiagarajan et al., 2013). Notably, in one (Stoppelkamp et al., 2015) of three reports (Brown et al., 2017; Lee et al., 2016) of experimental autoimmune uveitis (EAU), Dectin-1 has been found to be detrimental. Dectin-1 also appears to be pathogenic in animal models of spinal cord injury (Gensel et al., 2015) and stroke (Ye et al., 2020). Nevertheless, the function of Dectin-1 in CNS disorders may depend on the type of neuropathology, and the role of Dectin-1 in autoimmunity and neuroinflammation is still largely unexplored.
Given the well-described pro-inflammatory functions of Dectin-1 signaling, one may predict that Dectin-1 would exacerbate neuroinflammation in the EAE model of multiple sclerosis (MS). However, the present study demonstrates that Dectin-1 signaling in myeloid cells limits neuroinflammation and EAE severity, although a major Dectin-1 signaling molecule, Card9, promotes disease development. We found that Card9-independent Dectin-1 signaling involving the transcription factor NFAT, drove expression of Oncostatin M (Osm), an IL-6 family cytokine with neuroprotective functions (Janssens et al., 2015; Slaets et al., 2014; Wallace et al., 1999), and signaling through the Osm receptor (OsmR) on astrocytes reduced disease progression and promoted recovery in EAE. Furthermore, we identified a Card9-independent Dectin-1-mediated transcriptional program driving expression of Osm and other neuroprotective genes. Our findings provoke a re-consideration of Dectin-1 signaling and functions by identifying a mechanism of beneficial myeloid cell-astrocyte communication in CNS autoimmunity.
RESULTS
Elevated gene expression of the C-type lectin receptor, Dectin-1 (CLEC7A) are evident in MS lesions
We evaluated gene expression of CLRs in multiple datasets profiling MS brain lesions (GSE10800, GSE123496). Among genes encoding CLRs with known immune functions, CLEC7A (Dectin-1) and CLEC4A (DCIR) were notable for their elevated expression in MS brain specimens in two independent datasets (Fig. S1A–C)(Hendrickx et al., 2017; Voskuhl et al., 2019), suggesting possible involvement of Dectin-1 and DCIR in MS. In EAE, DCIR has been reported to be protective (Seno et al., 2015; Uto et al., 2016) but the function of Dectin-1 in autoimmune neuroinflammation remains unknown.
Dectin-1 is a beneficial C-type lectin receptor in EAE
Next, we sought to test the function of Dectin-1 in CNS autoimmunity using EAE induced with the MOG35–55 autoantigen peptide. We initially hypothesized that Dectin-1 may exacerbate EAE severity by promoting IL-1β expression and Th17 cell differentiation, given its known role in antifungal immunity (Gross et al., 2006; LeibundGut-Landmann et al., 2007) and the pathogenicity of Th17 cells in EAE development. Instead, we found that Dectin-1-deficient (Clec7a−/−) mice developed more severe disease than WT mice (Fig. 1A). A mild EAE induction with a reduced amount of adjuvant also showed the beneficial effect of Dectin-1 (Fig. 1B). Next, we tested whether administering a Dectin-1 agonist was sufficient to limit EAE severity. To test this, we used hot alkali-depleted zymosan (d-zymosan), which is specific to Dectin-1 but does not stimulate Toll-like receptor-2 (TLR2) (Ikeda et al., 2008). d-zymosan has an advantage over curdlan, another Dectin-1-specific ligand, for safe intravenous (i.v.) use in EAE possibly due to zymosan’s smaller particle size. We did not observe complication by injecting d-zymosan, although a majority of mice died by curdlan i.v. injection (unpublished data). Indeed, a single i.v. injection of d-zymosan on one day post-immunization (dpi) inhibited EAE development (Fig. 1C). Together, these results indicate that Dectin-1 limits EAE severity.
(A-C) EAE clinical scores (left panels) and AUC (right panels) for statistical analysis. Comparison between WT and Clec7a−/− mice using standard immunization (200 μg hkMtb/mouse) with n=7 mice/group (A) or reduced adjuvant immunization (50 μg hkMtb/mouse) with n=4 WT and n=5 Clec7a−/− mice/group (B). Comparison of WT mice receiving either hot alkali-depleted zymosan (dz) (500μg/mouse)(n=10) or PBS (n=9) i.v. at 1-dpi with standard immunization (C). Data representative of >3 independent experiments (A) or 2 independent experiments each (B, C). (D) Numbers of Th cell subsets in ILN between WT and Clec7a−/− mice at 9-dpi. Data representative of 3 independent experiments. (E, F) Total cell numbers (E) and numbers of indicated cell types (F) in spinal cord at 9-dpi. The main effect of genotype (WT < Clec7a−/−) (**) by 2-factor RM-ANOVA indicated in (F). Data are combined from three independent experiments. One datapoint denotes a result from one mouse (D-F). (G) LFB-PAS staining of lumbar SC in WT and Clec7a−/− mice at EAE 17-dpi. Scale 100 μm. Representative images from 10 mice/group combined from two independent experiments. Please also see Figures S1, 2.
Dectin-1 limits CNS inflammation in EAE
To determine how Dectin-1 regulates EAE, we evaluated immune cell subsets by flow cytometry in secondary lymphoid organs and in the spinal cord (SC) of WT and Clec7a−/− mice. Both groups showed no significant difference in numbers of various cell types in spleen and lymph node (LN) at 9-dpi (Fig. S1D–I). Additionally, no major effect on CD4+ T cell phenotypes by Dectin-1 was suggested based on numbers of regulatory T (Treg), Th1, Th17, or granulocyte macrophage colony stimulating factor (GM-CSF)+ Th cells, MOG recall responses, and IL-10 production by CD25+CD4+ T cells (Fig. 1D, Fig. S1J–L). Similarly, d-zymosan did not impact total cell numbers and the cellularity of various T helper cells, myeloid cell numbers, and ex vivo T cell recall response (Fig S2A–F). In summary, we did not observe substantial effects of Dectin-1 on the peripheral immune response that would explain the elevated disease severity in Clec7a−/− mice.
In contrast to the phenotype in the periphery, Clec7a−/− mice had elevated immune cell infiltration in the SC at 9-dpi across multiple immune cell subsets (Fig. 1E, ,F),F), suggesting that Dectin-1 broadly limited inflammation in the SC during EAE. Notably, CNS myeloid cells from Clec7a−/− mice did not show elevated surface expression of CD40, CD80, or CD86, suggesting no major alteration in myeloid cell activation (Fig. S2G). We also observed increased demyelination in SCs of Clec7a−/− mice by Luxol fast blue/periodic acid-Schiff (LFB-PAS) staining (Fig. 1G; Fig. S2H). Together, this demonstrates that Dectin-1 limits CNS inflammation during EAE.
To test whether Dectin-1 reduces immune cell migration to the CNS in a cell-intrinsic manner, we generated mixed bone-marrow (BM) chimeras reconstituted with both WT and Clec7a−/− BM cells (Fig. S2I, J). Following EAE induction, the relative proportion of CD11b+ myeloid cells derived from WT and Clec7a−/− BM cells were comparable in the spleen and the SC (Fig. S2K), suggesting Dectin-1 does not limit myeloid cell infiltration into the CNS in a cell-intrinsic manner. In summary, Dectin-1 decreased neuroinflammation in EAE, but this effect was not attributable to altered T helper cell polarization, CNS myeloid cell activation, or cell-intrinsic defects in myeloid cell migration into the CNS.
Card9 exacerbates EAE and promotes Th17 cell responses
Next, we evaluated the role of Card9, a major mediator of Dectin-1 signaling, in EAE. As expected, Card9−/− mice developed alleviated disease than WT controls (Fig. 2A), indicating that Card9, unlike Dectin-1, is pathogenic in EAE. Next, we used a BM chimera system to test whether immune cells were sufficient to mediate Card9 function in EAE. Indeed, recipients reconstituted with Card9−/− BM cells were resistant to EAE development, indicating that BM-derived immune cells are responsible for Card9 function (Fig. 2B).
(A) EAE clinical scores (left panel) and AUC (right panel) for statistical analysis. Comparison between WT (n=9) and Card9−/− (n=8) mice. Data are combined from two independent experiments. (B) EAE clinical scores from BM chimeras. WT BM cells were transferred to irradiated WT (white) or Card9−/−(gray) recipients. Another group is Card9−/− BM transferred to WT recipients (orange). n=7–13 mice/group, combined from three independent experiments. (C-G) Leukocytes in peripheral lymphoid organs at 9-dpi EAE. Representative flow cytometry plots for intracellular cytokine staining (C) and frequency of Th cell subsets in ILN (D, E). Numbers of indicated cell types in spleen (F, G). One datapoint denotes a result from one mouse. Data are combined from three independent experiments. Please also see Figure S3.
Not only did Card9 and Dectin-1 show divergent functions in EAE, the immune cell profile of Card9−/− mice in EAE was also clearly distinct from that of Clec7a−/− mice, particularly regarding T cell phenotypes. In Card9−/− mice, numbers of IL-17+IFNγ+ Th cells were reduced in inguinal lymph nodes (ILNs) and CD25+CD4+ T cells had enhanced ability to produce IL-10 ex vivo, while no differences were found in Treg cell numbers and T cell recall responses difference (Fig. 2 C–E; Fig. S3A–D). Numbers of neutrophils were also reduced in Card9−/− mice in the spleen (Fig. 2F). Although numbers of other individual cell types did not reach statistical significance, total cell numbers were reduced in the periphery of Card9−/− mice at 9-dpi (Fig. 2F, ,G;G; Fig. S3E–G). In summary, although Dectin-1 limits EAE, Card9 is pathogenic particularly with an enhanced encephalitogenic T cells and neutrophils.
Peripheral and CNS-resident myeloid cells express Dectin-1 in EAE
We next evaluated Dectin-1 expression under naïve and EAE conditions. Dectin-1 was expressed on neutrophils, monocytes, macrophages, and DCs in the spleen under naïve and EAE conditions, but not on T and B cells (Fig. 3A; Fig. S4A). During EAE, neutrophils and monocytes were the predominant Dectin-1-expressing cell types in the spleen (Fig. 3B). In the SC of EAE mice, Dectin-1+ cells were identified in white matter and co-localized with CD11b antibody staining signal, indicative of myeloid cells (Fig. 3C). Particularly for Iba1+ cells, Dectin-1 expression was more intensive in Iba1+ cells with amoeboid morphology than those with ramified morphology (Fig. S4B). Immunofluorescent (IF) histology did not show Dectin-1 expression by Tmem119+ microglia (Fig. S4C), but flow-cytometry did detect upregulation of Dectin-1 expression in microglia (Tmem119+CD11bloCD45lo) during EAE (Fig. S4D; Fig. 3D). Nevertheless, CNS-infiltrated myeloid cells had higher Dectin-1 expression than microglia did even in EAE mice (Fig. 3D).
(A) Flow cytometry histograms, indicating Dectin-1 expression in splenic neutrophils (CD11b+Ly6G+), monocytes (CD11b+Ly6C+Ly6G−), macrophages (CD11b+F4/80hi), and DCs (CD11b+CD11c+) from naïve and EAE 9-dpi WT mice. (B) Frequency of myeloid cell subsets in total splenocytes in naïve (n=7) and EAE 9-dpi (n=8) mice. Data are combined from 2 independent experiments. (C) Localization of Dectin-1 expressing cells with CD11b counter-staining in the lumbar SC of naïve and EAE 17-dpi mice. Bottom panels are enlarged images of regions indicated with squares in top panels. Scale 100 μm in upper panels and 25 μm in lower panels. (D) Flow cytometry histograms of Dectin-1 expression in microglia (CD11bloCD45loTmem119+), neutrophils (CD11b+Ly6G+), and monocytes (CD11b+Ly6G−Ly6C+) in SC from naïve and EAE 16-dpi mice. Representative data from two independent experiments. (E, F) EAE scores (left panels) and AUC for statistical analysis (right panels) of irradiation BM chimeras. WT or Clec7a−/− BM cells into irradiated WT recipients (n=9 for both groups) (E). WT BM into WT or Clec7a−/− recipients using (n=13 for both groups) (F). Data are combined from two independent experiments each. Please also see Figure S4.
Cells of hematopoietic origin mediate Dectin-1 function in EAE
To evaluate the contribution of hematopoietic-derived cells, we used a BM chimera approach. Specifically, we generated BM chimeras by adoptively transferring BM cells from Clec7a−/− or WT donor mice to WT recipients (Fig. S4E) or by transferring BM cells from WT donor mice to Clec7a−/− or WT recipients. Chimeras that received Clec7a−/− BM cells exhibited more severe disease than chimeras which received WT BM cells (Fig. 3E). Without Dectin-1 expression by lymphoid cells (Fig. S4A), this result demonstrates that hematopoietic-derived myeloid cells are likely to mediate the effect of Dectin-1 in limiting EAE. In reciprocal experiments with WT BM cell transfer, no difference was found between Clec7a−/− and WT recipients (Fig. 3F), suggesting that radiation-resistant cells, including microglia, were less likely to mediate the negative regulatory function of Dectin-1. Although the irradiation BM chimera approach does not fully rule out the involvement of microglia (Larochelle et al., 2016), the results strongly suggest that hematopoietic-derived myeloid cells mediate the Dectin-1 function in EAE.
Dectin-1 promotes expression of neuroprotective cytokine, Oncostatin M (Osm)
Previous studies suggest that some CNS-infiltrating myeloid cells could have protective functions in CNS injury and repair (Gadani et al., 2015; Stirling et al., 2009). Thus, we wondered whether the beneficial role of Dectin-1 could be mediated by neuroprotective factors expressed by myeloid cells. To investigate this, we used splenic CD11b+ myeloid cells for initial examination with the Dectin-1-specific agonist, curdlan. Among the candidate genes, encoding secreted proteins with neuroprotective functions, curdlan potently upregulated the expression of Osm (Fig. S4F), a multi-functional IL-6 family cytokine with neuroprotective roles in different CNS disorders (Guo et al., 2015; Houben et al., 2019; Janssens et al., 2015; Slaets et al., 2014). In addition to CD11b+ splenocytes, primary neutrophils, monocytes, and BM-derived DCs (BMDCs) upregulated Osm expression (Fig. 4A, ,B).B). Upregulation of Osm protein by curdlan stimulation was confirmed in supernatants of neutrophil cell culture, as well as neutrophil cell lysates (Fig. S4G).
(A, B) Osm mRNA expression in indicated myeloid cell types with ex vivo curdlan (100 μg/ml) stimulation for 3 hrs. Evaluated are flow-cytometry sorted BM monocytes (CD11b+Ly6ChiLy6G−) and neutrophils (CD11b+Ly6G+) (A), as well as GM-CSF-derived BMDCs and M-CSF-derived BMDM (B). Post-hoc Sidak test following 2-factor ANOVA indicated in (A, B). Mean ± SEM shown. Data are combined from two independent experiments. (C, D) Analyses of myeloid cells from SC and brain of EAE mice at 30-dpi. Gating of CD11bloCD45lo and CD11bhiCD45hi cells from and evaluation for Dectin-1 expression by flow cytometry (C). Gated cells in (C) were flow cytometry sorted, stimulated with curdlan (100μg/ml) for 3 hr ex vivo, and amounts of Osm mRNA were evaluated by RT-qPCR (D). Samples pooled from 2 mice each. Representative of 2 independent experiments. (E) Representative images from two independent experiments of RNAscope in situ hybridization (ISH) of Osm mRNA in the lumbar SC of WT naïve and EAE 17-dpi mice. Scale bars, 100 μm in main panels, 10 μm in inset. (F) Region-specific quantification of Osm mRNA signal per hpf (sum of integrated density) in lumbar SC regions from WT naïve and EAE 17-dpi mice using n=4 mice/group, analyzed by 2-factor ANOVA of log-transformed data with post-hoc Sidak test shown. Representative of two independent experiments. (G) Representative images from two independent experiments of combined ISH of Osm mRNA and CD11b staining in the ventrolateral white matter of lumbar SC from WT and Clec7a−/− mice at 17-dpi EAE. Scale bars, 100 μm in main panels, 10 μm in inset. (H) Quantification of mean Osm mRNA puncta per CD11b+ cell. One datapoint denotes a result from one mouse. Mean ± SEM. Data from two independent experiments. (I, J) Evaluation of Osm mRNA expression in CNS myeloid cell subsets at 20-dpi EAE by PrimeFlow. Quantification of Osm MFI (I) and representative histograms of Osm expression (J). One datapoint denotes a result from one mouse. Data from two independent experiments. Please also see Figure S4.
We next evaluated whether microglia could also upregulate Osm upon curdlan stimulation. Because of little Dectin-1 expression in microglia from naïve mice (Fig. 3D), we isolated Dectin-1-expressing microglia from EAE mice by flow-cytometry sorting CD11bloCD45lo cells, together with CNS-infiltrated myeloid cells (CD11bhiCD45hi), from WT EAE mice and stimulated them with curdlan. While CNS-infiltrated myeloid cells showed potent upregulation of Osm, microglia had a more muted response despite expressing Dectin-1 (Fig. 4 C, ,D).D). These results suggest that Dectin-1 signaling drives Osm expression in a cell-type-specific manner, whereby microglia show a more limited response than neutrophils, monocytes, and BM-derived dendritic cells (BMDC)s.
Osm expression is upregulated in the CNS during EAE
Osm protein expression is detected in MS lesions by histology (Ruprecht et al., 2001) and in culture supernatant of peripheral blood mononuclear cells (PBMCs) from MS patients (Ensoli et al., 2002). In EAE, we found an increase in serum Osm protein in WT EAE mice at 9-dpi, compared to WT naïve mice, while amounts of serum Osm protein in Clec7a−/− mice showed a slight but not statistically significant reduction at 9-dpi (Fig. S4J). Next, we sought to examine in situ Osm expression in the CNS during EAE. Because antibody (Ab) staining for Osm, a secreted cytokine, was diffuse and challenging to quantify in a cell-specific manner, we used RNAscope in situ mRNA hybridization to examine Osm expression in the CNS. SC from EAE mice at 17-dpi showed drastically increased Osm mRNA expression, observed particularly in ventral and lateral white matter lesions with corresponding DAPI-staining, reflecting peripheral cell infiltration (Fig. 4E, ,F).F). CD11b+ cells are a substantial but not exclusive source of Osm mRNA in white matter lesions (Fig. 4G, S4K). Clec7a−/− mice with 17-dpi EAE had reduced Osm mRNA expression in CD11b+ cells (Fig. 4H), although no significant difference was found in total SC homogenates (Fig. S4L). This suggests a local effect of Osm around myeloid cells, which are particularly responsible for Dectin-1-mediated Osm expression.
To determine which CNS myeloid cells express Osm during EAE at the single-cell level, we re-analyzed publicly available scRNAseq data from CNS myeloid cells in naïve and EAE conditions (GSE118948) (Fig. S4N, O). Neutrophils, monocytes, and microglia highly express both Osm and Clec7a during EAE (Fig. S4P, Q). Thus, we sought to confirm the results by PrimeFlow RNA assay, flow-cytometry based in situ hybridization. In Clec7a−/− mice, neutrophils showed a statistically significant reduction in Osm expression (p<0.01), while monocytes in Clec7a−/− mice showed a trend toward reduced Osm expression (p=0.06) (Fig. 4I, ,J).J). Osm expression by microglia and DCs were not altered between WT and Clec7a−/− mice (Fig. 4I). Based on these findings, we conclude that neutrophils and, to a lesser extent, monocytes contribute to Osm expression induced by Dectin-1 in the CNS during EAE.
Card9-independent signaling promotes distinct Dectin-1 effector functions
Next, we investigated how Osm expression was enhanced by Dectin-1. Although Card9 is a critical signaling molecule downstream of Dectin-1, we found that Card9 was dispensable for Osm expression (Fig. 5A, Fig. S5A). Given the divergent functions for Card9 and Dectin-1 in EAE development (Fig. 1, ,2),2), we hypothesize that Card9-independent signaling may activate a Dectin-1-mediated transcriptional program with distinct beneficial functions, as seen in driving Osm expression.
(A) Osm mRNA expression in BM neutrophils from WT, Clec7a−/−, and Card9−/− mice. Neutrophils were treated with or without curdlan (100 μg/ml) ex vivo for 3 hrs. Mean ± SEM, n=3 mice/group. Representative of 3 independent experiments. (B-G) RNAseq analyses of BM neutrophils from WT and Card9−/− mice (n=3 mice/group) treated with or without curdlan (100 μg/ml) ex vivo for 3 hrs. Proportions of genes which are up- or down-regulated in a Card9-dependent manner, in WT neutrophils with curdlan stimulation (B). Ratio of gene expression fold-change, comparing WT and Card9−/− (KO) neutrophils, with curdlan stimulation (points indicate individual genes) (C). Gene-concept network based on RNAseq results, showing pathway enrichment analysis (D, F). Heatmaps of selected genes with indicated associated pathways (E, G). Card9-dependent and -independent candidate genes are indicated in (D, E) and (F, G), respectively. (H, I) Plots of adjusted p-values for TF binding site enrichment near Card9-dependent genes (H) or Card9-independent genes (I). NFAT family and NFκB family TFs are indicated in turquoise and orange, respectively. (J) Venn diagram of genes with at least 3 predicted NFκB or NFAT binding sites in OCRs within 100 kb of each gene. (K) Schematic of Dectin-1 signaling with small molecule inhibitors. (L) RT-qPCR evaluation of Osm mRNA in WT BM neutrophils pre-treated with inhibitors at the indicated doses for 1 hr before curdlan stimulation (100 μg/ml) for 3 hrs. Data representative of 2 independent experiments. (M) Schematic of small molecule targets. (N, O) Osm mRNA in WT BM neutrophils stimulated with curdlan (100 μg/ml) for 3hrs after 1 hr pretreatment indicated small molecules (N), or with ionomycin (O). Data representative of two independent experiments (L, N, O). Please also see Figure S5.
To further characterize the Card9-independent Dectin-1-mediated transcriptional program, we focused on neutrophils, because neutrophils are among the most abundant myeloid cells in the CNS during EAE (Caravagna et al., 2018), limit late-stage EAE (Knier et al., 2018), can be neuroprotective (Sas et al., 2020), and contribute to Dectin-1-dependent Osm expression in SC of EAE mice (Fig. 4I, ,J).J). RNA sequencing was performed with neutrophils treated with or without curdlan for 3-hrs. We first identified 1,157 genes which were upregulated or downregulated by Dectin-1 stimulation in WT neutrophils (Fig. 5B). Among those genes, 567 genes were regulated by a Card9-independent manner (Fig. 5C). Pathway analyses revealed that Card9-dependent genes showed enrichment in pathways for pro-inflammatory factors, such as TLR signaling, MyD88 signaling, and IL-1 signaling (Fig. 5D, ,E).E). In contrast, Card9-independent genes were enriched in pathways including iron uptake and processing, lysosome and Golgi vesicle biogenesis, glycolysis, cellular response to stress, and interleukin signaling (Fig. 5F, ,G).G). Osm was among the Card9-independent genes found in the interleukin signaling pathway, which includes both neuroprotective factors and negative regulators of pro-inflammatory signaling, such as an inhibitor of TLR signaling (Tollip), an inhibitor of NFκB signaling (Nfkbib), and the decoy receptor for IL-1 (Il1r2) (Fig. 5G). Other Card9-independent genes besides Osm with reported neuroprotective functions in EAE, include Csf1 (Wlodarczyk et al., 2018), Cd93 (Griffiths et al., 2018), and Vegfa (Stanojlovic et al., 2016) (Fig. 5G). The RNAseq results were confirmed by RT-qPCR (Fig. S5B). In addition to neutrophils, Card9-independent gene expression by Dectin-1 stimulation was confirmed in monocytes, macrophages, and DCs to an extent depending on cell-type (Fig. S5C, D). In summary, Card9-independent Dectin-1 signaling drives expression of Osm and other genes encoding neuroprotective molecules in multiple myeloid cell types.
NFAT mediates Card9-independent upregulation of Osm by Dectin-1
Next, we looked for enrichment of predicted transcription factor (TF)-binding sites near Dectin-1-regulated gene loci by focusing on open chromatin regions (OCRs) in BM neutrophils using publicly available ATAC-seq data from the Immunological Genome (ImmGen) Project. We first found that NFκB-family TF-binding sites were enriched in Card9-dependent genes but not in Card9-independent genes (Fig. 5H, ,I).I). In contrast, NFAT-family TF-binding sites were enriched in Card9-independent genes, and Card9-dependent genes showed some degree of enrichment (Fig. 5H, ,I).I). While we do not rule out the involvement of NFκB signaling in Osm regulation, no predicted NFκB-family TF binding sites were identified in OCRs near Osm (Fig. 5J). Instead, OCRs in the Osm gene had multiple predicted NFAT-binding sites in both neutrophils and monocytes (Fig. S5E). Previous studies have shown that Dectin-1 can indeed induce NFAT activity through the Syk-PLCγ-Ca2+ signaling axis (Goodridge et al., 2007; Xu et al., 2009), but the transcriptional program downstream of this pathway remains less characterized compared to Card9 signaling.
Next, we used small molecule inhibitors to target signaling pathways downstream of Dectin-1 (Fig. 5K). Although inhibition of Raf1 did not block Osm upregulation by curdlan stimulation in neutrophils, inhibitors of Syk and NFAT did (Fig. 5L). Both inhibitors showed dose-dependent effects (Fig. 5L), and neither resulted in detectable cellular toxicity, suggesting that Dectin-1 enhances Osm expression via Syk and NFAT. Other genes, such as Csf1 and Vegfa, behaved as Osm did, but some Card9-independent genes, such as Cd93, did not require NFAT for upregulation (Fig. S5F). Furthermore, interfering with NFAT signaling by inhibiting phospholipase C (PLC) and calcineurin (CaN) blocked Osm upregulation (Fig. 5M, ,N),N), indicating that CaN and PLC are involved. Reciprocally, ionomycin upregulated Osm expression even in the absence of curdlan stimulation (Fig. 5O), suggesting increased intracellular calcium is sufficient for Osm upregulation. These findings demonstrate that Dectin-1 signaling induces Osm expression through a Card9-independent pathway, which includes Syk, PLC, Ca2+, CaN, and NFAT.
OsmR expressed on astrocyte limits EAE severity
Next, we sought to identify which cell types express OsmR. Astrocytes (GFAP+, ALDHL1L-eGFP+), and neurons (Neurofilament+) to a lesser extent, in SC white matter expressed OsmR under naïve and EAE conditions (Fig. 6A–C; Fig. S6A, B). In contrast, we could not detect OsmR on oligodendrocytes, microglia, or CD45+ immune cells (Fig. 6D–F). Furthermore, re-analysis of a published dataset (GSE100330) confirmed that Osmr expression is enriched in astrocytes compared to total CNS tissue in EAE SC (Fig S6C, D). Thus, while other CNS cell types have been reported to express OsmR (endothelial cells, microglia, neurons, oligodendrocytes), we focused our investigation on OsmR function in astrocytes given their high expression of Osmr mRNA (Fig. S6C) and protein (Fig. 6A, ,B).B). Osmrfl/fl mice were cryorecovered, backcrossed to the B6 background by a speed congenic approach, and crossed to generate Gfapcre;Osmrfl/fl mice with confirmed cre recombination (Fig. S6E–H). The Gfapcre;Osmrfl/fl mice had exacerbated disease severity compared to littermate controls (Osmrfl/fl), particularly showing impaired remission (day 18–35)(Fig. 6G, ,H).H). OsmR deletion in astrocytes had no impact on leukocyte numbers in the periphery at 9-dpi and in the CNS at 25-dpi EAE (Fig. S6I–K), suggesting that the beneficial function of astrocyte OsmR is not mediated by immune cell numbers. Notably, we found that Gfapcre;Osmrfl/fl mice also did not respond to d-zymosan administration as Osmrfl/fl mice did (Fig. 6I, ,J).J). Thus, the beneficial effect of Dectin-1 involves OsmR signaling in astrocytes.
(A-F) OsmR expression in ventro-lateral white matter of lumbar SC from naïve and EAE 17-dpi mice along with counter-staining for GFAP (A, inset in B), Neurofilament (C), MBP (D), CD45 (E), or Tmem119 (F). Scale bar, 25μm. Representative images from two independent experiments (total n=5 mice/group). (G, H) EAE scores of Osmrfl/fl and Osmrfl/fl;Gfapcre littermates (n=8 mice/group). Data quantified by total AUC (H). Representative of 3 independent experiments. (I, J) EAE scores of Osmrfl/fl and Osmrfl/fl;Gfapcre littermates (n=8–11 mice/group) administered PBS or d-zymosan i.v. at 1-dpi EAE. Data quantified by total AUC (J). Data combined from 2 independent experiments. Please also see Figure S6.
Impact of Dectin-1 on EAE is not attributed to hkMtb, used in EAE induction
Next, we sought to determine whether Dectin-1 function in EAE is attributed to the disease induction method which uses hkMtb as an adjuvant. To evaluate whether Dectin-1 recognizes hkMtb, we generated a Dectin-1 signaling reporter cell line (Fig. 7A; S7A). The system showed that zymosan and curdlan both induced robust GFP reporter expression, but hkMtb did not induce GFP expression, even at high concentrations (Fig. 7B, ,CC).
(A) Schematic of the Dectin-1 stimulation reporter cell line. Extracellular and trans-membrane domains of mouse Dectin-1 were fused to the cytoplasmic domain of CD3ζ. Activation of Dectin-1 was detected by a GFP reporter. (B) Representative flow cytometry results from two independent experiments, showing Dectin-1-GFP reporter at 20-hrs with or without curdlan (200 μg/ml) or hkMtb (200 μg/ml) stimulation in tissue culture. Values indicate percentages of GFP+Dectin-1+ cells. (C) Proportions of GFP+Dectin1+ mDectin-1/mCD3ζ-GFP reporter cells with titrated concentrations of hkMtb, zymosan, or curdlan with indicated concentrations. (D, E) RT-qPCR analysis of Il6 normalized to unstimulated control (D) and heatmap of Il1b, Il6, and Tnf expression normalized to unstimulated control (E). WT, Clec7a−/−, and Card9−/− BMDCs stimulated with 200 μg/ml hkMtb in tissue culture for 3 hrs. Mean ± SEM of duplicate wells shown, with data representative of two independent experiments. (F) Lgals9 and Vim mRNA in total SC homogenates from naïve and EAE 14-dpi WT mice. Mean ± SEM, n=3 mice/group. (G) EAE scores of WT mice administered anti-Gal9 antibody or isotype control intrathecally on day 9, 11, 13, 15. n=5 mice/group), quantified by AUC (right panel). (H) EAE scores of WT mice and Clec7a−/− mice administered anti-Gal9 antibody or isotype control intrathecally on day 9, 11, 13, 15. Mean ± SEM shown, n=5 mice/group. Data quantified by AUC (right panel). (I, J) Representative images from two independent experiments of astrocytes vs. Dectin-1-expressing cells (I) or neutrophils (J). Samples were obtained from SC of WT mice at 17-dpi EAE. Please also see Figure S7.
To confirm Dectin-1 was not responding to hkMtb in primary cells, we evaluated Clec7a−/− and Card9−/− BMDCs. Although Il1b, Il6, and Tnf mRNA expression was reduced in the absence of Card9, the absence of Dectin-1 did not alter expression of the genes upon hkMtb stimulation (Fig. 7D, ,E).E). Thus, while Dectin-1 does not detect hkMtb, Card9 mediates response to adjuvant likely through other CLRs upstream of Card9, as previously reported (Fig. S7B) (Miyake et al., 2013; Shenderov et al., 2013; Yonekawa et al., 2014). These results indicate that the beneficial function of Dectin-1 is not attributable to hkMtb adjuvant used in EAE induction but other stimuli, including endogenous Dectin-1 ligands.
Galectin-9 in the CNS limits EAE in a Dectin-1-dependent manner
Next, we sought to evaluate the role of endogenous Dectin-1 ligands in EAE, specifically focusing on reported Dectin-1 ligands, Galectin-9 (Gal-9) (Daley et al., 2017) and Vimentin (Thiagarajan et al., 2013). We found that Gal-9 (Lgals9) gene expression was potently upregulated in the SC during EAE to a greater extent than Vimentin (Vim) (Fig. 7F). Additionally, reanalyzing data from two independent public data (GSE 108000, 123496) showed that human LGALS9 mRNA were also elevated in MS brain specimens (Fig. S7C, D), suggesting possible involvement of Gal-9 in MS. These findings led us to test whether Gal-9 stimulation through Dectin-1 could promote Osm expression. Indeed, recombinant Gal-9 (rGal9) upregulated expression of Osm mRNA in a Dectin-1-dependent manner, at least in part (Fig. S7E). Next, we administered anti-Gal-9 Ab intrathecally at the time of symptom onset (9–15 dpi) and found that blocking Gal-9 led to an increase in EAE severity particularly with impaired remission (Fig. 7G). Thus, we found that Gal-9 in the CNS limits disease during the remission phase of EAE.
Gal-9 limits EAE by inducing T cell apoptosis by ligation of Tim3 on Th1 cells (Zhu et al., 2005). Thus, we tested whether the effect of CNS Gal-9 is mediated also through Dectin-1 in EAE. Intrathecal treatment with Gal-9 Ab exacerbated disease in WT mice but not in Clec7a−/− mice (Fig. 7H). Thus, the beneficial effect of Gal-9 in the CNS was dependent on Dectin-1. Together, these findings suggest that Gal-9 may limit EAE not only by acting through Tim3 on T cells, but also by acting as a Dectin-1 ligand on myeloid cells in the CNS.
Next, we considered which cell-types respond to Gal-9 through Dectin-1 in the CNS during EAE. As a previous study indicated astrocytes as a potential source of Gal-9 during inflammation (Steelman and Li, 2014), re-analysis of a published dataset (GSE100330) showed that astrocytes in SC of EAE mice upregulated Lgals9 mRNA (Fig. S7F). Furthermore, we observed the close proximity between GFAP+ astrocytes and Dectin-1+ cells, particularly Ly6G+ neutrophils, in the SC of EAE mice (Fig. 7I, ,J).J). Together, these findings suggest a potential model of bidirectional myeloid cell-astrocyte crosstalk in which (1) Gal-9 produced by astrocytes upregulates Osm via Dectin-1 in myeloid cells and (2) myeloid cell-derived Osm triggers beneficial OsmR signaling in astrocytes.
DISCUSSION
In this study, we found that Dectin-1 limits CNS inflammation in EAE and promotes beneficial myeloid cell-astrocyte crosstalk through Osm-OsmR signaling. Dectin-1 is generally known for its pro-inflammatory response in the setting of fungal infection, particularly by inducing IL-1β via the Card9-NFκB signaling axis and subsequent Th17 cell responses (Gross et al., 2006; LeibundGut-Landmann et al., 2007; Taylor et al., 2007), which are considered to be highly encephalitogenic. Thus, the beneficial role of Dectin-1 in EAE was initially unexpected. We found that Card9-independent Dectin-1 signaling induced expression of the neuroprotective cytokine, Osm, and a transcriptional program with protective and anti-inflammatory functions. In humans, eQTLs regulating CLEC7A (Dectin-1) gene expression have been identified (Consortium, 2015; Gour et al., 2018) and CLEC7A is expressed in active MS lesions (Hendrickx et al., 2017; Voskuhl et al., 2019). Despite the well-known inflammatory role of Dectin-1, some studies have suggested tolerogenic and anti-inflammatory functions of Dectin-1 signaling (Bode et al., 2019; Dillon et al., 2006; Karumuthil-Melethil et al., 2014). Furthermore, Dectin-1 signaling promotes axon regeneration following optic nerve crush injury (Baldwin et al., 2015) and treatment with zymosan (simultaneously stimulates TLR2 and Dectin-1) reduced EAE severity (Li et al., 2013). Thus, harnessing Dectin-1 signaling merits further investigation as a potential therapeutic approach for MS.
We have shown that d-zymosan treatment at 1-dpi delayed EAE onset. To evaluate treatment effects at later timepoints, a d-zymosan i.v. injection was performed also at either 9-dpi (onset) or 14-dpi (between onset and peak). However, a majority of mice died within 24 hrs of injection (unpublished data). Reduced amount of d-zymosan from 500 μg to 50 μg per mouse was tried at 9-dpi, but EAE scores were not changed (unpublished data). A previous study demonstrates a beneficial response with an injection of zymosan, rather than d-zymosan, at disease onset (100 μg/mouse, i.p. route) (Li et al., 2013). Together, certain conditions appeared to be required to achieve the beneficial outcome by Dectin-1 agonist stimulation.
We demonstrated that Dectin-1 did not detect adjuvant, hkMtb. Instead, Card9 rather functioned as a pathogenic integrator of signals from multiple Syk-coupled CLRs aside from Dectin-1 by detecting hkMtb. The function of Dectin-1 in EAE is also unlikely to be attributable to recognition of commensal fungi, because Dectin-1 limited EAE severity even with administration of an oral fluconazole treatment (data not shown). While we cannot completely rule out the contribution of microbial ligands, our findings suggest involvement of endogenous Dectin-1 ligands in EAE. Indeed, we found that Gal-9, an endogenous Dectin-1 ligand (Daley et al., 2017), acted in the CNS to limit EAE severity in a Dectin-1-dependent manner. Based on our results and a previous study (Zhu et al., 2005), Gal-9 may act through multiple complementary pathways in EAE through Dectin-1 in myeloid cells and through Tim3 in Th1 cells. Furthermore, other endogenous ligands, Annexin proteins (Bode et al., 2019), Vimentin (Thiagarajan et al., 2013), and various unidentified proteins with N-glycans (Chiba et al., 2014), may also contribute to Dectin-1 signaling. Understanding the role of endogenous Dectin-1 ligands in autoimmunity merits further investigation.
We found that Card9-independent signaling drives expression of Osm and other beneficial and anti-inflammatory genes through Syk, PLC, Ca2+, CaN, and NFAT. The existence of multiple Dectin-1 ligands raises the question of whether different ligands could bias Dectin-1 signaling to either a Card9-dependent or Card9-independent pathway. A recent study shows that Dectin-1 signaling triggered by Annexin proteins (endogenous ligands) can induce phosphorylation of Syk at Y348 but not at Y525, while β-glucans (microbial ligand) induce phosphorylation of both sites (Bode et al., 2019). Indeed, Y348 phosphorylation is also triggered by Gal-9 (Daley et al., 2017) and is critical for Syk-induced PLC signaling (Law et al., 1996) which is upstream of NFAT. Here, although Gal-9 can upregulate expression of Osm and Tnf genes ex vivo in bulk neutrophils (unpublished data), Osm and Tnf expression is mutually exclusive in CNS myeloid cells in vivo at a single cell level in EAE. Thus, Card9-dependent and independent pathways may not be co-activated in the same cells in vivo.
We found that the beneficial function of Dectin-1 was mediated by BM-derived myeloid cells, and CNS-infiltrated neutrophils and monocytes contribute to Osm upregulation by Dectin-1 in vivo during EAE. Yet, microglia also upregulated Dectin-1 expression in EAE, consistent with the disease-associated microglia (DAM) phenotype (Deczkowska et al., 2018). Although we cannot fully rule out a contribution of microglial Dectin-1 in EAE, neutrophils in particular may be involved, given their abundant infiltration in the CNS during EAE (Caravagna et al., 2018), protective functions in the CNS (Sas et al., 2020), and localization at sites of demyelination and axonal damage in the SC parenchyma during EAE (Carlson et al., 2008; Christy et al., 2013; Soulika et al., 2009; Steinbach et al., 2013; Wu et al., 2010). While the role of neutrophils in MS remains elusive, multiple studies suggest beneficial role of neutrophils, or granulocytic myeloid-derived suppressor cells (G-MDSCs), in both MS and EAE (Casacuberta-Serra et al., 2016; Elliott et al., 2018; Glenn et al., 2019; Hemond et al., 2019; Hertwig et al., 2016; Ioannou et al., 2012; Knier et al., 2018; Liu et al., 2015; Whittaker Hawkins et al., 2017).
We found that Dectin-1 promotes expression of Osm, a cytokine with described protective functions in cuprizone-induced demyelination (Houben et al., 2020; Janssens et al., 2015) and other models of neuropathology (Guo et al., 2015; Slaets et al., 2014). Osm protein is expressed in MS brains (Ruprecht et al., 2001) and is elevated in supernatants of cultured PBMCs from MS patients (Ensoli et al., 2002). In addition, a SNP in the OSMR gene was identified as a candidate risk factor for MS (Vandenbroeck et al., 2012). In this study, we found that Osm is expressed by myeloid cells in the SC of EAE mice and is upregulated by Dectin-1 signaling. Furthermore, we found that OsmR in astrocytes is beneficial in the remission phase of EAE. While we cannot rule out a role for Dectin-1 in the periphery, our findings demonstrate that Dectin-1 signaling in the CNS promotes myeloid-astrocyte crosstalk through the Osm-OsmR axis to limit EAE. Astrocytes are increasingly recognized as important players in CNS autoimmunity (Voskuhl et al., 2009; Wheeler et al., 2020; Wheeler and Quintana, 2019) and astrocyte gp130, which forms a heterodimer with OsmR, was shown to be protective in EAE (Haroon et al., 2011).
This study contributes to a growing body of evidence that Dectin-1 has important roles beyond the context of fungal infection. We advance this emerging understanding by identifying a beneficial mechanism of Dectin-1 specifically in the setting of autoimmune neuroinflammation. Together, our findings provoke a reconsideration of Dectin-1 and its functions beyond the context of infection and provide potential targets for therapeutic intervention in neuroinflammatory disorders.
LIMITATIONS OF STUDY
In this study, we identified a beneficial role for Dectin-1 signaling in limiting autoimmune neuroinflammation in the EAE model. However, EAE does not recapitulate all aspects of human CNS autoimmune disease and it remains to be determined whether Dectin-1 is involved in Multiple Sclerosis. In addition, our study has focused primarily on the role of Dectin-1-mediated Osm expression in neutrophils and monocytes in the CNS during EAE. However, we do not rule out a role for Dectin-1 in regulating the peripheral immune response during EAE. Future studies using targeted deletion of Dectin-1 (Clec7a) in a disease stage and cell type-specific manner will further define the site, timing, and cellular mediators of endogenous Dectin-1 signaling in EAE and may extend the contributions of Dectin-1 signaling in autoimmunity beyond those described in this study.
STAR METHODS
RESOURCE AVAILABILITY
Lead contact:
Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Mari L. Shinohara, PhD (ude.ekud@arahonihs.iram).
Materials Availability:
This study did not generate new unique reagents.
Data and Code Availability:
Relevant data and materials from this study will be made available upon request. Our RNA sequencing results are available as GSE148850. All custom code will be made available upon request through GitHub.
EXPERIMENTAL MODEL AND SUBJECT DETAILS
Mice
Six- to eight-week old age- and sex-matched mice of the C57BL/6 (B6) background were used for experiments unless otherwise specified. No difference in results between two sexes was found. Dectin-1 deficient (Clec7a−/−) mice were originally generated by Dr. Gordon Brown (U. of Aberdeen)(Taylor et al., 2007). Card9−/− mice were provided by Dr. Xin Lin (M.D. Anderson Cancer Center, Houston, TX)(Hsu et al., 2007). Osmrfl/fl mice on a mixed background of B6 and 129×1/SvJ (JAX #011081) were rederived from a cryopreserved line at Jackson Laboratories. We performed speed-congenic approach (DartMouse) to further backcrossed to B6 for 6 additional generations to achieve 99.8 % of the B6 genomic background (Fig. S6H). Osmr-fl mice were then crossed to Gfapcre (JAX #024098), and littermate controls were used for Osmrfl/fl experiments. Fixed tissues from Aldh1l1-eGFP mice (MMRRC #011015-UCD) were provided by the laboratory of Dr. Cagla Eroglu (Duke U.). All mice were housed under specific pathogen-free conditions and all animal experiments were performed as approved by Institutional Animal Care and Use Committee at Duke University.
Dectin-1 reporter cell line
A retroviral plasmid pMXs-IP-mCD3ζ-mDectin1 vector (Pyz et al., 2008), a gift from Gordon Brown (U. of Aberdeen, UK) and Pcl-Eco (packaging vector) were transfected to BOSC cells using lipofectamine LTX to generate retrovirus for gene transfection. The mCD3ζ-mDectin1 fusion protein was expressed in the TCR-negative 58α−β− mouse T hybridoma, expressing GFP upon mCD3ζ activation (Ise et al., 2010) (gift from Ken Murphy, Washington U.). Activated Dectin-1 was reported by GFP expression by the hybridoma and detected by flow cytometry. Cell lines used in this study did not undergo authentication in our laboratory.
METHOD DETAILS
Reagents, Abs, and recombinant proteins
Curdlan (β−1,3 glucan hydrate, from Alcaligenes faecalis, Sigma-Aldrich) was used as a Dectin-1 specific agonist for ex vivo experiments, unless otherwise indicated. Hot-alkali treated depleted zymosan (dz) (InvivoGen) was used as a Dectin-1-specific ligand for in vivo experiments. Heat-killed Mycobacterium tuberculosis (hkMtb) H37a Ra was purchased from BD Difco™. Small molecule signaling inhibitors were purchased from Cayman Chemical, with the exception of GW5074 (Sigma Aldrich), and concentrations for their use were determined using supplier recommendations and based on previous publications. Recombinant mouse (rm) M-CSF and GM-CSF proteins were obtained from BioLegend. Recombinant mouse Gal-9 was obtained from R&D. MOG35–55 peptide (MEVGWYRSPFSRVVHLYRNGK) was synthesized by United Biosystems. Enzyme-linked immunosorbent assay (ELISA) kits for detection of mouse Osm were purchased from R&D, and ELISA kit for detection of mouse IL-10 was purchased from BioLegend. Detailed list of Abs and reagents can be found in the Key Resources Table.
KEY RESOURCES TABLE
| REAGENT or RESOURCE | SOURCE | IDENTIFIER |
|---|---|---|
| Abs | ||
| Rat monoclonal anti-CD3e (clone 145–2C11) | BioLegend | Cat# 100306 |
| Rat monoclonal anti-CD4 (clone GK1.5) | BioLegend | Cat# 100451 |
| Armenian hamster anti-TCR-β (clone H57–597) | BioLegend | Cat# 109221 |
| Rat monoclonal anti-CD25 (clone PC61) | BioLegend | Cat# 102003 |
| Rat monoclonal anti-CD8 (clone 53–6.7) | BioLegend | Cat# 100722 |
| Rat monoclonal anti-IFNy (clone XMG1.2) | BioLegend | Cat# 505806 |
| Rat monoclonal anti-IL-17 (clone TC11–18H10.1) | BioLegend | Cat# 506904 |
| Rat IgG1, κ isotype control (clone RTK2071) | BioLegend | Cat# 400429 |
| Rat monoclonal anti-Foxp3 (clone MF-14) | BioLegend | Cat# 126405 |
| Rat monoclonal anti-GM-CSF (clone MP1–22E9) | BioLegend | Cat# 505405 |
| Rat IgG2a, κ isotype control (clone RTK2758) | BioLegend | Cat# 400507 |
| Rat monoclonal anti-CD45 (clone 30-F11) | BioLegend | Cat# 103114 |
| Rat monoclonal anti-CD45 (clone 30-F11) | BD | Cat# 564279 |
| Rat monoclonal anti-CD11b (clone M1/70) | BioLegend | Cat# 101257 |
| Rat monoclonal anti-CD11c (clone N418) | BioLegend | Cat# 117310 |
| Rat monoclonal anti-Ly6G (clone 1A8) | BioLegend | Cat# 127606 |
| Rat monoclonal anti-Ly6C (clone HK1.4) | BioLegend | Cat# 128008 |
| Rat monoclonal anti-CD19 (clone 6D5) | BioLegend | Cat# 115530 |
| Rat monoclonal anti-IA/IE (clone M5/114.15.2) | BioLegend | Cat# 107622 |
| Rat monoclonal anti-CD40 (clone 3/23) | BioLegend | Cat# 124609 |
| Rat monoclonal anti-CD80 (clone 16–10A1) | BioLegend | Cat# 104733 |
| Rat monoclonal anti-CD86 (clone GL-1) | BioLegend | Cat# 105018 |
| Rat monoclonal anti-F4/80 (clone BM8) | BioLegend | Cat# 123114 |
| Rat monoclonal anti-Dectin-1 (clone 2A11) | Biorad | Cat# MCA2289FA |
| Rat IgG2b isotype control (clone RTK4530) | BioLegend | Cat# 400606 |
| Rat monoclonal anti-Tmem119 (clone 106–6) | Abcam | Cat# ab210405 |
| Goat polyclonal anti-Rabbit (H+L) Highly Cross-Adsorbed Secondary Ab | ThermoFisher | Cat# 21245 |
| Rat monoclonal anti-CD45.1 (clone A20) | BioLegend | Cat# 110708 |
| Rat monoclonal anti-CD45.2 (clone 104) | BioLegend | Cat# 109814 |
| Rat monoclonal anti-CD11b (clone EPR19387) | Abcam | Cat# ab184308 |
| Rat monoclonal anti-Tmem119 (clone 28–3) | Abcam | Cat# ab209064 |
| Goat polyclonal anti-Iba1 | Novus | Cat# NB100–1028 |
| Rat monoclonal anti-OsmR (clone 18125) | R&D | Cat# MAB662 |
| Rat IgG2a isotype control (clone RTK2758) | BioLegend | Cat# 400501 |
| Rabbit polyclonal anti-GFAP | Abcam | Cat# ab7260 |
| Mouse monoclonal anti-GFAP (clone 5C10) | Novus | Cat# 05197 |
| Rat monoclonal anti-CD45 (clone 30-F11) | BioLegend | Cat# 103104 |
| Rabbit polyclonal anti-MBP | Abcam | Cat# ab40390 |
| Rabbit polyclonal anti-Neurofilament heavy | Abcam | Cat# ab8135 |
| Chicken polyclonal anti-Rat IgG (H+L) Cross-Adsorbed Secondary Ab | ThermoFisher | Cat# A-21472 |
| Goat polyclonal anti-Mouse IgG (H+L) Cross-Adsorbed Secondary Ab | ThermoFisher | Cat# A-11029 |
| Donkey polyclonal anti-Rabbit (H+L) Highly Cross-Adsorbed Secondary Ab | ThermoFisher | Cat# A-21206 |
| Donkey polyclonal anti-Goat (H+L) Highly Cross-Adsorbed Secondary Ab | ThermoFisher | Cat# A-11055 |
| Goat polyclonal anti-Rabbit (H+L) Highly Cross-Adsorbed Secondary Ab | ThermoFisher | Cat# A-21244 |
| Bacterial and Virus Strains | ||
| retroviral pMXs-IP-mCD3ζ-mDectin1 vector | gift from Gordon Brown (University of Aberdeen, UK) (under MTA) | N/A |
| Biological Samples | ||
| N/A | ||
| Chemicals, Peptides, and Recombinant Proteins | ||
| Curdlan (from Alcaligenes faecalis, beta-1,3 Glucan hydrate) | Sigma-Aldrich | Cat# C7821 |
| Zymosan Depleted (hot-alkali treated zymosan) | InvivoGen | Cat# tlr-zyd |
| GW5074 (Raf1 inhibitor) | Sigma-Aldrich | Cat# G6416 |
| BAY 61-36-6 (Syk inhibitor) | Cayman Chemical | Cat# 11423 |
| NFAT Inhibitor (11R-VIVIT) | Cayman Chemical | Cat# 13855 |
| Cyclosporine A (Calcineurin inhibitor) | Cayman Chemical | Cat#12088 |
| U-73122 (Phospholipase C inhibitor) | Cayman Chemical | Cat# 70740 |
| Recombinant mouse GM-CSF | BioLegend | Cat# 576304 |
| Recombinant mouse M-CSF | BioLegend | Cat# 576406 |
| Dynabeads Mouse T-activator CD3/CD28 | Gibco | Cat# 11456D |
| MOG35–55 peptide (MEVGWYRSPFSRVVHLYRNGK) | United Biosystems | Cat# U104628 |
| Freund’s adjuvant, complete (contains Mycobacterium tuberculosis (H37Ra, ATCC 25177), heat killed and dried) | Sigma-Aldrich | Cat# F5881 |
| Freund’s adjuvant, incomplete (does not contain Mycobacteria tuberculosis) | Sigma-Aldrich | Cat# F5506 |
| Pertussis Toxin | List Biological Technologies | Cat# 180 |
| LFB Solvent Blue 38 | Sigma-Aldrich | Cat# S3382 |
| Gill’s Hematoxylin No. 3 for tissue | Sigma-Aldrich | Cat# GHS316 |
| Schiff’s reagent | Sigma-Aldrich | Cat# S5133 |
| Collagenase D (from Clostridium histolyticum) | Roche | Cat# 11088866001 |
| Ionomycin (calcium salt from Streptomyces conglobatus) | Sigma-Aldrich | Cat# I0634 |
| Phorbol 12-myristate 13-acetate (PMA) | Sigma-Aldrich | Cat# P 1585 |
| Prolong Gold Antifade Mountant | Thermo-Fischer | Cat# P36930 |
| Mycobacterium tuberculosis H37 Ra, Desiccated (Heat-killed Mtb) | BD Difco | Cat# 231141 |
| RNAscope Probe- Mm-Osm | ACD | Cat# 427071 |
| PrimeFlow RNA Assay Probe- Mm-Osm | Invitrogen | Cat# VB1–10808-PF |
| Critical Commercial Assays | ||
| Cytofix/Cytoperm Kit | BD | Cat# 554714 |
| FOXP3 Fix/Perm Kit | BioLegend | Cat# 421401 |
| CellTrace Violet Cell Proliferation Kit | Invitrogen | Cat# C34557 |
| LIVE/DEAD Fixable Violet Dead Cell Stain Kit | Thermo-Fisher | Cat# L34955 |
| Mouse Oncostatin M/OSM DuoSet ELISA Kit | Fischer (R&D Systems) | Cat# DY49505 |
| EasySep Mouse CD4+ T Cell Isolation Kit | StemCell Technologies | Cat# 19852 |
| Mouse IL-10 ELISA MAX Assay | BioLegend | Cat# 431411 |
| PrimeFlow RNA Assay Kit | Invitrogen | Cat# 88-18005-204 |
| Deposited Data | ||
| Raw and analyzed RNA-seq data for “Genome-wide analysis of the CARD9/Dectin-1 transcriptional program in neutrophils and macrophages by RNA-seq” | This paper | GSE148850 |
| Analyzed microarray data for “Gene expression profiling of multiple sclerosis pathology identifies early patterns of demyelination surrounding chronic active lesions” | Hendrickx et al, 2017 | GSE108000 |
| Analyzed RNA-seq data for “Human brain tissues from healthy controls and multiple sclerosis patients” | Voskuhl et al, 2019 | GSE123496 |
| Mouse reference genome, version GRCm38v73 | Genome Reference Consortium | https://www.ncbi.nlm.nih.gov/grc/mouse |
| Analyzed ATAC-seq data for BM neutrophils (GN_BM) and monocytes (Mo_6C+II-_Bl) | Yoshida et al, 2019; Immunological Genome Project (Heng et al, 2008) | http://rstats.immgen.org/Chromatin/chromatin.html |
| Analyzed RNA-seq data for Osmr expression | Immunological Genome Project (Heng et al, 2008) | http://rstats.immgen.org/Skyline/skyline.html |
| Experimental Models: Cell Lines | ||
| Mouse: 58α−β− T hybridoma cell line with stable expression of a NFAT-GFP-hCD4 RV reporter construct | From laboratory of Ken Murphy (Washington University, USA) (Ise et al, 2010) | N/A |
| Human: BOSC-23 cells, retrovirus packaging cell line | N/A | RRID: |
| Experimental Models: Organisms/Strains | ||
| Mouse: Clec7a−/− ;B6.Clec7atm1Gdb/J | Generated by the laboratory Dr. Gordon Brown (University of Aberdeen, UK) (Taylor et al, 2007) | N/A |
| Mouse: Card9−/− (C57BL/6) | Generated by the laboratory Dr. Xin Lin (M.D. Anderson Cancer Center, Houston, TX) (Hsu et al, 2007) | N/A |
| Mouse: Osmrfl/fl; B6;129-Osmrtm1.1Nat/J (Backcrossed to the C57BL/6 background for this paper) | The Jackson Laboratory | JAX #011081 |
| Mouse: Aldh1l1-eGFP; Tg(Aldh1l1-EGFP)OFC789Gsat/Mmucd | Generated by the laboratory of Dr. Ben Barres (Stanford University, USA) (Cahoy et al, 2008) | RRID:MMRRCC_001015-UCD |
| Mouse: Gfapcre; B6.Cg-Tg(Gfap-cre)77.6Mvs/2J | The Jackson Laboratory | JAX #024098 |
| Oligonucleotides | ||
| Primers for RT-qPCR: see Table S1 | This paper | N/A |
| Primers for Osmrfl/fl recombination: see Table S1 | This paper | N/A |
| Recombinant DNA | ||
| pMXs-IP-mCD3ζ-Dectin-1 | Gift from Dr. Gordon Brown (University of Aberdeen, UK) (Under MTA) (Pyz et al, 2010) | N/A |
| Software and Algorithms | ||
| R statistical programming environment | Team et al, 2013 | https://www.r-project.org |
| Bioconductor | Huber et al, 2015 | https://bioconductor.org |
| DESeq2 | Love et al, 2014 | https://bioconductor.org/packages/release/bioc/html/DESeq2.html |
| Cutadapt | Martin et al, 2011 | https://github.com/marcelm/cutadapt/ |
| STAR | Dobin et al, 2013 | https://github.com/alexdobin/STAR |
| ReactomePA | Yu et al, 2016 | http://bioconductor.org/packages/release/bioc/html/ReactomePA.html |
| GOseq | Young et al, 2010 | https://bioconductor.org/packages/release/bioc/html/goseq.html |
| ImageJ | Schindelin et al., 2012 | https://imagej.net/Fiji |
| FlowJo | N/A | https://www.flowjo.com/solutions/flowjo |
| GraphPad Prism | N/A | https://www.graphpad.com/scientific-software/prism/ |
| Other | ||
| Documentation: analysis of Card9-dependent and -independent gene sets, transcription factor enrichment | This paper | https://github.com/medeerhake/manuscript_03 |
EAE induction and evaluation
Unless otherwise noted, EAE was induced as follows: MOG35–55 peptide (100 μg in 100 μl PBS) emulsified in CFA (100 μl including 2 mg/ml hkMtb) was subcutaneously (s.c.) injected into lower flanks of mice. Intraperitoneal injection of pertussis toxin (List Biologicals; 200 ng in 200 μl PBS) was performed on day 0 and 2. EAE induction was performed with reduced adjuvant in Fig. 1B, Fig. 3E, ,F,F, and Fig. 7H by using 0.5 mg/ml instead of 2 mg/ml hkMtb CFA (i.e., 50 μg/mouse instead of 200 μg/mouse). Mice were monitored daily for clinical signs of EAE and scores were assigned based on the following criteria: 0.5, partial tail limpness; 1, tail limpness; 1.5, impaired righting reflex; 2, partial hindlimb paralysis; 2.5, partial hindlimb paralysis with dragging of at least one hind paw; 3, bilateral hindlimb paralysis; 3.5, severe bilateral hindlimb paralysis with hunched posture; 4, hind- and forelimb paralysis; 5, death.
Cell isolation for flow cytometry analysis
Mice were euthanized with CO2 in addition to a secondary method, as recommended by American Veterinary Medical Association. BM was isolated from the femur and tibia by flushing marrow with a needle and syringe filled with sterile PBS and pipetting to obtain a single cell suspension. Spleens and ILNs were dissected and homogenized using sterile glass slides. SC cells were isolated by flushing the SC from the vertebral column with a needle and syringe filled with sterile PBS, minced in PBS including 5% FBS and 1mM HEPES, then digested with Collagenase D (Roche) at 37 C for 30 minutes. Following digestion, single cell suspensions were prepared by passing through an 18G needle and filtered through a 70 μm cell strainer. Cells were then resuspended in 38 % isotonic Percoll and centrifuged at 2,000 g for 30 min with no brake. Following centrifugation, the lipid and debris layer was aspirated from the top of the tube and the cell pellet was resuspended. All tissues were treated with RBC lysis solution prior to staining for flow cytometry.
Ab staining for flow cytometry
Analyses for live cells was performed using a LIVE/DEAD™ fixable dead cell stain kit (Invitrogen) prior to staining with fluorochrome-conjugated Abs, listed in the Key Resources Table, by flow cytometry using either Fortessa X20 or FACSCanto (BD systems). Results were analyzed using the FlowJo software. Specific cell types were gated as neutrophils (CD11b+Ly6G+), monocytes (CD11b+Ly6G−Ly6Chi), cDCs (CD11b+CD11c+, with MHC-IIhi for some experiments), F4/80hi macrophages (CD11b+F4/80hi), B cells (CD19+), CD4+ T cells (CD3+CD4+), CD8+ T cells (CD3+CD8+), microglia (CD45loCD11blo and Tmem119+, as indicated in the text).
PrimeFlow mRNA detection
Cells from the SC of EAE mice were isolated using the methods described above with LIVE/DEAD™ staining and fluorochrome-conjugated Abs for cell-surface markers. In situ hybridization for Osm mRNA was performed using the PrimeFlow RNA Assay Kit (Invitrogen) according to manufacturer’s instructions. Cells were analyzed by flow cytometry using Fortessa X20 (BD systems) and results were analyzed using the FlowJo software.
Intracellular cytokine staining for flow cytometry
Intracellular cytokine staining was performed on spleen and LN single cell suspensions following 6 hr stimulation with PMA (10ng/ml) (Sigma Aldrich) and ionomycin (1μg/ml) (Sigma Aldrich), with GolgiPlug (BD) in the final 4 hrs of stimulation. Staining was performed using a LIVE/DEAD™ staining followed by fluorochrome-conjugated Abs for cell surface proteins before fixation and permeabilization (BD Cytofix/Cytoperm Kit). Ab staining for intracellular cytokines was then performed in permeabilization buffer. Intracellular staining for Foxp3 was performed on single cell suspensions from spleen and LNs specifically using a FOXP3 Fix/Perm Kit (BioLegend).
T cell recall response assay
Lymph node CD4+ T cells from EAE mice were enriched using a CD4+ T cell negative selection kit (StemCell Technologies). Splenic CD11c+ cells from WT naïve mice were enriched using MACS-column purification (Miltenyi Biotec) with biotinylated mouse CD11c Abs (BioLegend) and streptavidin magnetic beads (Miltenyi Biotec). CD11c+ cells and CD4+ T cells were co-cultured at a 1:1 ratio in complete RPMI with 10 μg/ml MOG35–55 peptide. Cells were also labeled with CellTrace Violet (ThermoFisher) proliferation dye prior to co-culture. After 3 days, cells were collected to detect dilution of the proliferation dye by flow-cytometry as shown in Fig. S3K.
IL-10 expression by CD25+CD4+ T cells
Splenic CD4+ T cells from EAE mice were enriched using a CD4+ T cell negative selection kit (StemCell Technologies) according to manufacturer’s instructions. CD25+ cells were subsequently isolated from the CD4+ T cell pool using MACS-column purification (Miltenyi Biotec) with biotinylated mouse CD25 Abs (BioLegend) and streptavidin magnetic beads (Miltenyi Biotec). Isolated CD25+CD4+ T cells were cultured with “Mouse T-activator CD3/CD28” Dynabeads (Gibco) in complete RPMI. Supernatants were collected after 3 days and tested for IL-10 protein quantitation by ELISA (BioLegend).
Neutrophil, monocyte, and BM-derived cell culture
BM neutrophils were isolated using MACS-column purification (Miltenyi Biotec) with biotinylated mouse Ly6G Abs (BioLegend) and streptavidin magnetic beads (Miltenyi Biotec) for ex vivo study. BM monocytes, were isolated by flow cytometry-sorting as CD11b+Ly6G−Ly6C+ cells (Astrios sorter, Beckman Coulter). When neutrophils were compared to monocytes, flow cytometry-sorting was used to isolate neutrophils as CD11b+Ly6G+. BMDMs and BMDCs were generated by culturing BM cells with rmM-CSF (20 ng/ml, BioLegend) and rmGM-CSF (20 ng/ml, BioLegend), respectively. Complete RPMI medium was used for all cell culture studies.
Isolation of spinal cord tissue for histology
Transcardial perfusion was used to maximize integrity of brain and SC tissue to improve sample quality. Specifically, mice were administered sodium pentobarbital (100 mg/kg) by intraperitoneal injection and monitored until complete anesthesia was achieved (non-responsive to pedal reflex). The thoracic cavity was dissected, and the inferior vena cava severed prior to insertion of a needle in the left ventricle and slow manual administration of PBS followed by 4% paraformaldehyde (PFA). Following transcardial perfusion and fixation, spinal cord tissue was manually dissected and fixed in 4% PFA overnight before cryoprotection in 30% sucrose for 1–2 days. Tissues were embedded in Tissue-Tek OCT compound (Sakura), frozen, and stored at −80 °C.
LFB-PAS staining and imaging
Luxol fast blue (LFB)-Periodic Acid Schiff (PAS) staining was performed on transverse fixed-frozen sections (10 μm) of lumbar spinal cord using LFB Solvent blue 38, Gill’s Hematoxylin No. 3, and Schiff’s reagent (all obtained from Sigma-Aldrich). LFB-PAS stained sections were imaged on the Zeiss Axio Imager widefield microscope.
Immunofluorescent staining and imaging
Staining was performed with either floating sections in tissue culture wells or thaw-mounted sections on slides. Transverse fixed-frozen sections (25 μm) of lumbar spinal cord were washed with TBS-T, permeabilized with TBS 0.25% Triton 1× for 15min, washed with TBS-T, then incubated in blocking buffer (TBS-T 3% BSA) for at least 1 hr. Primary Ab staining was performed overnight at 4 °C, followed by washing in TBS-T. Secondary Ab staining with fluorochrome-conjugated Abs was performed for 2 hrs at 4 °C (Abs listed in Key Resources Table). Stained sections were washed and mounted using ProLong Gold Antifade Mountant with DAPI (ThermoFisher). Slides were imaged using the Zeiss 710 inverted confocal microscope and analyzed using ImageJ. IF images are typically representative of at least two high-power field (hpf) per sample, and data was obtained from several individual animals per experiment (sample size (n) denoting number of mice).
mRNA detection in tissue sections by RNAscope
To prepare samples for RNAscope, lumbar SC segments were dissected following transcardial perfusion (described above) and post-fixed overnight in 4% PFA. Samples were then transferred to 30% sucrose in PBS and kept overnight. Spinal cords were cryosectioned to 20 μm and thaw-mounted onto Superfrost Plus slides (Fisher Scientific). Slides were allowed to dry for 20 minutes at room temperature, and then stored at −20 C overnight. The RNAscope Multiplex Fluorescent Reagent Kit v2 (Advanced Cell Diagnostics, ACD) was used for in situ hybridization as previously described (Chamessian et al., 2018). Tissue pretreatment was performed for 30 min with Protease IV in the RNAscope kit at RT followed by probe hybridization and detection according to manufacturer’s instructions. We used probes designed by Advanced Cell Diagnostics to Osm (NM_001013365.2), specifically Mm-Osm (#427071). IF staining with Ab to CD11b was performed after the RNAscope procedure using methods described above. Slides were imaged using the Zeiss 710 inverted confocal microscope. For comparison of naïve and EAE conditions, Osm mRNA puncta were quantified by performing object detection using ImageJ, calculating the integrated density for each punctum, and summing over all puncta in a given 350 μm2 hpf. Positive signal, i.e., puncta, was defined as >5-fold higher than background. Five hpf per mouse were analyzed, one in each indicated region of lumbar SC. For evaluation of Osm expression in CD11b+ cells, z-stack images with 1.16 μm spacing were collected through the full thickness of each section. For each 350 μm2 ventrolateral white matter hpf per mouse, Osm puncta were quantified manually in a blinded manner. Specifically, Osm puncta per CD11b+ cell were quantified by examining multiple z-stacks in 3D space to identify cell-associated puncta.
RT-qPCR analysis
To evaluate gene expression in ex vivo stimulation experiments, total RNA was extracted from cells with TRIzol on purified cells, while RNeasy Micro Kit (Qiagen) was used for flow cytometry-sorted cells. cDNA synthesis was performed using qScript cDNA Mix (Quantabio). Real-time, quantitative polymerase chain reaction (RT-qPCR) was performed with SYBR FAST qPCR Master Mix (Kapa Biosystems) with primers shown in Table S1. Relative amounts of qPCR product were determined using the −ΔΔCt method (Livak and Schmittgen, 2001) comparing relative expression of housekeeping (Actb) and target genes. Error bars denote mean ± SEM of biological replicates in Fig. 4A, ,B;B; Fig. 5A; Fig. 7D, ,F;F; Fig. S4G–I; and Fig. S7E. In Figures 4D, Fig. 5L, ,N,N, ,O;O; Fig. S4F; and Fig. S5A–D, F error bars (sometimes too short to be identified) were calculated using RQ-Min = 2−(ΔΔCt + T *SD(ΔCt)) and RQ-Max = 2−(ΔΔCt − T *SD(ΔCt)) from triplicate wells as suggested by Applied Biosystems (manufacturer of qPCR machines). Results shown are representative of multiple independent experiments with similar results.
RNA-sequencing
BM neutrophils were obtained by MACS-column purification as described above. Each sample was obtained from an individual WT or Card9−/− mouse (n=3). Cells were stimulated for 3 hrs with curdlan (100 μg/ml). Total RNA was extracted from cells using the RNeasy Micro Kit (Qiagen). mRNA libraries were prepared using the KAPA stranded mRNA-seq kit by Duke Sequencing and Genomic Technologies Shared Resource facility. RNA libraries were sequenced on an Illumina HiSeq4000 using 50-bp single reads.
Experimental design
Sample sizes for animal experiments were selected with goal of minimizing animal numbers while maintaining sufficient power to detect biologically significant effects in statistical analysis of data from multiple replicate experiments. Although statistical tests were not used to determine sample size, we always repeated experiments and ran statistics to draw conclusions. No data points were excluded from figures in this manuscript. As indicated in the text or figure legend, all figures are from either one experiment representative of multiple replicate experiments or include data from multiple replicate experiments combined into a single figure. Definition of sample size (n) is indicated in figure legends. Mouse experiments were performed with age- and sex-matching of individuals in each experimental condition to reduce the effect of these biological covariates, and randomization of individual animals to treatment conditions was performed when feasible. Investigator blinding was performed for quantitative image analysis of in situ hybridization data and for animal experiments which used littermate controls.
QUANTIFICATION AND STATISTICAL ANALYSIS
Statistical analysis
EAE clinical scores were analyzed by calculating the area under the curve (AUC) summing clinical scores over the indicated period. Statistical analysis of EAE clinical score AUC was performed using a non-parametric Mann-Whitney U-test and, where indicated, AUC was normalized to the mean of the control group. Box plots of EAE clinical score AUC data include the following elements: center line, median; box limits, upper and lower quartiles; whiskers, minimum and maximum values. For remaining analyses, student’s t-test (paired or unpaired, as appropriate, two-sided in all cases) or analysis of variance (ANOVA) was applied (one- or two-factors, repeated measures as appropriate) as indicated in figure legends. If a two-factor ANOVA yielded an interaction term with p<0.1, then post-hoc Sidak testing with correction for multiple comparison was applied. If a two-factor ANOVA did not result in a significant interaction term (p>0.1), then any significant main effects are indicated in the figure and legend. Log-transformation was performed prior to 2-factor ANOVA as appropriate when data include values that varied greatly in magnitude between multiple cell types (Fig. 2F, ,G;G; Fig. 4A,,B;B; Fig. S1E, F, H, I; Fig. S2B, C; Fig. S3G; Fig. S6I–K). All results are expressed as means ± SEM unless otherwise noted, and criterion of significance was set as p<0.05 (*), p<0.01 (**), or p<0.001 (***). Apart from analysis of RNA-seq data (described below), Microsoft Excel and GraphPad Prism software were used for all statistical analyses.
Flow cytometry analysis
Flow cytometry analysis was performed using a BD FACSCanto II or BD Fortessa X-20 analyzer. Flow cytometry sorting was performed using B-C Astrios sorters. FlowJo software was used to analyze all flow cytometry data in this study. For all flow cytometry sorting experiments, at least one representative post-sort sample was re-analyzed for cell purity based on original markers before proceeding with further sample processing. All flow cytometry analysis in this study used: (1) an initial FSC-A/SSC-A gate to eliminate low FSC-A/SSC-A debris, (2) a FSC-H/FSC-A gate to identify single cells, and (3) Fixable Live/Dead stains to identify live cells for further analysis All gating strategies are described in the text where indicated.
RNA-seq analysis
Initial processing and analysis of sequencing results was performed by Duke Genomic Analysis and Bioinformatics core facility as described here: RNA-seq data was processed using the TrimGalore toolkit which employs Cutadapt (Martin, 2011) to trim low-quality bases and Illumina sequencing adapters from the 3’ end of the reads. Only reads that were 20nt or longer after trimming were kept for further analysis. Reads were mapped to the GRCm38v73 version of the mouse genome and transcriptome (Kersey et al., 2012) using the STAR RNA-seq alignment tool (Dobin et al., 2013). Reads were kept for subsequent analysis if they mapped to a single genomic location. Gene counts were compiled using the HTSeq tool. Only genes that had at least 10 reads in any given library were used in subsequent analysis. Normalization and differential expression was carried out using the DESeq2 (Love et al., 2014) Bioconductor (Huber et al., 2015) package with the R statistical programming environment (Team, 2013) (Table S2). The false discovery rate was calculated to control for multiple hypothesis testing.
Card9-dependent and -independent candidate genes
We first selected genes with significant differential expression following curdlan stimulation in WT neutrophils (log2 fold-change >|1.5| and adjusted p-value<0.05). Among statistically significant differentially expressed genes, we then selected Card9-dependent candidate genes (adjusted p-value < 0.05 for interaction of genotype and stimulation). Among the remaining genes, (adjusted p-value > 0.05 for interaction of genotype and stimulation), we further selected those genes with a stimulation-induced fold-change within 30 % of WT values (1 ± 0.3) and defined these as Card9-independent candidate genes (Table S3).
Reactome pathway enrichment analysis
Using these Card9-dependent and -independent candidate gene lists, we performed pathway enrichment analysis on those genes that are upregulated with curdlan stimulation using the ReactomePA package and gene set overlap analysis (Yu and He, 2016) (Table S3) and plotted the resulting enriched pathways (adjusted p-value < 0.05) using a cnetplot network diagram (genes are small grey points, pathways are colored, lines indicate correspondence of genes with pathways).
Transcription factor enrichment analysis
To identify potential transcription factors that may regulate Card9-dependent and -independent candidate genes, we developed an analysis approach which leverages existing datasets and tools. Our goal was to identify potential TF candidates based on predicted binding sites near genes in either the Card9-dependent or -independent candidate gene lists. We limited our analysis of predicted binding sites to OCRs in our cell type of interest (BM neutrophils) to better target relevant sites for possible TF binding. We obtained analyzed ATAC-seq result files from ImmGen for BM neutrophils which contained information on each OCR, an OCR score for the particular cell type, predicted TF binding sites within each OCR, and genes within 100 kb of each OCR (Heng et al., 2008; Yoshida et al., 2019) (downloaded from Immgen site on May 22nd, 2019). From this genome-wide dataset, we selected only OCRs with a score of >10 in BM neutrophils to specifically include regions of open chromatin in our analysis. From these OCRs, we generated a paired list of TFs (with predicted binding sites within a given OCR) and genes (within 100 kb of a given OCR). This paired list was then used as a custom reference for gene set overlap analysis, in which the category is a given TF. Then we used GOseq (Young et al., 2010) to perform gene set overlap analysis between either Card9-dependent or -independent genes and our custom reference. Benjamini Hochberg adjusted p-values were obtained for each TF category for either Card9-dependent or -independent genes (Table S3). We then plotted the - log(adjusted p-value) for each TF on a violin plot and labeled TFs in the NFκB or NFAT families (Fig. 5H, ,I).I). In addition, we plotted a Venn diagram of genes with at least 3 predicted binding sites of either NFκB or NFAT family TFs (within 100 kb of gene) (Fig. 5J)
Supplementary Material
1
2
Table S2. RNA-seq differential expression analysis results (Related to Figure 5)
3
Table S3. Additional analysis of Card9-independent and -dependent candidate genes (Related to Figure 5)
ACKNOWLEDGEMENTS
Funding: This study was funded by the National Multiple Sclerosis Society (Pilot Grant PP-1509-06274; Research Grant RG 4536B2/1), the NIH (R01-AI088100) to M.L.S. and the NIH (F30-AI140497, T32-GM007171) to M.E.D.
We appreciate the assistance of the Duke Center for Genomic and Computational Biology core facility and the Duke Cancer Institute Flow Cytometry Core, particularly Lynn Martinek. Christabel Tan in the laboratory of Cagla Eroglu (Duke U.) provided samples from Aldh1l1-eGFP mice. Gordon Brown (U. of Aberdeen, UK) provided the pMXs-IP-mCD3ζ - mDectin1 construct under MTA. Ken Murphy (Washington U.) provided the 58α−β− mouse T hybridoma cell line with stable expression of a NFAT-GFP-hCD4 RV reporter construct. Megumi Matsuda, Qianru He, and Zilong Wang, in the laboratory of Ru Rong Ji (Duke U.) provided assistance with RNAscope in situ hybridization. Tomoko Kadota and Tamira-Marie Bickems in Shinohara Lab provided assistance with mouse genotyping.
Footnotes
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DECLARATION OF INTERESTS
Ru-Rong Ji is a consultant of Boston Scientific and received research grant from the company. This activity is not related to the current study. The remaining authors declare no competing interests.
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