Information

NF-κB activated, but IRF blocked - Rewiring of immune response


Rubela virus has the following PAMPs: ssRNA, which will activate the following PRRs: TLR7, TLR8, RIG-I, and possibly MDA5. Dendritic cells infected with Rubela virus are reported to produce very low levels of IL-12p70 and to produce weak activation of naïve T-cells. DC-SIGN is one C-type lectin receptor (CLR) reported to be targeted by surface glycans on Rubela virus. Please explain in a few lines, via the principle of pattern recognition receptor rewiring, how the immune suppression by Rubela virus could be mediated.

My teacher's answer: Triggering of DC-SIGN along with e.g. TLR7/8 would activate NF-κB, but block IRF activation. This would lead to weak IL-12p70 induction, and instead propagate IL-23, and perhaps IL-10 levels in DC.

My question is, how is NF-κB activated, but IRF blocked? I would say that both will be activated, when the TLRs are triggered. Also, how does IL-23 get in the picture? I would say that TLR7/8 would give a type 1 response, and the DC-SIGN would give a regulatory T cell response.


C-type lectin receptor-induced NF-κB activation in innate immune and inflammatory responses

The C-type lectin receptors (CLRs) belong to a large family of proteins that contain a carbohydrate recognition domain (CRD) and calcium binding sites on their extracellular domains. Recent studies indicate that many CLRs, such as Dectin-1, Dectin-2 and Mincle, function as pattern recognition receptors (PRRs) recognizing carbohydrate ligands from infected microorganisms. Upon ligand binding, these CLRs induce multiple signal transduction cascades through their own immunoreceptor tyrosine-based activation motifs (ITAMs) or interacting with ITAM-containing adaptor proteins such as FcRγ. Emerging evidence indicate that CLR-induced signaling cascades lead to the activation of nuclear factor kappaB (NF-κB) family of transcriptional factors through a Syk- and CARD9-dependent pathway(s). The activation of NF-κB plays a critical role in the induction of innate immune and inflammatory responses following microbial infection and tissue damages. In this review, we will summarize the recent progress on the signal transduction pathways induced by CLRs, and how these CLRs activate NF-κB and contribute to innate immune and inflammatory responses.


ORIGINAL RESEARCH article

Xiaolong Yan 1,2 , Xueyan Zhao 1 , Ruixuan Huo 1 and Tianjun Xu 1,2,3,4,5*
  • 1 Laboratory of Fish Molecular Immunology, College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China
  • 2 Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
  • 3 National Pathogen Collection Center for Aquatic Animals, Shanghai Ocean University, Shanghai, China
  • 4 Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai, China
  • 5 International Research Center for Marine Biosciences, Ministry of Science and Technology, Shanghai Ocean University, Shanghai, China

MyD88 is a conserved intracellular adaptor, which plays an important role in the innate immune system. MyD88 transmits signals for downstream of toll-like and IL-1 receptors to activate NF-㮫 signaling pathway, which is tightly controlled in the immune response to maintain immune intensity and immune homeostasis at different stages. NF-㮫 signaling pathway has been extensively studied in mammals, but regulatory molecular mechanism is still unclear in teleost fish. We determined that IRF3 and IRF8 can regulate MyD88-mediated NF-㮫 signaling pathway in fish. Interestingly, MyD88 is precisely regulated by IRF3 and IRF8 through the same mechanism but in completely opposite ways. IRF3 promotes MyD88-mediated NF-㮫 signaling pathway, whereas IRF8 inhibits the signaling pathway. MyD88 is regulated via ubiquitin–proteasome degradation, whereas IRF3 or IRF8 inhibited or promoted MyD88 degradation in this pathway. Specifically, in the early stage of lipopolysaccharide (LPS) stimulation or Vibrio infection, up-regulation of IRF3 and down-regulation of IRF8 eventually increased MyD88 expression to activate the NF-㮫 signaling pathway to trigger immune response. In the late stage of stimulation, down-regulated IRF3 and up-regulated IRF8 synergistically regulate the expression of MyD88 to a normal level, thus maintaining the immune balance of homeostasis and preventing serious damage from persistent over-immunization. This study presents information on Myd88–NF-㮫 signaling pathway in teleost fish and provides new insights into its regulatory mechanism in fish immune system.


MATERIALS AND METHODS

Cell lines, virus, and animals.

The guinea pig cell line CRL 1405 was subcloned, and cells that were highly susceptible to BDV infection were used as a standard laboratory cell line for BDV infection (19). Furthermore, Vero cells were used throughout this study. Cells were cultured in Iscove's modified Eagle's medium (IMDM) supplemented with 5% fetal calf serum (FCS), 2 mM l -glutamine, and 100 U/ml gentamicin.

The fourth rat passage of the Giessen BDV strain He/80 was used for infections (40). In general, adherent cells were infected with a multiplicity of infection (MOI) of 0.01 to 1 in either 96-well or 6-well plates for 1 h in a volume of 25 μl (for 96-well plates) or 200 μl (for 6-well plates) of IMDM-2% FCS. For mock infections, 10% normal rat brain homogenate in IMDM-2% FCS was used. Thereafter, culture medium was added and the cells were cultivated for 5 to 7 days.

Female Lewis rats were obtained from the animal breeding facilities at the Friedrich Loeffler Institut, Bundesforschungsinstitut für Tiergesundheit, T࿋ingen, Germany. At the age of 6 weeks, the rats were infected intracerebrally in the left brain hemisphere with 0.05 ml of BDV, corresponding to 5 × 10 3 focus-forming units.

Retroviral infection of CRL 1405 cells.

The retroviral expression vectors and stable producer cell lines used for this study were described previously (12). Two days before infection, CRL cells were seeded in six-well plates at a density of 5 × 10 4 cells/well. For infections, cell culture supernatants containing the retroviral vectors were added to the CRL cells and the culture plates were centrifuged at 100 × g for 3 h. Thereafter, the supernatants were replaced with culture medium. The transfection efficiency was controlled for 2 days after infection, and if the transfection efficiency was below 20%, the infection procedure was repeated to increase the efficiency of infection/transfection, which ranged between 20 and 50%. The cells were cultured in the presence of 1 mg/ml zeocin (Invitrogen) for 2 weeks or until all cells were positive for green fluorescent protein (GFP), which was monitored by fluorometric analysis using a FACSCalibur flow cytometer (Becton Dickinson). Prior to each experiment, the cells were again screened for GFP fluorescence.

Electrophoretic mobility shift assay (EMSA).

For preparations of nuclear extracts, 2 × 10 5 CRL cells were seeded in 60-mm cell culture dishes and either infected with BDV (MOI = 1) or left uninfected on the next day. After 6 days, uninfected cells were stimulated with tetradecanoyl phorbol acetate (TPA 0.3 μg/ml) for 40 min. Cells were washed twice with cold phosphate-buffered saline (PBS) and then harvested in 400 μl of buffer A (10 mM KCl, 10 mM HEPES [pH 7.9], 0.1 mM EDTA, 0.1 mM EGTA, 1 mM dithiothreitol [DTT], and 1 mM phenylmethylsulfonyl fluoride). After 15 min of shaking at 4ଌ, 25 μl 10% Nonidet P-40 was added for 2 min, and the nuclei were pellet and resuspended in 50 μl of buffer B (20 mM HEPES [pH 7.9], 0.4 M NaCl, 1 mM EDTA, 1 mM EGTA, and 1 mM DTT). After 20 min of shaking and subsequent centrifugation, the protein concentrations of the nuclear extracts were determined (Bio-Rad, Germany). Eight micrograms of nuclear extract was incubated with 4 μg poly(dI-dC) 2 in binding buffer (0.1 M KCl, 10 mM Tris-HCl [pH 7.5], 5 mM MgCl2, 1 mM DTT, and 10% glycerol). After 20 min, 2 × 10 4 to 5 × 10 4 cpm of a 32 P-labeled double-stranded oligonucleotide (5′-GATCCAGAGGGGACTTTCCGAGTAC-3′) was added to the mixture and further incubated for 10 min at room temperature. Thereafter, the samples were separated in nondenaturing 5% polyacrylamide gels. After drying, the gels were subjected to autoradiography.

Luciferase reporter gene assay.

Cells (2.5 × 10 4 ) in 24-well plates were transfected with 0.05 μg 3× 㮫 reporter plasmid and 0.1 μl Lipofectamine 2000 (Invitrogen). After 5 h, the cells were stimulated with 0.3 μg/ml TPA. Twenty-four hours after transfection, the cells were harvested in 100 μl of lysis buffer (50 mM sodium morpholineethanesulfonic acid [Na-MES], 50 mM Tris-HCl [pH 7.5], 0.2% Triton X-100, and 1 mM DTT). The lysates were centrifuged for 5 min at 15,000 × g. For determination of the luciferase activity, 20 μl of cleared lysate was added to 50 μl of assay buffer (125 mM Na-MES, 125 mM Tris-HCl [pH 7.5], 25 mM magnesium acetate, and 2.5 mg/ml ATP) and quantified in a luminometer (Lumat LB 9501) using 50 μl of substrate solution (0.5 mM Luciferin, 1 mM NaOH). For normalization, protein concentrations were determined by the Bradford method (Bio-Rad).

Infectivity assay.

Virus infectivity was determined by the use of CRL 1405 cells. The cells were cultured for 7 days in the presence of different dilutions of BDV-infected cell lysates in flat-bottomed 96-well microtiter plates. Thereafter, cells were fixed with 4% paraformaldehyde-PBS and permeabilized with 1% Triton X-100-PBS. The presence of viral antigens was demonstrated by an immunohistochemical reaction using mouse anti-BDV monoclonal antibodies. The nonspecific binding of immunological reagents was blocked by incubation of the plates with 10% fetal calf serum-PBS. The reaction of monoclonal antibodies with cells was detected by use of a secondary anti-species biotin-labeled antibody (Dianova) and a streptavidin-peroxidase conjugate (Dianova). The reaction was visualized with ortho-phenylenediamine and H2O2 (Sigma).

Treatment with interferon.

CRL cells were infected with BDV (MOI = 0.1) and at 3 days postinfection (p.i.) were treated with either 100, 10, or 1 U of universal IFN-α/β (PBL Biomedical Laboratories) for an additional 3 days in 3 ml of culture medium. Thereafter, the viral infectivity was determined by the standard assay described above.

Immunohistochemistry.

Brain samples were obtained at different time points after infection and were fixed in 4% paraformaldehyde. All tissue sections were stained with hematoxylin-eosin. Immunohistochemistry was carried out for the presence of BDV-specific antigens, using an anti-BDV nucleoprotein-specific mouse monoclonal antibody (38/17C1) (55) as described previously (18), and for the detection of activated NF-㮫, using a pNF-㮫 (p65) phospho-specific rabbit antibody (NEB) at a 1:50 dilution. The staining reaction was enhanced by use of a biotinylated secondary antibody (1:200). For detection, an ABC kit (Vector) was used.


Discussion

Mechanistic Aspects.

Our working model for how U-STAT2, IRF9, and p65 collaborate on the IL6 promoter to enhance expression is shown in Fig. 3 G and H. We propose that STAT2 bridges the ISRE and κB elements by binding simultaneously to IRF9 and p65, bringing the potent transactivation domain of STAT2 into play to help activate the transcriptional machinery. As a component of U-ISGF3, STAT1 can participate in ISRE-dependent activation of IL6 expression, but it is not required since the U-STAT2–IRF9 complex functions well even without STAT1. However, STAT1 may assist by inducing the expression of U-STAT2 and IRF9 as target genes of phosphorylated ISGF3. Since the ISRE and κB elements are not close to one another in the linear DNA sequence of the promoter, it is likely that a loop is formed to facilitate their interaction. The high concentrations of U-STAT2 and IRF9 that help to drive IL6 expression are achieved late in response to type I IFNs, since the STAT1, STAT2, and IRF9 genes are all ISGs that are activated strongly by tyrosine-phosphorylated ISGF3 during the initial response to these IFNs. In many cancers, these three proteins, which comprise U-ISGF3, are expressed at a high level constitutively, as a result of exposure of the tumors to type I or III IFNs, or as a consequence of other inducing mechanisms, such as cell crowding (35). Although U-STAT2 plays a predominant role in driving IL6 expression, it remains possible that tyrosine-phosphorylated STAT2 also contributes. As shown in Fig. 1A, IL6 was induced 4 h after treatment with IFNβ, when tyrosine phosphorylation of STAT2 was apparent, but increased STAT2 expression was not.

The expression of IL6 in response to type I IFN requires that free NF-κB p65 is already present, but IFNβ does not liberate NF-κB from IκB in the cells we have studied. IL6 is not the only gene that is regulated by type I IFNs in an NF-κB–dependent manner, as both ISGF3 and NF-κB are required to induce expression of the βR1 gene in response to IFNβ (36). Signals generated in response to type I IFN interact with NF-κB–dependent signals in bone marrow-derived cells. In lymphoblasts, IFNα-induced activation of NF-κB is due to IκBα degradation, catalyzed by the IFN-dependent activation of PI3K and AKT (37). We show that IFNβ induces the expression of a small subset of NF-κB–dependent genes, including IL6, without activating the release of NF-κB from IκB or increasing the phosphorylation of p65. However, p65 is required for U-STAT2 plus IRF9 or IFNβ to induce IL6 expression.

We show that enhanced induction of IL6 by U-ISGF3 in combination with NF-κB stimulators depends on the presence of an ISRE in the IL6 promoter. In another study, Listeria monocytogenes and IFNβ were shown to induce the expression of the NOS2 and IL6 genes synergistically (38). Tyrosine-phosphorylated ISGF3 and NF-κB cooperatively regulate NOS2 transcription by recruiting STAT1 and p65 to a distant enhancer that is ∼30 kb upstream of the transcription start site (TSS), but not to putative ISREs located at −940 to −952 and −911 to −924. The cooperation of phosphorylated ISGF3 and NF-κB was considered to occur early in the response to type I IFNs, in agreement with our finding that priming by phosphorylated ISGF3 enhances IL6 induction in response to IL1 (Fig. 2B). In addition, synergistic induction of the IL6 gene in response to IFNγ and TLR-dependent signaling is associated with STAT1 occupancy at an enhancer that is ∼25 kb upstream of the TSS, followed by the priming of histone acetylation (39). Both studies show that STAT1 is recruited to the IL6 distal enhancer, thus increasing the formation of initiation complexes that include RNA polymerase II at the TSS. However, in our study, the enhanced activation of IL6 expression is much stronger in cells with high levels of U-ISGF3 than at early times in cells with phosphorylated ISGF3 (Fig. 2B). An ISRE at −1,513 to −1,526 in the IL6 promoter, rather than a much more distal enhancer, is responsible for the enhanced induction of IL6 expression in response to the U-ISGF3 that is formed late in the response to IFNβ, in combination with activators of NF-κB.

As an important coordinator of immune responses, NF-κB interacts with many other transcription factors. STAT3 and STAT1 interact with p65 physically. For example, STAT1α binds to p65, decreasing NF-κB nuclear localization and inhibiting target gene activation (40). We confirmed the interaction between U-STAT1 and p65 (Fig. 3 C and D) but it is not clear whether this interaction is direct. However, we did not detect the binding of p65 to IRF9, even though IRF9 is required for STAT2-induced NF-κB–dependent gene expression (Fig. 1I). U-STAT2 binds to IRF9 through its coil–coil domain (41), but we do not yet know which domain of U-STAT2 is responsible for its interaction with p65. However, we do know that the SH2 domain of STAT3 is essential for its interaction with NF-κB (38), suggesting that this domain of STAT2 might bind to p65 similarly.

The STAT1–NF-κB and STAT3–NF-κB complexes are likely to form in the cytosol, and we know that U-STAT2 is required for the translocation of p65 into the nucleus in bone marrow-derived macrophages (19). The EGF that is present in the culture medium for HME cells activates NF-κB (42, 43). However, we did not find a significant difference in the amount of IκBα bound to p65 when we compared HME cells with and without the expression of exogenous U-STAT2 (SI Appendix, Fig. S5C). We conclude that U-STAT2 and IRF9 do not affect the translocation of p65 into the nucleus in HME cells, in contrast to the situation in macrophages. IRF9 and STAT2 are required for enhanced IL6 expression but do not augment the expression of IL1 or IL8 in response to LPS (SI Appendix, Fig. S4 E and F), further supporting our conclusion that the ability of U-STAT2 and IRF9 to enhance NF-κB–dependent gene expression is promoter specific and probably dependent upon the presence of an ISRE element in the promoters of genes that show this cooperation.

We now find that IRF9 occupies a κB element that is very close to the transcription start site of the IL6 gene, and that p65 occupies a putative ISRE at the promoter in cells expressing high levels of both U-STAT2 and IRF9, but not in cells expressing a high level of IRF9 only. Combined with our finding that p65 interacts with U-STAT2 but not IRF9, the data strongly support our hypothesis that STAT2 functions as a bridge connecting p65 and IRF9 on the IL6 promoter. On the other hand, a recent study found that TNF induced the binding of NF-κB to an ISRE, driving the expression of some ISGs in hepatocytes (44). These findings suggest that the U-STAT2–IRF9–p65 complex might be assembled independently of κB elements, and that activation of NF-κB–dependent signaling might increase the formation of this complex, which might occupy ISREs at ISG promoters to drive a modest level of transcription. In summary, the U-STAT2–IRF9–p65 complex drives the transcription of a subset of NF-κB–dependent genes in response to type I and type III IFNs and a subset of ISGs in response to activators of NF-κB.

The Role of Synergistic Activation of IL6 Expression in Cancer.

Considering the important role of IL6 in the tumor microenvironment, we investigated the ability of U-STAT2 and IRF9 to regulate IL6 secretion in cancer cells, finding that decreasing the expression of IRF9 and U-STAT2 inhibited IL6 production and STAT3 activation in lung cancer HCC827 cells (Fig. 4 D and E), where STAT3 activation is dependent on autocrine IL6 (45). As a consequence, reducing the level of IRF9 repressed the growth of these cells (Fig. 4F), which contrasts with the function of ISGF3 as an activator of antiproliferative gene expression. Of note, decreasing IRF9 expression did not inhibit STAT3 activation and cell growth in normal fibroblasts (SI Appendix, Fig. S7). This is not the first time that ISGF3 has been found to promote cancer survival and metastasis. Our previous work showed that U-ISGF3 regulates about a quarter of IFNβ-induced ISGs (5), and that this subset is virtually identical to the set of IFN-induced genes in the interferon-related DNA damage resistance signature (IRDS) (46). In triple negative breast cancer cells, but not in ER-positive cells, the IRDS subset of ISGs is induced by a RIG-1 (DDX58)-dependent antiviral pathway when the cancer cells contact stromal fibroblasts (47). Additional functions of ISGF3 in cancer cell survival are not yet clear. Considering the instability of the cancer genome, ISGF3 might also play an important role in overcoming cell death induced by genomic instability in the process of tumorigenesis. We did not observe basal STAT2 tyrosine phosphorylation in the cancer cells that we studied. Therefore, U-STAT2–IRF9 and U-ISGF3 might be the principal mediators of collaboration with activators of NF-κB in cancer cells, and we did observe that high levels of U-STAT2 and IRF9 correlate with poor prognoses in lung adenocarcinoma. The U-STAT2–IRF9 complex, U-ISGF3, or both, may also interact with transcription factors other than NF-κB to induce the expression of genes that facilitate the growth of cancer cells.


Materials and Methods

The Institutional Review Board (IRB) at the Ohio State University has approved the in vitro experiments involving human blood cells from de-identified healthy donors. The consent requirements for the de-identified blood samples were waived by IRB. Primary monocytes were isolated from buffy coats purchased from American Red Cross Blood Service. MDMs were differentiated from monocytes as described (50). THP-1 control and THP-1/KO cell lines have been described previously (29). SeV and HIV-1 infection assays were performed as described previously (32, 39). Detailed materials and methods can be found in SI Appendix.


IRFs in Co-Binding Mechanisms of Transcriptional Regulation

Another layer of transcriptional regulation in which IRFs play a role can be found in enhancing and co-binding mechanisms. Transcription factors including IRF3/IRF7, ATF-2/c-Jun, NF-㮫 and architectural protein HMGI(Y) assemble together to form an enhanceosome (62, 77). Cooperative binding of transcription factors to the IFNβ enhancer region stimulates transcription of the IFNβ gene. It has been observed that binding-induced changes in DNA conformation and not the surface of protein-protein interactions is crucial for cooperative binding and transcriptional activation. Detailed analysis of this enhanceosome assembly was conducted on crystal structures of the DNA-binding domains of human IRF3, IRF7, and NF-㮫 bound to the IFNβ enhancer (PDB IDs𠄱T2K, 2O61, 2O6G) (62, 125). Additionally, IRF3 has been shown to interact with CBP, STING, MAVS, and TRIF adaptor proteins. Studies on the structure of the IRF3 phosphomimetic mutant S386/396E bound to CBP (5JEM) suggested that a conserved pLxIS motif is responsible for this cooperation.

A wide range of studies have identified a plethora of genes which are upregulated by the co-activating effects of NF-㮫 and IRFs. The first suggestion of such co-activating effects was of IRF1 and NF-㮫, present within the IFN regulatory element (IRE) of the IFNβ promoter. NF-㮫 upregulates IFNβ gene expression by binding two recognition sites in its promoter. These recognition sites flank the PRD-I motif on which IRF1 binds (1, 126, 127). IRF1/NF-㮫 co-activation therefore relies on both ISRE and 㮫 binding, in which IRFs and Nf㮫 sit next to each other on the DNA ( Figures 1C , ​ ,3). 3 ). IRF1 by itself is enough to upregulate IFNβ after Newcastle Disease viral infection, while NF-㮫 alone was shown not to induce upregulation. However, as mentioned before, the upregulation of IFNβ was far more potent when IRF1 and NF-㮫 bound simultaneously to its promoter region (1).

Cross-regulation between NF-㮫 and IRF3-activated signaling pathways is also evidenced by the presence of multiple 㮫 and ISRE binding sites in gene regulatory regions (42). The mechanism of IRF3/NF-㮫 is the same as described for IRF1/NF-㮫. Concerted action of NF-㮫 and IRF3 is mandatory for transcriptional activation of multiple genes, including chemokines Cxcl10 and Ccl5, activator of inflammasome Gbp5, Immune-Responsive Gene 1, and IFNβ1. Detailed activation kinetics analysis suggested that individual genes within this small cluster use distinct regulatory mechanisms (128, 129). Moreover, virus-induced genome-wide occupancy of IRF3 and p65/RelA binding sites correlated with co-binding of other antiviral transcription factors (130). Mechanistically, NF-㮫 was found in a genome-wide study of Wienerroither et al. to recruit the mediator kinase module of the transcription complex, while STATs in ISGF3 contact the core mediator module of the transcription complex, both necessary for successful gene transcription (131). Indeed, other genome-wide studies established that also in genes activated by IRF3 and RelA binding, MED1 and Polymerase II binding occurred at overlapping positions in the promoters, suggesting their roles in transcription complex recruitment (130).

More recently, interplay between IRF5 and NF-㮫 has also been revealed. The induction of the TLR7 pathway by Imiquimod lead to the upregulation of IRF5 via the activation of NF-㮫 and PU.1, which were found to bind to the first two exons of the IRF5 gene (132). Moreover, NF-㮫 plays a role in the recruitment of IRF5 to the non-canonical composite PU.1-ISRE binding sites in promoters of inflammatory genes in macrophages after LPS stimulation (133).

Together, these studies suggest that IRFs collaborate globally with NF-㮫 and other co-activators utilizing diverse regulatory mechanisms to precisely induce distinct transcriptional regulatory networks.


Macrophages as a Barrier to Chemotherapy and Immunotherapy

While the heterogeneity of TAM populations is still being deconvoluted, clinical evidence suggests that macrophages can contribute to shortcomings of chemo- and hyphenate immuno-therapy. High TAM density has been shown to be an independent poor prognostic marker in breast cancer patients, especially for HR-positive breast cancer (170). Importantly, macrophages have been shown to contribute to reduced efficacy of chemotherapy. Shree et al. discovered that in vitro cathepsin-expressing BMDMs shield mammary cancer cells from paclitaxel-induced cell death. They further demonstrated that tumors from MMTV-PyMT mice treated with paclitaxel had increased TAM infiltration, and cathepsin inhibition in combination with paclitaxel increased long-term survival (176). Similarly, tamoxifen-resistant ER-positive and HER2-negative clinical samples had a higher density of CD163+ macrophage populations and increased expression of EGFR than tamoxifen-sensitive samples, which positively correlated with tumor size and metastasis (177). Furthermore, macrophages can disrupt T cell infiltration, which immunotherapies rely on to mediate efficacy. For example, in lung cancer patients, macrophage exclusion of CD8+ T cells from tumor nests correlated with poor response to anti-PD-1 therapy. When macrophages were depleted with anti-CSF-1R therapy, CD8 T cells successfully infiltrated the tumor to interact with malignant cells and delay tumor progression (178). Also, importantly, in preclinical breast cancer models, when macrophages are depleted using anti-CSF-1R therapy (145, 178) or their phenotype was converted to an anti-tumor phenotype (179), anti-PD-1 therapy induced potent anti-tumor immunity. This highlights the deleterious effects of TAMs in tumors and the importance of targeting both innate and adaptive immune cells to achieve the full potential of immunotherapy and a durable anti-cancer immune response.

Targeting TAMs for Anti-Cancer Therapy

Both preclinical and clinical strategies to target the tumor-promoting functions of TAMs in cancer are being developed. These approaches have been reviewed in great detail and include inhibiting the recruitment of macrophages to tumors by blocking the CCL2�R2 or CCR5�L5 axes, depleting TAMs by blocking CSF-1 or CSF-1R blocking macrophage 𠇌heckpoint inhibitors” such as CD47/SIRP1α, PD-1/PD-L1, MHCI/LILRB1, and CD24/Siglec-10 and suppressing macrophages' pro-tumor activity (inhibition of TGF-β or VEGF) (36, 180�). Depletion or inhibition of macrophages using CCL2, CSF-1, and CSF-1R inhibitors has been shown to be effective against both mouse and human tumors (16, 36, 145, 185). Importantly, a recent study showed that CCL2 inhibition as a monotherapy led to more metastasis when the therapy was discontinued, which was driven in an IL-6- and VEGF-dependent manner (186). This study challenges the use of CCL2 as a monotherapy and highlights the need to understand the tumor microenvironment composition for successful anti-metastatic therapy.

CSF-1R is a promising target to address TAMs therapeutically, as high expression of CSF-1 or CSF-1R predicts cancer progression and mortality (187). Blockade of CSF-1R has been shown to decrease TAM infiltration, which subsequently results in the increase in CD8+ T cells and improves response to chemotherapy (95, 145). In a phase Ib study with advanced solid tumors, the combination of pexidartinib, a CSF-1R inhibitor, and paclitaxel was well-tolerated, and the combination showed reduced macrophage infiltration in the tumor microenvironment (188). However, in another phase I a/b study, emactuzumab, a monoclonal antibody against CSF-1R, showed reduction in immunosuppressive TAMs but did not demonstrate clinical benefit alone or in combination with paclitaxel (189). These studies suggest that a careful evaluation of the TME is important before deciding which patients would best benefit from CSF-1R therapy. Other caveats to anti-CSF-1R therapies include reports showing that inhibition of CSF-1R signaling can promote breast cancer metastasis (190).

To enhance anti-CSF-1R therapies, combining anti-CSF-1R with complementary chemotherapy and agents that enhance T cell function may markedly improve outcomes. In that regard, a recent study showed that addition of a CD40 agonist before anti-CSF-1R therapy induced a short-lived hyperactivated macrophage state that was enough to generate an effective T cell response in ICB-resistant tumors (191). Additionally, we have recently shown that CSF-1R inhibition leads to a significant reduction in TAMs and when combined with PARP inhibitor therapy results in an increase in overall survival, with some mice experiencing tumor-free survival for at least 1 year (159). Studies with CSF-1R signaling antagonists, combined with the drug paclitaxel or carboplatin, showed enhanced tumor control and reduced metastasis in preclinical models of breast cancer. Importantly, blockade of CSF-1 signaling also enhanced anti-tumor immunity and cytotoxic T cell infiltration to chemotherapy (145). The blockade of the CCR5�L5 axis, which decreased macrophage infiltration in tumors, is another exciting therapeutic target with ongoing clinical trials for breast cancer (192).

An alternative strategy is to convert pro-tumor TAMs to an anti-tumor phenotype. CD40 agonists (193), PI3Kγ inhibitors (194), CD47 inhibitors (195), and a class IIa HDAC inhibitor (179) have all been shown to reduce primary and metastatic murine breast tumors (179) and have emerged as novel modalities to convert TAMs to anti-tumor macrophages. In addition, other strategies have been shown to convert TAMs to an M1 phenotype and include Bruton's tyrosine kinase (BTK) inhibitors (196), TLR agonists (197), STAT3 inhibitors (198), IL-1Ra inhibitors (199), and LILRB2 inhibitors (200) Taken together, strategies to deplete or inhibit suppressive TAM functions or activate anti-tumor TAMs combined with chemotherapy and/or immunotherapy may have a great potential for the treatment of breast cancer patients. However, while many of these compounds in preclinical and clinical development are now filling our toolbox with TAM-targeting strategies, it will likely be necessary to further elucidate the complexity of TAM subsets including their ontogeny and phenotype for successful therapeutic targeting ( Figure 4 ).

Macrophage-targeting strategies for anti-cancer therapy have started to fill our toolbox. We now need to understand how these compounds work, which subsets of TAMs they modulate, and which breast cancer patients will benefit.

Therapeutic Targeting of TAM Metabolism for Anti-Cancer Therapy

The metabolic programming of TAMs is complex, and the underlying molecular mechanisms and crosstalk between tumor cells and stroma remain to be characterized. An in-depth analysis of these metabolic circuits may facilitate better appreciation for the functional fates of macrophages, including their pro- vs. anti-tumor phenotype. This important information would further support the clinical application of targeting TAM metabolism for anti-cancer therapy. There is some insight of the potential of this strategy from several recent publications that utilized other immune cell types including Tregs. Recently, Tregs were shown to activate the sterol regulatory element-binding protein 1 (SREBP1)-mediated fatty acid synthesis pathway in TAMs. SREBP1 induced M2-TAM metabolic fitness, mitochondrial integrity, and survival (201). Pharmacological inhibition of de novo fatty acid synthesis using a SREBP1 inhibitor, fatostatin, showed anti-tumor immunity when combined with ICB (anti-PD-1) in a B16 melanoma preclinical tumor model (201). Our group recently reported that PARP inhibition directly modulated macrophage metabolism by shunting glycolysis and inducing a dependence on lipid metabolism, which generated an immunosuppressive TME by inhibiting T cell function and thereby contributed to PARP inhibitor resistance (159). The use of fatostatin in combination with PARP inhibition and macrophage modulation significantly enhanced the overall survival of mice bearing brca1-deficeint TNBC (159). In line with our findings, inhibition of PARP induced upregulation of lipogenic genes by modulating the transcription factor specificity protein 1 (Sp1), which leads to the accumulation of lipid droplets in the liver (202). Similarly, a study suggested that genetic deletion as well as pharmacologic inhibition of PARP induced the expression of ATP-binding cassette transporters (ABCA1) and cholesterol efflux in macrophages (203). These studies highlight the role of both Tregs and PARP inhibitors in regulating macrophage lipid metabolism. Further molecular understanding on the mechanisms of how PARP inhibitors regulate TAM metabolism would provide future opportunity for promising therapeutic strategies.

In a preclinical syngeneic model of pancreatic ductal adenocarcinoma (PDAC), a TLR9 agonist, CpG oligodeoxynucleotide, induced a metabolic state that required fatty acid oxidation and shunting of TCA intermediates for de novo lipid biosynthesis. This shift in central carbon metabolism activated highly phagocytic macrophage that could overcome the CD47 𠇍on't-eat-me” signals on tumor cells to mediate an antitumor response (204). Macrophages cultured with PDAC-conditioned media compared to normal pancreatic cells had higher levels of vascular network formation, enhanced metastatic potential, increased levels of EMT, and a pronounced glycolytic signature. Inhibiting hexokinase II (HK2) with 2-deoxyglucose (2DG) inhibited glycolysis and reversed the pro-tumor TAM phenotype, highlighting the therapeutic potential of modulating TAM metabolism for anti-cancer therapy (205). Molecular metabolic control of TAMs has been demonstrated in vitro by inhibiting glutamine synthetase (GS). In human monocytes, GS expression activates an M2-like phenotype, which is reversed through pharmacological inhibition of GS by methionine sulfoximine (MSO). Inhibition of GS resulted in production of succinate, a critical regulator of the pro-inflammatory response, and enhanced glucose flux through glycolysis. Importantly, in ex vivo studies, GS restored T cell recruitment. In vivo, genetic deletion of macrophage-specific GS reduced metastasis in a preclinical mouse model of lung cancer (206). Taken together, precisely targeting the metabolic rewiring of TAMs may re-educate their phenotype and may overcome TAM-associated immunosuppression.


Results And Discussion

DAI/ZBP1 recruits RIP1 and RIP3 through RHIM domains

Analysis of the DAI amino-acid sequence revealed, in addition to the two known amino-terminal Z-DNA binding domains Zα and Zβ, two other conserved regions located in the central portion of the protein (supplementary Fig S1 online). Further analysis identified these two sequences as potential RHIMs (RHIM1 and RHIM2 Fig 1A), which are known to mediate homotypic protein–protein interactions. For example, a RHIM is present in the TLR-adaptor protein TRIF, in which it is responsible for the recruitment of the kinases RIP1 and RIP3, two other RHIM-domain-containing proteins ( Meylan et al, 2004 ). Interaction between RIP1 and RIP3 was also shown to take place through a homotypic RHIM–RHIM interaction ( Sun et al, 2002 ). In TLR3 signalling, the RHIM-dependent TRIF–RIP1 interaction is crucial for NF-κB activation, whereas RIP3 competes for this interaction and thus acts as an inhibitor of TLR3-mediated NF-κB activation ( Meylan et al, 2004 ).

The presence of two RHIM domains in DAI suggested that, similar to TRIF, DAI might also interact with one or both of the RIP kinases. Indeed when co-expressed in human embryonic kidney (HEK)293T cells, human DAI co-immunoprecipitated with RIP1 and RIP3, but not with RIP2 and RIP4 (which lack RHIMs), nor with Cardif (MAVS, IPS-1, VISA), the adaptor protein essential for RIG-I/MDA5 signalling (Fig 1B Meylan et al, 2005 ). Similarly, murine DAI interacted with RIP1 and RIP3 (supplementary Fig S2 online).

To map the DAI–RIP1/3 interaction site, various deletion constructs were generated (Fig 1D). Co-immunoprecipitation experiments showed that only the constructs of RIP1 and RIP3 that retained the RHIM domain-coding region were able to bind co-expressed DAI (Fig 1C,E). Four residues in the RHIM domain of RIP1 and RIP3 were previously shown to be essential for RHIM-based interactions ( Sun et al, 2002 ). When these crucial residues were mutated to alanines, a total impairment of DAI recruitment was observed (Fig 1C,F).

To investigate the involvement of the two DAI RHIM domains in RIP1/3 recruitment, we also generated DAI constructs with alanine substitutions in the corresponding four core residues of their RHIMs, as well as DAI deletion constructs for the first or second RHIM, or entire region comprising these two domains (Fig 1G). All DAI constructs lacking a functional RHIM1 were unable to bind to RIP1/3, whereas the targeting of the RHIM2 did not affect this interaction when DAI and RIPs were overexpressed (Fig 1H,I supplementary Fig S2C,D online). Taken together, these results show that DAI has two RHIM domains, in addition to the two described Z-DNA binding domains, and that it recruits RIP1 and RIP3 through RHIM–RHIM homotypic interactions.

DAI-induced NF-κB activation is RHIM-dependent

Considering the crucial role of the RHIM-dependent TRIF–RIP1 association in mediating NF-κB activation on TLR3 stimulation, we next examined whether this domain has a similar role in DAI signalling.

Overexpression of human or murine DAI in HEK293T cells activated an NF-κB-dependent promoter in a dose-dependent manner (Fig 2A data not shown). For this activity, the full-length protein was required, as the N- or C-terminal deletion constructs were inactive, regardless of the presence or absence of the RHIM domains (supplementary Fig S3A online). In contrast to NF-κB, neither human nor murine full-length or deletion DAI constructs significantly activated IRF transcription factors, as monitored by an interferon-stimulated regulatory element promoter (supplementary Fig S3B online data not shown) or by the upregulation of the interferon-inducible protein RIG-I (supplementary Fig S3C online). By contrast, Cardif or a dominant-active form of RIG-I potently activated IRFs in the same experimental setting, and acted as positive controls.

DAI constructs with mutations in the first or in both RHIMs were found to be unable to induce NF-κB activation (Fig 2A). Identical results were obtained with the corresponding deletion constructs, supporting the essential requirement of a functional RHIM1 domain. Furthermore, mutation or deletion of DAI RHIM2 resulted in a strong impairment of DAI activity (Fig 2A), indicating that RHIM2 is also important for DAI function.

In accordance with these functional data, we observed that overexpressed wild-type DAI co-immunoprecipitated with endogenous RIP1, and that mutation or deletion of RHIM2 strongly affected this interaction (Fig 2B supplementary Fig S4A online). This is in contrast to the data with overexpressed proteins (Fig 1H,I) and suggests that the DAI RHIM2 domain also contributes to the recruitment of RIP1 under more physiological conditions. As expected, DAI constructs lacking functional RHIM1 were unable to bind to endogenous RIP1 (Fig 2B supplementary Fig S4A online).

In addition to these observations, it was also observed that DAI induces NF-κB activation synergistically when co-expressed with RIP1 and RIP3 (supplementary Fig S4B,C online). This effect was not observed on co-expression of DAI 2RHIM * mutant, which is unable to bind to the two RIPs, nor when the RIP3 RHIM mutant was used. It should be noted that a kinase-inactive RIP3 (K50A) mutant did not show the synergistic NF-κB activation with DAI.

To corroborate the results of the NF-κB reporter assay, we generated HEK293-TRex cells expressing full-length or Δ2RHIM DAI in an inducible manner. In this system, induced expression of wild-type DAI led to spontaneous I-κB phosphorylation and degradation, whereas induction of the DAI Δ2RHIM protein had no effect (Fig 2C).

These observations emphasize the ability of DAI to activate NF-κB and further show that both RHIM domains are crucial for this activity.

RIP1 and RIP3 mediate DAI signalling to NF-κB

The results presented above suggest that RIP1 and possibly RIP3 are essential for DAI-mediated NF-κB activation. To verify this, the expression of RIP1 and RIP3 was knocked down using short interfering RNA (siRNA supplementary Fig S5A,B online). Silencing of RIP1 with two different oligonucleotides (but not a control siRNA) clearly impaired DAI-mediated NF-κB activation (Fig 3A). Interestingly, downregulation of RIP3 using two different siRNAs also resulted in a strong reduction of DAI signalling to NF-κB (Fig 3A). Therefore, it seems that both RIP1 and RIP3 participate in mediating DAI downstream events resulting in NF-κB activation. This situation is different from that which occurs in TRIF signalling, the second RHIM-dependent NF-κB activating pathway, where RIP3 acts as an inhibitor by competing with RIP1 for binding to the RHIM of TRIF ( Meylan et al, 2004 ). In support of the requirement of both kinases for DAI signalling, RIP1 and RIP3 can form a complex with DAI (Fig 3B).

A further indication that RIP3 is part of the DAI signalling complex comes from the observation that co-expression of these two proteins resulted in the appearance of a form of RIP3 that migrates more slowly on SDS–PAGE, which probably originates from post-translational modifications (Figs 1F, 3C,D). This change was absent when the RIP3 RHIM mutant (Figs 1F, 3C) or the DAI double-RHIM mutant constructs (Fig 3D) were used, but was present on RIP1 and RIP3 co-expression. This suggests that the assembly of the DAI–RIP1–RIP3 complex is necessary to induce RIP3 modifications. To determine the nature of the upper form of RIP3, immunoprecipitates of RIP3 were analysed using antibodies specific for phosphorylated serine (P-Ser), phosphorylated threonine (P-Thr) and ubiquitin. No signal was detected for P-Ser or ubiquitin by contrast, a strong signal corresponding to the upper form of RIP3 was obtained using the P-Thr antibody (Fig 3C data not shown). The absence of a P-Thr signal in the RIP3 RHIM-mutant immunoprecipitate argues for its specificity. Furthermore, treatment with calf intestinal alkaline phosphatase abolished the basal, as well as the DAI- and RIP1-induced migratory shift of RIP3 (Fig 3D), further indicating that this upper band is a hyper-phosphorylated form. When a kinase-inactive RIP3 (K50A) mutant construct was used, both basal and DAI-induced phosphorylations were abolished (Fig 3E). This suggests that the DAI and RIP3 interaction drives RIP3 autophosphorylation. RIP1 does not seem to be essential for DAI-induced RIP3 phosphorylation as this is still observed after RIP1 knockdown (supplementary Fig S6 online). Our results raise the interesting question of whether the lack of synergy in NF-κB induction between the kinase-inactive RIP3 and DAI (supplementary Fig S4C online) might be due to the absence of DAI-induced RIP3 autophosphorylation.

Collectively, these results show that both RIP1 and RIP3 contribute to DAI-induced NF-κB activation, and that recruitment of RIP3 to DAI induces its autophosphorylation.

The MCMV protein M45 inhibits DAI signalling

Viruses have evolved strategies to interfere with antiviral signalling pathways. A clear example is the RIG-I/MDA5 viral RNA-sensing pathway, which is targeted by various viruses such as hepatitis C or influenza viruses.

In a bioinformatics search for other RHIM-containing proteins, we found that this domain was also present in protein 45 of three related double-stranded DNA-containing herpes viruses: MCMV (or murid herpesvirus1), rat cytomegalovirus and tupaiid herpesvirus 1 (supplementary Fig S7A online). Interestingly, protein 45 of the MCMV (M45) is crucial for productive viral replication in macrophages and endothelial cells ( Brune et al, 2001 ), and is essential for the MCMV spread and pathogenesis in vivo ( Lembo et al, 2004 ). Recently, Upton et al (2008) identified the RHIM of MCMV M45 to be crucial for the suppression of cell death during infection. Moreover, M45 inhibits RIP1-dependent signalling by tumour necrosis factor (TNF Mack et al, 2008 ).

These observations led us to hypothesize that M45 could target DAI signalling. M45 is post-translationally processed at amino acid 277 during infection ( Lembo et al, 2004 ) and the RHIM-containing fragment (aa 1–277) retains RIP-binding and cell death suppression activity ( Upton et al, 2008 ). Therefore, we generated a construct corresponding to this polypeptide and tested its ability to bind to DAI, RIP1 and RIP3. As expected, interaction with both RIP kinases was observed (Fig 4A). M451−277 also bound to DAI, which was dependent on functional DAI RHIMs as shown by the absence of binding to the DAI RHIM double mutant (Fig 4A).

Next we tested the effect of M451−277 on DAI signalling. Co-expression of M451−277 inhibited DAI-induced NF-κB activation in a dose-dependent manner as monitored by reporter assay (Fig 4B). This inhibitory activity was again completely dependent on a functional RHIM, as a RHIM-mutated M451−277 construct had no effect (Fig 4B).

Reports from Upton et al (2008) and Mack et al (2008) showed the ability of M45 to target RIP1. The first identified the RHIM of MCMV M45 to be crucial for suppression of cell death, whereas the second mapped the inhibitory activity of M45 in RIP1-dependent signalling by TNF to its C-terminal portion (aa 977–1174). To clarify which of these two mechanisms account for the effect on DAI signalling, we generated the various M45 constructs used in these studies (supplementary Fig S7B online).

According to Mack et al (2008) , M45 constructs with the C-terminal part (aa 977–1174) could reduce TNF-induced NF-κB activation. By contrast, we found that these same constructs, when expressed alone, induced a moderate but consistent NF-κB activation on their own (supplementary Fig S7C online). In support of the requirement for the RHIM, but not the C-terminal domain of M45 to inhibit DAI signalling, we observed that an M45 construct comprising amino acids 1–976 blocked the DAI-induced NF-κB activation, and that this effect was abrogated by mutating the RHIM domain (Fig 4B).

Considering that M451−277 interacts with the DAI RHIM domain, we hypothesized that this could affect the recruitment of RIP1 and RIP3. Indeed, binding of RIP1 and/or RIP3 to DAI was strongly affected by the co-expression of RHIM-containing M45 constructs (Fig 4C,D data not shown). By contrast, the interaction between DAI and RIP kinases was altered neither by the expression of RHIM-mutated M45 constructs nor by the M45 C-terminal cleavage fragment. Interestingly, RIP3 phosphorylation was inhibited by M45 in an identical RHIM-dependent manner (Fig 4D). Thus, the MCMV M45 protein has the potential to block DAI signalling to NF-κB by interfering with the RHIM-dependent recruitment of RIP1 and RIP3. In line with this, one might consider the idea that M45 could also interfere with the DAI–RIPs complex by targeting not only DAI RHIMs but also RIP1 and RIP3 RHIM domains.

In summary, we have identified DAI as a new RHIM-containing protein, and provide evidence that these domains are crucial for the recruitment of RIP1 and RIP3, and subsequent NF-κB activation, which is in agreement with the recent report from Kaiser et al (2008 ). Furthermore, the MCMV M45 protein has the potential to block this pathway by disrupting DAI–RIP interactions. This, together with the observation by Upton et al (2008) that M45 is crucial for the suppression of cell death during MCMV infection, makes it highly probable that inhibition of DAI signalling contributes to the requirement of M45 for MCMV replication and pathogenesis in vivo.


Supplementary Material

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Keywords: NFAT, Syk, CR3, phenol glycolipid-1, Mycobacterium leprae, dendritic cell, macrophage, neutrophil

Citation: Doz-Deblauwe É, Carreras F, Arbues A, Remot A, Epardaud M, Malaga W, Mayau V, Prandi J, Astarie-Dequeker C, Guilhot C, Demangel C and Winter N (2019) CR3 Engaged by PGL-I Triggers Syk-Calcineurin-NFATc to Rewire the Innate Immune Response in Leprosy. Front. Immunol. 10:2913. doi: 10.3389/fimmu.2019.02913

Received: 30 August 2019 Accepted: 27 November 2019
Published: 17 December 2019.

Andrea Cooper, University of Leicester, United Kingdom

Roland Lang, University Hospital Erlangen, Germany
John S. Spencer, Colorado State University, United States

Copyright © 2019 Doz-Deblauwe, Carreras, Arbues, Remot, Epardaud, Malaga, Mayau, Prandi, Astarie-Dequeker, Guilhot, Demangel and Winter. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

† Present address: Ainhoa Arbues, Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland