C57BL/6 mice (wild type) were obtained from Jackson Laboratories (Bar Harbor, ME, USA). MARCO-deficient (MARCO^−/−) mice, obtained initially from Dr. Lester Kobzik (21), were bred and housed under specific pathogen-free conditions in the Animal Care Facility at the VA Ann Arbor Healthcare System. Both male and female mice were between the ages of 6–12 week at the time of infection and were humanely euthanized by CO₂ inhalation at the time of data collection. All experiments were approved by the Institutional Animal Committee on Use and Care and the Veterans Administration Institutional Animal Care and Use Committee under protocol # 0512-025 and were carried out according to NIH guidelines and the Guide for the Care and Use of Laboratory Animals.

Cryptococcus neoformans strain 52D was recovered from 10% glycerol frozen stocks stored at −80°C and grown to stationary phase at 37°C using Sabouraud dextrose broth (1% Neopeptone, 2% dextrose; Difco, Detroit, MI, USA) on a shaker. The cultures were centrifuged and washed with non-pyrogenic saline (Travenol, Deerfield, IL, USA). Cells were counted via hemocytometer and diluted to 3.3 × 10⁵ yeast/ml in sterile non-pyrogenic saline.

Mice were anesthetized via intraperitoneal (i.p.) injection of ketamine (100 mg/kg body weight) plus xylazine (6.8 mg/kg) and were restrained on a foam plate. A small incision was made through the skin covering the trachea. The underlying salivary glands and muscles were separated. A 30-G needle was attached to a 1 ml tuberculin syringe with C. neoformans suspension (3.3 × 10⁵ yeast/ml) and infection was performed by intratracheally injecting 30 µl (10⁴ CFU) of inoculum into the lungs. After inoculation, the skin was closed with cyanoacrylate adhesive and the mice were monitored during recovery from the anesthesia.

The lungs from each mouse were excised, washed in RPMI 1640 and digested enzymatically as previously described (30). In brief, lungs were minced with scissors followed by Gentle MACS homogenization and incubated at 37°C for 35 min in 5 ml/mouse digestion buffer [RPMI 1640, 5% FBS, penicillin, and streptomycin (Invitrogen, Grand Island, NY, USA); 1 mg/ml collagenase A (Roche Diagnostics, Indianapolis, IN, USA); and 30 µg/ml DNase I]. The cell suspension and tissue fragments were further dispersed by Gentle MACS homogenization and were centrifuged. Erythrocytes in the cell pellets were lysed by addition of 3 ml NH₄Cl buffer (0.829% NH₄Cl, 0.1% KHCO₃, and 0.0372% Na₂EDTA, pH 7.4) for 3 min followed by a threefold excess of RPMI 1640. Cells were re-suspended and subjected to syringe dispersion and filtered through a sterile 100-µm nylon screen (Nitex, Kansas City, MO, USA). The filtrate was centrifuged for 30 min at 1,500 × g with no brake in the presence of 20% Percoll (Sigma) to separate leukocytes from cell debris and epithelial cells. Leukocyte pellets were re-suspended in complete RPMI 1640 media and enumerated on a hemocytometer after dilution in trypan blue (Sigma).

For determination of fungal burden, small aliquots of digested lungs, spleens, and brains were collected. Series of 10-fold dilutions of the samples were plated on Sabouraud dextrose agar plates in duplicate 10-µl aliquots and incubated at room temperature. C. neoformans colonies were counted 2 days later and the number of CFU was calculated on a per-organ basis.

Individual LALN were excised and then dispersed using a 1-ml sterile syringe plunger and flushed through a 70-µm cell strainer (BD Falcon, Bedford, MA, USA) with complete media into a sterile tube. After being centrifuged at 2,500 rpm/min for 5 min, the supernatant was removed and the cell pellets were used for gene expression analysis by quantitative real-time RT-PCR (qRT-PCR) or flow cytometry.

Spleens were excised and dispersed using a 3-ml sterile syringe plunger and flushed through a 70-µm cell strainer (BD Falcon) with complete media. Isolated spleen cells were cultured in media with heat-killed C. neoformans in a ratio of 1:2 in 6-well plates with 2 ml complete RPMI 1640 medium at 37°C and 5% CO2 for 48 h. Supernatants were stored and analyzed for cytokine levels as described earlier. The Ag-specific cytokine production was quantified using a LEGENDplex cytometric bead array (CBA) kit (BioLegend, San Diego, CA, USA) following the manufacturer’s specifications and read on an LSRII flow cytometer (Becton, Dickinson Immunocytometry Systems, Mountain View, CA, USA). Analysis was performed using BioLegend’s LEGENDplex software.

Serum was obtained from the blood samples collected by severing the vena cava of the mice before lung excision. Blood samples were then allowed to clot and were spun to separate serum. Serum samples were diluted 100-fold and assayed for total IgE levels using a mouse IgE sandwich ELISA kit (BioLegend, San Diego, CA, USA) following the manufacturer’s specifications.

Total RNA from lung leukocytes was prepared using TRIzol reagent (Invitrogen), and first-strand cDNA was synthesized using Reverse Transcription Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Relative gene expression was quantified with SYBR green-based detection (Alkali Scientific) using a light cycler96 system (Roche) according to the manufacturer’s protocols. Relative gene expression was normalized to 18S mRNA using the 2^−ΔCt method. Fold induction of gene expression was normalized to baseline expression in uninfected mice using the 2^−ΔΔCt method.

Ab cell staining was performed as previously described (17). For extracellular staining, cells were washed in PBS then stained with Live Dead Fixable Aqua (Life Technologies) for 30 min. Cells were stained with extracellular antibodies (see below), washed, and fixed in 2% formaldehyde. For intracellular staining, the cells were stimulated with 50 ng/ml PMA and 1 μg/ml ionomycin (Millipore) for 6 h (lung and LALN leukocytes) or heat-killed C. neoformans for 24 h (spleen cells) prior to Ab staining. Brefeldin A and monensin (BioLegend) were added for the last 4 h. The cells were harvested, stained with extracellular, and subsequently intracellular antibodies (see below). Data were collected on a FACS LSR2 flow cytometer using FACSDiva software (Becton Dickinson Immunocytometry Systems, Mountain View, CA, USA) and analyzed using FlowJo software (Tree Star, San Carlos, CA, USA).

The following gating strategy was used to identify leukocyte subsets in the lungs. First, consecutive gates identified singlets, live cells and CD45⁺ leukocytes. Next, a series of selective gates were used to identify neutrophils (CD11b⁺Ly6G⁺); eosinophils (SSC^highCD11c^low/SiglecF⁺); Alveolar macrophages (CD11c^high/SiglecF⁺); and Ly6C^high monocytes (CD11c⁻/CD11b⁺/Ly6C^high). In cells expressing both CD11c and high levels of MHCII, autofluorescent (AF⁺) exudate macrophages were distinguished from non-AF (AF⁻) DCs. Thereafter, DC were further separated into moDC, CD11b⁺ DC and CD103⁺ DC as follows: moDC were gated as CD11c⁺MHCII^highCD64⁺ cells, then remaining CD11c⁺MHCII^highCD64⁻ cells were further divided into CD11b⁺ DC and CD103⁺ DC based on the expression of SIRPα and XCR1, respectively (31). A similar gating strategy was used for leukocytes in the LALN. To identify CD4⁺ Th cells, singlet and live cells were first selected and the total numbers of CD45⁺ leukocytes were identified. Next, the CD3⁺CD4⁺ cells were identified and the expression levels of specific cytokines (IFN-γ, TNF-α, IL-5, and IL-13) or transcriptional factors (Gata3) were evaluated. Total numbers of each cell population were calculated by multiplying the frequency of the population by the total number of leukocytes (the original hemocytometer count of total cells). Isotype control antibodies were used to set gates for positive events in all flow cytometric analyses.

All values are reported as mean ± SEM. Unpaired non-parametric test (Mann–Whitney) or two-way ANOVA with a Bonferroni post hoc test were used for comparisons of individual means. Statistical calculations were performed using GraphPad Prism version 6.00 (GraphPad Software, San Diego, CA, USA). Means with p values <0.05 were considered significantly different.

Our previous study showed that MARCO contributes to fungal control during the early/afferent phase of C. neoformans infection (19). However, whether MARCO expression affects long-term adaptive immunity against C. neoformans is unclear. To explore the function of MARCO during the late/efferent phase of cryptococcal infection, we infected WT and MARCO^−/− mice with C. neoformans strain 52D and analyzed the fungal burden at 35 days post infection (dpi). Whereas our prior results demonstrated that MARCO-deficient mice have increased fungal burden at the early stage of infection (19), we found that MARCO-deficient mice exhibit decreased pulmonary fungal burden at 35 dpi compared to WT mice (Figure 1A). Fungal burdens in spleen and brain were also lower in MARCO^−/− mice compared to WT mice at 35 dpi (Figure 1A). We further evaluated the effects of MARCO on the kinetics of pulmonary fungal growth during the efferent phase of C. neoformans infection. While equivalent growth of yeast in the lungs was noted in WT and MARCO^−/− mice at 21 dpi, MARCO deficiency resulted in lower fungal burden at 35 and 49 dpi (Figure 1B). Together, our results demonstrate that MARCO expression promotes pulmonary fungal persistence and systemic dissemination during the efferent phase of C. neoformans infection.

T helper cell polarization in the lungs is strongly correlated with clearance and persistence during the efferent phase of C. neoformans infection (32). To determine how MARCO expression affects T cell-mediated responses in the lungs, we analyzed leukocyte populations in the infected lungs of WT and MARCO^−/− mice using flow cytometry. The accumulation of total leukocytes and leukocyte subsets, including eosinophils, alveolar macrophages, and total DCs, in the infected lungs were similar between WT and MARCO^−/− mice at 21, 35, and 49 dpi (Figure S1 in Supplementary Material).

We next examined the effect of MARCO on T cell polarization during C. neoformans infection. There was no difference in the accumulation of CD4⁺ T cells in the lungs of C. neoformans-infected MARCO^−/− and WT mice during the efferent phase of cryptococcal infection (Figure 2A). However, MARCO deficiency resulted in reduced Il-5 and Il-13 mRNA expression, but not IFN-γ and TNF-α mRNA expression, by total lung leukocytes isolated from infected mice at 35 dpi, suggesting an impaired Th2 response in MARCO-deficient mice (Figure 2B). Phenotypes of T helper cells were further analyzed by intracellular staining using flow cytometry. Frequencies of CD4 T cells expressing IL-5 and IL-13 were significantly lower in MARCO^−/− mice compared to WT mice at 35 dpi (Figure 2C). By contrast, MARCO deficiency led to higher frequencies of CD4⁺ T cells expressing TNF-α albeit without affecting those expressing INF-γ at 35 dpi (Figure 2D). Collectively, our data demonstrated that MARCO expression did not affect accumulation of lung myeloid or lymphoid cells but altered the balance of T cell polarization away from protective Th1 responses toward non-protective Th2 responses in the lungs during the efferent phase of C. neoformans infection.

The balance of Th1/Th2 cytokines influences macrophage activation status and their subsequent fungicidal activities (33, 34). Exudate macrophages derived from recruited monocytes during infection have been shown to be the most efficient effector cells in killing C. neoformans (35). We next sought to determine whether MARCO expression affects the activation status of pulmonary macrophages during the efferent phase of C. neoformans infection. Equivalent recruitment of exudate macrophages was noted between infected MARCO^−/− and WT mice during the efferent phase of C. neoformans infection (Figure 3A). However, MARCO deficiency resulted in augmented mRNA expression of iNOS but not Arg1 by lung macrophages at 35 dpi (Figure 3B). Moreover, we found that MARCO deficiency resulted in significantly increased expression of CD80 and CD86 by exudate macrophages at 35 dpi (Figures 3C,D), consistent with improved pulmonary fungal clearance in these mice. Interestingly, expression of CD80, CD86, iNOS, and Arg1 by alveolar macrophages was similar between infected MARCO^−/− and WT mice (not shown). Thus, consistent with the diminished efferent Th1 responses, MARCO expression is associated with impaired classical activation of exudate macrophages in the lungs during the efferent phase of C. neoformans infection.

Since MARCO affected extra-pulmonary C. neoformans dissemination, we next studied its effects on systemic immune responses during the efferent phase of cryptococcal infection. To accomplish this, we evaluated the cytokine production by splenocytes of infected MARCO^−/− and WT mice in response to cryptococcal antigen. Consistent with results from the lungs, production of non-protective cytokines, including IL-4 and IL-10, was lower by splenocytes from MARCO^−/− compared to WT mice at 21 dpi (Figure 4A). The concentration of serum IgE, a hallmark of systemic Th2 response, was also significantly lower in MARCO^−/− mice compared to WT mice at 21 and 35 dpi (Figure 4B). Furthermore, MARCO deficiency led to elevated production of beneficial Th1 cytokines such as IFN-γ (21 and 35 dpi) and TNF-α (35 dpi) by splenocytes in response to cryptococcal antigen stimulation (Figure 4C). We next investigated whether T cells were the major source of antigen-triggered IFN-γ production in splenocyte cultures using intracellular flow cytometric analysis. We identified increased frequencies of IFN-γ-producing CD8⁺ T cells in MARCO^−/− mice compared to WT mice (Figure 4D). We also observed a similar, strong trend in increased frequencies of IFN-γ-producing CD4⁺ T cells in MARCO^−/− mice compared to WT mice (p = 0.1) (Figure 4D), which became significant when splenocyte culture were stimulated with PMA and ionomycin (data not shown). Interestingly, we also found a higher frequency of non-T cell populations (CD4⁻CD8⁻) producing IFN-γ in antigen stimulated splenocyte cultures from MARCO^−/− mice compared to those from WT mice (Figure 4D). These results indicate that MARCO expression also broadly affects IFN-γ production by cells outside the T cell compartment. Collectively, we found that MARCO expression promotes a systemic shift away from protective responses toward non-protective responses during the efferent phase of C. neoformans infection.

We next dissected the mechanisms by which MARCO modulates Th polarization. T cells are primed in the draining lymph nodes and their polarization is orchestrated by distinct DC subsets during C. neoformans infection (36). We, thus, looked at the priming of T cells in the LALN at 10 dpi, an early time point at the onset of T cell polarization. Though MARCO deficiency had no effect on the T cell expansion in LALNs at 10 dpi (Figure 5A), we found reduced expression of IL-13 by the LALN leukocytes of infected MARCO^−/− mice compared to WT mice (Figure 5B). Furthermore, expression of IFN-γ and the transcription factors T-bet and Eomesodermin by LALN leukocytes were similar between MARCO^−/− and WT mice (Figure 5B and data not shown). To further assess whether MARCO promotes Th2 priming in the LALN during C. neoformans infection, we performed intracellular staining for cytokines and transcription factors in LALN leukocytes. Consistent with our gene expression analysis, we found that MARCO deficiency resulted in reduced frequencies of LALN CD4⁺ T cells expressing Th2-associated cytokine IL-13 and transcriptional factor Gata3 at 10 dpi (Figure 5C). By contrast, MARCO deficiency had no effect on IFN-γ expression by CD4⁺ T cells in the LALN at 10 dpi. Thus, MARCO expression enhances early Th2 priming but appears to have little or no effect on early Th1 priming in the LALN during C. neoformans infection.

Pulmonary CD11b⁺ cDC have been shown to orchestrate the development of non-protective Th2 responses during cryptococcal infection (15). To test whether MARCO expression affects the accumulation of DC in the LALN, we analyzed leukocyte populations in the LALN of infected MARCO^−/− and WT mice at 10 dpi. While total leukocyte accumulation in the LALN was not altered in MARCO-deficient mice, MARCO expression significantly promoted the accumulation of migratory DC (CD11c⁺MHCII^high) in the LALN of infected mice (Figures 6A,B). We further explored whether MARCO affected the accumulation of specific DC subsets in the LALN during C. neoformans infection. Notably, MARCO deficiency selectively impaired accumulation of CD11b⁺ cDC, but had no effect on the accumulation of CD103⁺ cDC and moDC subsets in the LALN of C. neoformans-infected mice (Figure 6C). Thus, MARCO expression is critical for the accumulation of CD11b⁺ cDC in the LALN during C. neoformans infection.

The activation status of DC in the LALN can be influenced by fungal virulence factors and plays a vital role in the control of T cell polarization (16, 37). We further assessed the effect of MARCO on the activation status of CD11b⁺ cDC in the LALN during C. neoformans infection by analyzing the expression of classical activation markers (CD80 and CD86) as well as alternative activation marker (CD206) on CD11b⁺ cDC. We found that MARCO deficiency led to increased expression of CD80 and CD86 and decreased expression of CD206 by CD11b⁺ cDC in the LALN at 10 dpi (Figures 7A,B). Interestingly, MARCO deficiency had no effect on the activation status of CD103⁺ cDC and moDC in LALN of infected mice (not shown). These data show that MARCO expression specifically promotes alternative activation and inhibits classical activation of CD11b⁺ cDC in the LALN. Collectively, this MARCO-dependent accumulation and alternative activation of CD11b⁺ cDC in the LALN may represent a critical mechanism through which MARCO promotes the development of a stronger Th2 response and downregulates the Th1 response, leading to fungal persistence during the efferent phase of C. neoformans infection (Figure 8).