Bacterial infections are a common and deadly threat to vulnerable patients. Alternative strategies to fight infection are needed. β-Glucan, an immunomodulator derived from the fungal cell wall, provokes resistance to infection by inducing trained immunity, a phenomenon that persists for weeks to months. Given the durability of trained immunity, it is unclear which leukocyte populations sustain this effect. Macrophages have a life span that surpasses the duration of trained immunity. Thus, we sought to define the contribution of differentiated macrophages to trained immunity. Our results show that β-glucan protects mice from Pseudomonas aeruginosa infection by augmenting recruitment of innate leukocytes to the site of infection and facilitating local clearance of bacteria, an effect that persists for more than 7 d. Adoptive transfer of macrophages, trained using β-glucan, into naive mice conferred a comparable level of protection. Trained mouse bone marrow–derived macrophages assumed an antimicrobial phenotype characterized by enhanced phagocytosis and reactive oxygen species production in parallel with sustained enhancements in glycolytic and oxidative metabolism, increased mitochondrial mass, and membrane potential. β-Glucan induced broad transcriptomic changes in macrophages consistent with early activation of the inflammatory response, followed by sustained alterations in transcripts associated with metabolism, cellular differentiation, and antimicrobial function. Trained macrophages constitutively secreted CCL chemokines and robustly produced proinflammatory cytokines and chemokines in response to LPS challenge. Induction of the trained phenotype was independent of the classic β-glucan receptors Dectin-1 and TLR-2. These findings provide evidence that β-glucan induces enhanced protection from infection by driving trained immunity in macrophages.

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Despite nearly a century of antibiotic development and administration, infectious diseases account for significant morbidity and mortality in the modern healthcare system (1). This is particularly true in the hospital setting, where aging, immunocompromised, and critically ill patients are exposed to a broad array of pathogens (2). Therefore, new approaches to decrease the burden of infection among vulnerable populations are needed. Prophylactic immunomodulation that bolsters the host response to infection is a promising strategy to combat infection. Classically, vaccines have filled this niche. Vaccines induce highly specific and long-lived (months to years) cellular and humoral immunity that is mediated by memory T and B lymphocytes, respectively, of the adaptive immune system (3, 4). Yet, recent research shows that the innate immune system also retains memory of prior pathogen exposure and becomes armed to elicit more robust responses to subsequent infection (5, 6). This augmented state has been termed trained immunity or innate immune memory (79). Trained immunity differs from vaccine-induced immunity in two important ways. The typical duration is shorter and protection from infection is broadly based. Whereas vaccines evoke a memory response that last months to years, the duration of trained immunity is typically weeks to months (10, 11). Although vaccines target a specific pathogen, trained immunity provides broad protection against a diverse cohort of pathogens, and protection is not specific to the organism from which the training ligand was derived (1214).

Immunomodulatory compounds that induce trained immunity are a promising tool to augment the host response to infection or serve as an adjunct to antibiotics (15). β-Glucan, the most abundant polysaccharide of the fungal cell wall, possesses immunomodulatory properties that enhance the host response to diverse bacterial, fungal, and viral pathogens (16). β-Glucan reprograms the metabolic and epigenetic landscape of monocytes to induce enhancement of antimicrobial responses (1719). Importantly, β-glucan’s protective effects last weeks to months via trained immunity (20). However, monocytes have a life span of a few days, which is incompatible with sustaining the trained phenotype beyond that short timeframe (21). Evidence indicates that epigenetic changes in bone marrow progenitors may serve as a mechanism of providing trained monocytes to sustain the trained phenotype (22). Alternatively, training of differentiated macrophages provides a complementary mechanism to consider. Unlike monocytes, tissue macrophages have a lifespan of months to years and are key regulators of the host response to infection and inflammation (23). With the exception of the small intestinal walls, dermis, and heart, circulating monocytes do not significantly contribute to the population of tissue macrophages in most organs (24). Thus, whether β-glucan trains differentiated macrophages similarly to circulating monocytes is unclear. Additionally, the contribution of trained macrophages to protection from infection has not been adequately explored.

Macrophages are crucial for initiating and coordinating the host immune response to infection. The detection of microbial pathogen-associated molecular patterns by macrophages initiates a rapid inflammatory response that leads to mobilization of innate immune cells, chiefly monocytes and neutrophils, and their recruitment to the site of infection. Recruited myeloid cells respond by phagocytosing and killing the pathogen locally. Failure of the innate response may lead to bacterial dissemination and systemic infection, which dramatically increases morbidity and mortality (25). Therefore, the development of approaches to augment macrophage antimicrobial functions safely and effectively could serve to prevent and treat infections, especially in vulnerable populations in which innate immune function is suppressed or dysregulated (26, 27).

Macrophages detect β-glucan by the pattern-recognition receptors (PRRs) Dectin-1 and TLR-2 (2830). Genetic deficiency of Dectin-1 leads to recurrent infections with Candida albicans in humans (31). However, some macrophage responses to β-glucan are independent of Dectin-1 and TLR-2 (32). Furthermore, the importance of Dectin-1 and TLR-2 for inducing trained immunity in macrophages has not been determined. Understanding the signaling cascades that contribute to protective phenotype is important for optimizing the translational potential of β-glucan immunotherapy.

We tested the hypothesis that training of differentiated macrophages with β-glucan will provide resistance against infection with Pseudomonas aeruginosa, a common nosocomial pathogen with a high frequency of antibiotic resistance (33, 34). Furthermore, we hypothesized that β-glucan–induced protection is driven by antimicrobial, metabolic, and biochemical alterations in trained macrophages. Our results show that adoptive transfer of macrophages trained with β-glucan protects mice from P. aeruginosa infection by augmenting innate leukocyte recruitment to sites of infection and enhancing local bacterial clearance. Further, using a combination of transcriptomic, metabolomic, and immunologic techniques, we show that β-glucan–trained macrophages develop distinct metabolic and phenotypic characteristics and a robust antimicrobial phenotype. Finally, we demonstrate that β-glucan training is independent of Dectin-1 and TLR-2 signaling. These findings advance the paradigm of innate immune memory by demonstrating the trained phenotype in differentiated macrophages treated with β-glucan.

Wild-type (WT) male and female C57BL/6 mice, aged 10–12 wk, were purchased from The Jackson Laboratory (Bar Harbor, ME). Clec7a−/− (Dectin-1 knockout [KO]) and Tlr2−/− (TLR-2 KO) mice were purchased from The Jackson Laboratory. Clec7a−/−Tlr2−/− (double KO [DKO]) mice were generated at Vanderbilt University. The authenticity of KO strains was validated by routine genotyping. All experiments and procedures complied with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the Vanderbilt University Institutional Animal Care and Use Committee.

The β-d-glucan (1, 3) training reagent and linear glucan were isolated from C. albicans and purified as described previously (35). The purity of β-glucan isolates was confirmed using 1H and 13C nuclear magnetic resonance spectroscopy. All preparations of β-glucan were determined to be endotoxin free. It is important to note that the β-glucan training reagent used in this research is the same as that used in the studies of Ifrim (36), Cheng (19), Saeed (17), and Garcia-Valtanen (11). This reagent is prepared exclusively in the Williams laboratory and is recognized worldwide as the “gold-standard” immune training agent. Mice received 1 mg of β-glucan by i.p. injection of 0.2 ml vortexed suspension of 5% dextrose in H20. Treatment groups in cell culture received 5 mg/ml of β-glucan for the indicated times. Mice and macrophages treated with vehicle served as control.

Mice were infected with P. aeruginosa via the i.p. route, as described in our previous studies (37). P. aeruginosa was purchased from American Type Culture and Collection (ATCC 19660; Manassas, VA). Bacterial cultures were grown in tryptic soy broth for 22 h at 37°C, washed, and diluted in sterile saline. Mice were inoculated i.p. with 1 × 108 CFUs P. aeruginosa in 0.5 ml saline. Six hours after inoculation, body temperatures were measured by rectal thermometer, and mice were anesthetized. Whole blood was collected by carotid artery laceration under isoflurane anesthesia into heparinized microcentrifuge tubes, centrifuged at 2000 × g for 15 min at 4°C, and plasma was collected and stored at −80°C for storage until subsequent cytokine analysis. Following cervical dislocation, the peritoneal cavity was lavaged with 5 ml of cold sterile PBS. A portion of lavage fluid was diluted and plated on tryptic soy agar overnight, and bacterial colonies were counted to determine CFUs per milliliter recovered. The remaining peritoneal lavage fluid was centrifuged at 300 × g for 6 min at 4°C and diluted appropriately for flow cytometric analyses.

Femurs were harvested from mice and flushed with RPMI 1640 containing 2 mM glutamine and 25 mM HEPES (Life Technologies, Grand Island, New York) supplemented with 10% certified performance plus FBS (Life Technologies), 1% Antibiotic-Antimycotic (Life Technologies), and 10 ng/ml mouse rM-CSF (R&D Systems; Minneapolis, MN), henceforth referred to as complete media. Bone marrow cell suspensions were centrifuged at 300 × g for 6 min at 4°C and plated at a concentration of 5 × 104 cells/ml in complete media. After 7 d of differentiation, bone marrow–derived macrophages (BMDM) received fresh media and were treated with 5 mg/ml β-glucan or vehicle as unstimulated controls for 24 h. Macrophages were washed and allowed to rest in complete media for 3 d to generate the trained phenotype (3-d postgroup [3dp]). Separately, BMDM were maintained in complete media and stimulated with 5 mg/ml β-glucan or vehicle for 4 or 24 h prior to assessment (4- and 24-h groups).

Trained BMDM were prepared as above, harvested, and resuspended at a concentration of 5 × 106 cells/ml in PBS. One day prior to infection, mice received 1 × 106 control or trained BMDM by i.p. injection. Twenty-four hours later, mice were inoculated i.p. with 1 × 108 CFUs of P. aeruginosa. Core body temperature, whole blood collection, peritoneal lavage, flow cytometry, and cytokine analysis were performed as described above.

The concentration of IL-6, CCL3, CCL4, and TNF-α were measured by DuoSet ELISA kits from R&D Systems. Cytokines were measured from in vivo infection samples or conditioned cell culture media when indicated.

Cells collected by peritoneal lavage were resuspended in PBS at a concentration of 1 × 107 cells/ml and incubated with 1 mg/ml anti-mouse CD16/32 (eBioscience, San Diego, CA) prior to addition of fluorochrome-conjugated Abs (0.5 mg/1 × 106 cells) and incubation for 15 min at room temperature. Abs used to differentiate peritoneal leukocytes included anti-F4/80–FITC (clone BM8; eBioscience), anti–Ly-6G–PE (clone 1A8; BD Biosciences, San Jose, CA), and anti–Ly-6C–PE Cy5.5 (clone HK1.4; eBioscience) alongside respective isotype controls. Monocytes were identified as F4/80+Ly-6C+, macrophages as F4/80+Ly-6C, and neutrophils as Ly-6G+F4/80. Data were collected using an Accuri C6 flow cytometer and analyzed using Accuri C6 software (BD Biosciences).

BMDM were assessed with the Respiratory Burst Assay Kit (Cayman Chemical, Ann Arbor, MI). BMDM were incubated with dihydrorhodamine-123 for 1 h at 37°C. Rhodamine-123 fluorescence was determined by flow cytometry.

Staphylococcus aureus particles (Invitrogen, Carlsbad, CA) labeled with pHrodo Red dye were suspended in phenol red–free RPMI 1640 and sonicated for 10 min. pHrodo particles were added to BMDM cultures and placed in a Synergy H1 plate reader at 37°C (BioTek, Winooski, VT). pHrodo fluorescence was measured every 15 min for the indicated time.

One day prior to the assay, BMDM were plated at 1 × 105 cells per well in a 96-well plate. Cells were washed with warm PBS five times and placed in RPMI 1640 containing 0.1% FBS (Life Technologies). P. aeruginosa was prepared as above and diluted to 1 × 106 CFU/ml after passage of stock through a 26-gauge needle. Bacteria were added to BMDM, and plates were centrifuged at 515 × g for 4 min at 4°C. BMDM and bacteria were coincubated for 1 h at 37°C, and supernatants were collected and plated for bacterial counting, as above. BMDM were then washed with warm PBS five times and placed in RPMI 1640 containing 0.1% FBS (Life Technologies) and 300 mg/ml gentamicin (Sigma-Aldrich, St. Louis, MO) for 1 h. BMDM were washed with PBS and a solution of 0.02% Triton X-100 (Sigma-Aldrich) in PBS was added to the 96-well plate and vigorously pipetted to generate cellular lysates. Lysates were collected and plated for bacterial counting, as above.

One day prior to the assay, BMDM were plated at 5 × 104 cells per well in a 96-well Seahorse assay plate. All measurements were performed on a Seahorse XFe96 Extracellular Flux Analyzer (Agilent Technologies, Santa Clara, CA). The glycolysis and mitochondrial stress tests were performed using the manufacturer’s protocol. Briefly, extracellular acidification rate (ECAR) was measured at baseline and after the addition of 10 mM glucose (Sigma-Aldrich), 1 mM oligomycin (Agilent Technologies), and 50 mM 2-deoxyglucose (2-DG; Sigma-Aldrich). Oxygen consumption rate (OCR) was measured at baseline and after the addition of 1 mM oligomycin, 1 mM trifluoromethoxy carbonylcyanide phenylhydrazone (Agilent Technologies), and 0.5 mM antimycin A and rotenone (Agilent Technologies).

BMDM were plated at 2.4 × 105 cells per well in a 24-well plate 1 d prior to the assay. Fifty micromolars of MitoTracker Green dye (Invitrogen) or 100 nM tetramethylrhodamine, methyl ester (TMRM) dye (Invitrogen) was added for 30 min at 37°C to stain total and active mitochondria, respectively. BMDM were washed and assessed by flow cytometry using channel FL1 (green) for MitoTracker and FL3 (red) for TMRM.

BMDM were treated with β-glucan as described above. Fresh media containing 100 ng/ml LPS (ultrapure; Invitrogen) derived from Escherichia coli 0111:B4 was added to the cell culture. Four hours after incubation with LPS, cellular lysates were harvested for RNA as above. Separately, conditioned cell culture media was collected 6 h after incubation. After 6 and 24 h of LPS stimulation, the Seahorse extracellular flux assay was performed as above.

Total RNA was isolated under an RNase-free environment using the RNeasy Mini Kit (QIAGEN, Hilden, Germany) and treated with DNase (QIAGEN). Total RNA quality and concentration were verified with a Thermo Scientific NanoDrop 2000 spectrophotometer. Purified RNA was assessed with Qubit and 2100 Bioanalyzer (Agilent Technologies) and RNA integrity number was determined for each sample (38, 39). All samples had an RNA integrity number score of 7 or greater. mRNA Libraries were prepared using NEBNext Poly(A) selection (New England Biolabs). Sequencing was performed at paired-end 150 bp on an Illumina NovaSeq 6000 with at least 50 million reads per sample by Vanderbilt Technologies for Advanced Genomics. RNA sequencing (RNASeq) data were analyzed with Basepair (www.basepairtech.com). Briefly, reads were aligned to the mm10 genome using Spliced Transcripts Alignment to a Reference (STAR) after trimming and undergoing quality control with QC30 (40). Read counts were measured using featureCounts (41). Differentially expressed genes were identified using DESeq2 (42). Transcripts with log2 fold change of at least 1.0 and p adjusted <0.05 were considered significant for individual gene analysis. Gene Set Enrichment Analysis was used to define significantly altered biological processes sorted with Gene Ontology (GO) (4345). Raw data were deposited using the National Center for Biotechnology Information Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/). Accession number is as follows: GSE174141.

Cellular lysates were prepared using radioimmunoprecipitation assay buffer (Sigma-Aldrich) containing cOmplete protease inhibitor mixture and PhosSTOP phosphatase inhibitor mixture (Roche Diagnostics, Basel, Switzerland). Lysate protein concentrations were quantified using the bicinchoninic acid assay for normalization (Pierce, Thermo Fisher Scientific, Waltham, MA). Samples were separated by gel electrophoresis on Mini-Protean 4–20% Tris-glycine gels (Bio-Rad Laboratories, Hercules, CA). Sample proteins were transferred onto nitrocellulose membranes overnight (PerkinElmer, Boston, MA). Membranes were blocked with 5% fraction V BSA (Research Products International, Mount Prospect, IL) and incubated with primary Abs (1:1000 dilution) overnight at 4°C. Membranes were washed and then placed in HRP-conjugated secondary Abs (1:2000 dilution) for 2 h at room temperature followed by enhanced chemiluminescence reagent (Bio-Rad Laboratories). Protein bands were detected by film exposure.

Data were analyzed using GraphPad Prism 8.3.0 (La Jolla, CA) software unless otherwise noted. Data are expressed as mean ± SEM or median when noted. Data from experiments containing multiple groups were compared using one-way ANOVA, followed by Tukey post hoc multiple comparison test. Body temperature and bacterial counts were compared using the Mann–Whitney U test when comparing two groups or Kruskal–Wallis test, followed by Dunn post hoc multiple comparison test when comparing more than two groups. Differences in gene expression for RNASeq data were determined using the DESeq2 protocol. A p value of <0.05 was considered statistically significant.

To characterize the innate immune response to a clinically relevant pathogen after β-glucan training, mice were treated i.p. with 1 mg β-glucan or vehicle on two consecutive days and were infected with P. aeruginosa at 1, 3, 7, or 14 d later. Rectal temperature, bacterial counts, and leukocytes numbers were measured 6 h postinfection (Fig. 1A). Vehicle-treated control mice became hypothermic, whereas β-glucan–primed mice maintained normothermia across all time points (Fig. 1B). β-Glucan–treated mice showed significantly lower P. aeruginosa CFUs in peritoneal lavage as compared with vehicle-treated mice for up to 7 d following β-glucan treatment and returned to control levels on day 14 (Fig. 1C). The number of monocytes in the peritoneal cavity was significantly elevated in mice treated with β-glucan at 1 and 3 d prior to infection and returned to control levels at day 7 (Fig. 1D). Mice treated with β-glucan displayed elevated neutrophils in the peritoneal cavity following infection for up to 14 d, although infection-elicited i.p. neutrophil numbers waned after day 7 (Fig. 1E). The number of macrophages in the peritoneal cavity postinfection was significantly elevated for 7 d in mice treated with β-glucan treatment but diminished by day 14 (Fig 1F). Taken together, these results demonstrate that β-glucan treatment augments leukocyte recruitment and bacterial clearance for at least 7 d and confers physiologic protection for at least 14 d in response to infection with the clinically relevant pathogen P. aeruginosa.

FIGURE 1.

β-Glucan augments innate immune defense against P. aeruginosa in mice. (A) C57BL/6 mice were injected i.p. with β-glucan (1 mg) or vehicle on two consecutive days at 1, 3, 7, and 14 d prior to i.p. inoculation with 1 × 108 CFU P. aeruginosa with harvest of plasma and peritoneal lavage fluid 6 h postinfection. (B) Core (rectal) body temperature in vehicle- or β-glucan–treated mice. (C) CFUs of P. aeruginosa per milliliter of peritoneal fluid. (DF) Number of monocytes (D), neutrophils (E), or macrophages (F) in infected vehicle- or β-glucan–treated mice. Body temperature and clearance data shown as median. All other data shown as mean ± SEM. n = 10–20 mice per group. *p < 0.05, ***p < 0.001, ****p < 0.0001 by Mann–Whitney U test (B and C) or ANOVA with Tukey post hoc multiple comparison test (D–F).

FIGURE 1.

β-Glucan augments innate immune defense against P. aeruginosa in mice. (A) C57BL/6 mice were injected i.p. with β-glucan (1 mg) or vehicle on two consecutive days at 1, 3, 7, and 14 d prior to i.p. inoculation with 1 × 108 CFU P. aeruginosa with harvest of plasma and peritoneal lavage fluid 6 h postinfection. (B) Core (rectal) body temperature in vehicle- or β-glucan–treated mice. (C) CFUs of P. aeruginosa per milliliter of peritoneal fluid. (DF) Number of monocytes (D), neutrophils (E), or macrophages (F) in infected vehicle- or β-glucan–treated mice. Body temperature and clearance data shown as median. All other data shown as mean ± SEM. n = 10–20 mice per group. *p < 0.05, ***p < 0.001, ****p < 0.0001 by Mann–Whitney U test (B and C) or ANOVA with Tukey post hoc multiple comparison test (D–F).

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Trained or control BMDM were adoptively transferred i.p. 24 h prior to infection with P. aeruginosa (Fig. 2A). Mice treated with vehicle or control BMDM developed hypothermia 6 h postinfection, whereas mice that received β-glucan–treated BMDM maintained normothermia (Fig. 2B). Similar to in vivo systemic training with β-glucan, mice that received trained BMDM had lower bacterial counts in the peritoneal cavity than mice treated with vehicle or control BMDM (Fig. 2C). Mice treated with β-glucan–trained BMDM had significantly more neutrophils (Fig. 2D), monocytes (Fig. 2E), and macrophages (Fig. 2F) at the site of infection compared with mice receiving vehicle or control BMDM. These data demonstrate that adoptive transfer of trained macrophages is sufficient to reproduce the protective benefit of β-glucan treatment, supporting the premise that macrophages contribute to β-glucan–induced trained immunity and resistance to infection.

FIGURE 2.

Adoptive transfer of β-glucan–trained macrophages protects against P. aeruginosa infection. (A) BMDM were treated with β-glucan (5 µg) or vehicle for 24 h, washed, and allowed to rest for 3 d. C57BL/6 mice were injected i.p. with vehicle (PBS), control BMDM, or β-glucan–treated BMDM 24 h prior to i.p. inoculation with 1 × 108 CFU P. aeruginosa with subsequent harvest of plasma and peritoneal lavage fluid 6 h later. (B) Core (rectal) body temperature in vehicle, control BMDM–, or β-glucan BMDM–treated mice after P. aeruginosa challenge. (C) CFU of P. aeruginosa per milliliter of peritoneal fluid. (DF) Number of monocytes (D), neutrophils (E), or macrophages (F) in vehicle or control BMDM– or β-glucan BMDM–treated mice. Body temperature and clearance data shown as median. All other data shown as mean ± SEM. n = 10–15 mice per group. *p < 0.05, **p < 0.01 by Kruskal–Wallis test with Dunn post hoc multiple comparison test (B and C) or ANOVA with Tukey post hoc multiple comparison test (D–F).

FIGURE 2.

Adoptive transfer of β-glucan–trained macrophages protects against P. aeruginosa infection. (A) BMDM were treated with β-glucan (5 µg) or vehicle for 24 h, washed, and allowed to rest for 3 d. C57BL/6 mice were injected i.p. with vehicle (PBS), control BMDM, or β-glucan–treated BMDM 24 h prior to i.p. inoculation with 1 × 108 CFU P. aeruginosa with subsequent harvest of plasma and peritoneal lavage fluid 6 h later. (B) Core (rectal) body temperature in vehicle, control BMDM–, or β-glucan BMDM–treated mice after P. aeruginosa challenge. (C) CFU of P. aeruginosa per milliliter of peritoneal fluid. (DF) Number of monocytes (D), neutrophils (E), or macrophages (F) in vehicle or control BMDM– or β-glucan BMDM–treated mice. Body temperature and clearance data shown as median. All other data shown as mean ± SEM. n = 10–15 mice per group. *p < 0.05, **p < 0.01 by Kruskal–Wallis test with Dunn post hoc multiple comparison test (B and C) or ANOVA with Tukey post hoc multiple comparison test (D–F).

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Based on our in vivo data, we hypothesized that β-glucan enhances macrophage antimicrobial capacity, which we assessed using several approaches. BMDM trained with β-glucan (3dp) were significantly larger (Fig. 3A) and more granular (Fig. 3B) than control and 24-h BMDM, as measured by forward and side scatter using flow cytometry. Rhodamine-123 staining showed increased reactive oxygen species (ROS) production in 24-h and 3dp BMDM as compared with the control BMDM (Fig. 3C). Trained BMDM phagocytosed significantly more pHrodo-labeled bacteria particles over time than control BMDM (Fig. 3D). Increased numbers of viable P. aeruginosa were also present in trained BMDM as compared with controls, confirming augmented phagocytosis (Fig. 3E).

FIGURE 3.

β-Glucan–trained macrophages display a robust antimicrobial phenotype. BMDM were treated with β-glucan (5 µg) or treated with vehicle for 24 h (24h), washed, and allowed to rest for 3dp, followed by assessment of macrophage phenotype. (A) Cell size was measured by forward scatter. (B) Cell granularity as measured by side scatter. (C) Rhodamine-123 fluorescence was measured after a 15-min incubation period using flow cytometry. (D) Control or trained BMDM were incubated with pHrodo S. aureus particles. pHrodo mean fluorescence intensity (MFI) was measured every 15 min for 5 h. (E) BMDM were incubated with P. aeruginosa. Intracellular and extracellular CFU were quantified as described in Materials and Methods. Data shown as mean ± SEM. Experiments were performed with three to five biological replicates. *p < 0.05, **p < 0.01 by ANOVA with Tukey post hoc multiple comparison test (A–C) or repeated two-way ANOVA (D).

FIGURE 3.

β-Glucan–trained macrophages display a robust antimicrobial phenotype. BMDM were treated with β-glucan (5 µg) or treated with vehicle for 24 h (24h), washed, and allowed to rest for 3dp, followed by assessment of macrophage phenotype. (A) Cell size was measured by forward scatter. (B) Cell granularity as measured by side scatter. (C) Rhodamine-123 fluorescence was measured after a 15-min incubation period using flow cytometry. (D) Control or trained BMDM were incubated with pHrodo S. aureus particles. pHrodo mean fluorescence intensity (MFI) was measured every 15 min for 5 h. (E) BMDM were incubated with P. aeruginosa. Intracellular and extracellular CFU were quantified as described in Materials and Methods. Data shown as mean ± SEM. Experiments were performed with three to five biological replicates. *p < 0.05, **p < 0.01 by ANOVA with Tukey post hoc multiple comparison test (A–C) or repeated two-way ANOVA (D).

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We next sought to evaluate the metabolic phenotype of macrophages trained with β-glucan (Fig. 4). BMDM treated with β-glucan for 24 h had elevated baseline and maximal ECAR, an indirect measure of lactate production and glycolysis compared with control (Fig. 4A–C). Trained (3dp) BMDM displayed significantly higher ECAR levels than control and those treated for 24 h (Fig. 4A–C). Both 24-h and 3dp BMDM displayed elevated baseline and maximal OCR compared with control, indicating a sustained increase in oxidative phosphorylation (Fig. 4D–F).

FIGURE 4.

β-Glucan training augments metabolism and increases mitochondrial content and membrane potential in macrophages. BMDM were treated with β-glucan (5 µg) or vehicle for 24 h (24h), washed, and allowed to rest for 3dp, followed by assessment of macrophage metabolic phenotype. (A) Glycolysis stress test of control, 24h, and trained (3dp) BMDM on the Seahorse XFe96. ECAR was measured over time at baseline and after glucose, oligomycin, and 2-DG addition. (B) Basal ECAR as determined from three separate runs. (C) Maximum ECAR as determined from three separate runs. (D) Oxidative stress test of control, 24h, and trained BMDM on the Seahorse XFe96. OCR was measured over time at baseline and after oligomycin, FCCP, and rotenone and antimycin A administration. (E) Basal OCR as determined from three separate runs. (F) Maximum OCR as determined from three separate runs. (G) Enrichment plot for GO term “Mitochondrial Respiratory Chain Complex Assembly” for control versus trained (3dp) BMDM. (H) MitoTracker Green mean fluorescence intensity (MFI) was measured in BMDM by flow cytometry after 30-min incubation. (I) Enrichment plot for GO term “Mitochondrial ATP Synthesis-Coupled Proton Transport” for control versus trained (3dp) BMDM. (J) TMRM MFI was measured in BMDM by flow cytometry after 30-min incubation. (K and L) Basal and maximal ECAR as determined by Seahorse XFe96 in control and trained BMDM stimulated with vehicle or 100 ng/ml LPS for 4 and 24 h. (M and N) Basal and maximal OCR as determined by Seahorse XFe96 in control and trained BMDM stimulated with vehicle or 100 ng/ml LPS for 4 and 24 h. Data shown as mean ± SEM. Experiments were performed with three to five biological replicates. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by ANOVA with Tukey post hoc multiple comparison test.

FIGURE 4.

β-Glucan training augments metabolism and increases mitochondrial content and membrane potential in macrophages. BMDM were treated with β-glucan (5 µg) or vehicle for 24 h (24h), washed, and allowed to rest for 3dp, followed by assessment of macrophage metabolic phenotype. (A) Glycolysis stress test of control, 24h, and trained (3dp) BMDM on the Seahorse XFe96. ECAR was measured over time at baseline and after glucose, oligomycin, and 2-DG addition. (B) Basal ECAR as determined from three separate runs. (C) Maximum ECAR as determined from three separate runs. (D) Oxidative stress test of control, 24h, and trained BMDM on the Seahorse XFe96. OCR was measured over time at baseline and after oligomycin, FCCP, and rotenone and antimycin A administration. (E) Basal OCR as determined from three separate runs. (F) Maximum OCR as determined from three separate runs. (G) Enrichment plot for GO term “Mitochondrial Respiratory Chain Complex Assembly” for control versus trained (3dp) BMDM. (H) MitoTracker Green mean fluorescence intensity (MFI) was measured in BMDM by flow cytometry after 30-min incubation. (I) Enrichment plot for GO term “Mitochondrial ATP Synthesis-Coupled Proton Transport” for control versus trained (3dp) BMDM. (J) TMRM MFI was measured in BMDM by flow cytometry after 30-min incubation. (K and L) Basal and maximal ECAR as determined by Seahorse XFe96 in control and trained BMDM stimulated with vehicle or 100 ng/ml LPS for 4 and 24 h. (M and N) Basal and maximal OCR as determined by Seahorse XFe96 in control and trained BMDM stimulated with vehicle or 100 ng/ml LPS for 4 and 24 h. Data shown as mean ± SEM. Experiments were performed with three to five biological replicates. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by ANOVA with Tukey post hoc multiple comparison test.

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Because β-glucan increased oxidative metabolism in macrophages, we assessed mitochondrial mass and activity. First, we asked whether trained BMDM increased the available mitochondrial pool. We performed an unbiased transcriptomic analysis of macrophages trained with β-glucan and assessed metabolic pathways using GO to identify enriched pathways. BMDM trained with β-glucan (3dp) displayed increases in transcriptomic signatures associated with oxidative phosphorylation (GO: 0033108, normalized enrichment score = 1.344; (Fig. 4G). In concert with this finding, 3dp BMDM had significantly higher mitochondrial content as compared with control or 24-h BMDM, as demonstrated by increased MitoTracker Green staining (Fig. 4H). These changes were mirrored by an increase in transcription related to ATP biosynthesis (GO: 0042775, NES = 1.18; (Fig. 4I) and mitochondrial membrane potential, as measured by TMRM staining (Fig. 4J). Thus, β-glucan treatment induces a unique metabolic phenotype in differentiated macrophages characterized by elevated ECAR and OCR in association with increases in mitochondrial content and function.

Next, we sought to determine the effect of β-glucan training on the macrophage metabolic response to LPS challenge (Fig. 4K–N). Control and β-glucan–trained BMDM were stimulated with 100 ng/ml LPS for 6 and 24 h, and ECAR and OCR were measured. Trained BMDM displayed a significant increase in basal and maximal glycolytic rate at baseline and after 6 h of LPS stimulation as compared with control BMDM (Fig. 4K, 4L). After 24 h of LPS stimulation, both control and trained BMDM showed similar glycolytic rates. Trained BMDM showed increased basal and maximal OCR in the absence of LPS stimulation compared with control BMDM. Both control and trained BMDM showed no or modest increases in basal and maximal OCR, respectively, at 6 h after LPS challenge (Fig. 4M, 4N). However, trained BMDM showed more robust increases in basal and maximal OCR in response to 24 h of LPS stimulation compared with control BMDM.

To understand the evolution of the macrophage response to β-glucan over time, we looked further at the transcriptomic analysis of macrophages treated with β-glucan for 4 or 24 h or after completion of our training protocol (i.e., 3dp; (Fig. 5). Principal component analysis showed that β-glucan–induced significant alterations in macrophage gene expression. This representation demonstrates that acute stimulation (4 h) with β-glucan caused the largest variance in PC1 compared with control, with 24-h and 3dp BMDM more closely resembling control BMDM in PC1, although 24-h and 3dp BMDM sustained distinct differences in PC2 (Fig. 5A). After 4 h of β-glucan stimulation, the expression of 257 (211 up/46 down) genes were altered compared with vehicle-treated controls (Fig. 5B). Twenty-four hours after stimulation, BMDM were less transcriptionally active than after acute 4-h exposure, with 104 (67 up/37 down) transcripts significantly altered (Fig. 5B). After completion of the trained immunity protocol, 109 transcripts were altered, with most being downregulated rather than upregulated (29 up/80 down) (Fig. 5B). Evaluation of GO terms sorted by enrichment score showed that macrophages treated with β-glucan for 4 h triggered pathways consistent with acute inflammation and activation of the innate immune system (Fig. 5C). At 24 h, and in 3dp BMDMs, gene pathways associated with housekeeping and cellular differentiation predominated (Fig. 5D, 5E). These results point toward alterations in gene transcription that underpin the antimicrobial phenotype seen in trained BMDM.

FIGURE 5.

β-Glucan induces a distinct transcriptomic profile in macrophages. BMDM were treated with β-glucan (5 µg) or vehicle for 4 h (4h) or vehicle for 24 h (24h). A subset of 24 h BMDM were washed and allowed to rest for 3dp. Gene expression was measured using RNASeq. (A) Principal component analysis of BMDM harvested at specified time points. (B) Relative gene expression by BMDM treated with β-glucan relative to control at the specified time points. (C) Top 20 pathways identified by GO analysis at 4 h after β-glucan treatment relative to control. (D) Top 20 pathways identified by GO analysis at 24 h after β-glucan treatment relative to control. (E) Top 20 pathways identified by GO analysis at 3dp after β-glucan treatment relative to control. RNA quantification performed in duplicate. ES, enrichment score.

FIGURE 5.

β-Glucan induces a distinct transcriptomic profile in macrophages. BMDM were treated with β-glucan (5 µg) or vehicle for 4 h (4h) or vehicle for 24 h (24h). A subset of 24 h BMDM were washed and allowed to rest for 3dp. Gene expression was measured using RNASeq. (A) Principal component analysis of BMDM harvested at specified time points. (B) Relative gene expression by BMDM treated with β-glucan relative to control at the specified time points. (C) Top 20 pathways identified by GO analysis at 4 h after β-glucan treatment relative to control. (D) Top 20 pathways identified by GO analysis at 24 h after β-glucan treatment relative to control. (E) Top 20 pathways identified by GO analysis at 3dp after β-glucan treatment relative to control. RNA quantification performed in duplicate. ES, enrichment score.

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We analyzed the impact of β-glucan treatment on cytokine production at the mRNA and protein levels (Fig. 6). Transcriptomic data revealed that treatment of BMDM with β-glucan for 4 h induced transcription of numerous proinflammatory cytokines and reduced transcription of others, such as TGF-β (Fig. 6A). In 24-h and 3dp BMDM, transcription of proinflammatory cytokines returned to near or below baseline levels, and suppressed cytokines remained suppressed (Fig. 6A). Challenge of control and 3dp BMDM with LPS potently induced cytokine production with no discernable differences among groups (Fig. 6A). Measurement of TNF-α and IL-6 concentrations in culture supernatants from control and 3dp BMDM also showed no significant difference in LPS-induced cytokine production among groups (Fig. 6B, 6C). Because β-glucan training in vivo leads to increased leukocyte recruitment, we next sought to determine if training impacted the ability of BMDM to produce and secrete chemokines. Transcripts of several chemokines that facilitate neutrophil and monocyte recruitment were upregulated 4 h after β-glucan stimulation in BMDM (Fig. 6D). Many of these transcripts remained upregulated in the 24-h and 3dp BMDM groups. Challenge of control and 3dp BMDM with LPS potently induced chemokine production with no discernable differences among the groups (Fig. 6D). Measurement of CXCL1 and CXCL2 concentrations in culture supernatants from control and 3dp BMDM showed potent induction of chemokine production with small differences among groups, although concentrations of CXCL2 were significantly higher in 3dp BMDM compared with control (Fig. 6E, 6F). Similar patterns of cytokine and chemokine secretion by control and 3dp BMDM were observed after challenge with heat-killed P. aeruginosa (Supplemental Fig. 1). Thus, LPS-induced production of proinflammatory cytokines and chemokines is sustained in trained BMDM.

FIGURE 6.

β-Glucan alters macrophage cytokine and chemokine production. BMDM were treated with β-glucan (5 µg) or vehicle for 4 h (4h) or vehicle for 24 h (24h). A subset of 24-h BMDM were washed and allowed to rest for 3dp. Cytokine mRNA expression was measured by RNASeq; protein was measured by ELISA. (A) Heatmaps of cytokine mRNA expression by BMDM at 4 or 24 h or 3 d relative to control and by control and 3dp BMDM at 4 h after LPS challenge. (B and C) Concentrations of TNF-α and IL-6 in conditioned media from control and 3dp BMDM before and after LPS challenge. (D) Heatmaps of chemokine mRNA expression by BMDM at 4 or 24 h or 3 d relative to control and by control and 3dp BMDM at 4 h after LPS challenge. (E and F) Concentrations of CXCL1 and CXCL2 in conditioned media from control and 3dp BMDM before and after LPS challenge. (G and H) Concentrations of CCL3 and CCL4 in conditioned media from control and 3dp BMDM after treatment with 2-DG or oligomycin for 6 h. Data normalized to untreated control BMDM. (I) C57BL/6 mice were injected i.p. with β-glucan (1 mg) or vehicle on two consecutive days prior to i.p. inoculation with 1 × 108 CFU P. aeruginosa with subsequent harvest of plasma 6 h later. (JM) Concentrations of IL-6, TNF-α, CXCL1, and CXCL2 in peritoneal lavage at 6 h after P. aeruginosa challenge. RNASeq experiments were performed in duplicate. All other in vitro experiments were performed with three to five biological replicates. n = 5 mice per group for in vivo experiments. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by ANOVA with Tukey post hoc multiple comparison test.

FIGURE 6.

β-Glucan alters macrophage cytokine and chemokine production. BMDM were treated with β-glucan (5 µg) or vehicle for 4 h (4h) or vehicle for 24 h (24h). A subset of 24-h BMDM were washed and allowed to rest for 3dp. Cytokine mRNA expression was measured by RNASeq; protein was measured by ELISA. (A) Heatmaps of cytokine mRNA expression by BMDM at 4 or 24 h or 3 d relative to control and by control and 3dp BMDM at 4 h after LPS challenge. (B and C) Concentrations of TNF-α and IL-6 in conditioned media from control and 3dp BMDM before and after LPS challenge. (D) Heatmaps of chemokine mRNA expression by BMDM at 4 or 24 h or 3 d relative to control and by control and 3dp BMDM at 4 h after LPS challenge. (E and F) Concentrations of CXCL1 and CXCL2 in conditioned media from control and 3dp BMDM before and after LPS challenge. (G and H) Concentrations of CCL3 and CCL4 in conditioned media from control and 3dp BMDM after treatment with 2-DG or oligomycin for 6 h. Data normalized to untreated control BMDM. (I) C57BL/6 mice were injected i.p. with β-glucan (1 mg) or vehicle on two consecutive days prior to i.p. inoculation with 1 × 108 CFU P. aeruginosa with subsequent harvest of plasma 6 h later. (JM) Concentrations of IL-6, TNF-α, CXCL1, and CXCL2 in peritoneal lavage at 6 h after P. aeruginosa challenge. RNASeq experiments were performed in duplicate. All other in vitro experiments were performed with three to five biological replicates. n = 5 mice per group for in vivo experiments. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by ANOVA with Tukey post hoc multiple comparison test.

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Consistent with constitutive expression of some chemokine transcripts by 3dp BMDM, conditioned media from 3dp BMDM contained higher levels of CCL3 (Fig. 6G) and CCL4 (Fig. 6H) than untreated controls. Addition of 500 mM 2-DG or 1 mM oligomycin, to block glycolysis or oxidative phosphorylation, respectively, blunted the secretion of both of these chemokines in control and trained macrophages (Fig. 6G, 6H). Thus, β-glucan facilitates constitutive production of some chemokines in BMDM, which is dependent on β-glucan–induced augmentation of metabolism.

We next undertook experiments to determine whether cytokine and chemokine production after β-glucan training and infection in vivo mirrored that of BMDM ex vivo. Mice were treated with β-glucan for two consecutive days, followed by challenge with P. aeruginosa 24 h later. Peritoneal lavage was obtained for cytokine measurements 6 h after infectious challenge (Fig. 6I). P. aeruginosa challenge potently induced production of IL-6, TNF-α, CXCL1, and CXCL2 in control mice (Fig. 6J–M). All of these cytokines were significantly lower in peritoneal lavage from β-glucan–trained mice (Fig. 6J–M). These findings show that local cytokine production is diminished in trained mice, compared with controls, and may be influenced by the greatly augmented clearance of bacteria observed in trained mice (see (Fig. 1).

We aimed to define the PRR pathways necessary for β-glucan–induced trained immunity. Because Dectin-1 and TLR-2 are the two major surface receptors for β-glucan on innate leukocytes, we hypothesized that deficiency of these receptors would ablate β-glucan–induced trained immunity. To test this hypothesis, we treated WT, Dectin-1 (Dec1 KO), TLR-2 (TLR-2 KO), and Dectin-1/TLR-2 DKO mice with β-glucan 48 and 24 h prior to i.p. inoculation with P. aeruginosa (Fig. 7A). In all genotypes, vehicle-treated controls developed hypothermia, but β-glucan–treated mice maintained normothermia (Fig. 7B). There were no statistically significant differences observed in core body temperature when comparing β-glucan–treated mice across genotypes. β-Glucan–treated mice of all genotypes showed lower P. aeruginosa CFUs in peritoneal lavage than vehicle-treated controls (Fig. 7C). There were no differences in P. aeruginosa CFUs between genotypes in the β-glucan–treated mice. β-Glucan treatment increased the numbers of monocytes (Fig. 7D), neutrophils (Fig. 7E), and macrophages (Fig. 7F) in the peritoneal lavage postinfection. Dec1 KO mice had significantly higher numbers of monocytes and neutrophils in the lavage than WT mice. No other differences were seen between genotypes in the β-glucan–treated groups.

FIGURE 7.

β-Glucan–induced protection against P. aeruginosa is independent of Dectin-1 and TLR-2. (A) WT, Dectin-1 KO, TLR-2, or Dectin-1/TLR-2 DKO C57BL/6 mice were injected i.p. with β-glucan (1 mg) or vehicle 48 and 24 h prior to i.p. inoculation with 1 × 108 CFU P. aeruginosa with subsequent harvest of plasma and peritoneal lavage fluid 6 h later. (B) Core (rectal) body temperature in vehicle- or β-glucan–treated mice 6 h after i.p. P. aeruginosa. (C) CFUs of P. aeruginosa per milliliter of peritoneal fluid. (DF) Number of monocytes (D), neutrophils (E), or macrophages (F) in infected vehicle- or β-glucan–treated mice. Body temperature and clearance data shown with median. All other data shown as mean ± SEM. n = 10–15 mice per group. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by Kruskal–Wallis test followed by Dunn post hoc multiple comparison test (B and C) or ANOVA with Tukey post hoc multiple comparison test (D–F).

FIGURE 7.

β-Glucan–induced protection against P. aeruginosa is independent of Dectin-1 and TLR-2. (A) WT, Dectin-1 KO, TLR-2, or Dectin-1/TLR-2 DKO C57BL/6 mice were injected i.p. with β-glucan (1 mg) or vehicle 48 and 24 h prior to i.p. inoculation with 1 × 108 CFU P. aeruginosa with subsequent harvest of plasma and peritoneal lavage fluid 6 h later. (B) Core (rectal) body temperature in vehicle- or β-glucan–treated mice 6 h after i.p. P. aeruginosa. (C) CFUs of P. aeruginosa per milliliter of peritoneal fluid. (DF) Number of monocytes (D), neutrophils (E), or macrophages (F) in infected vehicle- or β-glucan–treated mice. Body temperature and clearance data shown with median. All other data shown as mean ± SEM. n = 10–15 mice per group. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by Kruskal–Wallis test followed by Dunn post hoc multiple comparison test (B and C) or ANOVA with Tukey post hoc multiple comparison test (D–F).

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Additionally, we determined whether loss of Dectin-1 and TLR-2 impacted β-glucan–induced metabolic alterations in BMDM by performing extracellular flux analysis. WT and DKO BMDM were treated with β-glucan for 24 h and assessed immediately or allowed to rest for 3 d to induce trained immunity (i.e., 3dp). DKO BMDM had reduced basal ECAR levels after both 24 h and 3dp β-glucan as compared with WT BMDM; however, no differences were seen in max ECAR levels (Fig. 8A–C). WT and DKO BMDM showed no significant differences in basal and max OCR levels after 24 h β-glucan and in the trained group (Fig. 8D–F).

FIGURE 8.

Metabolic alterations in β-glucan–trained macrophages are independent of Dectin-1 and TLR-2. BMDM from WT and DKO mice were treated with β-glucan (5 µg) or vehicle for 24 h (24h), washed, and allowed to rest for 3dp, followed by assessment of macrophage metabolic phenotype. (A) Glycolysis stress test of control, 24h, and 3dp BMDM on the Seahorse XFe96 in WT and DKO mice. ECAR was measured over time at baseline and after glucose, oligomycin, and 2-DG administration. (B) Basal ECAR in each group from multiple replicates. (C) Maximum ECAR in each group from multiple replicates. (D) Oxidative stress test of control, 24h, and trained BMDM on the Seahorse Xfe96. OCR was measured over time at baseline and after oligomycin, FCCP, and rotenone and antimycin A administration. (E) Basal OCR in each group from multiple replicates. (F) Maximum OCR in each group from multiple replicates. Data shown as mean ± SEM. Experiments were performed with three biological replicates. **p < 0.01, ***p < 0.001 by ANOVA with Tukey post hoc multiple comparison test.

FIGURE 8.

Metabolic alterations in β-glucan–trained macrophages are independent of Dectin-1 and TLR-2. BMDM from WT and DKO mice were treated with β-glucan (5 µg) or vehicle for 24 h (24h), washed, and allowed to rest for 3dp, followed by assessment of macrophage metabolic phenotype. (A) Glycolysis stress test of control, 24h, and 3dp BMDM on the Seahorse XFe96 in WT and DKO mice. ECAR was measured over time at baseline and after glucose, oligomycin, and 2-DG administration. (B) Basal ECAR in each group from multiple replicates. (C) Maximum ECAR in each group from multiple replicates. (D) Oxidative stress test of control, 24h, and trained BMDM on the Seahorse Xfe96. OCR was measured over time at baseline and after oligomycin, FCCP, and rotenone and antimycin A administration. (E) Basal OCR in each group from multiple replicates. (F) Maximum OCR in each group from multiple replicates. Data shown as mean ± SEM. Experiments were performed with three biological replicates. **p < 0.01, ***p < 0.001 by ANOVA with Tukey post hoc multiple comparison test.

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To directly measure activation of the Dectin-1 and TLR-2 signaling pathways by the β-glucan training reagent, we treated BMDM with 5 mg/ml β-glucan (two separate batches) for 0.5, 1, and 2 h and measured phosphorylation of inhibitor of kB kinase (IkK) and spleen tyrosine kinase (Syk) by Western blot. Concurrently, BMDM were treated with 5 mg/ml linear β-glucan for 0.5, 1, and 2 h or with 100 ng/ml LPS for 1 h as positive controls. LPS and linear glucan induced strong IkK phosphorylation and moderate Syk phosphorylation, whereas neither batch of β-glucan training reagent induced phosphorylation of either protein, as compared with unstimulated BMDM (Fig. 9).

FIGURE 9.

The β-glucan training reagent induces weak Dectin-1 and TLR-2 activation. Protein was isolated from BMDM treated with β-glucan for 0.5, 1.0, or 2.0 h. BMDM treated with 100 ng/ml LPS for 1 h or linear glucan for 0.5, 1.0, or 2.0 h served as positive controls. Western blot of pIkK, total IkK, pSyk, and total Syk. Blots are representative of three repeated experiments.

FIGURE 9.

The β-glucan training reagent induces weak Dectin-1 and TLR-2 activation. Protein was isolated from BMDM treated with β-glucan for 0.5, 1.0, or 2.0 h. BMDM treated with 100 ng/ml LPS for 1 h or linear glucan for 0.5, 1.0, or 2.0 h served as positive controls. Western blot of pIkK, total IkK, pSyk, and total Syk. Blots are representative of three repeated experiments.

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The major finding of this study is that β-glucan elicited a trained immune phenotype in differentiated macrophages that conferred protection from infection with P. aeruginosa. We found that β-glucan training augmented the host response to P. aeruginosa infection by facilitating recruitment of innate leukocytes and augmenting bacterial clearance at the site of infection. Adoptive transfer of macrophages treated ex vivo with β-glucan into naive mice recapitulated the protective phenotype. Furthermore, β-glucan–induced significant alterations in macrophage gene transcription and metabolism. These changes underpinned a robust enhancement of macrophage antimicrobial functions, including phagocytosis, ROS generation, and cytokine production. This study advances our understanding of trained immunity by showing the contributions of differentiated macrophages and defining cellular and molecular mechanisms of training in these effector cells. Our findings suggest that differentiated macrophages, which survive for weeks to months in situ, contribute to the protective phenotype conferred by treatment with β-glucan. In addition, β-glucan–induced protection was preserved after loss of Dectin-1 and TLR-2, which suggests that alternative receptors drive the trained phenotype.

β-Glucan has long been described as an immunomodulatory agent with the capacity to augment the host response against bacterial, viral, and fungal pathogens (4649). More recent studies show that β-glucan–mediated innate immunomodulation lasts for several weeks (11, 50). Ciarlo and colleagues (50) showed that training of mice with zymosan, of which β-glucan is the major biologically active component, induced training that conferred protection from E. coli peritonitis and listeriosis for 5 wk. Furthermore, they demonstrated that zymosan treatment enhanced survival after P. aeruginosa pneumonia for 1 wk. Our study shows sustained and robust protection from P. aeruginosa infection for at least 2 wk after training with β-glucan. This raises the question of what mechanisms support this innate immune memory phenotype. One possibility is that β-glucan induces long-term changes to bone marrow progenitor cells that can serve to sustain the trained phenotype. Indeed, β-glucan promotes hematopoietic stem cell precursor (HSPC) expansion and myelopoiesis, which confers a survival benefit in mice repeatedly treated with the myeloablative drug 5-fluorouracil (51). Additionally, HSPCs treated with depleted zymosan, a β-glucan enriched for Dectin-1 signaling, and adoptively transferred into Dectin-1–deficient mice secreted higher levels of IL-6 and TNF-α when isolated and challenged ex vivo with the synthetic triacylated lipopeptide Pam3CysSerLys4 (52). Mice trained with β-glucan and subsequently infected with Mycobacterium tuberculosis undergo HSPC expansion after training and ultimately demonstrate improved survival after pulmonary infection (53). Ciarlo and colleagues (50) also demonstrated myelopoiesis in mice trained with zymosan but did not observe alterations in protection from Listeria monocytogenes infection in mice depleted of neutrophils by treatment with anti–Ly-6G. Their findings support the notion that enhanced local antimicrobial activity, rather than recruitment of β-glucan–trained myeloid cells, mediates protection against intracellular pathogens such as M. tuberculosis and L. monocytogenes. However, it is unclear whether β-glucan–trained HPSCs mediate augmented protection against an acute infection with common extracellular pathogens such as P. aeruginosa. The present study indicates that augmented neutrophil recruitment is important for improved clearance of P. aeruginosa in mice trained with β-glucan. These findings are consistent with our prior observations in β-glucan–trained mice infected with E. coli and suggest that expansion and mobilization of neutrophil precursors from bone marrow may contribute to the trained phenotype in vivo (54). Nevertheless, further studies are needed to fully characterize the impact of immune training on HSPC function and the impact on neutrophil expansion and recruitment during infection.

Our study shows that macrophages trained with β-glucan confer resistance to infection after adoptive transfer, which supports the notion that β-glucan trains macrophages that are poised to immediately respond to infection. Very little is known about β-glucan–induced innate immune memory in differentiated macrophages, although there is some evidence to suggest that short-term treatment with β-glucan immediately before LPS influences BMDM activation (55). Bistoni and colleagues (56) reported that systemic infection with a low-virulence variant of C. albicans confers resistance to infection with a broad array of pathogens and macrophages were central mediators of the protective effect. Although they did not identify the C. albicans component causing the trained effect, their results are similar to the results of the current study in which we employed C. albicans–derived β-glucan and support the contention that macrophages have the capacity to facilitate the trained phenotype in vivo. Likewise, Ciarlo and colleagues (50) showed that depletion of macrophages with clodronate-laden liposomes depleted the protective effects of zymosan against L. monocytogenes infection. Our findings extend those observations by showing that adoptive transfer of macrophages trained with β-glucan confers resistance to infection with P. aeruginosa. Macrophages represent a population of leukocytes that are well suited to sustain the trained phenotype because of their central role as regulators of the innate immune response to infection and a life span that is compatible with preserving the trained phenotype for weeks (57).

Our characterization of innate immune memory in macrophages reveals interesting distinctions when compared with the canonical monocyte profile. Trained monocytes activate hypoxia-inducible factor-1α to shift energy production primarily toward glycolysis and away from oxidative metabolism, even in oxygen-rich environments, a phenomenon known as aerobic glycolysis (58). In contrast, training of macrophages with β-glucan augments both glycolytic and oxidative metabolism. In this study, we show that enhancement of oxidative metabolism seems to be achieved by expansion of the functional mitochondria pool and increased mitochondrial membrane potential. Furthermore, we show that inhibition of either glycolytic or oxidative metabolism with 2-DG and oligomycin, respectively, blunted the ability of trained macrophages to constitutively secrete chemokines. This suggests that augmentation of broad metabolic pathways contributes to the antimicrobial phenotype in β-glucan–trained macrophages.

A key tenet of β-glucan–trained immunity is augmented cytokine production in response to infection or LPS challenge and its purported ability to reverse endotoxin tolerance in monocytes previously exposed to LPS (18). Results of the current study show that macrophages trained with β-glucan sustain the ability to secrete cytokines in response to LPS. Macrophages trained with β-glucan secrete comparable levels of IL-6 and TNF-α after stimulation with LPS compared with untrained controls. Furthermore, transcriptomic profiling of macrophages after LPS challenge revealed similarity in cytokine and chemokine expression between β-glucan–trained and control macrophages. Interestingly, we observed decreased cytokine and chemokine concentrations in peritoneal lavage from β-glucan–trained mice after i.p. P. aeruginosa challenge compared with vehicle-treated controls. The disparity in cytokine production in vivo versus that observed in cultured macrophages could be explained by the augmented ability of β-glucan–trained mice to clear bacteria from the site of infection, thus decreasing local and systemic inflammation. We previously published data showing that a training agent’s ability to increase or decrease cytokine production in macrophages does not necessarily correlate with its ability to protect against infection (38, 59). This interpretation has been corroborated by work in human monocytes (60, 61). Instead, we propose that examination of direct antimicrobial functions, such as phagocytosis, ROS production, microbial killing, and leukocyte recruitment, rather than reliance on cytokine production alone, is a more accurate metric of the ability of an agent to confer trained immunity. Trained macrophages showed enhanced phagocytosis and ROS generation in the current study, indicating augmentation of direct antimicrobial functions. Taken together, our findings indicate that β-glucan induces a macrophage phenotype that is more effective at recruiting leukocytes to the site of infection and mediating direct microbial clearance. Dectin-1 and TLR-2 are both well-characterized PRRs for β-glucan (62, 63). Dectin-1 deficiency diminishes cellular responses to β-glucan in vitro, but its role in response to fungal infection has been disputed (64, 65). Similarly, the contribution of TLR-2 to β-glucan–induced immune responses and the host response to infection has not been fully elucidated in vivo (66). In this study, we show that neither Dectin-1 nor TLR-2 are required for β-glucan–induced protection against P. aeruginosa infection or β-glucan–induced metabolic reprogramming in macrophages. Given that different fungi containing β-glucan trigger different surface receptors on leukocytes, this phenomenon should be confirmed in infections with other pathogens. Interestingly, β-glucan has been shown to stimulate macrophages independently of Dectin-1 and TLR-2, adding further evidence to the possibility that β-glucan–trained immunity occurs independently of either receptor (32, 67). Other receptor families that have been reported to mediate β-glucan recognition include complement receptor 3 (CR3; CD18/CD11b), lactosylceramide, and scavenger receptors (6870). These varying results may be due to the fact that β-glucan of varying structural motifs can be derived from wide-ranging species of fungi (71, 72). Our finding that a linear β-glucan derived from C. albicans induces Syk and IKK phosphorylation, whereas the branched β-glucan training reagent does not, supports this contention. Clearly, further research is needed to further identify β-glucan structure, receptors, and signaling pathways.

Our findings support the development of agents that induce trained immunity to fight infection in the clinical realm and show that training with β-glucan provides protection against P. aeruginosa infection. Our results are complemented by the work of Ciarlo and colleagues (50), who showed that training with zymosan confers protection from P. aeruginosa pneumonia. Among the critically ill, P. aeruginosa has emerged as a common pathogen leading to serious healthcare-associated infections (73). P. aeruginosa accounts for nearly 20% of infections in intensive care units, and the mortality rate of these infections approaches 40% (74). Furthermore, the prevalence of antimicrobial-resistant P. aeruginosa is increasing dramatically, due in part to the spread of mobile genetic elements that convey antibiotic resistance and poor antibiotic stewardship among health care providers (7577). Thus, there is an acute need for the development of alternative strategies to prevent and abate P. aeruginosa infections. Induction of trained immunity by agents such as β-glucan provides an opportunity to augment host resistance to common pathogens.

Given the importance of differentiated macrophages for the protective phenotype induced by β-glucan, future studies should explore the efficacy of newly developed agents for inducing trained immunity in these cells. Because β-glucan is one of the most extensively characterized immune training agents, it is a logical candidate to inform future drug-discovery efforts. However, our work and other studies indicate that noncanonical signaling pathways may be responsible for the trained phenotype. Thus, β-glucan is a promising candidate for development for use against increasingly common and lethal nosocomial pathogens such as P. aeruginosa.

We thank the Vanderbilt Technologies for Advanced Genomics core for performing RNASeq. We also thank Yaomin Xu, Yu Wang, and Caley Stothers for help with RNASeq analysis.

This work was supported by the National Institute of General Medical Sciences, National Institutes of Health (NIH) Grants GM119197 (to E.R.S. and D.L.W.), GM121711 (to J.K.B.), GM141927 (to J.K.B.), GM083016 (to D.L.W.), GM108554 (to N.K.P.), and GM007347 (Vanderbilt Medical Scientist Training Program: C.L.S. and M.A.M.); National Institute of Allergy and Infectious Diseases AI151210 (to E.R.S.); the American Heart Association Grant 19PRE34430054 (to C.L.S.); and Vanderbilt University Medical Center Award VFRS (to N.K.P.). The Agilent Seahorse Extracellular Flux Analyzer is housed and managed within the Vanderbilt High-Throughput Screening Core Facility, an institutionally supported core, and was funded by NIH Shared Instrumentation Grant 1S10OD018015.

C.L.S. and E.R.S. wrote the manuscript and designed the figures. C.L.S., D.L.W., and E.R.S. designed experiments. C.L.S., K.R.B., A.M.O., N.K.P., M.A.M., L.L., J.K.B., A.H., and T.K.P. performed experiments. C.L.S., D.L.W., and E.R.S. analyzed data. All authors approved the final manuscript.

The data presented in this article have been submitted to National Center for Biotechnology Information Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE174141.

The online version of this article contains supplemental material.

Abbreviations used in this article

BMDM

bone marrow–derived macrophage

2-DG

2-deoxyglucose

DKO

double KO

3dp

three-days postgroup

ECAR

extracellular acidification rate

GO

Gene Ontology

HSPC

hematopoietic stem cell precursor

IkK

inhibitor of kB kinase

KO

knockout

OCR

oxygen consumption rate

PRR

pattern-recognition receptor

RNASeq

RNA sequencing

ROS

reactive oxygen species

Syk

spleen tyrosine kinase

TMRM

tetramethylrhodamine, methyl ester

WT

wild-type

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The authors have no financial conflicts of interest.

Supplementary data