Immunomodulatory (IM) metabolic reprogramming in macrophages (Mϕs) is fundamental to immune function. However, limited information is available for human Mϕs, particularly in response plasticity, which is critical to understanding the variable efficacy of immunotherapies in cancer patients. We carried out an in-depth analysis by combining multiplex stable isotope-resolved metabolomics with reversed phase protein array to map the dynamic changes of the IM metabolic network and key protein regulators in four human donors’ Mϕs in response to differential polarization and M1 repolarizer β-glucan (whole glucan particles [WGPs]). These responses were compared with those of WGP-treated ex vivo organotypic tissue cultures (OTCs) of human non-small cell lung cancer. We found consistently enhanced tryptophan catabolism with blocked NAD+ and UTP synthesis in M1-type Mϕs (M1-Mϕs), which was associated with immune activation evidenced by increased release of IL-1β/CXCL10/IFN-γ/TNF-α and reduced phagocytosis. In M2a-Mϕs, WGP treatment of M2a-Mϕs robustly increased glucose utilization via the glycolysis/oxidative branch of the pentose phosphate pathway while enhancing UDP-N-acetyl-glucosamine turnover and glutamine-fueled gluconeogenesis, which was accompanied by the release of proinflammatory IL-1β/TNF-α to above M1-Mϕ’s levels, anti-inflammatory IL-10 to above M2a-Mϕ’s levels, and attenuated phagocytosis. These IM metabolic responses could underlie the opposing effects of WGP, i.e., reverting M2- to M1-type immune functions but also boosting anti-inflammation. Variable reprogrammed Krebs cycle and glutamine-fueled synthesis of UTP in WGP-treated OTCs of human non-small cell lung cancer were observed, reflecting variable M1 repolarization of tumor-associated Mϕs. This was supported by correlation with IL-1β/TNF-α release and compromised tumor status, making patient-derived OTCs unique models for studying variable immunotherapeutic efficacy in cancer patients.

Macrophages (Mϕs), an essential component of innate immunity, play a central role in inflammation and host defense (1) and are frequently the dominant members of the infiltrating cells in human tumors (2). Mϕs orchestrate immune responses to exert protumoral or antitumoral activity by interacting with cancer cells, T lymphocytes (key players in adaptive immunity and central to tumoricidal activity), and other immune cells in the tumor microenvironment (3, 4). Classically activated (M1) mouse Mϕs are characterized by elevated expression of MHC class II, IL-12, and TNF-α; excess production of reactive oxygen species and NO; and enhanced tumoricidal activity. In contrast, alternatively activated (M2) Mϕs are protumorigenic (5). Most tumor-associated Mϕs (TAMs), including those in non-small cell lung cancer (NSCLC), are M2-like, expressing high levels of vascular endothelial growth factor, arginase 1, cyclooxygenase-2–derived PGE2, and anti-inflammatory IL-10 (6, 7). Mouse TAMs are known to promote tumor progression by suppressing CTL activation (8), upregulating checkpoint proteins such as programmed death ligand 1 (9) and B7-H4 (10), as well as by reducing their own capacity for Ag presentation (e.g., reduced MHC class II expression) (11). Moreover, T cell exclusion from tumor islets by TAM action correlates with poor NSCLC patient survival and may well contribute to the lack of response to anti–programmed death ligand 1 therapies (12).

Evidence is mounting for the importance of Mϕ metabolism in modulating tumor immunity (5, 1320). It is now known that mouse Mϕs undergo variable metabolic reprogramming depending on the method of polarization. LPS and IFN-γ–activated (M1-type) Mϕs or M(LPS + IFN-γ) (21) display accelerated glycolysis, the pentose phosphate pathway (PPP), and tryptophan (Trp) catabolism, but reduced oxidative phosphorylation, glutaminolysis, and Krebs cycle activity, as well as accumulation of citrate and succinate as a result of two breaks in the Krebs cycle (2227). However, glutamine (Gln) metabolism appears to be important for both M1- and M2-type murine Mϕs. Gln catabolism was found to be required for IL-4–induced M2 polarization in murine Mϕs (M2-Mϕs) by fueling the production of UDP-N-acetyl-glucosamine (UDPGlcNAc) and consequent N-glycosylation of cell surface receptors of M2-Mϕs (23). However, Gln metabolism was also enhanced in LPS-driven murine M1-Mϕs and human monocytes, which could support arginase and NO production (28). In human cancer cells and murine T/dendritic cells, NO in turn activates glycolysis (2931), which is also a hallmark of mouse M(LPS + IFN-γ). We have also seen activated glutaminolysis in murine M1-Mϕs in a stable isotope resolved metabolomic (SIRM) study (7). The reason for such divergence in Gln metabolism is unclear but illustrates the plasticity of glutaminolysis in response to Mϕ polarization.

It is also known that the products of the reprogrammed metabolism modulate key functions of activated Mϕs, as the enzymes that catalyze the reprogramming. For example, citrate accumulation fuels the production of the antimicrobial (32) but also anti-inflammatory (33, 34) metabolite itaconate in LPS-activated murine and human Mϕs. The latter role of itaconate involves a complex feedback loop in immunomodulation. Namely, sustained itaconate production by LPS stimulation limited type 1 IFN response while promoting anti-inflammatory program mediated by NF Erythroid 2 Like 2 activation in human and murine Mϕs, as well as succinate dehydrogenase (SDH) inhibition in murine Mϕs. Blocked IFN response in turn attenuates inflammatory gene expression and itaconate production (34). Succinate produced from citrate stabilizes hypoxia-inducible factor 1α (HIF-1α) (35) and induces mitochondrial reactive oxygen species production (36), which regulate M1-Mϕ activation in murine Mϕs. Releasing extracellular succinate activates the succinate receptor GPR91 (SUCNR1) on the cell surface to induce proinflammatory IL-1β production in an autocrine manner in mouse Mϕs and human myeloid cells (15). Acetyl-CoA derived from citrate via citrate lyase activity is a substrate for arachidonate synthesis, which is required for producing the immunosuppressive (37) modulator PGE2 in LPS-activated human Mϕs (38). The other acetyl-CoA derived from citrate via citrate lyase activity product, oxaloacetate, can produce NADPH via the concerted action of malate dehydrogenase (MDH) and malic enzyme (ME) to fuel superoxide anion production via NADPH oxidase (i.e., O2 burst) for bactericidal activity (38, 39). Trp catabolism initiated by superoxide or proinflammatory cytokine-induced indoleamine-2,3-dioxygenase (IDO) produces quinolinate (QA), the accumulation of which accompanies M1 activation of human Mϕs (40, 41). QA buildup in human M1-Mϕs also results from the loss of QPRT, which underlies compromised mitochondrial functions for lack of NAD+ replenishment supported by the QPRT activity (42). However, QA has also been thought to fuel NAD+ synthesis during inflammation. NAD+ is depleted by ADP-ribosylation catalyzed by poly(ADP-ribose) polymerase (PARP) for repairing DNA strand breaks and by ADP-ribosyltransferases for modulating the activity of cellular proteins in human or murine Mϕs and cell surface receptors in other mouse leukocytes (40, 43). Another product of Trp catabolism, picolinate, is also known to activate M1 polarization of murine Mϕs while inducing tumoricidal activity (4446). Furthermore, the LPS-driven murine Mϕ activation is modulated by the glycolytic enzyme pyruvate kinase M2 (PKM2) via dimerization and HIF-1α activation (47).

Despite these key roles of Mϕ metabolism in immunomodulation, our understanding of the metabolic reprogramming derives primarily from polarized murine Mϕ models. Whether these and additional metabolic events occur in polarized human Mϕs is still unclear. Even less is known about the temporal dependence and the plasticity of an individual’s response to polarization and immune modulators in human Mϕs. A recent report indicates that human Mϕs from young and old individuals differ in their immunomodulatory (IM) metabolism and functions (42).

β-Glucans are dietary fibers comprising d-glucose (d-Glc) subunits linked via β-(1→3) and β-(1→6) or β-(1→4) glycosyl bonds. Bioactive β-glucans [with β-(1→3) bonds], yeast-derived whole glucan particles (WGPs) in particular, have been shown to elicit numerous proinflammatory responses by ligating to pattern recognition receptors, such as dectin-1 and CR3 (48), on the surface of innate immune cells. We and others showed that WGPs reversed the immunosuppressive property of murine TAMs and myeloid-derived suppressor cells, leading to CD4/CD8 T cell activation and reduced regulatory T cell numbers (7, 49). We also showed that this reversion of murine TAMs to an M1-like state was accompanied by enhanced glycolysis and glutaminolysis (7). β-Glucan–enhanced glutaminolysis was recently shown to replenish fumarate, which modulated H3K27 acetylation and/or H3K4 methylation in human monocytes to promote innate immune memory or trained immunity (50). β-Glucan also reversed immune tolerance by suppressing immune-responsive gene 1 expression and itaconate production while restoring SDH expression in tolerant human monocytes (51). However, other than our recent finding on WGP-induced activation of Glc metabolism in an NSCLC patient’s tumor tissues (52), there is little information on β-glucan’s effect on IM functions and metabolism in human Mϕs, particularly for old individuals. This knowledge is important for delineating the responses of Mϕs to β-glucan in NSCLC tissues, because NSCLC is a disease mainly of the aged. In turn, the information will be valuable for better understanding β-glucan’s action in an ongoing combination clinical trial for NSCLC (NCT03003468 sponsored by Merck).

In this study, we used [13C6]Glc as a single tracer and [2H2] or [D2]Glc + [13C5]Gln + [15N2]Trp as triple tracers coupled with SIRM analysis to globally define time-course changes in IM metabolism, along with the analysis of IM function in human Mϕs (derived from four healthy donors) in response to differential polarization and WGPs. We also investigated the effect of WGPs on IM metabolism and function in ex vivo human NSCLC organotypic tissue cultures (OTCs) using [13C6]Glc or [13C5,15N2]Gln as tracers. We compared the responses of human Mϕs to WGPs in vitro with the effects of WGPs on NSCLC OTCs ex vivo to gain a better understanding on the plasticity and TAM component of the latter response.

Monocytes were isolated from whole human peripheral blood of two each healthy male (UK096 and UK168) and female (UK094 and UK166) donors using the RosetteSep human monocyte enrichment mixture kit (STEMCELL). There is no known history of smoking, hypertension, atherosclerosis, diabetes mellitus, or cancer for any of the four healthy donors. UK094, UK166, and UK168 have seasonal allergy but were not under the influence at the time of blood collection. Monocytes were differentiated in six-well plates (Nunclon Δ; Thermo Fisher) for 6 d in monocytes differentiation medium (MDM) containing DMEM, 10% FBS, 10 mM Glc, 2 mM Gln, 1× Anti-anti, and 50 ng/ml CSF-1 at 37°C/5% CO2 at a density of 3–5 × 106 cells/well before polarization. Cells were maintained in MDM (M0) or polarized to either M1 with 100 ng/ml LPS + 20 ng/ml IFN-γ or to M2a subtype with 20 ng/ml each IL-4 + IL-13 for 1–3 d.

Mϕs were prestained with Hoechst 33342 (NucBlue reagent; catalog number [Cat#] R37605; Fisher) as per vendor’s directions, fixed with 4% paraformaldehyde for 10 min, then washed twice with PBS. Cells were blocked and permeabilized in blocking solution for 1 h (5% heat-inactivated goat serum + 0.3% Triton X-100 in PBS), followed by overnight incubation at 4°C with the following primary Abs: mouse CD206 (Cat# 321102, 1:100 dilution; BioLegend) and rabbit IDO1 (Cat# 86630, 1:100 dilution; Cell Signaling). Excess primary Abs were removed with four washes in buffer composed of 1× PBS, 5% heat-inactivated goat serum, and 0.1% Triton X-100. After washing, appropriate secondary Abs (Alexa Fluor 488 goat anti-rabbit 1:500 dilution, Cat# A11008 and Alexa Fluor 647 goat anti-mouse 1:500 dilution, Cat# A21235; Life Technologies) were added and allowed to hybridize for 1 h. Cells were washed four times with wash buffer to remove excess secondary Abs. Cells in each well were then covered with 50% Stay-Brite antifade solution (Ursa Bioscience) and stitch imaged using an EVOS M7000 (Invitrogen) inverted fluorescent microscope with appropriate filters.

For tissue staining, formalin-fixed, paraffin-embedded tissues were cut into 4-µm sections, rehydrated, and processed for Ag retrieval in 10 mM sodium citrate + 0.05% Tween 20 (pH 6) before multiplex staining using the Tyramide SuperBoost kits (Cat# B40922, B40916; Life Technologies) (53), as per vendor’s protocol. In brief, tissue slides were blocked in 10% goat serum for 1 h at room temperature, incubated sequentially with each primary Ab (mouse anti-PCNA, 1:4000, Cat# 25865 and anti-rabbit RIP1, 1:100, Cat# 34935; Cell Signaling) at 4°C overnight, followed by incubation with the appropriate secondary Ab (see earlier) for 1 h at room temperature and reaction with tyramide working solution for 10 min. The stained slides were mounted in Prolonged Gold antifade reagent + DAPI (Cat# P36931; Invitrogen) overnight at 4°C before microscopy on an Olympus FV1200 Confocal system.

All stitched Mϕ images were analyzed using CellProfiler (54). The nuclei were segmented and counted in each image. The nuclei segmentation was inspected manually, and images that did not segment well were either removed from analysis or reanalyzed to improve segmentation. The segmented nuclei were then masked with the other channels of the image to determine the colocalized intensity of those channels. Both the colocalized intensity and total intensity of the channels were normalized by the number of nuclei.

Phagocytic activity was determined using pHrodo Red zymosan dye–conjugated bioparticles (Cat# P35364; Life Technologies) as per vendor’s instructions. In brief, 2 × 105 unpolarized Mϕs were plated on a 384-well SV µClear black plate (Cat# 788091; Greiner) and polarized with LPS + IFN-γ or IL-4 + IL-13 for 2–3 d before WGP treatment as described earlier. Treated Mϕs were then incubated with pHrodo bioparticles at 0.1 mg/ml in MDM at 37°C, 5% CO2 in a Cytation 3 plate reader (Biotek) and read with excitation and emission wavelengths of 560 and 590 nm, respectively. Readings were taken every 5 min over a 2-h period to generate kinetic curves. After phagocytosis reading, the bioparticle-containing media were replaced with DMEM containing Hoechst 33342 (NucBlue reagent, Cat# R37605; Fisher), incubated for 15 min, and washed three times with PBS before reading at excitation and emission wavelengths of 360 and 460 nm, respectively. The phagocytosis readings were normalized to the Hoechst readings.

Cellular cytokine levels were obtained from reversed phase protein array (RPPA) analysis of protein extracts using appropriate Abs, as described later. The spot intensity for each cytokine was normalized to the corresponding protein intensity acquired from the Fast Green protein staining before immunostaining. Medium cytokines were quantified on 10-µl samples using the Milliplex Human Cytokine/Chemokine Magnetic Bead Premixed 29 Plex Kit (cat# HCYTMAG-60K-PX29) per vendor’s protocol except that the method was adapted for 384-well plate assays by scaling down all reagents proportionally. Fluorescent bead reading was performed in 96-well plates with 80 µl Sheath Fluid per well on a Luminex 200 analyzer (Luminex Corporation). Fluorescent intensity was calibrated with a standard curve of 29 cytokine standards at 0, 3.2, 6.4, 16, 80, 400, and 2000 pg/ml.

At the end of the polarization period, Mϕs in six-well plates were used as they were or split into 12-well plates at 700,000 cells/well for tracer and WGP treatment. For the [13C6]Glc or [13C5,15N2]Gln experiments, media were changed to fresh MDM with unlabeled Glc or Gln replaced, respectively, by 0.2% [13C6]Glc or 2 mM [13C5,15N2]Gln. For the triple-tracer experiment, media were changed to fresh MDM with unlabeled Glc, Gln, and Trp replaced, respectively, by 0.2% [D2]Glc, 2 mM [13C5]Gln, and 78 µM [15N2]Trp. One set of M[IL-4 + IL-13] in all tracer experiments was also treated with 100 μg/ml WGPs and cultured for another 24 h before harvest. Media were collected at 0 and 24 h after treatment and spun at 3500 × g for 15 min at 4°C to remove debris before extraction. At harvest, cells were rinsed twice in cold PBS and briefly (<1 min) in nanopore water to remove salts before the addition of cold acetonitrile to quench metabolism (55).

Lung tissues were collected from consented patients at the operating room within 5 min of surgical resection and placed in DMEM in accordance with Health Insurance Portability and Accountability Act regulations. All tissue experiments were carried out via a protocol approved by the University of Kentucky Institutional Review Board (14-0288-F6A). The pair of cancerous (CA) and noncancerous (NC) tissues were thinly sliced to <1 mm thickness as previously described (56, 57) and incubated in Glc and Gln-free DMEM supplemented with dialyzed FBS, penicillin, streptomycin, and 15 mM [13C6]Glc + 2 mM unlabeled Gln or 2 mM [13C5,15N2]Gln + 15 mM unlabeled Glc ± 100 µg/ml WGPs for 24 h at 37°C/5% CO2 with gentle rocking to facilitate nutrient uptake and waste product mixing. Culture media were sampled at 0 and 24 h of incubation. Tissue slices were then quickly rinsed three times in cold PBS and then briefly in Nanopure water to remove medium components and salts, blotted dry, weighed on a 4-place balance, and flash frozen in liquid N2.

Polar extraction of human Mϕs in plates quenched as described earlier was performed as previously described (58). In brief, cells were scraped twice in acetonitrile:Nanopure water (2:1.5, v/v), followed by addition of CHCl3 to a final ratio of 2:1.5:1 acetonitrile:Nanopure water:CHCl3. The top layer of polar extracts was aliquoted and lyophilized for nuclear magnetic resonance (NMR) and ion chromatography ultra-high-resolution Fourier transform mass spectrometry (IC-UHR-FTMS) analysis. The remaining pellets were removed of lipids as described previously (59). The residues after lipid extraction were homogenized in SDS buffer containing 62.5 mM Tris (pH 6.8), 2% SDS, and 1 mM DTT using a mini-pestle, followed by centrifugation at 14,800 rpm for 10 min at 4°C to obtain protein extracts. Protein concentrations were determined by microBCA assay (Pierce Chemical), per vendor’s protocol.

For tissue extraction, the frozen tissue slices were homogenized in 60% cold CH3CN in a ball mill (Precellys-24; Bertin Technologies, Washington, DC) for denaturing proteins and optimizing extraction. Polar metabolites were extracted by the same solvent partitioning method as described earlier (58). The polar extracts were lyophilized in aliquots for NMR and IC-UHR-FTMS analysis.

All culture media were deproteinized in 80% acetone at −80°C for 0.5 h before centrifugation, lyophilization, and reconstitution in 100% D2O for 1H-NMR analysis (60). In parallel, 10 µl of each medium sample or an aliquot of cell polar extracts was derivatized in ethyl chloroformate before direct infusion UHR-FTMS analysis as described previously (61). This method complemented NMR or IC-UHR-FTMS analysis by quantifying all amino acids and their isotopologues.

IC-UHR-FTMS was performed as previously described (52). In brief, polar extracts were reconstituted in 20 μl Nanopure water and analyzed by a Dionex ICS-5000+ ion chromatograph interfaced to an Orbitrap Fusion Tribrid mass spectrometer (Thermo Fisher Scientific, San Jose, CA) operating at a resolution setting of 500,000 (full width at half maximum at mass-to charge ratio 200) on MS1 acquisition to capture all [13C], [15N], and [2H] isotopologues. The chromatograph was outfitted with a Dionex IonPac AG11-HC-4 µm RFIC&HPIC (2 × 50 mm) guard column upstream of a Dionex IonPac AS11-HC-4 µm RFIC&HPIC (2 × 250 mm) column. Chromatography and mass spectrometric settings were the same as described previously (60) with mass-to charge ratio range of 80–700. Metabolites and their isotopologues were identified, and their peak areas were integrated and exported to Excel via the TraceFinder 3.3 (Thermo) software package. Peak areas were corrected for natural abundance as previously described (62), after which fractional enrichment and micromoles of metabolites per gram of protein were calculated to quantify [13C] incorporation into various metabolites.

Lyophilized polar extracts were dissolved in 35 µl D2O containing 8.81 nmol d6- (2,2-dimethyl-2-silapentane-5-sulfonate [DSS]; Cambridge Isotope Laboratories, Tewksbury, MA) for NMR analysis. NMR spectra were recorded at 15°C on a 1.7-mm inverse triple-resonance HCN cryoprobe on a Bruker AVANCE III NMR at 16.45 T (Bruker Corp., Billerica, MA). A 1H 90° pulse with solvent presaturation was used to acquire 1D 1H spectra with an 8403-Hz spectral width, 2-s acquisition time, 4-s relaxation delay, and 512 transients. The free induction decays were zero filled to 131,072 points, apodized with a 1-Hz line-broadening exponential before Fourier transformation, followed by phasing, baseline correction, and referencing to the internal DSS resonance at 0 ppm. 1D 1H{[13C]} Heteronuclear Single Quantum Coherence spectra were recorded with [13C] broadband adiabatic decoupling during the acquisition time of 0.25 s. A total of 4200 data points were collected for each transient, and a total of 1024 transients were acquired with 12 ppm (8403 Hz) spectral width with a recycle time of 2 s. The Heteronuclear Single Quantum Coherence spectra were then apodized with unshifted Gaussian function and 4-Hz exponential line broadening and zero filled to 16,384 data points before Fourier transformation, phasing, and baseline correction. The metabolites were identified using in-house databases (6365) The “peak picking” routine in the MestReNova software (Mestrelab Research S.L., Santiago de Compostela, Spain) was used to quantify resonances of interest, such as the central and [13C] satellites of the methyl resonance of lactate and those of the anomeric 1H resonance of α-Glc. Each peak area was ratioed to that of the methyl resonance of d6-DSS to determine the analyte quantity and then normalized to the cell protein content. The final metabolite content was expressed as micromole per gram of protein.

Protein extracts (at 0.34–1.25 mg/ml) from the tracer experiments of Figs. 2 and 6 and Supplemental Figs. 13 were mixed at a 1:1 ratio with a printing buffer (ArrayJet) before printing as two to four drops per spot onto a glass slide coated with 16 nitrocellulose membrane pads (ONCYTE SuperNOVA 16-6 mm, cat# 705016; Grace Bio-Labs) using a microarray printer (ArrayJet, Roslin, U.K.) as previously described (66). Membranes were incubated in a 1:2 × 106 dilution of 0.001% stock of Fast Green protein stain in 30% methanol + 7% acetic acid for 5 min, and dried and scanned with InnoScan 710 AL Microarray Scanner (Innopsys, Carbonne, France) to determine the amount of proteins deposited per sample spot. Slides were then rinsed in Nanopure H2O and washed twice at 5 min each in TBST (20 mM Tris, 150 mM NaCl, 0.001% Tween 20 [pH 7.6]) with each pad sealed under ProPlate slide chambers (Grace Bio-Labs). After blocking for 30 min in TBST containing 5% FBS (blocking buffer), each pad was incubated in a primary Ab (at 1:50–200 dilution; see later for vendor information) against a protein target for 2 h at room temperature, followed by rinsing three times at 5 min each in TBST and incubation with fluorescent secondary Ab (LICOR-IRDye 800) at 1:1000 dilution in blocking buffer for 1 h at room temperature. Slides were rinsed three times for 5 min each in TBST and vacuum suctioned to dryness before scanning using InnoScan. Fluorescence image analysis of spots was done using the Innopsys Mapix software. Background fluorescence for each spot was subtracted from the fluorescence signal for that spot, followed by normalization to the corresponding Fast Green signal. Normalized signals were averaged across replicates.

The primary Abs used were obtained from the following vendors with the following catalog numbers: ProteinTech Group—caspase 3, 19677-1-AP; CD38, 60006-1-Ig; CS, 16131-1-AP; CSF1, 25949-1-AP; CSF2, 17762-1-AP; fructose-1,6-bisphosphatase 1 (FBP1), 12842-1-AP; fumarate hydratase (FH), 11375-1-AP; glucose-6-phosphate dehydrogenase, Ag5526; glutamate dehydrogenase 1 [GLUD1], 14299-1-AP; glucose transporter 1, 18068-1-AP; glycogen synthase kinase 3B (GSK3B), 22104-1-AP; glycogen synthase 1 (GYS1), 10566-1-AP; HIF-1α, 20960-1-AP; HK3, 13333-1-AP; isocitrate dehydrogenase 1 (IDH1), 66197-1-Ig; IDH2, 15932-1-AP; IDO1, 13268-1-AP; IFN-γ, 15365-1-AP; IL-1β, 16806-1-AP; IL-4, 66142-1-Ig; IL-6, 66146-1-Ig; IL-10, 60269-1-Ig; IL-23A, 66196-1-Ig; KGA/GAC (glutaminase 1), 12855-1-AP; LDHA—19987-1-AP; c-MAF, 55013-1-Ap; MDH1, 15904-1-AP; OGDH, 15212-1-AP; pyruvate carboxylase (PC), 16588-1-AP; PCK1, 16754-1-AP; PCK2, 14892-1-AP; pyruvate dehydrogenase (PDH) E1 subunit α, 21829-1-AP; PFKFB3, 13763-1-AP; PGD, 14718-1-AP; PKM2, 60268-1-Ig; PYGB, 55380-1-AP; PYGL, 15851-1-AP; QPRT, 25174-1-AP; SDHB, 10620-1-AP; TGF-β1, 21898-1-AP; TNF-α, 60291-1-Ig; vascular endothelial growth factor, 19003-1-AP; Abnova—CLEC7A, PAB2591; Biomatik—aconitate decarboxylase 1, CAC08562; Invitrogen—CD166, MA5-23850; glutaminase 2, PA5-72963; MDH2, PA5-21700; CCL3, AHC6034; IL-13, 14-7139-81; BD Biosciences—CD206, 555954; St. Johns Labs—glutamate-oxaloacetate transaminase 2, STJ99292; and Trevigen—PAR, 4335-MC-100.

Kinetic curve fitting was carried out by nonlinear regression using Kaleidagraph (Synergy software, v 4.5) to obtain the linear slope values, which were reported as means ± SEM. Pairwise comparisons were made using the two-tailed Student t test. For the phagocytosis assays, the normalized fluorescence time-course data were analyzed as single exponential, as linear regressions to the last 13 points, or as the full curves according to the following equation:

S (t)= a + b [t +(exp(kt)1)/k],
(1)

where S(t) is the observed signal, a is the intercept at t = 0, b is the slope of the linear region at t > 60 minutes, and k is an apparent rate constant that describes the curved portion of the time course. The program returns the best estimate for the parameters a, b, and k; the SD of the estimates; and the correlation coefficient and χ2 for the fits. The linear slope parameters were evaluated for changes among treatments using the Student two-tailed t test.

For ratios r = a/b, the errors were calculated assuming independence of the components as

Δr =<r>{(Δa/a)2+(Δb/b)2}0.5,
(2)

where Δa and Δb are the standard errors of a and b, respectively, and <r> is the mean of the ratio r.

Time courses for each donor were analyzed on three technical replicates and compared for different treatments using the unpaired Student two-tailed t test.

Surgical patients provided consent for freshly resected tissue specimens under the approved Institutional Review Board protocol (14-0288-F6A; 13-LUN-94-MCC) of the University of Kentucky.

Expression of lineage markers

After 2 d of LPS + IFN-γ or IL-4 + IL-13 polarization, human Mϕs responded with an overexpression of IDO1 or CD206 (relative to unstimulated Mϕs, M[CSF1], or M0-Mϕs), respectively, as illustrated for the UK166 Mϕs in (Fig. 1A. The time course of these responses differed among different donors, particularly for the IDO1 expression. The LPS + IFN-γ–polarized Mϕs, herein referred to as M[LPS + IFN-γ] or M1-Mϕs of UK096 (male, age 67 y), UK094 (female, age 65 y), and UK166 (female, age 25), showed an increase in IDO1 overexpression with 1–3 d of treatment, while that of UK168 (male, age 31 y) did not (Fig. 1B). IDO1 overexpression was reported in M1-type human Mϕs, but CD206 overexpression was not evident for M2-type human Mϕs after 1 d of polarization (67). This difference in CD206 expression patterns between the literature and ours could be a result of different methods (IL-4 + IL-13 versus IL-4 only) of polarization. WGP treatment attenuated CD206 overexpression in all four donors’ Mϕs treated with IL-4 + IL-13 (M[IL-4 + IL-13] or M2a-Mϕ; herein referred to as M2-Mϕ), independent of the duration of the treatment. WGPs also enhanced IDO1 expression in M2-Mϕs (relative to M1-Mϕs), but only after 3 d of polarization for UK096. These data on the expression of lineage markers suggest plasticity of human Mϕs in terms of functional responses elicited by different polarization methods and timing. They also point to the importance of reporting the polarization method and duration for proper comparison of responses of Mϕ lineage markers to immune perturbations.

FIGURE 1.

Human Mϕs display differential lineage markers and phagocytosis/immune effector production in response to polarization and WGP treatments. Human Mϕs were prepared from the PBMCs of four donors, polarized, and treated with WGPs as described in the Materials and Methods. Cells were stained for lineage markers CD206 and IDO, as well as subjected to phagocytosis and cytokine/chemokine assays as described in the Materials and Methods. (A) CD206 (orange) and IDO (green) staining for M[CSF1] (M0), M[LPS + IFN-γ] (M1), and M[IL-4 + IL-13] (M2) ± WGPs of UK166 after 2 d of polarization. (B) Average image intensities (n = 3) normalized to those of M0 CD206 and IDO. (C) Time-course changes (n = 3) in the phagocytosis rate (slope of the linear time course) for four donors’ Mϕs. Phagocytosis rates were normalized to those of M0. (D) Proinflammatory (IL-1β, IL-6, IFN-γ, TNF-α, and IP-10 or CXCL10) and anti-inflammatory effector (IL-10) release into the medium (n = 3). Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request.

FIGURE 1.

Human Mϕs display differential lineage markers and phagocytosis/immune effector production in response to polarization and WGP treatments. Human Mϕs were prepared from the PBMCs of four donors, polarized, and treated with WGPs as described in the Materials and Methods. Cells were stained for lineage markers CD206 and IDO, as well as subjected to phagocytosis and cytokine/chemokine assays as described in the Materials and Methods. (A) CD206 (orange) and IDO (green) staining for M[CSF1] (M0), M[LPS + IFN-γ] (M1), and M[IL-4 + IL-13] (M2) ± WGPs of UK166 after 2 d of polarization. (B) Average image intensities (n = 3) normalized to those of M0 CD206 and IDO. (C) Time-course changes (n = 3) in the phagocytosis rate (slope of the linear time course) for four donors’ Mϕs. Phagocytosis rates were normalized to those of M0. (D) Proinflammatory (IL-1β, IL-6, IFN-γ, TNF-α, and IP-10 or CXCL10) and anti-inflammatory effector (IL-10) release into the medium (n = 3). Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request.

Close modal

Phagocytosis

Because phagocytosis is important both for bactericidal action and for tissue repair (68), we determined the dependence of the phagocytotic capacity in human Mϕs on polarization method/duration or WGP treatment. (Fig. 1C shows the time-dependent response of phagocytosis to differential polarization and WGP treatments for the four donors. M1-Mϕs (Fig. 1C, red squares) had a lower basal phagocytotic capacity than M0-Mϕs (black circles) or M2-Mϕs (gray triangles) regardless of the donor or polarization time. This is consistent with a recent report on reduced phagocytosis in human Mϕs with the inflammatory phenotype (42). However, the time-course changes in the phagocytotic capacity differed among the individual donors, i.e., that in the M2-Mϕs of UK094, UK166, and UK168 decreased with time, while that in the M2-Mϕs of UK096 did not. In all four cases, WGP treatment (Fig. 1C, blue down triangles) robustly decreased this capacity in M2-Mϕs toward that of the M1-Mϕs.

Cytokine/chemokine release

We further measured key cytokine/chemokine (effectors) release into the medium by the four donors’ Mϕs. We saw in general enhanced release of proinflammatory effectors by M1-Mϕs (Fig. 1D, red squares) versus M0-Mϕs (Fig. 1D, black circles) for all four donors, including IL-6, IFN-γ, TNF-α, and IL-1β (except for UK096 and UK166, for which IL-1β levels were too low to determine) (Fig. 1D). The time course of these effector changes varied among donors, except for that of IFN-γ, which consistently decreased from days 1 to 3. IFN-γ release by M1-Mϕs was also consistently higher than that by M2-Mϕs (Fig. 1D, gray triangles) for all donors and polarization durations. However, enhanced release of TNF-α, IL-1β, and IL-6 by M1-Mϕs versus M2-Mϕs was donor and time dependent. Likewise, the enhanced release of immunosuppressive cytokine IL-10 (69) by M2-Mϕs versus M1-Mϕs was donor and time dependent. An opposite response of IL-10 release by M2-Mϕs versus M1-Mϕs was reported previously (67), which points to the plasticity of this cytokine’s response to differential polarization. Moreover, enhanced release of proinflammatory chemokine CXCL10 (IP-10) was evident from days 1 to 3 for M1-Mϕs versus M2-Mϕs for all donors. CXCL10 can recruit tumor-infiltrating T cells and NK cells for tumor suppression (70) but can also induce tumor metastasis via interaction with its receptor CXCR3 (71). CXCL10 and CXCR3 were overexpressed in metastatic lung adenocarcinoma specimens and associated with poor prognosis (72).

WGP treatment (Fig. 1D, blue down triangle) had a profound effect on effector releases by human M2-Mϕs. WGP consistently enhanced the release of IL-1β, IL-6, and TNF-α by M2-Mϕs of all four donors and often to levels greater than those in M1-Mϕs (Fig. 1D), but it failed to promote IFN-γ release by M2-Mϕs in all but one case (UK096). WGPs also enhanced the release of anti-inflammatory IL-10 but had little effect on the CXCL10 release by M2-Mϕs of all four donors. Thus, a dichotomy of the effect of WGPs existed in terms of immune functions. On the one hand, WGPs elicited M1-like proinflammatory responses, which is consistent with its known M1 repolarization effect on M2-type mouse Mϕs (7). On the other hand, WGPs further promoted IL-10 release by M2-Mϕs, which contrasts with its suppression of IL-10 gene expression in mouse M2-Mϕs (7). IL-10 is generally known as a key cytokine for repressing proinflammatory responses while facilitating tissue repair (73).

In parallel to the functional characterization described earlier, we used triple tracers, [2H2]Glc + [13C5]Gln + [15N2]Trp, or single tracer, [13C6]Glc, to track the time-course changes of the metabolic activities in the Mϕs derived from the four donors in response to differential polarization and WGP treatment. Cells were polarized for 1–3 d before tracer addition to all treatments and WGP addition to M2-Mϕs for another 24 h. The [13C], [15N], and/or [2H] incorporation into metabolites of various metabolic pathways was determined by a combination of NMR and UHR-FTMS methods (61, 66).

Changes in glycolysis, Krebs cycle, and the QA pathway in different polarization states of Mϕs

With [2H2]Glc + [13C5]Gln + [15N2]Trp as tracers, we tracked simultaneously the time-course changes in glycolytic, Krebs cycle, and Trp catabolic activities in human Mϕs in response to polarization and WGPs. As shown in (Fig. 2A, [2H2]Glc (Fig. 2Aa) and [13C5]Gln (Fig. 2Ac) were consumed while releasing, respectively, [2H]lactate (Fig. 2Ab) and [13C]lactate (Fig. 2Ab′) into the medium by UK096’s Mϕs. Accurate quantification of Gln consumption was difficult because it accounted for only a small fraction of the Gln administered. It is clear that LPS + IFN-γ–polarized M1-Mϕs (red squares) did not show significantly enhanced [2H]lactate or [13C]lactate release, or buildup of cellular [2H]/[13C]lactate (Fig. 2Ag, g′) relative to M2-Mϕs (gray triangles) or M0-Mϕs (black circles), which together with no significant changes in Glc consumption indicates at most minor changes in glycolytic activity. This response is contrary to the accelerated glycolysis observed in M1-type mouse Mϕs (25). In contrast, compared with the other three Mϕ types, Trp consumption by M1-Mϕs (Fig. 2Af) was greatly enhanced and was accompanied by a large buildup of [15N]QA (N*-QA, (Fig. 2Ai′) and unlabeled QA (0-QA; (Fig. 2Ai), which indicate activated Trp catabolism into QA. WGP treatment of M2-Mϕs (blue down triangle) enhanced [2H]lactate release (Fig. 2Ab), cellular [2H]lactate buildup, and Glc consumption but had little effect on [13C]lactate release, which suggests enhanced glycolysis, but not Gln transformation, into lactate via glutaminolysis. The latter agrees with no significant changes in the release of [13C]Glu (Fig. 2Ad) and [13C]succinate (Fig. 2Ae), or in the buildup of cellular [13C]2-hydroxyglutarate (2HG; (Fig. 2Ah′), which are also products of glutaminolysis. However, we saw enhanced buildup of [13C]2HG and [2H]2HG (Fig. 2Ah) in M1-Mϕs versus M1-Mϕs, which suggests that the 2HG synthesis pathway was activated by LPS + IFN-γ polarization.

FIGURE 2.

Pathway tracking via triple tracers reveals time-dependent changes in nutrient uptake, glycolysis, and Krebs cycle activities in UK096 Mϕs in response to differential polarization and WGP treatments. UK096 Mϕs were prepared and treated as in (Fig. 1 except for the addition of the triple-tracer ([2H2]Glc + [13C5]Gln + [15N2]Trp) mixture as described in the Materials and Methods. Polar extracts of the cells and media were analyzed by 1H-NMR (Aa–f, b′) and IC-UHR-FTMS (Ag–i, gi). The pathway schemes track the fate of pre-existing [12C] (black circle)/[14N] (black diamond) and [13C]/[15N] (blue diamond) atoms from [13C5]Gln and [15N2]Trp into medium and cellular metabolites through uptake/secretion, glycolysis, the Krebs cycle, and GSH/Trp metabolism. Black circle: [12C]; red and blue circles: [13C] from PDH- and ME-initiated Krebs cycle reactions, respectively. (A) Unlabeled (0), 2H-labeled (D*), and 13C-labeled (C*) metabolite distributions in media (Aa–f, b′) and cells (Ag, g′, h, h′). (B) Cellular 2H (D*) and [13C] isotopologue (C*) distributions of Krebs cycle metabolites (Bag). Each data point was an average of two or three replicates. Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request. ACOD1, aconitate decarboxylase; AST, aspartate aminotransferase; Ex, extracellular; GLS, glutaminase; IRG1, immune-responsive gene 1; Ita, itaconate; Lac, lactate; Suc, succinate; SucCoA, succinyl CoA.

FIGURE 2.

Pathway tracking via triple tracers reveals time-dependent changes in nutrient uptake, glycolysis, and Krebs cycle activities in UK096 Mϕs in response to differential polarization and WGP treatments. UK096 Mϕs were prepared and treated as in (Fig. 1 except for the addition of the triple-tracer ([2H2]Glc + [13C5]Gln + [15N2]Trp) mixture as described in the Materials and Methods. Polar extracts of the cells and media were analyzed by 1H-NMR (Aa–f, b′) and IC-UHR-FTMS (Ag–i, gi). The pathway schemes track the fate of pre-existing [12C] (black circle)/[14N] (black diamond) and [13C]/[15N] (blue diamond) atoms from [13C5]Gln and [15N2]Trp into medium and cellular metabolites through uptake/secretion, glycolysis, the Krebs cycle, and GSH/Trp metabolism. Black circle: [12C]; red and blue circles: [13C] from PDH- and ME-initiated Krebs cycle reactions, respectively. (A) Unlabeled (0), 2H-labeled (D*), and 13C-labeled (C*) metabolite distributions in media (Aa–f, b′) and cells (Ag, g′, h, h′). (B) Cellular 2H (D*) and [13C] isotopologue (C*) distributions of Krebs cycle metabolites (Bag). Each data point was an average of two or three replicates. Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request. ACOD1, aconitate decarboxylase; AST, aspartate aminotransferase; Ex, extracellular; GLS, glutaminase; IRG1, immune-responsive gene 1; Ita, itaconate; Lac, lactate; Suc, succinate; SucCoA, succinyl CoA.

Close modal

The earlier findings were largely recapitulated in the Mϕs of UK094, UK168, and UK166 (Supplemental Fig. 1A). These included lack of accelerated glycolysis in M1-Mϕs, WGP-induced activation of glycolysis in M2-Mϕs (Supplemental Fig. 1Aa–c), as well as enhanced synthesis of 2HG from Gln (Supplemental Fig. 1Ad–f) and QA from Trp in M1-Mϕs (Supplemental Fig. 1Ag–i). Notable responses that differed among donors’ Mϕs included WGP-enhanced synthesis of 2HG from Gln in M2-Mϕs of UK166 (Supplemental Fig. 1Af), that of QA from Trp in M2-Mϕs of UK168 (Supplemental Fig. 1Ah), diminished (instead of sustained) synthesis of QA from Trp from 1- to 3-d polarized M1-Mϕs of UK094 (Supplemental Fig. 1Ag), as well as increased release of Gln-derived Glu (Supplemental Fig. 1Ak) and succinate (Supplemental Fig. 1An) into the medium by M1-Mϕs of UK168 (Supplemental Fig. 1A). Note that enhanced succinate release may be related to the enhanced depletion of cellular [13C]succinate in M1-Mϕs of UK168 (Supplemental Fig. 1An). Together, these data point to the plasticity of glycolytic/glutaminolysis activation in response to M1-type polarization and WGP treatment.

Tracking the glycolytic product [2H2]pyruvate into the Krebs cycle, we found depletion of the PDH-mediated production of [2H]citrate (D*-citrate) in UK096’s M1-Mϕs versus M2-Mϕs after 1–3 d of polarization (Fig. 2Bf), which is consistent with reduced Krebs cycle activity reported for mouse M1-Mϕs (23). However, we did not observe a buildup of [2H]α-ketoglutarate (D*-αKG, (Fig. 2Bb) resulting from a break at IDH, nor did we see a buildup of [2H]succinate (Fig. 2Bd) with depletion of [2H]fumarate (Fig. 2Be) resulting from the break at SDH in the Krebs cycle. These two breaks are known to occur in mouse M1-Mϕs (23). However, significant buildup of [2H]citrate-derived [2H]itaconate (D*-ItaC, (Fig. 2Bg) was evident in the day 1 polarized M1-Mϕs, which diminished in the day 2 and 3 counterparts. This buildup of Glc-derived itaconate is consistent with that seen in mouse M1-Mϕs (23, 51). We also tracked the transformations of the product of glutaminolysis [13C5]Glu through the Krebs cycle and into glutathione (GSH) biosynthesis. [13C5]Glu (Fig. 2Ba′) was predominantly converted to [13C5]GSH (Fig. 2Bc′), as evident from the high buildup of [13C5]GSH, particularly in the M1-Mϕs. [13C5]Glu was also converted via the Krebs cycle to [13C]succinate (Fig. 2Bd′), [13C]fumarate (Fig. 2Be′), and [13C]citrate (Fig. 2Bf′) and more so in M1-Mϕs (red squares) than M2-Mϕs (gray triangles) during day 1 or 2 of polarization. The production of [13C]lactate from [13C]Gln (Fig. 2Ab′, g′) points to the activity of MEs, which converts [13C]malate to [13C]pyruvate and subsequently to [13C]lactate. The high amounts of [13C]lactate (in mmol/g protein released into the medium (Fig. 2Ab′) compared with the much lower levels of the Krebs cycle intermediates (in µmol/g protein; (Fig. 2Bb′–f′) suggests that this anaplerotic ME pathway is very active in human Mϕs. Moreover, we saw elevated buildup of [13C]itaconate in M1-Mϕs in a similar time course as that for [2H]itaconate except at a higher level (Fig. 2Bg′ versus g). This suggests that Gln is a more important source for fueling itaconate synthesis in UK096’s M1-Mϕs. Itaconate has been shown to induce the development of immune tolerance in LPS-treated human monocytes, in addition to being an antimicrobial metabolite (51). Gln was also a better fuel for the enhanced production of another key immunoregulatory metabolite 2HG in UK096’s M1-Mϕs, as described earlier. However, glycolysis was not significantly enhanced in UK096’s M1-Mϕs, implicating the presence of a counteracting mechanism for regulating glycolysis. For example, 2HG buildup could activate prolyl hydroxylase, thereby destabilizing HIF-1α to attenuate glycolysis (74).

WGPs had a polarization time-dependent effect on the Krebs cycle activity in UK096’s M2-Mϕs. Notably, it suppressed the synthesis of αKG (Fig. 2Bb, b′) and succinate from both Glc and Gln (Fig. 2Bd, d′) in 1-day polarized M2-Mϕs, but this effect was diminished after 3-d polarization. In contrast, WGP had an insignificant effect on Glc-fueled fumarate production after 1-d polarization but enhanced it after 2–3 d of polarization (Fig. 2Be), which was also the case for Glc-fueled Glu synthesis (Fig. 2Ba). The opposite effect of WGP on succinate and fumarate production could be mediated by SDH activation, which is consistent with the ability of β-glucan to restore SDH expression in tolerant human monocytes (51). Also, fumarate accumulation was shown to revert the tolerizing effect of itaconate (51). As such, the capacity of WGPs to repolarize M2-Mϕs to M1-Mϕs increases with polarization duration for UK096.

A similar trend in responses of Mϕs to polarization methods/duration and WGP treatment was seen for the other three donors, UK094, UK168, and UK166. These included no apparent breaks at the IDH (Supplemental Fig. 1Ba–f) and SDH (Supplemental Fig. 1Bg–l) sites in M1-Mϕs (Supplemental Fig. 1B), highly active ME pathway in all Mϕ types that led to abundant release of [13C]lactate into the medium (Fig. 2Ab′ and data not shown), depletion of [2H]citrate in M1-Mϕs versus M2-Mϕs (Supplemental Fig. 1Ba–c), and highest buildup of [13C]itaconate in 1-d polarized M1-Mϕs (Supplemental Fig. 1Bm–o). However, other responses showed plasticity, notably the lack of WGP effect on [13C]fumarate synthesis from Gln in M2-Mϕs for UK094 (Supplemental Fig. 1Bj) and UK168 (Supplemental Fig. 1Bk) and the much lower production of itaconate from Gln by M1-Mϕs for UK094 and UK166 (Supplemental Fig. 1Bm, o) than for UK096 and UK168 (Supplemental Fig. 1Bn, o, (Fig. 2B). These differences are expected to impact immune functions. Also, notably, the UK094’s Mϕs were less tightly bound to culture plates and suffered from losses during cell harvest for metabolite extraction, leading to the inability to reliably determine the very low levels of [2H]αKG, [2H]succinate, [2H]fumarate, and [2H]itaconate (Supplemental Fig. 1B).

Our SIRM data suggest that the initial part of the Krebs cycle was consistently attenuated in the human M1-Mϕs, but this attenuation is unlikely to result from the breaks at the IDH and SDH sites reported for the mouse M1-Mϕs. Our results also suggest that itaconate synthesis in the human M1-Mϕs was mainly fueled by Gln, while its consistent enhancement and subsequent diminishment from 1 to 3 d of polarization is expected to elicit robust changes in immune functions. Moreover, the variable effect of WGPs on succinate-to-fumarate conversion in the M2-Mϕs could lead to variable capacity for immune resolution and tissue repair.

Activation of PPP and gluconeogenesis in different polarization states of Mϕs

In addition to glycolysis, we traced the PPP, which is an important route of Glc utilization, for the four donors’ Mϕs in response to differential polarization and WGP treatment, as shown in (Fig. 3 (UK096) and Supplemental Fig. 2 (UK094, UK168, UK166). Enhanced PPP activity in UK096’s M1-Mϕs versus M2-Mϕs after all 3 d of polarization was evidenced by the increased buildup of [2H2]Glc-derived PPP intermediates, including [2H]ribose/ribulose-5-phosphate (D*-R5P, (Fig. 3c), [2H]sedoheptulose-7-phosphate (D*-S7P, (Fig. 3d, d′), and [2H]fructose-6-phosphate (D*-F6P, (Fig. 3e). We also noted the depletion of [2H]6-phosphogluconate (D*-6PG, (Fig. 3b) and the buildup of the product [2H]R5P in the M1-Mϕs regardless of the polarization times, which suggests activation of PGD (6-phosphogluconate dehydrogenase in the oxidative branch of PPP) activity and thus enhanced NADPH production. 6PG depletion and PGD gene upregulation were reported previously in mouse M[LPS + IFN-γ] versus M[IL-4] after 1 d of polarization (23).

FIGURE 3.

Temporal dependence of reprogrammed PPP and GNG in UK096 Mϕs in response to polarization and WGP treatments. Polar extracts from (Fig. 2 were analyzed for the distribution of PPP and gluconeogenic metabolites by IC-UHR-FTMS. The pathway scheme tracks the fate of pre-existing [12C] (black circles) and [13C] (red circles) atoms from [13C5]Gln into metabolites through both oxidative and non-Ox branches of PPP, as well as GNG. Not all expected labeled metabolites were shown, and Dx in parenthesis denotes scrambled D positions across different C atoms. Time-course changes in the abundance of metabolite isotopologues (n = 3) shown include D* (sum of all 2H-labeled species) and C*Dx (sum of all 13C-labeled species that contained 0 to x number of D). a, a′, G6P; b, b′, 6PG; c, c′, R5P; d, d′, S7P; e, e′, F6P; f, f′, F1. Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request. E4P, erythrose-4-phosphate; GAP, glyceraldehyde-3-phosphate; G6PD, glucose-6-phosphate dehydrogenase; TA, transaldolase; TK, transketolase; X5P, xylulose-5-phosphate.

FIGURE 3.

Temporal dependence of reprogrammed PPP and GNG in UK096 Mϕs in response to polarization and WGP treatments. Polar extracts from (Fig. 2 were analyzed for the distribution of PPP and gluconeogenic metabolites by IC-UHR-FTMS. The pathway scheme tracks the fate of pre-existing [12C] (black circles) and [13C] (red circles) atoms from [13C5]Gln into metabolites through both oxidative and non-Ox branches of PPP, as well as GNG. Not all expected labeled metabolites were shown, and Dx in parenthesis denotes scrambled D positions across different C atoms. Time-course changes in the abundance of metabolite isotopologues (n = 3) shown include D* (sum of all 2H-labeled species) and C*Dx (sum of all 13C-labeled species that contained 0 to x number of D). a, a′, G6P; b, b′, 6PG; c, c′, R5P; d, d′, S7P; e, e′, F6P; f, f′, F1. Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request. E4P, erythrose-4-phosphate; GAP, glyceraldehyde-3-phosphate; G6PD, glucose-6-phosphate dehydrogenase; TA, transaldolase; TK, transketolase; X5P, xylulose-5-phosphate.

Close modal

WGP treatment of the M2-Mϕs led to a buildup of [2H]6PG with no accumulation of the product [2H]R5P, which points to attenuated PGD activity, opposite to the action of LPS + IFN-γ. Notably, [2H]R5P, [2H]S7P, and [2H]F6P can also be formed from [2H2]Glc via the combined action of transketolase and transaldolase in the nonoxidative (non-Ox) branch of PPP, which is difficult to assess based on the 2H-labeling patterns of these metabolites alone. We thus performed a [13C6]Glc tracer experiment on UK096’s Mϕs under 2 d of polarization and WGP treatment for the M2-Mϕs. As shown in Supplemental Fig. 2B, enhanced buildup of [13C5]S7P and [13C6]S7P (Supplemental Fig. 2Bd) occurred in the M1-Mϕs versus M2-Mϕs after 2 d of polarization, which suggests, respectively, increased activity of transketolase in the forward direction (Supplemental Fig. 2B, green arrows) and transaldolase in the reverse direction (Supplemental Fig. 2B, blue arrows), i.e., increased carbon flow via both oxidative and non-Ox branches of PPP. Enhanced synthesis of uniformly labeled glucose-6-phosphate (G6P; [13C6], Supplemental Fig. 2Ba), R5P ([13C5], Supplemental Fig. 2Bc), S7P ([13C7], Supplemental Fig. 2Bd), and F6P ([13C6], Supplemental Fig. 2Be), as well as increased conversion of [13C6]6PG (Supplemental Fig. 2Bb) to [13C5]R5P was also evident in M1-Mϕs versus M2-Mϕs (Supplemental Fig. 2B), which recapitulates the trend for the [2H2]Glc tracing (Fig. 3) and reflects increased PGD activity in the oxidative branch.

We also saw [13C5]Gln-derived PPP metabolites in UK096’s Mϕs (Fig. 3a′–e′), albeit at lower levels than those of the 2H-labeled counterparts. 13C labeling of these metabolites indicates their transformations from [13C5]Gln via gluconeogenesis (GNG). GNG occurrence is further confirmed by [13C] incorporation into fructose-1,6-bisphosphate (C*Dx-F1,6BP, (Fig. 3f′), F6P (Fig. 3e′), and G6P (Fig. 3a′). As for the case for the 2H-labeled counterparts, enhanced buildup of [13C]R5P/S7P and depletion of [13C]6PG were evident in the M1-Mϕs versus M2-Mϕs, which again points to activation of the oxidative branch of PPP at the PGD site. We did not see a significant increase in [13C]F1,6BP (Fig. 3f′) conversion to [13C]F6P (Fig. 3e′) in the M1-Mϕs versus M2-Mϕs, which is catalyzed by the enzyme FBP1. FBP1 was shown to be one of the top upregulated proteins in human M1-Mϕs versus M2-Mϕs (75). However, our RPPA analysis did not show such an increase in FBP1 expression (Fig. 5B), which corroborated our SIRM-based FBP1 activity assay. This disagreement may be because of the different method of M1 polarization, which used GM-CSF coupled with LPS in the previous study (75) versus M-CSF coupled with LPS + IFN-γ in our study to generate M1-Mϕs. WGP treatment greatly enhanced the buildup of [13C]G6P, [13C]F6P, and [13C]F1,6BP in the M2-Mϕs, which suggests activation of GNG (76).

Similar activation of the oxidative PPP at the PGD site in the M1-Mϕs was evident for the other three donors, as was WGP enhancement of GNG in the M2-Mϕs, albeit less robust for UK094 and UK168 (Supplemental Fig. 2A). In summary, LPS + IFN-γ (M1) polarization activated both oxidative and non-Ox branches of PPP to enhance the production of NADPH and R5P, while WGPs stimulated GNG in IL-4 + IL-13 (M2) polarized Mϕs. These altered metabolic events may help maintain redox homeostasis in the M1-Mϕs and anabolic capacity in WGP-treated M2-Mϕs.

WGP increases glycogen synthesis in M2-like Mϕs

Glycogen metabolism has been reported to modulate acute inflammatory responses via transformations into G6P to fuel NADPH production from the oxidative PPP, which then enables maintenance of high GSH levels for M[LPS + IFN-γ] survival (77). We first tracked [13C6]Glc incorporation into UK096’s Mϕs in response to 2–3 d of polarization and WGP treatment. As shown in Supplemental Fig. 3A, [13C]glycogen accumulated to a higher level in the M1-Mϕs versus M2-Mϕs after both 2 d (red line, Supplemental Fig. 3Ac) and 3 d (red line, Supplemental Fig. 3Ac′) of polarization, but its two precursors, [13C6]G1P (Supplemental Fig. 3Aa) and [13C] uridine diphosphoglucose (UDPG) (Supplemental Fig. 3Ab), did not build up. These data suggest that glycogen accumulation is more likely to be caused by decreased glycogen degradation rather than increased glycogen synthesis in the M1-Mϕs. WGP treatment of the M2-Mϕs also led to enhanced buildup of [13C]glycogen in the M2-Mϕs after 2 d (blue line, Supplemental Fig. 3Ac), but not 3 d (blue line, Supplemental Fig. 3Ac′), of polarization, as was the case for its two precursors, [13C]G1P/UDPG (Supplemental Fig. 3Aa, b). These data are consistent with WGP stimulation of glycogen synthesis in 2-d, but not 3-d, polarized M2-Mϕs. A similar trend in the responses of [2H]G1P (Supplemental Fig. 3Ad, g) and [2H]UDPG (Supplemental Fig. 3Ae, h) to LPS + IFN-γ polarization or WGP treatment of the M2-Mϕs was evident for the [2H2]Glc + [13C5]Gln tracer experiment. In addition, we saw large buildup of [2H2]G1P-derived [2H2]glucose-1,6-bisphosphate (G1,6BP; Supplemental Fig. 3Af) (78) elicited by WGPs in the M2-Mϕs, which suggests diversion of G1P from glycogen to G1,6BP synthesis. Moreover, the fractional enrichment of [2H]G1P (Supplemental Fig. 3Ag) increased, but much less so for that of [2H]UDPG (Supplemental Fig. 3Ah) and [2H]G1,6BP (Supplemental Fig. 3Ai) in WGP-treated versus control M2-Mϕs. The distinct responses of 2H enrichment in UDPG and G1P (Supplemental Fig. 3Ag versus h) suggest additional input to the [2H]G1P pool, which presumably comes from [2H]glycogen degradation. Together, these data point to increased glycogen synthesis and utilization along with diversion of G1P to G1,6BP synthesis induced by WGP treatment in the M2-Mϕs.

The lack of a significant effect of M1 versus M2 polarization on [2H2]Glc incorporation into G1P and UDPG was also evident for UK168 (Supplemental Fig. 3Bg, i) and UK166 (Supplemental Fig. 3Bm, o), but not for UK094, which showed enhanced buildup of [2H]G1P/UDPG in 1-day polarized M1-Mϕs (Supplemental Fig. 3Ba, c). Likewise, the effect of WGPs on the M2-Mϕs was largely recapitulated for UK168 and UK166, but not for UK094 (Supplemental Fig. 3Ba–e), in terms of [2H]G1P, [2H]UDPG, and [2H]G1,6BP (Supplemental Fig. 3B). We were unable to track [2H] incorporation into glycogen because of the low 2H-NMR sensitivity. However, by relating the changes in the labeling patterns of the precursors to the corresponding UK096’s data (Supplemental Fig. 3A), we surmise that glycogen degradation is enhanced in UK166’s and UK168’s M1-Mϕs, while both glycogen synthesis and degradation were activated by WGPs in UK166’s and UK168’s M2-Mϕs. In addition, diversion of G1P to G1,6BP synthesis in WGP-treated M2-Mϕs appeared to occur in all cases. Thus, both consistency and plasticity of glycogen metabolism were evident in human Mϕs in response to M1 polarization and WGP treatment, which is expected to have consequences in immune functions.

Nucleotide biosynthesis

Reprogrammed pyrimidine and hexosamine pathways implicate increased protein glycosylation in M[IL-4 + IL-13]

Glc fuels the synthesis of pyrimidine and sugar nucleotides by providing precursors to the pyrimidine ring (Asp), ribose (phosphoribosyl pyrophosphate [PRPP]), and the N-acetylglucosamine units (N-acetylglucosamine-1-phosphate [NAcGN1P]) (scheme in (Fig. 4A). (Fig. 4A showed that [2H2]Glc conversion to Asp (Fig. 4Aa) was not altered appreciably in UK096’s M1-Mϕs versus M2-Mϕs, while [2H] incorporation into PRPP (Fig. 4Ab) was enhanced after 1–3 d of polarization. The latter presumably results from enhanced PPP activity (Fig. 3). However, subsequent 2H labeling of UTP (Fig. 4Ac) was attenuated in the 1-day polarized M1-Mϕs (red squares) versus M2-Mϕs (gray triangles). This UTP response was opposite to that of its product UDPGlcNAc (Fig. 4Ae), which showed increased 2H labeling in the M1-Mϕs versus M2a-Mϕs, particularly after 1 d of polarization. 2H labeling in the other precursor NAcGN1P (Fig. 4Ad) did not differ between the M1-Mϕs and M2-Mϕs. WGP treatment of the M2-Mϕs (blue down triangles) repolarized 2H labeling of UTP toward the M1 type, which could be because of WGP-induced depletion of [2H]Asp (blue down triangles, (Fig. 4Aa). In contrast, WGPs had only a minor effect on 2H labeling of UDPGlcNAc but significantly enhanced that of the precursor NAcGN1P (Fig. 4Ad). These data point to regulation of UTP synthesis in the M1-Mϕs occurring downstream of Asp and that of UDPGlcNAc synthesis downstream of UTP and NAcGN1P. Changes in the fractional enrichment of [2H]UTP in response to polarization and WGP treatments (Supplemental Fig. 4Aa) were consistent with those in the [2H]UTP level (Fig. 4Ac), which points to enhanced UTP synthesis by IL-4 + IL-13 polarization and WGP suppression of this activity. However, we saw increased levels (Fig. 4Ae) with comparable fractional enrichment of [2H]UDPGlcNAc (Supplemental Fig. 4Ab) in the M1-Mϕs versus M2-Mϕs, which, together with the reduced 2H labeling in the precursors UTP and NAcGN1P, suggest blocked UDPGlcNAc utilization in the M1-Mϕs. In addition, WGP treatment substantially increased the fractional enrichment of [2H]UDPGlcNAc in the M2-Mϕs with a minor effect on the level, which also points to reduced utilization of UDPGlcNAc. UDPGlcNAc is a marker of N- and O-glycosylation of proteins, which were shown to be required for M2 polarization and functions (23, 79). Moreover, we saw [13C] incorporation from [13C5]Gln into PRPP (Fig. 4Ab′) via GNG (Fig. 4A). The change patterns of 13C-labeled Asp (Fig. 4Aa′), PRPP, and UTP (Fig. 4Ac′) were largely akin to those of the 2H-labeled counterparts, but those of UDPGlcNAc (C*NxDx-UDPGlcNAc, (Fig. 4Ae′) and its precursor NAcGN1P (C*NxDx-NAcGN1P, (Fig. 4Ad′) differed between the 13C- and 2H-labeled species, i.e., the [13C]UDPGlcNAc level was not enhanced in the M1-Mϕs versus M2-Mϕs, and WGP treatment did not elevate the level of [13C]NAcGN1P in the M2-Mϕs. Because the 13C-labeled species included additional contribution of [15N] derived from [15N2]Trp, our data suggest that Trp catabolism may have an important influence on UDPGlcNAc synthesis. Furthermore, the higher fractional enrichment of [13C]UDPGlcNAc in 1-d polarized M2-Mϕs than the M1 counterpart (Supplemental Fig. 4Ad) with depletion in its level (Fig. 4Ae′) again suggests activation of both synthesis and utilization.

FIGURE 4.

Temporal dependence of reprogrammed nucleotide metabolism in UK096 Mϕs in response to differential polarization and WGP treatments. Polar extracts from (Fig. 2 were analyzed by IC-UHR-FTMS for the distribution of labeled metabolite in the pyrimidine nucleotide/hexosamine biosynthesis pathways (HBPs) (A) and the purine nucleotide/dinucleotide biosynthesis/salvage pathway (B). The pathway schemes track the fate of pre-existing [12C] (black circles)/[14N] (black diamonds) and [2H] (D)/[13C] (red circles)/[15N] (blue diamonds) atoms derived from the transformations of [2H2]Glc (D2-Glc), [13C5]Gln, and [15N2]Trp via glutaminolysis, the Krebs cycle, PPP, and Trp catabolism. Not all expected labeled metabolites were shown, and Dx in parenthesis denotes scrambled D positions across different C atoms. The labeled species illustrated represent the top abundant [2H], [13C], and [15N] isotopologues for each metabolite. Time-course changes in the abundance of metabolite isotopologues shown (n = 3) include D* (sum of all D-labeled species), C*NxDx (sum of all 13C-labeled species that contained 0 to x number of [15N] and/or [2H]), and 0 or unlabeled ([12C]/[14N]/[1H]). Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request. CHO-THF, formyl tetrahydrofolate; HpX, hypoxanthine; NAcGN1(6)P, N-acetylglucosamine-1 (6)-phosphate; NAMPT, nicotinamide phosphoribosyl transferase; PNP, purine nucleoside phosphorylase; UDPGlcNAc, UDP-N-acetylglucosamine.

FIGURE 4.

Temporal dependence of reprogrammed nucleotide metabolism in UK096 Mϕs in response to differential polarization and WGP treatments. Polar extracts from (Fig. 2 were analyzed by IC-UHR-FTMS for the distribution of labeled metabolite in the pyrimidine nucleotide/hexosamine biosynthesis pathways (HBPs) (A) and the purine nucleotide/dinucleotide biosynthesis/salvage pathway (B). The pathway schemes track the fate of pre-existing [12C] (black circles)/[14N] (black diamonds) and [2H] (D)/[13C] (red circles)/[15N] (blue diamonds) atoms derived from the transformations of [2H2]Glc (D2-Glc), [13C5]Gln, and [15N2]Trp via glutaminolysis, the Krebs cycle, PPP, and Trp catabolism. Not all expected labeled metabolites were shown, and Dx in parenthesis denotes scrambled D positions across different C atoms. The labeled species illustrated represent the top abundant [2H], [13C], and [15N] isotopologues for each metabolite. Time-course changes in the abundance of metabolite isotopologues shown (n = 3) include D* (sum of all D-labeled species), C*NxDx (sum of all 13C-labeled species that contained 0 to x number of [15N] and/or [2H]), and 0 or unlabeled ([12C]/[14N]/[1H]). Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request. CHO-THF, formyl tetrahydrofolate; HpX, hypoxanthine; NAcGN1(6)P, N-acetylglucosamine-1 (6)-phosphate; NAMPT, nicotinamide phosphoribosyl transferase; PNP, purine nucleoside phosphorylase; UDPGlcNAc, UDP-N-acetylglucosamine.

Close modal

Many of the pyrimidine metabolites in the Mϕs of the other three donors showed different labeling time-course changes in responses to polarization and WGP treatments (data not shown). However, one consistent response was seen for all four donors, i.e., enhanced fractional enrichment of [2H]UDPGlcNAc in the M2-Mϕs by WGPs (Supplemental Fig. 4Bb, d–f) with decrease or no discernable changes in the levels (Supplemental Fig. 4Ba–c, e). This suggests blocked UDPGlcNAc utilization by WGPs for protein glycosylation, which was accompanied by reduced CD206 levels (Fig. 1) and presumably attenuated M2-type functions.

Reprogrammed purine nucleotide and dinucleotide pathways suggest activation of ADP ribosylation in M[LPS + IFN-γ] and by WGP

Like pyrimidine nucleotides, Glc provides the precursors for the synthesis of purine nucleotides and dinucleotides (PRPP for ribose and Ser/Gly for purine rings) via the PPP and one-carbon pathway (scheme in (Fig. 4B) (66). [2H2]Glc incorporation into inosine (Ino) monophosphate (IMP) both in terms of levels (Fig. 4Ba) and fractional enrichment (Supplemental Fig. 4Aa) was comparable between UK096’s M1-Mϕs and M2-Mϕs, but subsequent conversion to [2H]ATP (Fig. 4Bb, Supplemental Fig. 4Cb) or [2H]GTP (Fig. 4Bc and data not shown) was enhanced in the M1-Mϕs versus M2-Mϕs. These data suggest activated ATP/GTP synthesis in the M1-Mϕs versus M2-Mϕs downstream of IMP synthesis. We also noted comparable [2H]IMP conversion to [2H]Ino (Fig. 4Bf, Supplemental Fig. 4Cc), but subsequent conversion to [2H]ribose-1-phosphate (R1P; (Fig. 4Bg, Supplemental Fig. 4Ce) via the action of purine nucleoside phosphorylase was enhanced in the M1-Mϕs versus M2-Mϕs. These data point to increased catabolism and/or salvage synthesis of purine nucleotides (80). To better delineate de novo versus salvage synthesis of purine nucleotides, we analyzed the 13C labeling patterns of purine nucleotide metabolites for the [13C6]Glc tracer experiment of Supplemental Figs. 2 and 4. We found that the fractional enrichment of the [13C5] isotopologues dominated for all metabolites regardless of the treatments (Supplemental Fig. 4D), while that of [13C>5] (number of [13C] > 5 for ATP/GTP) or [13C>10] (number of [13C] > 10 for NADH/ADP-ribose [ADPR]) isotopologues was negligible (data not shown). Because the [13C5] and [13C>5]/[13C>10] isotopologues, respectively, represent [13C] incorporation into ribose and nucleobase plus ribose (81), these data suggest that [13C6]Glc was incorporated mainly into the ribose unit of purine nucleotides via the salvage (80) rather than de novo synthesis pathway. We also noted that the fractional enrichment of [13C5]R1P (Supplemental Fig. 4Dg) was higher than that of [13C5]Ino (Supplemental Fig. 4Df) and comparable with that of [13C5]R5P (Supplemental Fig. 4Da), which indicates [13C6]Glc transformation to [13C5]R5P and then to [13C5]R1P as part of the salvage pathway (80). Thus, the heightened incorporation of [2H2]Glc into R1P and ATP/GTP in the M1-Mϕs points to enhanced production of ATP/GTP (Fig. 4B, Supplemental Fig. 4) mainly via the salvage pathway. Also noted was the WGP-enhanced incorporation of [2H2]Glc into IMP (Fig. 4Ba), Ino (Fig. 4Bc), and R1P (Fig. 4Be) in the M2-Mϕs without promoting the buildup of [2H]ATP/GTP but with elevation of their fractional enrichment (Supplemental Fig. 4Cb and data not shown) and the buildup of [2H]NADH (Fig. 4Bd). These data point to enhanced salvage synthesis and utilization of ATP for fueling NADH/NAD+ synthesis in WGP-treated M2-Mϕs.

NAD+ is the substrate for ADP ribosylation of proteins such as PARP, and the turnover of ADP-ribosylated proteins produces ADPR (82). We saw, respectively, transient and sustained increase of [2H]ADPR levels in the M1-Mϕs and WGP-treated M2-Mϕs relative to the M2-Mϕs (Fig. 4Be). Along with depletion of the precursor [2H]NAD(H) (Fig. 4Bd), ADPR buildup and increased release of nicotinamide by the M1-Mϕs (Supplemental Fig. 4Di) indicate increased ADP-ribosylation activity and turnover. Our findings agree with a recent report on LPS-induced nicotinamide accumulation, NAD+ depletion, and buildup of PARylated PARP in human Mϕs (42). Furthermore, we saw an elevated ratio of [13C10]ADPR:[13C5]ADPR (Supplemental Fig. 4Dh) in WGP-treated M2-Mϕs versus untreated M2-Mϕs in the [13C6]Glc tracer study. A higher ratio not only indicates higher ADP-ribosylation activity but also NAD+ resynthesis by consuming the released nicotinamide, because both are required for producing [13C10]ADPR, while [13C5]ADPR can be produced via ADP ribosylation only (cf. scheme in Supplemental Fig. 4D). This is consistent with the lack of buildup of nicotinamide (Supplemental Fig. 4Di) and excess buildup of [2H]NADH (Fig. 4Bd) in WGP-treated M2-Mϕs versus M2-Mϕs. ADP ribosylation of proteins has been shown to mediate LPS-induced activation of human monocytes (43), while CD38 (NAD+ glycohydrolase) that also consumes NAD+ to generate cyclic ADPR and ADPR (83) is known to activate murine Mϕs in response to bacterial infection (84). In contrast, NAD+ homeostasis is crucial to sustaining oxidative phosphorylation and immune resolution (42). Thus, the simultaneous activation of NAD+ homeostasis and ADP ribosylation by WGPs implicates boosting of both M1- and M2-type functions.

Gln is a required N source for purine biosynthesis, but it is not expected to be a significant carbon source unless it is transformed via GNG to produce Gly, Ser, and R5P. We saw sizable [13C] and [15N] incorporation into all nucleotide metabolites containing purine rings in UK096’s Mϕs (Fig. 4Ba′–f′, Supplemental Fig. 4C, and data not shown), which indicates the glutaminolysis to GNG pathway as a key route for supporting purine nucleotide biosynthesis in human Mϕs. We also noted a lower [13C] fractional enrichment of IMP (Supplemental Fig. 4Cf) than that of Ino (Supplemental Fig. 4Ch) and ADPR (Supplemental Fig. 4Ci) in all Mϕs (Supplemental Fig. 4C), which is unexpected from the usual precursor and product relationship. We have shown recently that such an atypical relationship signifies preferential diversion of labeled precursors for purine biosynthesis in human lung cancer tissue slice cultures (66) and activated mouse T cells (85). Thus, the present data implicate preferential routing of Gln-derived IMP to the production of Ino and NADH, which also points to the importance of the purine salvage pathway. The scheme in (Fig. 4B also showed the more abundant isotopologues of ATP, i.e., [2H2] (D2)-ATP, [13C3] (red circles)-ATP, and [15N1]/[15N2] (blue diamonds), [2H2]ATP, which is consistent with their respective transformations from [2H2]Glc, [13C5]Gln, and [15N2]Trp via PPP, glutaminolysis-GNG-PPP, and Trp catabolic pathways. Moreover, levels of [13C]IMP, [13C]ATP, [13C]Ino, [13C]NADH, and [13C]ADPR did not show discernable responses to polarization or WGP treatments other than the buildup of [13C]IMP and depletion of [13C]ATP (Fig. 4Bb′) in WGP-treated versus untreated M2-Mϕs, as well as the buildup of [13C]ADPR (Fig. 4Be′) in the M1-Mϕs and WGP-treated M2-Mϕs versus M2-Mϕs after 1 d of treatment (Fig. 4B). These changes in levels contrasted with only minor changes in the corresponding fractional enrichment ([13C]IMP, Supplemental Fig. 4Cf, [13C]ATP, 4Cg, and [13C]ADPR, 4Ci) and reduced fractional enrichment for [13C]Ino (Supplemental Fig. 4Ch) by WGPs (Supplemental Fig. 4C). Together, they suggest blockade of IMP conversion to Ino and enhanced ATP utilization in the M2-Mϕs elicited by WGPs, as well as enhanced ADPR production or ADPR ribosylation activity in 1-d polarized M1-Mϕs, which diminished thereafter.

Consistent treatment responses of Mϕs from the other three donors included (1) sizable [13C] and [15N] incorporation into all nucleotide metabolites containing purine rings (Supplemental Fig. 4Ea–c, g–i, p–r); (2) lower [13C] enrichment of IMP (Supplemental Fig. 4Ea, g, p) than that of Ino (Supplemental Fig. 4Eb, h, q) and ADPR (Supplemental Fig. 4Ec, i, r); (3) [2H2], [13C3], and [15N1/15N2, 2H2] isotopologues as top abundant products of ATP (cf. (Fig. 4B); and (4) excess buildup of [2H]IMP (Supplemental Fig. 4Ed, j, s) with fewer changes in the fractional enrichment (data not shown) and higher [2H] enrichment of ATP (Supplemental Fig. 4Ee, l, u) and ADPR (Supplemental Fig. 4Ef, m, v) in WGP-treated versus control M2-Mϕs (Supplemental Fig. 4E). Also consistently observed for UK168 and UK166, but not for UK094, were enhanced buildup of [2H]Ino in WGP-treated M2-Mϕs (Supplemental Fig. 4Ek, t) and of [2H]R1P (Supplemental Fig. 4Ek, t) and increases in fractional enrichment in the M1-Mϕs (Supplemental Fig. 4Eo, x). The rest of the responses varied qualitatively and/or quantitatively as a function of polarization durations.

Altogether, our data indicate that the salvage pathway and Trp catabolism contribute significantly to the synthesis of purine nucleotides/dinucleotides while implicating preferential diversion of GNG-mediated transformations of Gln-carbon into purine nucleotides, which occurs downstream of IMP. They also implicate activation of ADP ribosylation along with enhanced Trp catabolism and blockade of NAD+ resynthesis in M[LPS + IFN-γ], leading to enhanced proinflammatory functions and mitochondrial dysfunctions. They further point to the ability of WGPs to restore ADP ribosylation while boosting NAD+ resynthesis in M[IL-4 + IL-13], thereby sustaining both immune activation and resolution.

The mSIRM data described earlier revealed multiple sites of altered metabolic regulation in response to differential polarization and WGP treatments. To quantify a large number of protein candidates with very limited Mϕ protein lysates, we used RPPA, instead of Western blotting. We saw enhanced expression of SLC2A1 or glucose transporter 1 (Fig. 5Aa) and PKM2 (Fig. 5Ab) elicited by WGPs in UK096’s M2-Mϕs (Fig. 5A), which correlated with the enhanced release of [2H]lactate into the medium or glycolytic activity (Fig. 2Ab). Lower levels of MDH1 (Fig. 5Ag) were related to the depletion of [2H]citrate or decrease in the initial Krebs cycle activity in the M1-Mϕs (Fig. 2Bf), while increased levels of FH (Fig. 5Af) correlated with the buildup of [2H]fumarate in WGP-treated M2-Mϕs (Fig. 2Be). However, in contrast with the two Krebs cycle breaks in mouse M1-Mϕs, we saw no suppression of IDH2 and SDHB proteins in UK096’s M1-Mϕs versus M2-Mϕs (data not shown), which is consistent with the lack of buildup in [2H]αKG or [2H]succinate (Fig. 2B). Overexpression of PC (Fig. 5Ak), PCK2 (Fig. 5Al), and FBP1 (Fig. 5Am) agrees with the buildup of [13C]hexose phosphate products or heightened GNG activity evident in WGP-treated versus untreated M2-Mϕs (Fig. 3). Although GLUD1 (Fig. 5An), but not glutamate-oxaloacetate transaminase 2 (data not shown), was induced by WGPs in the M2-Mϕs, we saw no corresponding buildup of its product [13C]αKG and downstream [13C] metabolites (Fig. 2B). This could result from enhanced utilization of [13C]oxaloacetate (OAA) required for the increase in [13C5]Gln–mediated GNG activity.

FIGURE 5.

Temporal dependence of changes in metabolic proteins and immune modulators/effectors in four donors’ Mϕs in response to polarization and WGP treatments. Cell lysates of UK096 Mϕs (A) from (Fig. 2 and three other donors from Supplemental Fig. 1 (B) were subjected to RPPA analysis of various protein targets, as described in the Materials and Methods. Image intensities for each target were normalized to those of total protein (n = 3). PKM2 in glycolysis; PGD in PPP. Pyruvate dehydrogenase E1 subunit α (PDHE1α), citrate synthase (CS), 2-oxoglutarate dehydrogenase (OGDH), FH, and MDH1/2 in the Krebs cycle. GLUD1 in the glutaminolysis pathway. PC, PCK1/2 PEP carboxykinase 2, and FBP1 in GNG. PYGB/PYGL glycogen phosphorylase brain/liver form, GYS1 muscle glycogen synthase, and GSK3B (liver forms) in glycogen metabolism. IDO1, QPRT, and PARylated proteins in Trp/NAD+ metabolism. IL-1B, IL-1β, and nitric oxide synthase 2 (NOS2) in immune function. C-type lectin domain containing 7A (CLEC7A), BZIP transcription factor (MAF), mannose receptor C type 1 (MRC1), CD163 scavenger receptor cysteine-rich type 1 protein M130, and RELA NF NF-κB P65 subunit in immune modulation. Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request. GLUT1 or SLC2A1, glucose transporter 1.

FIGURE 5.

Temporal dependence of changes in metabolic proteins and immune modulators/effectors in four donors’ Mϕs in response to polarization and WGP treatments. Cell lysates of UK096 Mϕs (A) from (Fig. 2 and three other donors from Supplemental Fig. 1 (B) were subjected to RPPA analysis of various protein targets, as described in the Materials and Methods. Image intensities for each target were normalized to those of total protein (n = 3). PKM2 in glycolysis; PGD in PPP. Pyruvate dehydrogenase E1 subunit α (PDHE1α), citrate synthase (CS), 2-oxoglutarate dehydrogenase (OGDH), FH, and MDH1/2 in the Krebs cycle. GLUD1 in the glutaminolysis pathway. PC, PCK1/2 PEP carboxykinase 2, and FBP1 in GNG. PYGB/PYGL glycogen phosphorylase brain/liver form, GYS1 muscle glycogen synthase, and GSK3B (liver forms) in glycogen metabolism. IDO1, QPRT, and PARylated proteins in Trp/NAD+ metabolism. IL-1B, IL-1β, and nitric oxide synthase 2 (NOS2) in immune function. C-type lectin domain containing 7A (CLEC7A), BZIP transcription factor (MAF), mannose receptor C type 1 (MRC1), CD163 scavenger receptor cysteine-rich type 1 protein M130, and RELA NF NF-κB P65 subunit in immune modulation. Student t test p values for pairwise comparison among M1, M2, and M2WGP Mϕs will be provided as a table on request. GLUT1 or SLC2A1, glucose transporter 1.

Close modal

To better resolve the dynamic changes and regulation of glycogen metabolism in UK096 Mϕs, we analyzed the response of the key enzymes GYS1, glycogen phosphorylase (PYGB and PYGL), and GSK3B (86). We saw enhanced expression of PYGB (Fig. 5Ao), PYGL (Fig. 5Ap), and GYS1 (Fig. 5Aq) induced by WGPs in the M2-Mϕs (Fig. 5A). We also saw a minor increase in GSK3β expression by WGPs (Fig. 5Ar), which could contribute to negative regulation of GYS1 via phosphorylation. These data point to a complex balance between activated glycogen synthesis and degradation machineries that underlie the observed 13C labeling patterns of the glycogen pathway metabolites (Supplemental Fig. 3). However, the lack of changes in PYGL, PYGB, and GYS1 expression in response to M1 versus M2 polarization (Fig. 5A) suggests that the increased glycogen buildup in the M1-Mϕs versus M2-Mϕs (Supplemental Fig. 3Ac,c′) did not result from expression changes of these proteins, but rather from changes in their posttranslational modifications and/or allosteric control. Glycogen deposition (87) or metabolism (77) is known to regulate M1-type inflammatory responses, and STAT1 expression was shown to mediate such responses in mouse Mϕs (77). We saw elevated levels of STAT1 in the M1-Mϕs versus M2-Mϕs (Fig. 5As), which is consistent with the reported role of glycogen in immune modulation.

We also observed enhanced levels of protein PARylation (PAR) or ADP ribosylation in the M1-Mϕs and WGP-treated M2-Mϕs (Fig. 5At). This corroborates the changes in the labeling patterns of ADPR (Fig. 4B, Supplemental Fig. 4C, 4E) and the [13C10]/[13C5] ratio of ADPR (Supplemental Fig. 4Dh), which reflect increased ADP-ribosylation activity. Overexpression of IDO1 (Fig. 5Au) and suppression of QPRT (Fig. 5Av) were evident in the M1-Mϕs versus M2-Mϕs (Fig. 5A), which should underlie the excess buildup of Trp-derived QA in the M1-Mϕs (Fig. 2Ai′). Lower IDO1 overexpression but higher QPRT overexpression elicited by WGPs in the M2-Mϕs versus M1-Mϕs can account for the lower buildup of QA while supporting enhanced NAD+ resynthesis in WGP-treated M2-Mϕs as reasoned earlier from the SIRM data (cf. (Fig. 4B, Supplemental Fig. 4D). Furthermore, we saw WGP-induced MAF (Fig. 5Az), but not Dectin-1 (CLEC7A; (Fig. 5Ay), expression in the M2-Mϕs (Fig. 5A), which is consistent with the activation of Dectin-1 by WGP binding to this C-type lectin receptor and subsequent activation of the Maf gene expression in bone marrow–derived mouse Mϕs (7). However, these results are opposite to those of a more recent study, where MAF expression was suppressed by WGPs in human M2-like Mϕs (88). Nevertheless, WGP-induced buildup of proinflammatory cytokines IL-1β or IL-1B, IL-6, IFN-γ, TNF-α (UK096; (Fig. 1D), and to a small extent nitric oxide synthase 2 (Fig. 5Ax) is consistent with the responses of mouse bone marrow–derived mouse Mϕs (7) and our human Mϕs to WGP treatment (88). Also notable was the WGP-enhanced release of anti-inflammatory cytokine IL-10 (Fig. 1D) but suppressed M2-Mϕ markers CD206 (mannose receptor C type 1, (Fig. 5Aa′) and CD163 (Fig. 5Ab′) and elevated levels of the proinflammatory transcription factor RELA (89) (NF-κB p65 subunit) (Fig. 5Ac′). Suppression of CD206 has been linked to the downregulation of sedoheptulose kinase (CARKL), which converts sedoheptulose to S7P to regulate M2 activation (90). Together, these protein responses of UK096’s Mϕs to WGPs support the SIRM data on a dual role of WGPs in boosting both inflammatory and anti-inflammatory functions. They also revealed consistency and plasticity from those previously reported for mouse and human Mϕs.

Last, we saw a minor increase in the levels of PGD (Fig. 5Aj) under M1 stimuli, which cannot explain the opposite responses in [2H]6PG and [2H]R5P between the M1-Mϕs and WGP-treated M2-Mϕs (Fig. 3b, c). We surmise that other R5P-producing reactions, such as that catalyzed by CARKL, contribute to these metabolic responses, i.e., downregulation of CARKL by WGPs in the M2-Mϕs could lead to the lack of buildup in R5P. Also, it is possible that allosteric and/or posttranslational modification modulation of PGD underlies WGP-mediated buildup of [2H]6PG.

Similar to UK096 described earlier, altered expression of multiple enzymes may be key to reprogramming central metabolism in the other donors’ Mϕs elicited by differential polarization and WGPs. These include (1) enhanced expression of SLC2A1 (Fig. 5Ba, q, f′) for increased uptake of Glc in WGP-treated M2-Mϕs (data not shown); (2) enhanced expression of PC, PCK2 (data not shown), and FBP1 (Fig. 5Bb, r, h′) for activated GNG (Supplemental Fig. 2) in WGP-treated M2-Mϕs; (3) enhanced expression of GYS1 (Fig. 5Bc, i′, s) for increased glycogen synthesis and that of PYGB (Fig. 5Bd, j′, t) for increased glycogen utilization in WGP-treated M2-Mϕs of UK168 and UK166; (4) enhanced expression of IDO1 (Fig. 5Bi, o′, y) with reduced expression of QPRT (Fig. 5Bp′, z) for increased buildup of QA in the M1-Mϕs (Fig. 2A, Supplemental Fig. 1A); and (5) enhanced expression of IDO1 and QPRT (Fig. 5Bj, p′, z) for less QA buildup (Fig. 2A, Supplemental Fig. 1A) and increased NADH synthesis (Fig. 4B) in WGP-treated M2-Mϕs. In addition, although PGD levels were unresponsive to WGP for UK096’s (Fig. 5Aj) and UK168’s M2-Mϕs (Fig. 5Ac′), they were enhanced by WGPs in UK94’s (Fig. 5Am) and UK166’s M2-Mϕs (Fig. 5Bs′), which could account for the relatively higher buildup of [2H]R5P in the latter (Supplemental Fig. 2Ab, l) than the former cases (Fig. 3c, Supplemental Fig. 2Ag).

In contrast, protein expression changes alone could not account for some of the time-course changes of metabolic activity in the four donors’ Mϕs in response to polarization or WGPs. Notably, we did not see corresponding changes in the expression of relevant enzymes CS (Fig. 5Ad), OGDH (Fig. 5Ae), or IDH1/2 (data not shown) that could account for the sharp decline in [2H]citrate and [2H]αKG levels from 1- to 3-d polarized M1-Mϕs and M2-Mϕs of UK096 (Fig. 2B). Likewise, the expression patterns of these enzymes (Fig. 5) could not fully explain the differential time-course changes in the levels of labeled Krebs cycle metabolites in M2-Mϕs in response to WGPs among the four donors (Fig. 2B, Supplemental Fig. 1B, and data not shown). These results point to the complexity and plasticity in the modulation of the Krebs cycle activity in human Mϕs by polarization or WGPs. Further investigation is needed to resolve this complexity at the individual level.

Furthermore, we saw expression changes in immune regulators that were related to those of immune effectors in the four donors’ Mϕs. These include (1) enhanced expression of STAT1 (Fig. 5Ba′, k, q′) to the buildup of intracellular IL-1β (Fig. 5Bh, n′, x) and/or increased release of IL-6 (Fig. 1D) in the M1-Mϕs; (2) enhanced expression of RELA (Fig. 5Bb′, l, r′) to increased production of proinflammatory cytokines IL-1β, IL-6, and TNF-α (Fig. 1D) in the M1-Mϕs and/or WGP-treated M2-Mϕs (91); (3) enhanced expression of mannose receptor C type 1 (Figs. 1B, 5Az, and data not shown) to increased production of anti-inflammatory cytokine IL-10 (Fig. 1D) in the M2-Mϕs; and (4) correlation of enhanced MAF expression (Fig. 5Az, 5Bf′, p, v′) to a boost in IL-10 release in the M2-Mϕs in response to the WGP treatment. These protein expression changes reiterate the role of WGPs in boosting both proinflammatory and anti-inflammatory functions of human Mϕs.

We have previously shown that WGPs elicited M1-like IM metabolic responses from CA lung OTCs of an NSCLC patient (UK021), but not from those of another patient (UK049), based on [13C]6-Glc tracer studies (52). These metabolic distinctions correlated with reduced mitotic index and increased necrosis in UK021 versus no responses in UK049 CA OTCs (52). As a part of this study, we also performed [13C5,15N2]Gln tracer experiments on UK021 lung OTCs along with the analysis of cytokine release. As shown in (Fig. 6A, WGPs enhanced the buildup of [13C5,15N1]Glu (C5N1, (Fig. 6Aa, direct product of glutaminolysis) and its subsequent transformation products via the Krebs cycle (Fig. 6Ab, αKG, 6Ad, fumarate, 6Ae, malate, 6Af, citrate, 6Ag, Asp, 6Aj, GSH) in CA but less so in NC OTCs of UK021. We also noted the lack of changes in [13C5,15N2]Gln metabolism into succinate (Fig. 6Ac), itaconate (Fig. 6Ah), and 2HG (Fig. 6Ai). Many of these IM metabolic responses to WGPs were akin to those of 1- to 2-d polarized M[IL-4 + IL-13] of UK166 (Supplemental Fig. 1). They were accompanied by enhanced release of proinflammatory cytokines (67, 92) IL-1β, MIP-1α, and TNF-α relative to the control treatment (Fig. 7A). Moreover, these cytokine releases by CA lung OTCs of UK021 were more pronounced than those of the UK049 counterparts, which displayed insignificant metabolic responses to WGPs. These new data further supported our conclusions on the capacity of WGPs in boosting both M1- and M2-type responses from CA lung tissues of UK021.

FIGURE 6.

IM metabolic responses of ex vivo lung OTCs of NSCLC patients to WGP treatment. CA and matched NC lung OTCs were freshly prepared from five NSCLC patients and cultured in the presence of [13C6]Glc (UK052, C; UK020, B) or [13C5,15N2]Gln (UK021, A; UL065 and UK062, B) ± WGPs for 24 h, followed by extraction and analysis by NMR and IC-UHR-FTMS as described in the Materials and Methods. The pathway schemes track the fate of pre-existing [12C] (black circles) and [13C] (red, blue, and green circles) atoms from [13C6]Glc or pre-existing [12C]/[14N] (black diamonds) and [13C]/[15N] (blue diamond) atoms from [13C5,15N2]Gln into metabolites of glycolysis, the Krebs cycle, pyrimidine/purine synthesis pathways, and glutaminolysis. x-Axis denotes the number of [13C] (0–x; C1–Cx) and/or [15N] atoms in isotopologues of metabolite. Green circles: PC-initiated Krebs cycle reactions; all other symbols and abbreviations are as in (Fig. 2. (A) Isotopologue distributions of metabolites for patient UK021, n = 1; (B and C) those for patients UL065, UK062, and UK052, respectively, n = 2; (D) WGP-induced changes in mitotic index (green or PCNA) and necroptosis (red or RIP1) in CA OTCs of NSCLC patient UK062, n = 2. Student t test p values for pairwise comparison among M1, M2a, and M2WGP Mϕs will be provided as a table on request. Note that WGP-induced changes in the labeling patterns of many individual metabolite showed large variations, presumably because of the intrinsic tissue heterogeneity. However, the same trend was evident for multiple metabolites in the Krebs cycle, which points to a change in the cycle activity.

FIGURE 6.

IM metabolic responses of ex vivo lung OTCs of NSCLC patients to WGP treatment. CA and matched NC lung OTCs were freshly prepared from five NSCLC patients and cultured in the presence of [13C6]Glc (UK052, C; UK020, B) or [13C5,15N2]Gln (UK021, A; UL065 and UK062, B) ± WGPs for 24 h, followed by extraction and analysis by NMR and IC-UHR-FTMS as described in the Materials and Methods. The pathway schemes track the fate of pre-existing [12C] (black circles) and [13C] (red, blue, and green circles) atoms from [13C6]Glc or pre-existing [12C]/[14N] (black diamonds) and [13C]/[15N] (blue diamond) atoms from [13C5,15N2]Gln into metabolites of glycolysis, the Krebs cycle, pyrimidine/purine synthesis pathways, and glutaminolysis. x-Axis denotes the number of [13C] (0–x; C1–Cx) and/or [15N] atoms in isotopologues of metabolite. Green circles: PC-initiated Krebs cycle reactions; all other symbols and abbreviations are as in (Fig. 2. (A) Isotopologue distributions of metabolites for patient UK021, n = 1; (B and C) those for patients UL065, UK062, and UK052, respectively, n = 2; (D) WGP-induced changes in mitotic index (green or PCNA) and necroptosis (red or RIP1) in CA OTCs of NSCLC patient UK062, n = 2. Student t test p values for pairwise comparison among M1, M2a, and M2WGP Mϕs will be provided as a table on request. Note that WGP-induced changes in the labeling patterns of many individual metabolite showed large variations, presumably because of the intrinsic tissue heterogeneity. However, the same trend was evident for multiple metabolites in the Krebs cycle, which points to a change in the cycle activity.

Close modal
FIGURE 7.

IM effector responses of ex vivo CA lung OTCs of NSCLC patients to WGP treatment. Media from the tracer experiments in (Fig. 6 (n = 1) and the tracer study of UK049 OTCs (n = 2) performed previously (52) were analyzed for cytokines as described in the Materials and Methods. The data were presented as the ratio of WGP to control values. Dashed lines denote a ratio of 1. (A) UK49, UK21; (B) UK20, UL65; (C) UK52, UK62.

FIGURE 7.

IM effector responses of ex vivo CA lung OTCs of NSCLC patients to WGP treatment. Media from the tracer experiments in (Fig. 6 (n = 1) and the tracer study of UK049 OTCs (n = 2) performed previously (52) were analyzed for cytokines as described in the Materials and Methods. The data were presented as the ratio of WGP to control values. Dashed lines denote a ratio of 1. (A) UK49, UK21; (B) UK20, UL65; (C) UK52, UK62.

Close modal

To examine further how individual NSCLC patient tissues respond to WGPs, we performed SIRM studies on additional ex vivo lung OTCs using [13C6]Glc or [13C5,15N2]Gln as tracer. (Fig. 6B illustrated the IM metabolic changes in four such examples. WGPs enhanced the conversion of [13C5,15N2]Gln to [13C5,15N1]Glu (Fig. 6Ba) and [13C5,15N1]GSH (Fig. 6Bh) via glutaminolysis without significantly impacting [13C5,15N1]Glu transformations through the Krebs cycle (Fig. 6Bb–f) except for a minor buildup of [13C]αKG (Fig. 6Bb) in CA OTCs of UL065 (red circles versus gray circles, (Fig. 6B). These responses were akin to those of 1-d polarized counterparts of UK168 (Supplemental Fig. 1B). For UK052’s CA OTCs (Fig. 6C), we saw WGP-elicited depletion of [13C] isotopologues of citrate (Fig. 6Cb), αKG (Fig. 6Cc), and 2HG (Fig. 6Ch) derived from [13C6]Glc, which could result from attenuated activity in the first half of the Krebs cycle. WGPs also induced the buildup of glycogen (Fig. 6Cd) and oxidized glutathione (GSSG, (Fig. 6Ck) in UK52’s CA OTCs. Moreover, the matched NC counterparts of these patients showed largely no response or an opposite response to WGP treatment (blue circles versus black circles, (Fig. 6A–C). Note that there were large variations in the replicate data for individual metabolites of UK52’s OTCs such that WGP-induced changes hardly reach statistical significance (Fig. 6C). These variations are presumably due to intrinsic slice heterogeneity as we have encountered previously (93) and described later. However, consistent changes in citrate and αKG isotopologues collectively point to attenuated Krebs cycle activity. These changes were in part similar to those of WGP-treated 1-d polarized counterparts of UK096 (Figs. 2B, 4, Supplemental Fig. 3A). In both cases, IM metabolic changes were accompanied by increased release of proinflammatory cytokines (IL-1β, MIP-1α, and TNF-α for both and IL-6 for UL065) (Fig. 7B, 7C), as is the case for UK021.

In the third example (UK062) with [13C5,15N2]Gln as tracer, we saw attenuated levels of unlabeled/[13C]lactate, as well as unlabeled, 13C-labeled, and/or 15N-labeled Krebs cycle metabolites in WGPs versus control CA lung OTCs (Fig. 6Bl–t), which is opposite to those observed for UK021 (Fig. 6A). Similar responses of the NC counterparts to WGPs were also evident, but not for Glu (Fig. 6Bk) and GSH (Fig. 6Br). These metabolic responses to WGPs were accompanied by increased release of IL-1β and TNF-α (but not IL-6 or MIP-1α) relative to the control CA OTCs (Fig. 7C), as well as reduced mitotic index (green PCNA fluorescence) (Fig. 6D). Because TAMs are not expected to proliferate, we attributed the PCNA response to originate from the cancer cells. Attenuated cancer cell proliferation would lead to decreased lactate production and compromised Krebs cycle activity in UK062’s CA OTCs. Thus, in this example, we may have seen cancer cell responses to WGPs that overwhelmed those of TAMs, as we have reported previously for brain-metastasized lung CA OTCs (93).

In the fourth example (UK020), we saw no pathway-wise changes of [13C6]Glc metabolism in lung CA OTCs induced by WGPs (Fig. 6B) that reflected those of the human Mϕ counterparts (Figs. 2, 4, Supplemental Figs. 1, 4). This is similar to the case for UK49 reported previously (52). Likewise, there was no enhanced release of the proinflammatory cytokines in WGP-treated versus control CA OTCs (Fig. 7B), which qualifies this patient’s lung CA OTCs as nonresponder.

As noted earlier, individual patient tissue OTCs were heterogeneous in cellularity and necrotic status (RIP1 as an indicator) (cf. CA-Ctl1 versus CA-Ctl2, (Fig. 6D). Consequently, each tissue OTC may vary in its basal functional and metabolic properties, leading to larger than typical variances in phenotypic and metabolic responses to treatments. In contrast, such heterogeneity is intrinsic to the patient tumors and is likely to govern variable sensitivity to drug treatments.

We have measured in-depth IM metabolic networks in human Mϕs prepared from the PBMCs of two each female (young and old) and male (young and old) human donors as a function of polarization method/duration and WGP treatment. The two older subjects (>60 y old) were age matched to lung cancer patients for comparison with IM metabolic responses to WGP in ex vivo lung cancer OTCs. A recent report has indicated distinct IM metabolism of human Mϕs between young and old subjects (42). It should be emphasized that our conclusion was drawn from consistent trends in the responses to immune modulations among four different donors, rather than from the statistical average of the responses averaged over the donors. Due to the very large variation in metabolic responses to immune modulations among the four donors (e.g., [2H]itaconate or [13C]itaconate in (Fig. 2B versus Supplemental Figs. 1B, 2, 3), meaningful statistical analysis could not be performed on this limited number of biological replicates. These large variations illustrate the plasticity of metabolic activity in human Mϕs in response to immune modulations.

Our mSIRM analyses show that although there were individual variations, consistent responses of the four donors to polarization and WGP treatment were observed. First, we noted preferred diversion of gluconeogenic products to ADPR production, as indicated by the higher [13C] fractional enrichment in ADPR than in its precursor ATP (Supplemental Fig. 4Cg versus i; data not shown). This diversion is likely to be mediated via the salvage synthesis of NAD+ (blue arrows, (Fig. 4B) and could represent an important mechanism for sustaining NAD+ turnover and ADP ribosylation in human Mϕs. Other consistent events included attenuated Krebs cycle and pyrimidine/UDPGlcNAc turnover, as well as enhanced itaconate production, oxidative PPP leading to R5P buildup, Trp catabolism (QA buildup), and ADP ribosylation in M[LPS + IFN-γ] versus M[IL-4 + IL-13] (Figs. 2, 3, 4, 5, Supplemental Figs. 14). These metabolic events were accompanied by increased level, or release of proinflammatory effectors IL-1β, IL-6, IFN-γ, and IP-10 enhanced expression of IDO1 and reduced phagocytosis (Fig. 1). Such linkages of IM metabolism to immune functions generally agree with the metabolic roles in modulating proinflammatory responses in M[LPS + IFN-γ] (43, 94, 95), except that the role of R5P and QA in immune modulation is still unclear. There is some indication that R5P can elicit proinflammatory responses by disrupting the LKB1–AMPK complex (96), thereby blocking AMPK-mediated anti-inflammation (97). Although QA buildup has been reported in human M1-Mϕs (41), Trp catabolism to QA is thought to be anti-inflammatory (40). Such apparent contradiction awaits further investigations to resolve.

Although enhanced glycolysis and glutaminolysis on LPS + IFN-γ versus IL-4 + IL-13 polarization were evident in proliferative M1-type mouse Mϕs derived from bone marrow (7, 94), these responses were plastic in our human Mϕ studies as indicated, respectively, by variable donor-dependent Glc uptake/[2H]lactate release and [13C]Gln uptake/[13C]Glu release/[13C]5Glu/GSH synthesis (Fig. 2, Supplemental Fig. 1). It is possible that such a distinction between human and mouse Mϕ metabolism is attributable to differences in proliferative capacity. This could also be said for the lack of the Krebs cycle breaks via suppression of IDH and SDH in human M[LPS + IFN-γ], which is known to occur in M1-type mouse Mϕs (23). Instead, variable buildup of 2HG (Fig. 2A, Supplemental Fig. 1A) and suppressed expression of MDHs (Fig. 5A and data not shown) could contribute to the flexible changes in the Krebs cycle activity and immunomodulation in our human M[LPS + IFN-γ] versus M[IL-4 + IL-13]. 2HG has been shown to block SDH activity in cancer cells (98), and we recently showed that SDH blockade led to T cell activation (99).

WGP is known to elicit proinflammatory responses (including enhanced glycolysis and glutaminolysis) in mouse M2-type Mϕs (7, 48). In this study, we observed a subset of known M1-type responses of IM metabolism in WGP-treated human M[IL-4 + IL-13], regardless of age or gender. These include time-dependent enhancement of glycolysis, glutaminolysis, Trp catabolism to QA (Fig. 2, Supplemental Fig. 1), and protein PARylation (Fig. 5 and data not shown), as well as reduced turnover of Gln-fueled UDPGlcNAc (Fig. 4A, Supplemental Fig. 4A, 4B). These metabolic events were accompanied by the enhanced release of proinflammatory cytokines IL-1β, IL-6, and TNF-α (Fig. 1D). In particular, WGP-enhanced TNF-α and IL-6 secretion could be induced by suppressed CD206 expression (Fig. 1B), because TNF-α and IL-6 gene expressions were shown to be downregulated by CD206 in mouse Mϕs (100). Suppressed CD206 expression in WGP-treated M[IL-4 + IL-13] could in turn be caused by reduced N-linked glycosylation using UDPGlcNAc as substrate. CD206 suppression could also be mediated by CARKL downregulation, which was shown to deplete R5P and enhance TNF-α/IL-6 release in LPS-activated mouse Mϕs (90). Thus, the depletion of R5P, along with the buildup of 6PG, in WGP-treated M[IL-4 + IL-13] versus M[LPS + IFN-γ] not only reflects enhanced oxidative PPP (M1-like) (101) but could also point to blocked CARKL (M2-like) (90). As such, our mSIRM characterization suggests mixed polarization of M[IL-4 + IL-13] by WGPs, while revealing a potential link of WGP-induced CD206 suppression to altered PPP activity that warrants future studies.

We also saw other aspects of metabolism indicative of mixed polarization in WGP-treated M[IL-4 + IL-13]. These include the lack of activated itaconate synthesis (Fig. 2B), maintenance of NAD(H) synthesis (Fig. 4B), and boosted synthesis of F1,6BP or F6P from Gln via GNG (Fig. 3, Supplemental Fig. 2A). Notable is the close match of the time-course change patterns of [13C]F1,6BP or [13C]F6P with those of IL-1β (Fig. 1D) in WGP-treated M[IL-4 + IL-13]. F1,6BP has been shown to enhance M2-type IL-10 production while attenuating M1-type cytokine production in inflamed mouse tissues (102). Thus, it is likely that WGP-activated gluconeogenic production of F1,6BP orchestrates the time-dependent diminishment of the increase in IL-1β release along with boosting of IL-10 release in M[IL-4 + IL-13]. The dichotomy of WGP-elicited IM metabolic reprogramming could help maintain homeostasis of immune responses, which could in turn account for the lack of immune toxicity of WGP treatment in human subjects (48). Moreover, our data demonstrated the plasticity in the IM responses of human donors’ M[IL-4 + IL-13] to WGPs; notably, variations in the activation of Glc/Gln uptake, lactate release to the media, and the buildup of 2HG, fumarate, QA, G6P, F1,6BP, G1P/UDPG/G1,6BP, and IMP/Ino/R1P (Figs. 2, 3, 4, Supplemental Figs. 14). These variations respectively reflect flexible responses of glycolysis, the Krebs cycle, GNG, glycogen turnover, and nucleotide salvage pathway to WGP treatment. Based on the literature, including our own findings on BM-derived mouse Mϕs (7), they could translate into variable immune functions and therapeutic efficacy.

Our mSIRM approach provided simultaneous and robust in situ assays for the activities of many established plus some unexpected IM metabolic pathways using very limited human specimens. The level of detail and complexity in IM metabolism resolvable by this approach cannot be achieved with conventional metabolite profiling or even single-tracer approaches. The pathway information thus acquired revealed many key enzyme/transporter candidates involved in modulating the IM metabolic changes, which can then be verified by protein expression analysis. High-throughput quantification of these many proteins with very limited cell or tissue lysates was made possible by adopting RPPA. In this study, we showed that the combination of mSIRM and RPPA not only verified metabolic regulation at the protein expression level but also implicated that at the transcriptional level. For example, glycolytic activation by WGPs in UK096’s M[IL-4 + IL-13] (Fig. 2A) could be mediated by PKM2 overexpression (Fig. 5), which can promote HIF-1α activity and transcriptional control of glycolytic enzyme/IL-1β expression (47). Also, F1,6BP buildup in WGP-treated M[IL-4 + IL-13] can enhance tetramerization of PKM2 (103), thereby boosting IL-10 production via enhancing gene transcription (47). Furthermore, UDPGlcNAc metabolism activated by WGPs can be linked to MAF overexpression in M[IL-4 + IL-13] (Fig. 5), which was shown to modulate M2-type responses in mouse Mϕs, including IL-10 gene expression (88, 104). However, in a previous report (88), MAF was suppressed by WGPs in M2-like Mϕs differentiated and polarized using FACS-sorted CD14+ human monocytes. This apparent contradiction is puzzling, but one possible cause could be the different methods of monocyte isolation, i.e., FACS sorting by Liu et al. (88) versus the use of RosetteSep kit in this report. If so, WGP’s effect on IM metabolism and regulation in human Mϕs depends heavily on specific monocyte populations. Further investigations are required to clarify this point and to verify WGP-induced changes in metabolic regulation surmised from mSIRM analysis.

WGP-induced metabolic responses (activated glycolysis [52] and glutaminolysis, but not itaconate production) in UK021’s CA lung OTCs (Fig. 6A) reflect those of M1- and M2-type Mϕs (Supplemental Fig. 1). The attendant M1-type increase in the release of proinflammatory cytokines (Fig. 7A) correlates with the increase in tissue necrosis reported previously (52), presumably due at least in part to the tumoricidal action of repolarized TAMs. This is corroborated by the link of relatively less proinflammatory cytokine release (Fig. 7A) to insignificant M1-type metabolic response in WGP-treated UK49’s CA lung OTCs observed previously (52). Such linkage of WGP-induced IM metabolic responses to proinflammatory cytokine release is also evident in other CA lung OTCs, including the responder OTCs of UL065 and UK052 (Fig. 6B, 6C) versus the nonresponder OTCs of UK020 (Figs. 6B–D, 7A, 7B). An exception is the divergence of IM metabolic responses (Fig. 6B) from the response of cytokine release (Fig. 7C) in WGP-treated lung CA OTCs of UK062, which could be explained by the massive loss of proliferative cancer cells (Fig. 6D). The resulting attenuation of cancer cell metabolism would mask WGP-induced changes in TAM metabolism, but not cytokine release (93). Thus, as the case for isolated human Mϕs, WGPs elicited mixed-type IM metabolic responses and immune effector release in patient-derived CA OTCs, which could be attributed to the response of the TAMs. Because this response varied among different CA OTCs, we surmise that such variability could lead to variable immunotherapeutic efficacy of WGPs in human cancer patients. Future studies on linking WGP-induced IM responses of patient-derived OTCs to those of the corresponding patients will substantiate this hypothesis.

In conclusion, we presented comprehensive changes of IM metabolic networks in four human donors’ Mϕs in response to differential polarization and WGP treatments. We found both consistency and divergence in the network responses compared with those of the mouse counterparts. Notable is the consistent activation of glycolysis, glutaminolysis, Trp catabolism to QA, and protein PARylation, as well as reduced turnover of UDPGlcNAc by WGPs in M[IL-4 + M13], which was related to increased releases of immune effectors. We also saw maintenance or reinforced M2-type IM metabolism by WGPs, such as increased synthesis of F1,6BP via GNG and enhanced production of anti-inflammatory cytokine IL-10, which could be related to WGP’s low immune toxicity in human. We further found that as was the case for human Mϕs in vitro, reprogrammed IM metabolic activities occurred variably in WGP-treated NSCLC OTCs ex vivo, which were correlated with proinflammatory cytokine releases and compromised tumor status. Thus, the ex vivo OTC systems could serve as unique models for studying the immune microenvironment of individual patients and its response to immunotherapeutics, which can help predict treatment efficacy in cancer patients.

We thank Huan Song for assistance with immunostaining of tissue slices, Dr. M. Bousamra for supplying the tissue, and Dr. Y. Cai for assisting the experiment with patient UL065.

This work was supported by the National Institutes of Health (NIH), National Cancer Institute Grants P01CA163223-01A1 and 1U24DK097215-01A1; NIH, National Institute of Diabetes and Digestive and Kidney Diseases Grant 1R01CA118434-01A2; NIH, National Institute of Environmental Health Sciences Grants 5R21ES025669-02 and 5R01ES22191; NIH, National Institute of General Medical Sciences Grant 5P20GM121327; shared resource(s) of the University of Kentucky Markey Cancer Center Grant P30CA177558; and endowment funds to T.W.-M.F. and A.N.L.

The online version of this article contains supplemental material.

Abbreviations used in this article:

     
  • ADPR

    ADP-ribose

  •  
  • CA

    cancerous

  •  
  • Cat#

    catalog number

  •  
  • DSS

    2,2-dimethyl-2-silapentane-5-sulfonate

  •  
  • F1,6BP

    fructose-1,6-bisphosphate

  •  
  • FBP1

    fructose-1,6-bisphosphatase 1

  •  
  • FH

    fumarate hydratase

  •  
  • F6P

    fructose-6-phosphate

  •  
  • G1,6BP

    glucose-1,6-bisphosphate

  •  
  • G1P

    glucose-1-phosphate

  •  
  • G6P

    glucose-6-phosphate

  •  
  • Glc

    glucose

  •  
  • Gln

    glutamine

  •  
  • GLUD1

    glutamate dehydrogenase 1

  •  
  • GNG

    gluconeogenesis

  •  
  • GSH

    glutathione

  •  
  • GSK

    glycogen synthase kinase

  •  
  • GYS1

    glycogen synthase 1

  •  
  • 2HG

    2-hydroxyglutarate

  •  
  • HIF-1α

    hypoxia-inducible factor 1α

  •  
  • IC-UHR-FTMS

    ion chromatography ultra-high-resolution Fourier transform mass spectrometry

  •  
  • IDH

    isocitrate dehydrogenase

  •  
  • IDO

    indoleamine-2, 3-dioxygenase

  •  
  • IM

    immunomodulatory

  •  
  • IMP

    inosine monophosphate

  •  
  • Ino

    inosine

  •  
  • αKG

    α-ketoglutarate

  •  
  • M1-Mϕ

    M1-type macrophage

  •  
  • macrophage

  •  
  • MDH

    malate dehydrogenase

  •  
  • MDM

    monocytes differentiation medium

  •  
  • ME

    malic enzyme

  •  
  • NAcGN1P

    N-acetylglucosamine-1-phosphate

  •  
  • NC

    noncancerous

  •  
  • NMR

    nuclear magnetic resonance

  •  
  • non-Ox

    nonoxidative

  •  
  • NSCLC

    non-small cell lung cancer

  •  
  • OTC

    organotypic tissue culture

  •  
  • PARP

    poly(ADP-ribose) polymerase

  •  
  • PC

    pyruvate carboxylase

  •  
  • PDH

    pyruvate dehydrogenase

  •  
  • 6PG

    6-phosphogluconate

  •  
  • PGD

    6-phosphogluconate dehydrogenase

  •  
  • PKM2

    pyruvate kinase M2

  •  
  • PPP

    pentose phosphate pathway

  •  
  • PRPP

    phosphoribosyl pyrophosphate

  •  
  • QA

    quinolinate

  •  
  • QPRT

    quinolinate phosphoribosyl transferase

  •  
  • R1P

    ribose-1-phosphate

  •  
  • R5P

    ribulose-5-phosphate

  •  
  • RPPA

    reversed phase protein array

  •  
  • SDH

    succinate dehydrogenase

  •  
  • SIRM

    stable isotope resolved metabolomic

  •  
  • S7P

    sedoheptulose-7-phosphate

  •  
  • TAM

    tumor-associated macrophage

  •  
  • Trp

    tryptophan

  •  
  • UDPG

    uridine diphosphoglucose

  •  
  • UDPGlcNAc

    UDP-N-acetyl-glucosamine

  •  
  • UHR-FTMS

    ultra-high-resolution Fourier transform mass spectrometry

  •  
  • WGP

    whole glucan particle

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The authors have no financial conflicts of interest.

Supplementary data