N ‐acetylaspartate release by glutaminolytic ovarian cancer cells sustains protumoral macrophages

Article14 July 2021Open Access Transparent process N-acetylaspartate release by glutaminolytic ovarian cancer cells sustains protumoral macrophages Alessio Menga Alessio Menga orcid.org/0000-0002-2827-5298 Department of Molecular Biotechnologies and Health Sciences, University of Turin, Turin, Italy Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Molecular Biotechnology Center, Turin, Italy Search for more papers by this author Maria Favia Maria Favia orcid.org/0000-0001-6039-9365 Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Department of Biomedical Sciences, University of Padova, Padova, Italy Search for more papers by this author Iolanda Spera Iolanda Spera Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Maria C Vegliante Maria C Vegliante Haematology and Cell Therapy Unit, IRCCS-Istituto Tumori ‘Giovanni Paolo II', Bari, Italy Search for more papers by this author Rosanna Gissi Rosanna Gissi Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Anna De Grassi Anna De Grassi Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Luna Laera Luna Laera orcid.org/0000-0002-5266-1156 Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Annalisa Campanella Annalisa Campanella Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Andrea Gerbino Andrea Gerbino Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Giovanna Carrà Giovanna Carrà Molecular Biotechnology Center, Turin, Italy Department of Clinical and Biological Sciences, University of Turin, Orbassano, Italy Search for more papers by this author Marcella Canton Marcella Canton orcid.org/0000-0002-8967-4049 Department of Biomedical Sciences, University of Padova, Padova, Italy Fondazione Istituto di Ricerca Pediatrica Città della Speranza - IRP, Padova, Italy Search for more papers by this author Vera Loizzi Vera Loizzi Policlinico University of Bari “Aldo Moro”, Bari, Italy Search for more papers by this author Ciro L Pierri Ciro L Pierri Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Gennaro Cormio Gennaro Cormio Policlinico University of Bari “Aldo Moro”, Bari, Italy Gynecologic Oncology Unit, IRCCS, Istituto Tumori Giovanni Paolo II, Bari, Italy Search for more papers by this author Massimiliano Mazzone Corresponding Author Massimiliano Mazzone [email protected] orcid.org/0000-0001-8824-4015 Department of Molecular Biotechnologies and Health Sciences, University of Turin, Turin, Italy Molecular Biotechnology Center, Turin, Italy Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, Department of Oncology, KU Leuven, Leuven, Belgium Search for more papers by this author Alessandra Castegna Corresponding Author Alessandra Castegna [email protected] orcid.org/0000-0003-0235-6847 Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Fondazione Istituto di Ricerca Pediatrica Città della Speranza - IRP, Padova, Italy Search for more papers by this author Alessio Menga Alessio Menga orcid.org/0000-0002-2827-5298 Department of Molecular Biotechnologies and Health Sciences, University of Turin, Turin, Italy Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Molecular Biotechnology Center, Turin, Italy Search for more papers by this author Maria Favia Maria Favia orcid.org/0000-0001-6039-9365 Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Department of Biomedical Sciences, University of Padova, Padova, Italy Search for more papers by this author Iolanda Spera Iolanda Spera Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Maria C Vegliante Maria C Vegliante Haematology and Cell Therapy Unit, IRCCS-Istituto Tumori ‘Giovanni Paolo II', Bari, Italy Search for more papers by this author Rosanna Gissi Rosanna Gissi Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Anna De Grassi Anna De Grassi Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Luna Laera Luna Laera orcid.org/0000-0002-5266-1156 Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Annalisa Campanella Annalisa Campanella Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Andrea Gerbino Andrea Gerbino Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Giovanna Carrà Giovanna Carrà Molecular Biotechnology Center, Turin, Italy Department of Clinical and Biological Sciences, University of Turin, Orbassano, Italy Search for more papers by this author Marcella Canton Marcella Canton orcid.org/0000-0002-8967-4049 Department of Biomedical Sciences, University of Padova, Padova, Italy Fondazione Istituto di Ricerca Pediatrica Città della Speranza - IRP, Padova, Italy Search for more papers by this author Vera Loizzi Vera Loizzi Policlinico University of Bari “Aldo Moro”, Bari, Italy Search for more papers by this author Ciro L Pierri Ciro L Pierri Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Search for more papers by this author Gennaro Cormio Gennaro Cormio Policlinico University of Bari “Aldo Moro”, Bari, Italy Gynecologic Oncology Unit, IRCCS, Istituto Tumori Giovanni Paolo II, Bari, Italy Search for more papers by this author Massimiliano Mazzone Corresponding Author Massimiliano Mazzone [email protected] orcid.org/0000-0001-8824-4015 Department of Molecular Biotechnologies and Health Sciences, University of Turin, Turin, Italy Molecular Biotechnology Center, Turin, Italy Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, Department of Oncology, KU Leuven, Leuven, Belgium Search for more papers by this author Alessandra Castegna Corresponding Author Alessandra Castegna [email protected] orcid.org/0000-0003-0235-6847 Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy Fondazione Istituto di Ricerca Pediatrica Città della Speranza - IRP, Padova, Italy Search for more papers by this author Author Information Alessio Menga1,2,3, Maria Favia2,4,†, Iolanda Spera2,†, Maria C Vegliante5,†, Rosanna Gissi2,†, Anna De Grassi2, Luna Laera2, Annalisa Campanella2, Andrea Gerbino2, Giovanna Carrà3,6, Marcella Canton4,7, Vera Loizzi8, Ciro L Pierri2, Gennaro Cormio8,9, Massimiliano Mazzone *,1,3,10 and Alessandra Castegna *,2,7 1Department of Molecular Biotechnologies and Health Sciences, University of Turin, Turin, Italy 2Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Bari, Italy 3Molecular Biotechnology Center, Turin, Italy 4Department of Biomedical Sciences, University of Padova, Padova, Italy 5Haematology and Cell Therapy Unit, IRCCS-Istituto Tumori ‘Giovanni Paolo II', Bari, Italy 6Department of Clinical and Biological Sciences, University of Turin, Orbassano, Italy 7Fondazione Istituto di Ricerca Pediatrica Città della Speranza - IRP, Padova, Italy 8Policlinico University of Bari “Aldo Moro”, Bari, Italy 9Gynecologic Oncology Unit, IRCCS, Istituto Tumori Giovanni Paolo II, Bari, Italy 10Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, Department of Oncology, KU Leuven, Leuven, Belgium †These authors contributed equally to this work **Corresponding author. Tel: +32 16 37 32 13; E-mail: [email protected] ***Corresponding author. Tel: +39 080 5442322; E-mail: [email protected] EMBO Reports (2021)22:e51981https://doi.org/10.15252/embr.202051981 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions Figures & Info Abstract Glutaminolysis is known to correlate with ovarian cancer aggressiveness and invasion. However, how this affects the tumor microenvironment is elusive. Here, we show that ovarian cancer cells become addicted to extracellular glutamine when silenced for glutamine synthetase (GS), similar to naturally occurring GS-low, glutaminolysis-high ovarian cancer cells. Glutamine addiction elicits a crosstalk mechanism whereby cancer cells release N-acetylaspartate (NAA) which, through the inhibition of the NMDA receptor, and synergistically with IL-10, enforces GS expression in macrophages. In turn, GS-high macrophages acquire M2-like, tumorigenic features. Supporting this in␣vitro model, in silico data and the analysis of ascitic fluid isolated from ovarian cancer patients prove that an M2-like macrophage phenotype, IL-10 release, and NAA levels positively correlate with disease stage. Our study uncovers the unprecedented role of glutamine metabolism in modulating macrophage polarization in highly invasive ovarian cancer and highlights the anti-inflammatory, protumoral function of NAA. Synopsis This study reveals a crosstalk between ovarian cancer cells and tumor associated macrophages. Glutamine addicted cancer cells release the signaling metabolite N-acetylaspartate (NAA), which in turn polarizes macrophages towards a GS-high, M2-like state. Glutaminolysis upon GS silencing in ovarian cancer cells leads to the release of NAA, which acts synergically with IL-10 to polarize macrophages toward a GS-high, M2- like phenotype. NAA acts as a competitor of the NMDA receptor (NMDAR) ligand. Concomitant treatment with NMDA abrogates the effect of NAA on LPS/IFNγ macrophages. The GS levels in macrophages from the ascitic fluid of ovarian cancer patients correlate with the cancer stage, ascitic IL-10 and NAA levels. Introduction The mechanisms underlying tumor growth, cancer cell invasion, and metastasis (Kolonin, 2012; Arvizo et al, 2013; Dragosavac et al, 2013) are often associated with cancer cell adaptation toward specific nutrient preferences for growth, invasion, and energy metabolism (Yang et al, 2014). These metabolic preferences are often dictated by oncogenic alterations associated with tumorigenesis (Dang et al, 2009; Gao et al, 2009; Weinberg et al, 2010; Gaglio et al, 2011) but also to the acquisition of a malignant state, which is dependent on cancer stage (Nomura et al, 2010; Benjamin et al, 2012; Caneba et al, 2012; Agus et al, 2013). Among the different nutrients, glutamine (Gln) is a key metabolite for cancer cell growth, as this amino acid becomes essential for “addicted” cancer cells (Weinberg et al, 2010; Wise & Thompson, 2010; Le et al, 2012; Castegna & Menga, 2018). This dependence relies on the many crucial roles Gln plays in the cell. Besides sustaining anaplerotically the TCA cycle, Gln represents a carbon and/or nitrogen source for other amino acids, fatty acids, and nucleotides (DeBerardinis & Cheng, 2010; Wise & Thompson, 2010; Rajagopalan & DeBerardinis, 2011; Daye & Wellen, 2012; Metallo et al, 2012). It is also the main source of N-acetyl glucosamine, necessary for protein glycosylation (Spiro, 2002), and of glutathione (Sappington et al, 2016), which endogenously detoxifies the cell from harmful radical species (Lauderback et al, 2003; Forman et al, 2009). Finally, Gln is emerging as an important modulator of many signaling pathways, such as mTOR, a regulator of autophagy (Van Der Vos et al, 2012) and protein synthesis (Nicklin et al, 2009). A positive correlation between Gln dependence of ovarian cancer cells and tumor aggressiveness has been extensively elucidated (Yang et al, 2014). Gln metabolism is fundamental also for tumor-associated macrophage (TAM) function, as macrophage-specific targeting of glutamine synthetase (GS) in tumor-bearing mice skews TAMs and MAMs (namely metastasis-associated macrophages) toward an “M1-like” state, promoting tumor vessel pruning, vascular normalization, accumulation of cytotoxic T cells, and metastasis inhibition (Palmieri et al, 2017; Menga et al, 2020). Furthermore, GS is strongly upregulated in Gln-deprived macrophages (van der Vos et al, 2012; Palmieri et al, 2017; Shang et al, 2020). These results suggest that the increased consumption of Gln by Gln-addicted cancer cells creates a state of Gln shortage in the tumor microenvironment (TME) that might trigger the acquisition of a GS-high protumoral phenotype of TAMs. However, evidence with this respect is elusive. Here, we provide unprecedented evidence of a metabolic crosstalk mechanism occurring between glutaminolytic ovarian cancer cells and macrophages, which is confirmed in ovarian cancer patients and we unravel the protumoral role of a known metabolite. Results Gln dependency of low-aggressive OVCAR3 cells was achieved through GS (GLUL) stable silencing, as assessed at both the RNA and protein levels (Fig 1A). Additionally, in this study, we also included SKOV3 cells as they are per se highly glutaminolytic and express very low levels of GS (Fig 1A). Compared to their scramble control (shNT), targeting GLUL in OVCAR3 cells leads to increased GLS1 transcript levels (Fig 1B), upregulated cellular glutamine transporters, LAT1 and ASCT2 (Fig 1C) and Gln uptake (Fig 1D), to a similar extent as observed in SKOV3 cells. In vitro, Gln was crucial for OVCAR3-shGLUL cell proliferation (Fig 1E and F) compared with OVCAR3-shNT cells. The propensity for migration (Fig 1G), invasion (Fig 1H and I), and angiogenesis (Fig 1J–M) in OVCAR3-shGLUL and, similarly, in SKOV3 cells was also enhanced in a Gln dependent fashion compared with OVCAR3-shNT cells, indicating that Gln addiction, generated in OVCAR3 cells by GS downmodulation, correlates with the acquisition of invasive, metastatic, and angiogenetic features of OVCAR3 cells. Figure 1. GS knockdown in OVCAR3 cells reprograms glutamine metabolism A. qRT–PCR quantification of GLUL mRNA transcript and GS protein expression in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL after 24 h of culture (n = 3 biological replicates). B, C. qRT–PCR quantification of (B) glutaminase (GLS1) and (C) glutamine transporters (LAT1 and ASCT2) mRNA in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL after 24 h of culture (n = 3 biological replicates). D. Extracellular Gln levels measured at different indicated time points in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL cells (n = 3 biological replicates). E, F. Effect of 24 h of glutamine deprivation on cell proliferation measured by occupied wound assay (E) (n = 6 biological replicates) and clonogenic test (F) (n = 3 biological replicates) in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL cells. G. Cell migration propensity was measured through a Matrigel-coated micropore filter in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL (n = 3 biological replicates). The migration of the cells, stained with Calcein-AM, was analyzed by fluorescence microscopy. The scale bars indicate 100 μm. H, I. Cell invasion valuated by qRT–PCR quantification of (H) CDH1 and (I) MMP2 transcript levels in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL (n = 3 biological replicates). J. Quantitative analysis of the total lengths of the endothelial capillary network formed by HUVEC cells cocultured with SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL for 6 h (n = 6 biological replicates). K. Quantification of released VEGF by SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL cells in conditioned media (n = 3 biological replicates). L, M. Angiogenesis propensity measured by qRT–PCR quantification of (L) NOS2 and (M) CDH5 mRNA levels in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL cells (n = 3 biological replicates). Data information: Data are displayed as mean ± SEM. Statistical significance was calculated by one-way ANOVA analyses with Tukey correction (A–C, G–M), two-way ANOVA analyses with Tukey correction (D–F) and defined as *P < 0.05, **P < 0.01, ***P < 0.001. Download figure Download PowerPoint We then cocultured LPS/IFNγ-stimulated human macrophages with OVCAR3-shGLUL or OVCAR3 cells and tested their polarization status. A marked decrease in M1 markers (Fig 2A) and increase in M2 markers (Fig 2B) were evident in LPS/IFNγ macrophages cocultured with OVCAR3-shGLUL (and SKOV3) but not in those cocultured with OVCAR3 cells, compared with LPS/IFNγ macrophages alone. This was paralleled by augmented GS expression at both RNA and protein levels (Fig 2C and D), as well as higher glutamine transporters (Fig 2E) but lower GLS1 expression (Fig 2F) in LPS/IFNγ-stimulated macrophages cocultured with SKOV3 or OVCAR3-shGLUL compared with OVCAR3-shNT cells, suggesting that Gln addiction in OVCAR3 cells positively correlates with the induction of a high GS, M2-like phenotype in macrophages. OVCAR3-shGLUL and SKOV3 media displayed higher release of IL-10 (Fig 3A), which is known to induce GS expression (Palmieri et al, 2017) in macrophages, and of NAA (although to a lower extent and at a later time point in SKOV3) compared with OVCAR3 media (Fig 3B), suggesting the OVCAR3-shGLUL cells might instate a complex crosstalk mechanism by releasing different signals in the TME. From a metabolic point of view, increased extracellular NAA concentration correlated with higher asparagine (Asn) uptake (Fig 3C) and higher intracellular levels of citrate, aspartate (Asp), and glutamate (Glu) (Fig 3D–F) in OVCAR3-shGLUL compared with OVCAR3-shNT and SKOV3 cells. At a later time point (84 h), SKOV3 cells also displayed higher citrate and aspartate (Fig EV1A and B), associated with a mild but significant increase in NAA. A significant decrease in NAA levels (Fig EV1C) is induced by GS overexpression in SKOV3 cells (Fig EV1D). Both N-acetyl transferase (NAT8L) and ATP-citrate lyase (ACLY) were upregulated in OVCAR3-shGLUL and SKOV3 compared with OVCAR3 cells (Fig 3G and H), suggesting that citrate might represent a source of both Acetyl-CoA and Asp, the latter via oxaloacetate transamination, which is facilitated by Glu accumulation (Fig 3I). Figure 2. OVCAR3-shGLUL cells enhance LPS/IFNγ macrophage polarization toward a M2-like, GS-high phenotype compared with OVCAR3 cells A, B. qRT–PCR quantification of (A) M1 and (B) M2 markers in resting (Mφ) and LPS/IFNγ macrophages after a 24 h of coculture with or without SKOV3, OVCAR3-shNT, or OVCAR3-shGLUL cells (n = 3 biological replicates). C. qRT–PCR quantification of GLUL transcript in resting (Mφ) and LPS/IFNγ macrophages after coculture with or without SKOV3, OVCAR3-shNT, or OVCAR3-shGLUL cells (n = 3 biological replicates). D. GS protein expression quantification (with representative blot) in LPS/IFNγ macrophages after coculture with or without SKOV3, OVCAR3-shNT, or OVCAR3-shGLUL cells (n = 3 biological replicates). E, F. qRT–PCR quantification of (E) LAT1 and ASCT2 and (F) GLS1 transcript level in resting (Mφ) and LPS/IFNγ macrophages after coculture with or without SKOV3, OVCAR3-shNT, or OVCAR3-shGLUL cells (n = 3 biological replicates). Data information: Data are displayed as mean ± SEM. For all panels, statistical significance was calculated by one-way ANOVA analyses with Tukey correction and defined as *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Download figure Download PowerPoint Figure 3. GLUL knockdown effect on release of IL-10 and NAA and on consequent metabolic aspects A, B. Extracellular levels of (A) IL-10, and (B) NAA in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL cells (n = 3 biological replicates). C–F. Extracellular levels of Asn (C) and cytosolic levels of citrate (D), Asp (E), and Glu (F) in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL cells (n = 3 biological replicates). G, H. qRT–PCR quantification of (G) NAT8L and (H) ACLY mRNA in SKOV3, OVCAR3-shNT, and OVCAR3-shGLUL cells (n = 3 biological replicates). I. Ammonia production driven by glutaminolysis interferes with mitochondrial dehydrogenases, favoring citrate, AcCoA and OAA mitochondria accumulation. Up-regulation of NAT8L along with Glu accumulation, driving OAA transamination to Asp, leads to NAA production. NAA is also synthesized by NAT8L in the cytoplasm using AcCoA derived from citrate via ACLY. In the absence of intracellularly synthesized Gln, Glu drives OAA transamination leading to Asp, which accumulates due to decreased ASNS activity. AcCoA: Acetyl-CoA; ASNS: asparagine synthetase; AST: aspartate transaminase; ACLY: ATP-citrate synthase; GLS1: glutaminase; GS: glutamine synthetase; NAA: N-acetylaspartate; NAT8L: N-acetyltransferase 8 like; OAA: oxaloacetate; 2-OG: 2-oxoglutarate; PC: pyruvate carboxylase; PDH: pyruvate dehydrogenase. Data information: Data are displayed as mean ± SEM. Statistical significance was calculated by two-way ANOVA analyses with Tukey correction (A, B), one-way ANOVA analyses with Tukey correction (C–H), and defined as *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Download figure Download PowerPoint Click here to expand this figure. Figure EV1. SKOV3 metabolic reprogramming mimics that of OVCAR3-shGLUL cells A, B. Intracellular levels of (A) citrate, (B) aspartate (Asp) in SKOV3 cells compared with OVCAR3-shNT and OVCAR3-shGLUL cells (n = 3 biological replicates). C. NAA levels in SKOV3 cells compared with SKOV3-over-GLUL cells (n = 6 biological replicates). Metabolite levels are all measured with LC-MS/MS analysis after 84-h incubation. D. Transduction of SKOV3 cells verified by the RFP fluorescent signal. The images were collected by CELENA® S Digital Imaging System at 10× magnification (n = 3 biological replicates). The scale bars indicate 25 μm. Data information: Data are displayed as mean ± SEM. Statistical significance was calculated by one-way ANOVA analyses with Tukey correction (A, B), unpaired t-test (C) and defined as *P <0.05. Download figure Download PowerPoint Then, we wondered whether NAA, together with IL-10, contributes to polarize macrophages toward an “M2-like” phenotype. NAA treatment in Gln-deprived LPS/IFNγ (Fig 4A and B) macrophages acted similarly to IL-10 in promoting an M2-like state, since CD206 and CD163 mRNA levels were significantly higher in NAA-treated compared with LPS/IFNγ macrophages, but lower than NAA/IL-10-treated cells (Fig 4A and B). Conversely, co-treatment of NAA and NAA/IL-10 cells with an excess of the antagonist N-methyl-d-aspartate (NMDA, 30 times more than NAA) completely rescued the M1 to M2 switch, since it prevented CD206 and CD163 mRNA increase (Fig 4A and B) while promoting CD80 mRNA levels and TNFα release (Fig 4C and D). These results were confirmed by FACS studies (Fig EV2), indicating that NAA possibly acts by competing with ligands of the NMDA receptor and not through its metabolism. In support to this, the signaling effect of NAA in LPS/IFNγ macrophages was not abolished by silencing aspartoacylase (ASPA), the enzyme that catalyzes NAA deacetylation (Figs 4E and EV3A) when localized in the cytosol (Hershfield et al, 2006). Furthermore, following NAA treatment (10 μM), the extracellular levels of the molecule were unchanged after 24 h (Fig 4F). Mirroring these data, a 48-h time course incubation with 10 μM or even 20 μM NAA did not result in significant changes in its intracellular content (Fig 4G). The M1 to M2 switch promoted by NAA was associated with an increase in GS levels, which were completely abrogated by NMDA (Fig 4H). NAA-mediated trans-differentiation in Gln-rich medium (Fig EV3B–E) induced a M2-like switch with a similar trend to that observed when Gln was absent, although the increase in M2 markers was significantly less pronounced compared with the corresponding Gln-depleted samples, particularly for the treatments with NAA, IL-10, and IL-10/NAA (Fig EV3F–H). On the contrary, the increase in CD80 was less pronounced in the Gln-depleted compared with the Gln-rich samples (Fig EV3I). Furthermore, NAA treatment on IL-10 differentiating macrophages enhanced the M2-like phenotype, as indicated by the increased CD206, CD163, and GLUL levels in NAA/IL-10 compared with IL-10 macrophages (Fig EV3J–L). Altogether, these results indicate that NAA acts together with IL-10 in inducing an M2-like phenotype in macrophages by impeding NMDA receptor activation, which consequently leads to GS expression, previously shown to sustain the M2-like polarization (Palmieri et al, 2017; Menga et al, 2020). Figure 4. Effect of NAA on macrophage polarization A–C. qRT–PCR quantification of (A) CD206, (B) CD163, and (C) CD80 mRNA in LPS/IFNγ macrophages treated with NAA (10 μM) and/or IL-10 and/or NMDA in a Gln-depleted medium (n = 3 biological replicates). D. Extracellular TNFα levels in LPS/IFNγ macrophages treated with NAA (10 μM) and/or IL-10 and/or NMDA in a Gln-depleted medium (n = 3 biological replicates). E. qRT–PCR quantification of CD163 mRNA in ASPA-silenced LPS/IFNγ macrophages treated with NAA (10 μM) and/or IL-10 and/or NMDA in a Gln-depleted medium (n = 3 biological replicates). F. Extracellular NAA levels in LPS/IFNγ macrophages treated for 24 h with NAA (10 μM) and/or IL-10 and/or NMDA in a Gln-depleted medium (n = 3 biological replicates). G. Intracellular NAA levels in LPS/IFNγ macrophages treated for 24 h with NAA (10 and 20 μM) and/or IL-10 and/or NMDA in a Gln-depleted medium (n = 3 biological replicates). H. qRT–PCR quantification of GLUL mRNA in LPS/IFNγ macrophages treated with NAA (10 μM) and/or IL-10 and/or NMDA in a Gln-depleted medium (n = 3 biological replicates). I. Representative traces of Ca2+ influx in resting (red line) and LPS/IFNγ (black line) macrophages, measured after NMDA (300 μm), NAA (10 μM), or ATP (100 μM)/Bradykinin (1 μM) treatments in a Gln-depleted medium. Data information: Data are displayed as mean ± SEM (A–C, E–I) or ± SD (D). Statistical significance was calculated by one-way ANOVA analyses with Tukey correction (A–H) and defined as *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Download figure Download PowerPoint Click here to expand this figure. Figure EV2. Effect of NAA on macrophage polarization by FACS A, B. Flow cytometric quantification of the percentage of CD80+(A) and MHCII+ (B) cells after specific treatments. Mφ macrophages were used as a control. Representative overlaid flow cytometry histograms normalized to cell count (n = 3 biological replicates) are shown. Data information: Data are displayed as mean ± SEM. Statistical significance was calculated by one-way ANOVA analyses with Tukey correction and defined as *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Download figure Download PowerPoint Click here to expand this figure. Figure EV3. Effect of NAA on macrophages in different conditions A. qRT–PCR quantification of ASPA mRNA levels in LPS/IFNγ macrophages treated with NAA (10 μM) and/or IL-10 and/or NMDA and/or with siASPA (n = 3 biological replicates). B–E. qRT–PCR quantification of (B) CD206, (C) CD163, (D) CD80, and (E) GLUL mRNA levels in resting (Mφ) macrophages and LPS/IFNγ macrophages treated with NAA (10 μM) and/or IL-10 and/or NMDA (n = 3 biological replicates) in the presence of Gln. F–I. Comparison between qRT–PCR quantifications of (F) CD206, (G) CD163, (H) CD80, and (I) GLUL mRNA levels in LPS/IFNγ macrophages treated with NAA (10 μM) and/or IL-10 and/or NMDA (n = 3 biological replicates) in the absence of Gln, with qRT–PCR quantifications of the same markers in LPS/IFNγ macrophages treated with NAA (10 μM) and/or IL-10 and/or NMDA (n = 3 biological replicates) in the presence of Gln (n = 3 biological replicates). J–L. qRT–PCR quantification of (J) CD206, (K) CD163, (L) GLUL mRNA levels in IL-10 macrophages treated with NAA (10 μM) and/or NMDA (n = 3 biological replicates). Data information: Data are displayed as mean ± SEM. For (A-E, J-L) panels, statistical significance was calculated by one-way ANOVA analyses with Tukey correction, for (F-I) panels by unpaired t-test and defined as *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Download figure Download PowerPoint To obtain deeper insights into the mechanism by which NAA acts as NMDAR antagonist, we analyzed the available NMDAR structures crystallized in complex with agonists and antagonists. The list of the PDB entries highlighted through by pGenThreader, used for the following analysis, is reported in Dataset EV1. The cryo-EM structure of Homo sapiens NMDAR is available as apo-protein under the code 6irg.pdb (Zhang et al, 2018). Xenopus laevis cryo-EM/crystallized structures used for our comparative analysis were solved in complex with Glu and Gly agonists (as reported in 5iov.pdb, (Zhu et al, 2016) and 5uow.pdb, (Lü et al, 2017)) or with allosteric inhibitor (Ro25-6981, i.e., as reported in 5iov.pdb and 4tll.pdb, (Lee et al, 2014) or with the MK-801 channel blocker (5uow.pdb, (Lü et al, 2017)). In addition, the R. norvegicus GluN2D ligand-binding core (3oem.pdb) was solved in complex with NMDA co-agonist (as reported in 3oem.pdb (Vance et al, 2011)). NMDA (from 3oem.pdb) and Glu (from 5uow.pdb) ligands appear well superimposed