Abstract
Phagocytosis is required for the optimal efficacy of many approved and promising therapeutic antibodies for various malignancies. However, the factors that determine the response to therapies that rely on phagocytosis remain largely elusive. Here, we demonstrate that mitochondrial fission in macrophages induced by multiple antibodies is essential for phagocytosis of live tumor cells. Tumor cells resistant to phagocytosis inhibit mitochondrial fission of macrophages by overexpressing glutamine-fructose-6-phosphate transaminase 2 (GFPT2), which can be targeted to improve antibody efficacy. Mechanistically, increased cytosolic calcium by mitochondrial fission abrogates the phase transition of the Wiskott–Aldrich syndrome protein (WASP)–Wiskott–Aldrich syndrome interacting protein (WIP) complex and enables protein kinase C-θ (PKC-θ) to phosphorylate WIP during phagocytosis. GFPT2-mediated excessive use of glutamine by tumor cells impairs mitochondrial fission and prevents access of PKC-θ to compartmentalized WIP in macrophages. Our data suggest that mitochondrial dynamics dictate the phase transition of the phagocytic machinery and identify GFPT2 as a potential target to improve antibody therapy.
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Data availability
The mRNA profile data are available at the GEO database (accession number GSE159661). Previously published data that were reanalyzed here are available under accession codes GSE32918 and GSE181063. Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.
References
Aderem, A. How to eat something bigger than your head. Cell 110, 5–8 (2002).
Underhill, D. M. & Goodridge, H. S. Information processing during phagocytosis. Nat. Rev. Immunol. 12, 492–502 (2012).
Gordon, S. R. et al. PD-1 expression by tumour-associated macrophages inhibits phagocytosis and tumour immunity. Nature 545, 495–499 (2017).
Matlung, H. L., Szilagyi, K., Barclay, N. A. & van den Berg, T. K. The CD47–SIRPα signaling axis as an innate immune checkpoint in cancer. Immunol. Rev. 276, 145–164 (2017).
Feng, M. et al. Phagocytosis checkpoints as new targets for cancer immunotherapy. Nat. Rev. Cancer 19, 568–586 (2019).
Zhang, C. C. & Fu, Y. X. Another way to not get eaten. Nat. Immunol. 19, 6–7 (2018).
van den Berg, T. K. & Valerius, T. Myeloid immune-checkpoint inhibition enters the clinical stage. Nat. Rev. Clin. Oncol. 16, 275–276 (2019).
Dahal, L. N., Roghanian, A., Beers, S. A. & Cragg, M. S. FcγR requirements leading to successful immunotherapy. Immunol. Rev. 268, 104–122 (2015).
Nimmerjahn, F. & Ravetch, J. V. Fcγ receptors as regulators of immune responses. Nat. Rev. Immunol. 8, 34–47 (2008).
Pallasch, C. P. et al. Sensitizing protective tumor microenvironments to antibody-mediated therapy. Cell 156, 590–602 (2014).
Su, S. et al. Immune checkpoint inhibition overcomes ADCP-induced immunosuppression by macrophages. Cell 175, 442–457 (2018).
Mills, E. L., Kelly, B. & O’Neill, L. A. J. Mitochondria are the powerhouses of immunity. Nat. Immunol. 18, 488–498 (2017).
Mehta, M. M., Weinberg, S. E. & Chandel, N. S. Mitochondrial control of immunity: beyond ATP. Nat. Rev. Immunol. 17, 608–620 (2017).
Rambold, A. S. & Pearce, E. L. Mitochondrial dynamics at the interface of immune cell metabolism and function. Trends Immunol. 39, 6–18 (2018).
Park, D. et al. Continued clearance of apoptotic cells critically depends on the phagocyte Ucp2 protein. Nature 477, 220–224 (2011).
Wang, Y. et al. Mitochondrial fission promotes the continued clearance of apoptotic cells by macrophages. Cell 171, 331–345 (2017).
Overdijk, M. B. et al. Antibody-mediated phagocytosis contributes to the anti-tumor activity of the therapeutic antibody daratumumab in lymphoma and multiple myeloma. MAbs 7, 311–321 (2015).
Turaj, A. H. et al. Antibody tumor targeting is enhanced by CD27 agonists through myeloid recruitment. Cancer Cell 32, 777–791 (2017).
Bakalar, M. H. et al. Size-dependent segregation controls macrophage phagocytosis of antibody-opsonized targets. Cell 174, 131–142 (2018).
Chan, D. C. Mitochondria: dynamic organelles in disease, aging, and development. Cell 125, 1241–1252 (2006).
Buck, M. D. et al. Mitochondrial dynamics controls T cell fate through metabolic programming. Cell 166, 63–76 (2016).
Zhang, W. et al. GFPT2-expressing cancer-associated fibroblasts mediate metabolic reprogramming in human lung adenocarcinoma. Cancer Res. 78, 3445–3457 (2018).
Altman, B. J., Stine, Z. E. & Dang, C. V. From Krebs to clinic: glutamine metabolism to cancer therapy. Nat. Rev. Cancer 16, 619–634 (2016).
Cai, W. F. et al. Glutaminase GLS1 senses glutamine availability in a non-enzymatic manner triggering mitochondrial fusion. Cell Res. 28, 865–867 (2018).
Rambold, A. S., Kostelecky, B., Elia, N. & Lippincott-Schwartz, J. Tubular network formation protects mitochondria from autophagosomal degradation during nutrient starvation. Proc. Natl Acad. Sci. USA 108, 10190–10195 (2011).
Ho, P. C. et al. Phosphoenolpyruvate is a metabolic checkpoint of anti-tumor T cell responses. Cell 162, 1217–1228 (2015).
Chang, C. H. et al. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell 162, 1229–1241 (2015).
Barger, S. R. et al. Membrane–cytoskeletal crosstalk mediated by myosin-I regulates adhesion turnover during phagocytosis. Nat. Commun. 10, 1249 (2019).
Chen, J. et al. SLAMF7 is critical for phagocytosis of haematopoietic tumour cells via Mac-1 integrin. Nature 544, 493–497 (2017).
Su, X. et al. Phase separation of signaling molecules promotes T cell receptor signal transduction. Science 352, 595–599 (2016).
Martin, E. W. et al. Valence and patterning of aromatic residues determine the phase behavior of prion-like domains. Science 367, 694–699 (2020).
Ong, J. Y. & Torres, J. Z. Phase separation in cell division. Mol. Cell 80, 9–20 (2020).
Higgs, H. N. & Pollard, T. D. Regulation of actin filament network formation through ARP2/3 complex: activation by a diverse array of proteins. Annu. Rev. Biochem. 70, 649–676 (2001).
Sasahara, Y. et al. Mechanism of recruitment of WASP to the immunological synapse and of its activation following TCR ligation. Mol. Cell 10, 1269–1281 (2002).
Fried, S. et al. Triple-color FRET analysis reveals conformational changes in the WIP–WASp actin-regulating complex. Sci. Signal. 7, ra60 (2014).
Higgs, H. N. & Pollard, T. D. Activation by Cdc42 and PIP2 of Wiskott–Aldrich syndrome protein (WASp) stimulates actin nucleation by Arp2/3 complex. J. Cell Biol. 150, 1311–1320 (2000).
Alberti, S., Gladfelter, A. & Mittag, T. Considerations and challenges in studying liquid–liquid phase separation and biomolecular condensates. Cell 176, 419–434 (2019).
Martinez-Quiles, N. et al. WIP regulates N-WASP-mediated actin polymerization and filopodium formation. Nat. Cell Biol. 3, 484–491 (2001).
Ahn, J. H. et al. Tyrphostin A9 improves blastocyst development in porcine embryos through induction of dynamin-related protein 1-dependent mitochondrial fission. Mitochondrion 35, 80–86 (2017).
Kato, M. et al. Redox state controls phase separation of the yeast ataxin-2 protein via reversible oxidation of its methionine-rich low-complexity domain. Cell 177, 711–721 (2019).
Perocchi, F. et al. MICU1 encodes a mitochondrial EF hand protein required for Ca2+ uptake. Nature 467, 291–296 (2010).
Csordas, G. et al. MICU1 controls both the threshold and cooperative activation of the mitochondrial Ca2+ uniporter. Cell Metab. 17, 976–987 (2013).
Moreau, V. et al. A complex of N-WASP and WIP integrates signalling cascades that lead to actin polymerization. Nat. Cell Biol. 2, 441–448 (2000).
Weiskopf, K. & Weissman, I. L. Macrophages are critical effectors of antibody therapies for cancer. MAbs 7, 303–310 (2015).
Gordon, S. Phagocytosis: the legacy of Metchnikoff. Cell 166, 1065–1068 (2016).
Toda, C. et al. UCP2 regulates mitochondrial fission and ventromedial nucleus control of glucose responsiveness. Cell 164, 872–883 (2016).
Sukumar, M., Roychoudhuri, R. & Restifo, N. P. Nutrient competition: a new axis of tumor immunosuppression. Cell 162, 1206–1208 (2015).
Altman, B. J., Stine, Z. E. & Dang, C. V. From Krebs to clinic: glutamine metabolism to cancer therapy. Nat. Rev. Cancer 16, 619–634 (2016).
Oki, T., Yamazaki, K., Kuromitsu, J., Okada, M. & Tanaka, I. cDNA cloning and mapping of a novel subtype of glutamine:fructose-6-phosphate amidotransferase (GFAT2) in human and mouse. Genomics 57, 227–234 (1999).
Simpson, N. E., Tryndyak, V. P., Beland, F. A. & Pogribny, I. P. An in vitro investigation of metabolically sensitive biomarkers in breast cancer progression. Breast Cancer Res. Treat. 133, 959–968 (2012).
Swamy, M. et al. Glucose and glutamine fuel protein O-GlcNAcylation to control T cell self-renewal and malignancy. Nat. Immunol. 17, 712–720 (2016).
Xu, M. M. et al. Dendritic cells but not macrophages sense tumor mitochondrial DNA for cross-priming through signal regulatory protein α signaling. Immunity 47, 363–373 (2017).
Slawson, C., Copeland, R. J. & Hart, G. W. O-GlcNAc signaling: a metabolic link between diabetes and cancer? Trends Biochem. Sci. 35, 547–555 (2010).
Wang, V. M. et al. CD9 identifies pancreatic cancer stem cells and modulates glutamine metabolism to fuel tumour growth. Nat. Cell Biol. 21, 1425–1435 (2019).
Elgass, K., Pakay, J., Ryan, M. T. & Palmer, C. S. Recent advances into the understanding of mitochondrial fission. Biochim. Biophys. Acta 1833, 150–161 (2013).
Bergeron-Sandoval, L. P., Safaee, N. & Michnick, S. W. Mechanisms and consequences of macromolecular phase separation. Cell 165, 1067–1079 (2016).
Hnisz, D., Shrinivas, K., Young, R. A., Chakraborty, A. K. & Sharp, P. A. A phase separation model for transcriptional control. Cell 169, 13–23 (2017).
Shin, Y. & Brangwynne, C. P. Liquid phase condensation in cell physiology and disease. Science 357, eaaf4382 (2017).
Snead, W. T. & Gladfelter, A. S. The control centers of biomolecular phase separation: how membrane surfaces, PTMs, and active processes regulate condensation. Mol. Cell 76, 295–305 (2019).
Raimundo, N. et al. Mitochondrial stress engages E2F1 apoptotic signaling to cause deafness. Cell 148, 716–726 (2012).
Barkal, A. A. et al. Engagement of MHC class I by the inhibitory receptor LILRB1 suppresses macrophages and is a target of cancer immunotherapy. Nat. Immunol. 19, 76–84 (2018).
Sabari, B. R. et al. Coactivator condensation at super-enhancers links phase separation and gene control. Science 361, eaar3958 (2018).
Wilson, F. H. et al. A functional landscape of resistance to ALK inhibition in lung cancer. Cancer Cell 27, 397–408 (2015).
Giambra, V. et al. NOTCH1 promotes T cell leukemia-initiating activity by RUNX-mediated regulation of PKC-θ and reactive oxygen species. Nat. Med. 18, 1693–1698 (2012).
Schwayer, C. et al. Mechanosensation of tight junctions depends on ZO-1 phase separation and flow. Cell 179, 937–952 (2019).
Svitkina, T. Imaging cytoskeleton components by electron microscopy. Methods Mol. Biol. 1365, 99–118 (2016).
Zhao, Q. et al. Targeting mitochondria-located circRNA SCAR alleviates NASH via reducing mROS output. Cell 183, 76–93 (2020).
Burianek, L. E. & Soderling, S. H. Under lock and key: spatiotemporal regulation of WASP family proteins coordinates separate dynamic cellular processes. Semin. Cell Dev. Biol. 24, 258–266 (2013).
Hu, C. M. et al. High glucose triggers nucleotide imbalance through O-GlcNAcylation of key enzymes and induces KRAS mutation in pancreatic cells. Cell Metab. 29, 1334–1349 (2019).
Tajan, M. et al. A role for p53 in the adaptation to glutamine starvation through the expression of SLC1A3. Cell Metab. 28, 721–736 (2018).
Sokol, R. J., Hudson, G., James, N. T., Frost, I. J. & Wales, J. Human macrophage development: a morphometric study. J. Anat. 151, 27–35 (1987).
Delarue, M. et al. mTORC1 controls phase separation and the biophysical properties of the cytoplasm by tuning crowding. Cell 174, 338–349 (2018).
Iredale, P. A. & Dickenson, J. M. Measurement of intracellular free calcium ion concentration in cell populations using Fura-2. Methods Mol. Biol. 41, 203–213 (1995).
Sarek, G. et al. CDK phosphorylation of TRF2 controls t-loop dynamics during the cell cycle. Nature 575, 523–527 (2019).
Acknowledgements
This work was supported by grants from National Key Research and Development Program of China (2021YFA1103000), Natural Science Foundation of China (92057210, 82125017, 91942309, 81971481, 82173064), Science and Technology Program of Guangzhou (202103000070), Tip-Top Scientific and Technical Innovative Youth Talents of Guangdong special support program (2016TQ03R553), Guangdong Science and Technology Department (2017B030314026) and the Guangdong Basic and Applied Basic Research Foundation (2019A1515011632).
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S.S., Jiang Li and Y.Y. conceived the ideas and designed the experiments. Jiang Li, Y.Y., Z. Liu, Guoyang Zhang, Jiaqian Li, Q.X., S.Y., B.Z., J.P., X.L. and Y. Li performed the experiments. Jiang Li, Y.Y., Z. Liu, S.L., L.M., P.R., Jiang Liu, H.D., J.W., Z. Liang, Guoyang Zhang, X.G., Guoliang Zhang, N.C., Y. Lu, Q.Z., M.H. and C.D. analyzed the data. J.H., J.F., Q.C. and R.F. analyzed and interpreted the resulting data. Guoliang Zhang provided instruction for imaging experiments. S.S., Jiang Li and Y.Y. wrote the paper.
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Extended data
Extended Data Fig. 1 Sensitivity of cancer cells to phagocytosis.
a, Macrophages labeled with CMTPX were coincubated with anti-CD47 antibodies and indicated cancer cells labeled with CFSE for 12 hr at a 1:2 ratio. Double-positive cells represent the macrophages that engulfed tumour cells. The percentage is CMTPX+CFSE+ cells in the whole macrophage (CMTPX+) population. The quantitation is in Fig. 1a. b, Macrophages were cocultured with CFSE-labeled RL or Raji cells for 8 hr at a 1:2 ratio. Phagocytosis (arrows) was detected by fluorescence microscopy. The representative pictures represent 3 independent experiments. Scale bars, 50 μm. c, The quantitation of phagocytosis of macrophages cocultured with indicated B lymphoma cells and Rituximab. d, The quantitation of phagocytosis of macrophages coincubated with the indicated Her2+ breast cancers. e-g, Levels of CD20 (e), CD47 (f) and Her2 (g) in indicated cell lines were evaluated by flow cytometry. c-g, n = 5 experiments, 3 replicates each; P values were calculated using two−tailed Student’s t-test (c, d).
Extended Data Fig. 2 Mitochondrial fission is involved in phagocytosis.
a, Macrophages were cocultured with CFSE-labeled cancer cells and anti-CD47 antibodies for 12 hr at a 1:2 ratio. Representative images for Mito−Tracker Red from 3 independent experiments. Scale bars, 10 μm. b, The quantitation of mean length of mitochondria of Fig. 1c. c, The mean length of mitochondria around the phagocytic cup/engulfed tumour cell and the rest of the macrophages in Fig. 1c. d-g, Macrophages were coincubated with cancer cells and Rituximab (RTX), anti-CD47 antibodies (α-CD47) or Trastuzumab (Tras) for 8 hr (lymphoma) or 12 hr (solid cancer) at a 1:2 ratio. Afterwards, macrophages were sorted by CD14 magnetic beads and analyzed for Drp1 by western blotting. Representative blots and the quantitation of 3 experiments. h, i, Macrophages were cocultured with Raji cells labeled with pHrodo for 8 hr at a 1:2 ratio. The macrophages were defined as CD14 positive and divided into pHrodo−and pHrodo+ subpopulation. CD14+ pHrodo− and CD14+ pHrodo+ were sorted (h) and subjected to immunoblotting (i). j, Representative immunoblots and the quantitation of Drp1 in MCF-7 cells transduced with a control sgRNA (sgCtrl) or sgRNA against Drp1 (sgDrp1) from 3 experiments. Single en dashes represent untreated control. k, MCF-7 cells with Drp1 knockout were cocultured with macrophages for 12 hr at a 2:1 ratio. Macrophages were sorted and analyzed for Drp1 by western blotting from 3 experiments. b-g, i-k. Mean ± s.d.; n = 3 independent experiments (d-g, i-k); n = 10 cells/experiment, 3 independent experiments (b, c); P values were calculated using two-tailed Student’s t-test (c-g), One-Way ANOVA with Dunnett-t test (b) and Tukey’s multiple comparisons test (i-k).
Extended Data Fig. 3 Mitochondrial fission improves phagocytosis in vitro.
a, The efficiency of Drp1 silencing was evaluated by western blotting, representative blot from 3 independent experiments. Single en dashes represent untreated control. b, Macrophages with Drp1 knockdown were cocultured with CFSE-labeled BT-474 cells and Trastuzumab for 12 hr at a 1:2 ratio. Representative 3D immunofluorescence images for Mito-Tracker Red and CFSE and the quantitation of the mean length of mitochondria of 3 experiments. Scale bars, 10 μm. c, Macrophages with Drp1 knockdown were cocultured with pHrodo-labeled Raji cells and Rituximab for 8 hr at a 1:2 ratio. Representative flow cytometry plots of the CD14 gate. d, Macrophages with Drp1 knockdown were coincubated with CFSE-labeled MCF-7 cells and anti-CD47 antibodies. Representative images are shown (n = 3). Scale bars, 10 μm. e-g, CMTPX-labeled macrophages pretreated with MDIVI were coincubated with Deep Red Dye-labeled LS174T (e) or DLD1 (f) cells and anti-CD47 antibodies, or with CFSE-labeled BT-474 cells (g) and Trastuzumab. The percentage of CMTPX+ Deep Red Dye+ cells or CMTPX+CFSE+ in the CMTPX+ population is shown. h, Macrophages pretreated with MDIVI were coincubated with CFSE-labeled Raji cells and Rituximab. Representative images (n = 3) are shown. Scale bars, 10 μm. i, Autologous macrophages were cocultured with CFSE-labeled primary B cells and Rituximab for 8 hr at a 1:2 ratio. Macrophages with total transfer of fluorochrome from B cells were phagocytosed macrophages (gate). Macrophages were gated by side scatter (SSC) for analysis. j, Macrophages with Drp1 knockdown were cocultured with Raji cells and evaluated by confocal microscopy at indicated time points. The macrophages that engulfed more than one tumour cell are indicated by arrows. Scale bars, 20 μm. The quantitation is right. a-c, e-g, i, j, Mean ± s.d.; n = 3 independent experiments (a, j); n = 10 cells/experiment, 3 independent experiments (b); n = 3 experiments, 5 replicates each (c); n = 5 (e-g) and 3 (i) experiments, 3 replicates each; P values were calculated using One-Way ANOVA with Tukey’s multiple comparisons test.
Extended Data Fig. 4 Mitochondrial fission improves phagocytosis in vivo.
a, Macrophages isolated from C57BL/6 mice were labeled with CMTPX and coincubated with CFSE-labeled MC38 cells and anti-CD47 antibodies for 12 hr at a 1:2 ratio. The phagocytosis was evaluated by flow cytometry. b, The mouse experimental schematic. Wild-type or Csf1op/op mice bearing tumour cells (TCs) were intratumourally injected with wild-type macrophages after grafts were palpable (about 7 days) and intraperitoneally injected with anti-CD47 antibodies 2 days after macrophage injection. c, The quantitation of Fig. 1h. d, Macrophages isolated from C57BL/6 mice were labeled with CMTPX and coincubated with CFSE-labeled EO771 cells and anti-CD47 antibodies for 12 hr at a 1:2 ratio. The phagocytosis was evaluated by flow cytometry. e, Tumour growth curves of mice inoculated with EO771 cells and treated as (b), p value is shown in bottom. f, The quantitation of total macrophages and those with phagocytosis of tumour cells in Fig. 1i. a, c-f, Mean ± s.d.; n = 5 experiments, 3 replicates each (a, d); n = 6 mice per group (c, e, f); P values were calculated using two-tailed Student’s t-test (a, d) and One-Way ANOVA with Tukey’s multiple comparisons test (c, e, f).
Extended Data Fig. 5 GFPT2 in tumour cells mediates glutamine competition with macrophages.
a, The GFPT2 levels of indicated tumour cells were determined by western blotting. b, The relative protein levels of Fig. 2c was quantified from 3 experiments. c, Macrophages were coincubated with B lymphoma cells and Rituximab for 8 hr at a 1:2 ratio. Glutamine levels in medium were evaluated by LC-MS. Single en dashes represent macrophage alone. d, GFPT2 was silenced by shRNA. The representative blots and quantitation of 3 experiments are shown. Single en dashes represent untreated control (d-r). e, UDP-GlcNAc levels of T47D cells with GFPT2 knockdown were detected by LC-MS. f, g, Macrophages (Mϕ) were coincubated with RL and T47D cells with GFPT2 knockdown in transwells at a 1:2 ratio for 8 hr in the presence of Rituximab (Raji) and anti-CD47 antibodies (T47D), respectively. Glutamine levels in medium (f) and macrophages (g) were evaluated by LC-MS. h, i, T47D cells with GFPT2 knockdown were coincubated with macrophages and anti-CD47 antibodies. Representative western blots for Drp1 in macrophages and quantitation of 3 experiments (h). Phagocytosis was evaluated by flow cytometry (i). j, Macrophages were cocultured with T47D cells with GFPT2 knockdown and anti-CD47 antibodies. Macrophages were sorted. Representative western blots for Drp1 distribution in the whole cell lysates, mitochondrial fraction and cytosolic fraction and quantitation of 3 experiments. k, The quantitation of Drp1 colocalization with mitochondria of Fig. 3f. l, The quantitation of Fig. 3g. m, Raji and MCF-7 cells were transfected with empty vectors (EV) or vectors expressing GFPT2 (OE). The representative blots and quantitation of 3 experiments. n, UDP-GlcNAc levels in indicated cells were detected by LC-MS. o-r, Macrophages were coincubated with cancer cells with GFPT2 overexpression and Rituximab (Raji) or anti-CD47 antibodies (MCF7). Glutamine levels in medium (o) and macrophages (p) were evaluated by LC-MS. The mean length of mitochondria in macrophages and phagocytosis of tumour cells was evaluated by immunofluorescence microscopy. The quantitation is shown (q, r). a-r, Mean ± s.d.; n = 3 independent experiments (a, b, d, h, j, m). n = 8 replicates (c, e-g, n-p); n = 3 experiments, 3 replicates each (l, i); n = 10 cells/experiment, 3 independent experiments (k, q); n = 10 fields (magnification, 100×) in 10 independent experiments (r); P values were calculated using One-Way ANOVA with Dunnett-t test (a-c) and Tukey’s multiple comparisons test (d-r).
Extended Data Fig. 6 GFPT2 is targetable in vivo and associated with antibody efficacy in patients.
a, GFPT2 levels in MC38 and CMT-93 cells were determined by western blotting. The representative blots and quantitation of 3 independent experiments are shown. b, Representative immunoblots of GFPT2 in CMT-93 cells with GFPT2 knockout and quantitation of 3 independent experiments are shown. c, d, GFPT2 levels in mouse (left) or human (right) primary monocyte-derived macrophages and tumour cells that were resistant to phagocytosis were determined by western blotting. Representative blots (c) and quantitation of 3 independent experiments are shown (d). e, UDP-GlcNAc levels in primary monocyte-derived macrophages and indicated tumour cells treated with 142.5 μM azaserine for 0.5 hr were detected by LC-MS. The relative levels are shown. Single en dashes represent untreated control. f, MC38 cells were transduced with empty vectors or vectors expressing GFPT2 (GFPT2-OE). The GFPT2 levels were determined by western blotting. The representative blots and quantitation of 3 independent experiments are shown. g, The Kaplan–Meier survival curves of overall survival in 916 patients with diffuse large B-cell lymphoma receiving Rituximab-containing treatments with high or low GFPT2 expression from GSE32918 and GSE181063 online databases. P values were calculated using Log-rank (Mantel-Cox) test. h, Autologous monocyte-derived macrophages labeled with CFSE were cocultured with primary B-CLL cells labeled with Deep Red Dye for 8 hr at a 1:2 ratio with or without Rituximab (RTX) or azaserine. Representative immunofluorescence images for CFSE and Deep Red Dye are shown (n = 13). Scale bars, 20 μm. a, b, d-f, Mean ± s.d.; n = 3 independent experiments; P values were calculated using two-tailed Student’s t-test (a, d for left, e), One-Way ANOVA with Dunnett-t test (d for right) and Tukey’s multiple comparisons test (b, f).
Extended Data Fig. 7 WASP and WIP form a condensed liquid phase.
a, The ratio of polarized side/offside actin intensity of Fig. 5a was calculated. b, c, Macrophages with Drp1 knockdown were cocultured with Raji cells labeled with Deep Red and Rituximab at a ratio of 1:2 for 8 hr. Representative images (b) and the quantitation of actin intensity (c) are shown. Scale bars, 5 μm. d, The previously reported model of WIP-WASP interaction. In the resting state, the WBD domain of WIP binds directly to the WH1 domain of WASP and inhibits actin polarization. WIP, which is disassociated with WASP and phosphorylated by PKC-θ, promotes actin polarization. e, The western blot analysis of WIP and WASP from 5 × 104 macrophage lysates and recombinant protein standards. The arrows indicate the point on the standard curve corresponding to the density of WASP and WIP bands (n = 3). The concentration of WIP and WASP in macrophage cytoplasm was determined to be 9.7 ± 0.8 and 8.9 ± 1.0 μM, respectively. f, Visualization of turbidity caused by droplet formation. Representative pictures of tubes containing 10 μM WIP (above), 10 μM WASP (middle) or 10 μM WASP + 10 μM WIP (below) (n = 3). g, Representative light microscopy images of a mixture of recombinant WIP and WASP at various concentration gradients (n = 3). Scale bars, 10 μm. h, Representative western blots showing levels of recombinant WIP and WASP in solution (S) and separated droplets (P) (n = 3). Droplets were separated from the solution phase by sedimentation. i, Representative time-lapse micrographs of WIP puncta fusion in HEK293 cells transfected with DsRed-WIP and WASP (n = 3). Scale, 5 μm. j, The quantitation of FRAP analysis in Fig. 5e. 0 s is the starting of the bleaching event. Plots were generated from 20 droplets in 4 independent experiments. Mean ± s.d.; k, Schematics of WASP full length, △WH1 mutation and △VCA mutation. l, Schematics of the sedimentation assay. m, Liquid droplets of recombinant WASP-wild-type (WT), △WH1 mutation or △VCA mutation in the presence of recombinant WIP (10 μM each) (n = 3). Scale bars, 10 μm. a, c, e, j, Mean ± s.d.; n = 4 cells/experiment, 3 independent experiments (a, c), n = 3 independent experiments (e). P values were calculated by One-Way ANOVA with Tukey’s multiple comparisons test (a, c).
Extended Data Fig. 8 Mitochondrial fission regulates WASP-WIP phase transition.
a, Autologous macrophages with Drp1 knockdown were cocultured with primary human B cells labeled with Deep Red and Rituximab for 4 hr at a 1:2 ratio. Representative images and quantitation of WASP and WIP colocalization are shown. Scale bars, 5 μm. b, Macrophages pretreated with MDIVI were cocultured with Raji cells and Rituximab for 4 hr at a 1:2 ratio. Soluble (S) and pellet (P) fractions of sorted macrophages were separated via centrifugation. GAPDH is a loading control for the total lysates (T) and soluble fractions (n = 3). Single en dashes represent untreated control. c, The efficiency of Mfn1 silencing was detected by western blotting. d, The quantitation of colocalization of WIP and WASP in Fig. 6d. e, The quantitation of phagocytosis detected by flow cytometry. f, Raji cells with GFPT2 overexpression were and cocultured with macrophages and Rituximab at a 2:1 ratio for 4 hr. Scale bars, 5 μm. The quantitation is in Fig. 6f. g, Macrophages were cocultured with Raji cells and Rituximab in complete medium or glutamine deprived (Gln-d) medium at a 1:2 ratio for 4 hr. Scale bars, 5 μm. The quantitation is in Fig. 6g. h, Macrophages were treated with 3% 1,6 Hexanediol for 15 s. Representative images and the quantitation of WASP-WIP colocalization are shown. i, Macrophages were treated with 3% 1,6 Hexanediol for 15 s and cocultured with BT-474 cells with GFPT2 overexpression and anti-CD47 antibodies. The phagocytosis was evaluated by flow cytometry. a, c-e, h, i, Mean ± s.d.; n = 10 cells/experiment, 3 independent experiments(a, d, h); n = 4 (e) and 3 (i) experiments, 3 replicates each; n = 3 independent experiments (c); P values were calculated using One-Way ANOVA with Tukey’s multiple comparisons test (a, c-e) and two-tailed Student’s t-test (h, i).
Extended Data Fig. 9 Cytosolic calcium increased by mitochondrial fission disrupts WASP-WIP LLPS.
a-d, Macrophages pretreated with MDIVI were cocultured with Raji cells and Rituximab at a 1:2 ratio for 4 hr. Representative images of 2’,7’-Dichlorodihyrofluorescein diacetate (H2-DCFDA) (a) and the quantitation of H2-DCFDA fluorescence (b). Scale bars, 10 μm. Fluo-4 fluorescence in the cytoplasm of macrophages was evaluated by confocal microscopy, and the quantitation is in (c). Representative blots for cytosolic cytochrome C in sorted macrophages and the quantitation of 3 experiments (d). e, f, Phase diagrams (left) of WIP and WASP at different concentrations of cytochrome C (e) or H2O2 (f) from 3 experiments. Green and red blocks indicate that droplets were present and absent, respectively. The percent area of the image occupied by condensates relative to the maximal phase separation observed are plotted (right) with the mixture of 10 μM WIP and 10 μM WASP and increasing concentration of cytochrome C or H2O2, respectively. P value was calculated by comparing with the first group. g, Fura-2-labeled macrophages were cocultured with Raji cells and Rituximab (RTX) at a 1:2 ratio for 4 hr. Cytosolic Ca2+ was quantitated. h, The percent area of the image occupied by condensates relative to the maximal phase separation observed are plotted with the mixture of 10 μM WIP and 10 μM WASP and increasing concentration of CaCl2. P value was calculated by comparing with the first group. i, Rhod-2 fluorescence of macrophages with Drp1 knockdown was evaluated by confocal microscopy. j, Macrophages were cocultured with Raji cells and Rituximab in complete medium or glutamine deprived medium at a 1:2 ratio for 4 hr. Representative images and the quantitation of Fluo-4 fluorescence. Scale bars, 5 μm. k, The efficiency of MICU1 knockdown was detected by western blotting. l, Macrophages with MICU1 knockdown were cocultured with Raji cells labeled with Deep Red and Rituximab at a 1:2 ratio for 4 hr. Representative images (n = 3). Scale bars, 5 μm. m, The quantitation of colocalization of WIP and WASP in Fig. 7f. n, The quantitation of Fig. 7h. o, Representative western blots of WASP and WIP in macrophages treated with CaCl2 with BAPTA-AM of 3 independent experiments. Total lysates (T) were centrifuged for separating soluble (S) and pellet (P) fractions. Single en dashes in a-d, i-k, n, o represent untreated control. b-k, m, n, Mean ± s.d.; n = 10 cells/experiment, 3 independent experiments (b, c, i, j, m); n = 3 independent experiments (d, k); n = 3 experiments, 5 replicates each (e, f, h); n = 4 fields/sample (magnification, 100×) in 3 independent experiments (n); n = 5 replicates (g). P values were calculated using One-Way ANOVA with Tukey’s multiple comparisons test (b-d, g, i-k, m, n) and Dunnett-t test (e, f, h).
Extended Data Fig. 10 Phase separation of WIP and WASP prevents PKC-θ from phosphorylating WIP.
a, Macrophages pretreated with the PKC-θ inhibitor Sotrastaurin (Sot) or Myristoylated-Calbiochem (Myr) were cocultured with Raji cells and Rituximab for 4 hr at a 1:2 ratio. Afterwards, macrophages were sorted by CD14 magnetic beads. Representative western blots of phosphorylated and total WIP in macrophages and quantitation of 3 independent experiments are shown. Single en dashes represent untreated control. b, Macrophages with Drp1 knockdown were cocultured with Raji cells and Rituximab for 4 hr at a 1:2 ratio. Afterwards, macrophages were sorted by CD14 magnetic beads. Western blots of phosphorylated and total WIP of macrophages and quantitation of 3 independent experiments are shown. c, The quantitation of fluorescence intensities along the dashed lines in Fig. 8e is shown. d, Schematics highlighting the primary findings of this study: WASP forms concentrated liquid-like droplets with WIP via its WH1 domain in the resting state. During efficient phagocytosis, cytosolic calcium increased by mitochondrial fission abrogates phase separation of the complex and enables kinase PKC-θ to phosphorylate WIP, which facilitates cytoskeleton arrangement and phagocytosis. Resistant tumour cells vigorously compete with macrophages (Mϕ) for glutamine by overexpression of GFPT2, which results in depletion of glutamine in the tumour microenvironment that disrupts mitochondrial fission in macrophage. The inhibition of mitochondrial fission blunts cytosolic calcium influx due to mitochondrial calcium sequestration, maintains WASP-WIP phase separation, and denies the access of PKC-θ to compartmentalized WIP in macrophages, leading to tumour resistance to phagocytosis induced by multiple therapeutic antibodies. a, b Mean ± s.d.; n = 3 independent experiments; P values were calculated using One-Way ANOVA with Tukey’s multiple comparisons test.
Supplementary information
Supplementary Information
Supplementary Tables 1–3.
Supplementary Video 1
Phagocytosis of Raji cells by macrophages in the presence of rituximab.
Supplementary Video 2
RL cells and macrophages in the presence of rituximab.
Supplementary Video 3
Raji cells and macrophages in the presence of rituximab.
Supplementary Video 4
Raji cells and macrophages transduced with shGFP in the presence of rituximab.
Supplementary Video 5
Raji cells and macrophages transduced with shDrp1-1 in the presence of rituximab.
Supplementary Video 6
Raji cells and macrophages transduced with shDrp1-2 in the presence of rituximab.
Supplementary Video 7
Time-lapse movie of the WIP and WASP phase separation.
Supplementary Video 8
FRAP of overexpressed mEGFP–WASP puncta.
Supplementary Video 9
FRAP of overexpressed DsRed–WIP puncta.
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Li, J., Ye, Y., Liu, Z. et al. Macrophage mitochondrial fission improves cancer cell phagocytosis induced by therapeutic antibodies and is impaired by glutamine competition. Nat Cancer 3, 453–470 (2022). https://doi.org/10.1038/s43018-022-00354-5
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DOI: https://doi.org/10.1038/s43018-022-00354-5
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