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O-GlcNAcylation promotes pancreatic tumor growth by regulating malate dehydrogenase 1

Abstract

Oncogenic Kras-activated pancreatic ductal adenocarcinoma (PDAC) cells highly rely on an unconventional glutamine catabolic pathway to sustain cell growth. However, little is known about how this pathway is regulated. Here we demonstrate that Kras mutation induces cellular O-linked β-N-acetylglucosamine (O-GlcNAc), a prevalent form of protein glycosylation. Malate dehydrogenase 1 (MDH1), a key enzyme in the glutamine catabolic pathway, is positively regulated by O-GlcNAcylation on serine 189 (S189). Molecular dynamics simulations suggest that S189 glycosylation on monomeric MDH1 enhances the stability of the substrate-binding pocket and strengthens the substrate interactions by serving as a molecular glue. Depletion of O-GlcNAcylation reduces MDH1 activity, impairs glutamine metabolism, sensitizes PDAC cells to oxidative stress, decreases cell proliferation and inhibits tumor growth in nude mice. Furthermore, O-GlcNAcylation levels of MDH1 are elevated in clinical PDAC samples. Our study reveals that O-GlcNAcylation contributes to pancreatic cancer growth by regulating the metabolic activity of MDH1.

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Fig. 1: O-GlcNAcylation regulates Gln metabolism in PDAC cells.
Fig. 2: Key enzymes in the Gln pathway in PDAC are modified by O-GlcNAc.
Fig. 3: S189 O-GlcNAcylation enhances MDH1 activity.
Fig. 4: O-GlcNAcylation of MDH1 regulates Gln metabolism and redox homeostasis.
Fig. 5: O-GlcNAcylation of MDH1 promotes tumor growth and upregulated in pancreatic cancer.

Data availability

The human pancreatic tumor data (Fig. 1c) were derived from the TCGA Research Network (http://cancergenome.nih.gov). The crystal structure of a ternary complex of porcine cytoplasmic malate dehydrogenase, α-ketomalonate and tetrahydro-NAD was obtained from the PDB database (https://www.rcsb.org/structure/5MDH). The crystal structure of hMDH1 is available at https://www.rcsb.org/structure/7RM9. All other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

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Acknowledgements

This work was supported by the National Key R&D Program of China (2021YFF1200404 and 2021YFA1201201 to R.Z., 2017YFA0505002 to W.Q.), the National Science Foundation of China (NSFC, grant nos. 31971212 and 91753125 to W.Yi., U1967217 to R.Z.), the National Science Foundation of Zhejiang Province (LZ21C050001 to W.Yi.), the Mizutani Foundation for Glycoscience (210036 to W.Yi.), National Independent Innovation Demonstration Zone Shanghai Zhangjiang Major Projects (ZJZX2020014), Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study (SN-ZJU-SIAS-003), Fundamental Research Funds for Central Universities (226-2022-00043, 226-2022-00192 and K20220228) and BirenTech Research (BR-ZJU-SIAS-001). Y.W. acknowledges the access to computational resources from the Information Technology Center and State Key Lab of Computer-Aided Design (CAD) & Computer Graphics (CG) of Zhejiang University. R.Z. also acknowledges financial support from the W. M. Keck Foundation (grant award 2019–2022).

Author information

Authors and Affiliations

Authors

Contributions

W.Yi. conceived the project; W.Yi. designed the cell biology and biochemistry experiments; R.Z. designed the molecular dynamics simulation experiments; Q.Z., D.G., W. Yang and Z.L. performed the cell biology, biochemistry and xenograft experiments; H.Z. and Y.W. performed the molecular dynamics simulation experiments; Z.F. and W.Q. performed the mass spectrometry analysis; L.W., Y.W., W.Q., R.Z. and W.Yi. analyzed the data; L.W. and J.Z. provided tumor tissue samples; Q.Z. and W.Yi. wrote the paper with input from all authors.

Corresponding authors

Correspondence to Ruhong Zhou or Wen Yi.

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Nature Chemical Biology thanks Matthew Pratt and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 OGT depletion inhibits cell proliferation in PDAC cells.

a, Quantification and statistical analysis of OGT and O-GlcNAcylation levels from 24 pairs of human pancreatic tumor (T) and adjacent peritumoral (N) tissue samples. b, Immunoblotting analysis of OGT and O-GlcNAcylation levels in pancreas ductal epithelial cells (HPDE) and PDAC cells (AsPC-1, HPAC, HPAF-II, 8988 T, SW1990 and PANC1). c and d, Immunoblotting of OGT levels in HPDE and PDAC cells stably transfected with scramble or shOGT. e, Relative cell proliferation rate of PDAC cells stably transfected with scramble or shOGT (n = 3 independent assays). Immunoblots are representative of three independent experiments. Error bars of data in e denote the means ± SD. Statistical analyses were performed by two-tailed Student’s t-test.

Source data

Extended Data Fig. 2 Kras activated mutation promotes OGT expression in PDAC cells.

a, Immunoblotting of GFPT, OGT and O-GlcNAc levels in HPDE cells upon ectopic expression of KrasG12D. b, Immunoblotting of O-GlcNAc levels in SW1990 cells upon depletion of Kras. c, Immunoblotting of O-GlcNAc levels upon OGT depletion in HPDE cells expressing KrasG12D. d, Cell proliferation rate of HPDE cells expressing KrasG12D upon OGT depletion (n = 3 independent assays). Immunoblots are representative of three independent experiments. Error bars of data in d denote the means ± SD. Statistical analyses were performed by two-tailed Student’s t-test.

Source data

Extended Data Fig. 3 Analysis of relative abundance of metabolites upon OGT depletion.

a–b, Relative abundance of metabolites in the TCA cycle (a) and the serine metabolism (b) in SW1990 cells stably transfected with scramble or shOGT (n = 3 independent assays). c–e, Relative abundance of metabolites in the Gln metabolism (c), the TCA cycle (d) and the serine metabolism (e) in HPDE cells stably transfected with scramble or shOGT (n = 3 independent assays). Error bars of data in a, b, c, d and e denote the means ± SD. Statistical analyses were performed by two-tailed Student’s t-test.

Source data

Extended Data Fig. 4 Key enzymes in the Gln metabolism are O-GlcNAc modified.

a–c, Analysis of O-GlcNAcylation levels of GOT1 (a), MDH1 (b) and ME1 (c) in the presence of TMG (100 μM) or OGT overexpression in HEK293T cells. d–f, Analysis of O-GlcNAcylation levels of GOT1 (d), MDH1 (e) and ME1 (f) in the presence of OSMI-4 (20 μM) in HEK293T cells. Immunoblots are representative of three independent experiments.

Source data

Extended Data Fig. 5 Molecular dynamics simulations of substrate-bound MDH1.

a, The definition of NADH-binding site. Eight residues, shown in stick and colored in magenta, around NADH were selected to represent the NADH’s binding site. b, Time-dependent COM distance between NADH and binding site of the nonglycosylated (left) and glycosylated S189 forms (right) in pMDH1. The thin lines represent the trajectories of each simulation while the thick line represents the average. c, The distribution of COM distance between NADH and its binding site. d, The definition of MAK-binding site. Five residues, shown in stick and colored in magenta, around MAK were selected to represent the MAK’s binding site. e, Time-dependent COM distance between MAK and binding site of the nonglycosylated (left) and glycosylated S189 forms (right). f, The distribution of COM distance between MAK and its binding site.

Source data

Extended Data Fig. 6 Glycosylation stabilizes substrate-enzyme interactions.

a, The residue root-mean-square fluctuation (RMSF) of pMDH1. The difference is the RMSF value of nonglycosylated simulations minus the RMSF value of the glycosylated simulations. A positive value indicates a residue is more rigid with S189 glycosylation while a negative value indicates a residue is more flexible. b, Comparison of the interaction network (contact probability) between MDH1 with NADH (left), and MDH1 with MAK (right) of WT (top) and MDH1 with glycosylated S189 (bottom). Only the residues with a probability of more than 10% are shown. c, The overall average contact probabilities between NADH and MAK of WT (left) MDH1 with glycosylated S189 (right). d, The snapshot of the interaction network between substrates and glycosylated S189. e, The contact probability between GlcNAc and all residues of MDH1, and a schematic diagram to show the major contact residues. f, Relative enzymatic activity of WT or the triplet mutant of MDH1 in the presence or absence of OGT overexpression (n = 5 independent assays). Error bars of data in f denote the means ± SD. Statistical analyses were performed by two-tailed Student’s t-test.

Source data

Extended Data Fig. 7 MDH1 S189 glycosylation promotes PDAC cell proliferation.

a, Immunoblotting of MDH1 expression in HPDE and PDAC cells upon stably transfection with scramble or shMDH1. b, Relative cell proliferation rate of HPDE and PDAC cells upon stably transfection with scramble or shMDH1 (n = 3 independent assays). c, Immunoblotting of MDH1 in PANC-1 cells stably expressing scramble shRNA, shMDH1, shRNA-resistant WT or S189A MDH1. d and e, Cell proliferation rate of SW1990 (c) and PANC-1 cells (d) stably expressing scramble shRNA, shMDH1, shRNA-resistant WT or S189A MDH1 (n = 5 independent assays). f and g, Relative clone numbers generated from SW1990 (f) and PANC-1 cells (g) stably expressing scramble shRNA, shMDH1, shRNA-resistant WT or S189A MDH1 (n = 5 independent assays). h and i, Cell proliferation rate of SW1990 (h) and PANC-1 cells (i) reconstituted with WT or S189A MDH1 upon OGT overexpression (n = 5 independent assays). Immunoblots are representative of three independent experiments. Error bars of data in b, d, e, f, g, h and i denote the means ± SD. Statistical analyses were performed by two-tailed Student’s t-test.

Source data

Extended Data Fig. 8 MDH1 glycosylation promotes PDAC cell proliferation in part through redox regulation.

a, Relative cell proliferation of SW1990 cells reconstituted with WT or S189A MDH1, in the presence or absence of ME1 depletion and malate (n = 5 independent assays). b, Immunoblotting of SW1990 cells reconstituted with WT or S189A MDH1, in the presence or absence of ME1 depletion and malate. c, Relative cell number of SW1990 cells reconstituted with WT or S189A MDH1 after treatment with 5 mM NAC, 5 mM GSH or 4 mM cell-permeable malate for 24 h (n = 5 independent assays). d, Cell survival rate of SW1990 cells reconstituted with WT or S189A MDH1 after treatment with indicated concentrations of H2O2 for 1 h (n = 5 independent assays). e, Relative cell number of SW1990 cells reconstituted with WT or S189A MDH1 after incubation with 4 mM cell-permeable malate for 12 h, followed by treatment with 0.3 mM H2O2 for 16 h (n = 5 independent assays). Error bars of data in a, c, d and e denote the means ± SD. Statistical analyses were performed by two-tailed Student’s t-test.

Source data

Supplementary information

Supplementary Information

Supplementary Tables 1–4, Supplementary Figs. 1–16 and unmodified western blots of supplementary figures.

Reporting Summary

Supplementary Video 1

Molecular dynamics simulation of glycosylated MDH1.

Supplementary Video 2

Molecular dynamics simulation of nonglycosylated MDH1.

Supplementary Data 1

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Zhu, Q., Zhou, H., Wu, L. et al. O-GlcNAcylation promotes pancreatic tumor growth by regulating malate dehydrogenase 1. Nat Chem Biol (2022). https://doi.org/10.1038/s41589-022-01085-5

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