Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Mitochondrial NADP+ is essential for proline biosynthesis during cell growth

Nature Metabolism volume 3, pages 571–585 (2021)Cite this article

Subjects

Abstract

Nicotinamide adenine dinucleotide phosphate (NADP+) is vital to produce NADPH, a principal supplier of reducing power for biosynthesis of macromolecules and protection against oxidative stress. NADPH exists in separate pools, in both the cytosol and mitochondria; however, the cellular functions of mitochondrial NADPH are incompletely described. Here, we find that decreasing mitochondrial NADP(H) levels through depletion of NAD kinase 2 (NADK2), an enzyme responsible for production of mitochondrial NADP+, renders cells uniquely proline auxotrophic. Cells with NADK2 deletion fail to synthesize proline, due to mitochondrial NADPH deficiency. We uncover the requirement of mitochondrial NADPH and NADK2 activity for the generation of the pyrroline-5-carboxylate metabolite intermediate as the bottleneck step in the proline biosynthesis pathway. Notably, after NADK2 deletion, proline is required to support nucleotide and protein synthesis, making proline essential for the growth and proliferation of NADK2-deficient cells. Thus, we highlight proline auxotrophy in mammalian cells and discover that mitochondrial NADPH is essential to enable proline biosynthesis.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Loss of NADK2 renders cells dependent on proline for cell proliferation.
Fig. 2: NADK2 is required for anchorage-independent cell growth.
Fig. 3: NADK2 is required for the maintenance of proline levels.
Fig. 4: In vivo infusions with 13C isotopes reveal that proline synthesis occurs mainly in the pancreas.
Fig. 5: NADK2 activity is required for glutamine-dependent proline biosynthesis.
Fig. 6: Proline levels do not alter the NADK2-dependent regulation of mitochondrial respiration.
Fig. 7: Proline becomes limiting for nucleotide synthesis in NADK2-deficient cells.
Fig. 8: NADK2 loss inhibits protein synthesis and triggers activation of the GCN2–eIF2α–ATF4 pathway.

Similar content being viewed by others

Data availability

Supplementary Information including Supplementary Tables 1–3 and a figure exemplifying the gating strategy for Extended Data Fig. 6 are provided with this paper. All other data are available from the corresponding author upon request. Source data are provided with this paper.

References

  1. DeBerardinis, R. J. & Chandel, N. S. Fundamentals of cancer metabolism. Sci. Adv. 2, e1600200 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Pollak, N., Dölle, C. & Ziegler, M. The power to reduce: pyridine nucleotides–small molecules with a multitude of functions. Biochem. J. 402, 205–218 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Hosios, A. M. & Vander Heiden, M. G. The redox requirements of proliferating mammalian cells. J. Biol. Chem. 293, 7490–7498 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Hoxhaj, G. & Manning, B. D. The PI3K–AKT network at the interface of oncogenic signalling and cancer metabolism. Nat. Rev. Cancer 20, 74–88 (2020).

    Article  CAS  PubMed  Google Scholar 

  5. Xiao, W., Wang, R.-S., Handy, D. E. & Loscalzo, J. NAD(H) and NADP(H) redox couples and cellular energy metabolism. Antioxid. Redox Signal. 28, 251–272 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Fan, J. et al. Quantitative flux analysis reveals folate-dependent NADPH production. Nature 510, 298–302 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Lewis, C. A. et al. Tracing compartmentalized NADPH metabolism in the cytosol and mitochondria of mammalian cells. Mol. Cell 55, 253–263 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Schieber, M. & Chandel, N. S. ROS function in redox signaling and oxidative stress. Curr. Biol. 24, R453–R462 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Goodman, R. P., Calvo, S. E. & Mootha, V. K. Spatiotemporal compartmentalization of hepatic NADH and NADPH metabolism. J. Biol. Chem. 293, 7508–7516 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Nilsson, R. et al. Metabolic enzyme expression highlights a key role for MTHFD2 and the mitochondrial folate pathway in cancer. Nat. Commun. 5, 3128 (2014).

    Article  PubMed  Google Scholar 

  11. Locasale, J. W. Serine, glycine and one-carbon units: cancer metabolism in full circle. Nat. Rev. Cancer 13, 572–583 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Patra, K. C. & Hay, N. The pentose phosphate pathway and cancer. Trends Biochem. Sci. 39, 347–354 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Piskounova, E. et al. Oxidative stress inhibits distant metastasis by human melanoma cells. Nature 527, 186–191 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ju, H.-Q., Lin, J.-F., Tian, T., Xie, D. & Xu, R.-H. NADPH homeostasis in cancer: functions, mechanisms and therapeutic implications. Signal Transduct. Target. Ther. 5, 231 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Agledal, L., Niere, M. & Ziegler, M. The phosphate makes a difference: cellular functions of NADP. Redox Rep. 15, 2–10 (2010).

    Article  CAS  PubMed  Google Scholar 

  16. Hoxhaj, G. et al. Direct stimulation of NADP+ synthesis through Akt-mediated phosphorylation of NAD kinase. Science 363, 1088–1092 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Ohashi, K., Kawai, S. & Murata, K. Identification and characterization of a human mitochondrial NAD kinase. Nat. Commun. 3, 1248 (2012).

    Article  PubMed  Google Scholar 

  18. Pomerantz, D. J. et al. Clinical heterogeneity of mitochondrial NAD kinase deficiency caused by a NADK2 start loss variant. Am. J. Med. Genet. A 176, 692–698 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zhang, K. et al. Deficiency of the mitochondrial NAD kinase causes stress-induced hepatic steatosis in mice. Gastroenterology 154, 224–237 (2018).

    Article  CAS  PubMed  Google Scholar 

  20. Cantor, J. R. et al. Physiologic medium rewires cellular metabolism and reveals uric acid as an endogenous inhibitor of UMP synthase. Cell 169, 258–272 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Bayraktar, E. C. et al. MITO-Tag mice enable rapid isolation and multimodal profiling of mitochondria from specific cell types in vivo. Proc. Natl Acad. Sci. USA 116, 303–312 (2019).

    Article  CAS  PubMed  Google Scholar 

  22. Tanner, J. J., Fendt, S.-M. & Becker, D. F. The proline cycle as a potential cancer therapy target. Biochemistry 57, 3433–3444 (2018).

    Article  CAS  PubMed  Google Scholar 

  23. Poncet-Montange, G., Assairi, L., Arold, S., Pochet, S. & Labesse, G. NAD kinases use substrate-assisted catalysis for specific recognition of NAD. J. Biol. Chem. 282, 33925–33934 (2007).

    Article  CAS  PubMed  Google Scholar 

  24. Rydström, J. Mitochondrial NADPH, transhydrogenase and disease. Biochim. Biophys. Acta 1757, 721–726 (2006).

    Article  PubMed  Google Scholar 

  25. Arruabarrena-Aristorena, A., Zabala-Letona, A. & Carracedo, A. Oil for the cancer engine: the cross-talk between oncogenic signaling and polyamine metabolism. Sci. Adv. 4, eaar2606 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Elia, I. et al. Proline metabolism supports metastasis formation and could be inhibited to selectively target metastasizing cancer cells. Nat. Commun. 8, 15267 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Harris, I. S. & DeNicola, G. M. The complex interplay between antioxidants and ROS in cancer. Trends Cell Biol. 30, 440–451 (2020).

    Article  CAS  PubMed  Google Scholar 

  28. Chen, L., Ducker, G. S., Lu, W., Teng, X. & Rabinowitz, J. D. An LC–MS chemical derivatization method for the measurement of five different one-carbon states of cellular tetrahydrofolate. Anal. Bioanal. Chem. 409, 5955–5964 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Ben-Sahra, I., Hoxhaj, G., Ricoult, S. J. H., Asara, J. M. & Manning, B. D. mTORC1 induces purine synthesis through control of the mitochondrial tetrahydrofolate cycle. Science 351, 728–733 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ben-Sahra, I., Howell, J. J., Asara, J. M. & Manning, B. D. Stimulation of de novo pyrimidine synthesis by growth signaling through mTOR and S6K1. Science 339, 1323–1328 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Donnelly, N., Gorman, A. M., Gupta, S. & Samali, A. The eIF2α kinases: their structures and functions. Cell. Mol. Life Sci. 70, 3493–3511 (2013).

    Article  CAS  PubMed  Google Scholar 

  32. Wolfson, R. L. & Sabatini, D. M. The dawn of the age of amino acid sensors for the mTORC1 pathway. Cell Metab. 26, 301–309 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Bradshaw, P. C. Cytoplasmic and mitochondrial NADPH-coupled redox systems in the regulation of aging. Nutrients 11, 504 (2019).

  34. Houten, S. M. et al. Mitochondrial NADP(H) deficiency due to a mutation in NADK2 causes dienoyl-CoA reductase deficiency with hyperlysinemia. Hum. Mol. Genet. 23, 5009–5016 (2014).

    Article  CAS  PubMed  Google Scholar 

  35. Sullivan, L. B. et al. Supporting aspartate biosynthesis is an essential function of respiration in proliferating cells. Cell 162, 552–563 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Birsoy, K. et al. An essential role of the mitochondrial electron transport chain in cell proliferation is to enable aspartate synthesis. Cell 162, 540–551 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Brandriss, M. C. Isolation and preliminary characterization of Saccharomyces cerevisiae proline auxotrophs. J. Bacteriol. 138, 816–822 (1979).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. De Ingeniis, J. et al. Functional specialization in proline biosynthesis of melanoma. PLoS ONE 7, e45190 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Allfrey, V., Daly, M. M. & Mirsky, A. E. Synthesis of protein in the pancreas. The role of ribonucleoprotein in protein synthesis. J. Gen. Physiol. 37, 157–175 (1953).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Case, R. M. Synthesis, intracellular transport and discharge of exportable proteins in the pancreatic acinar cell and other cells. Biol. Rev. Camb. Philos. Soc. 53, 211–354 (1978).

    Article  CAS  PubMed  Google Scholar 

  41. Logsdon, C. D. & Ji, B. The role of protein synthesis and digestive enzymes in acinar cell injury. Nat. Rev. Gastroenterol. Hepatol. 10, 362–370 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Ye, J. et al. The GCN2–ATF4 pathway is critical for tumour cell survival and proliferation in response to nutrient deprivation. EMBO J. 29, 2082–2096 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Tameire, F. et al. ATF4 couples MYC-dependent translational activity to bioenergetic demands during tumour progression. Nat. Cell Biol. 21, 889–899 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Marin-Valencia, I. et al. Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse human glioblastomas in the mouse brain in vivo. Cell Metab. 15, 827–837 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Hui, S. et al. Glucose feeds the TCA cycle via circulating lactate. Nature 551, 115–118 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Chen, W. W., Freinkman, E., Wang, T., Birsoy, K. & Sabatini, D. M. Absolute quantification of matrix metabolites reveals the dynamics of mitochondrial metabolism. Cell 166, 1324–1337 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Vinci, M. et al. Advances in establishment and analysis of three-dimensional tumor spheroid-based functional assays for target validation and drug evaluation. BMC Biol. 10, 29 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Chen, G. & Deng, X. Cell synchronization by double thymidine block. Bio. Protoc. 8, e2994 (2018).

  49. Chen, W. W., Freinkman, E. & Sabatini, D. M. Rapid immunopurification of mitochondria for metabolite profiling and absolute quantification of matrix metabolites. Nat. Protoc. 12, 2215–2231 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank C. Llamas and P. Mishra for guidance with Seahorse assays; C. Yang for assistance with xenograft experiments; L. Zacharias, M. Martin and T. Mathews for mass spectrometry assistance; and N. Loof, T. Shih and the Moody Foundation Flow Cytometry Facility for flow cytometry assistance. The research was supported by the Cancer Prevention and Research Institute of Texas (CPRIT; RR190087). G.H. is a CPRIT Scholar. R.J.D. is an HHMI Program investigator, the Robert L. Moody, Sr. Faculty Scholar at University of Texas Southwestern Medical Center and Joel B. Steinberg, M.D. Chair in Paediatrics. J.A.P. III is supported in part by Vanderbilt Center for Undiagnosed Diseases (VCUD; 5U01HG007674).

Author information

Author notes

  1. These authors contributed equally: Diem H. Tran, Rushendhiran Kesavan.

Authors and Affiliations

  1. Children’s Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Diem H. Tran, Rushendhiran Kesavan, Halie Rion, Mona Hoseini Soflaee, Ashley Solmonson, Divya Bezwada, Hieu S. Vu, Feng Cai, Ralph J. DeBerardinis & Gerta Hoxhaj

  2. Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA

    John A. Phillips III

  3. Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Ralph J. DeBerardinis

Authors
  1. Diem H. Tran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rushendhiran Kesavan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Halie Rion
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mona Hoseini Soflaee
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ashley Solmonson
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Divya Bezwada
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hieu S. Vu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Feng Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. John A. Phillips III
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ralph J. DeBerardinis
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Gerta Hoxhaj
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

D.H.T. and R.K. performed and analysed experiments. H.R. performed immunoblots, cell proliferation assays and analysed data. M.H.S., D.B., H.S.V. and F.C. performed LC–MS/MS analyses. A.S. performed in vivo infusion experiments. J.A.P. III provided patient-derived fibroblasts. R.J.D. provided intellectual contribution, discussed ideas and data and reviewed the manuscript. G.H. conceived and directed the project, designed the experiments, analysed the data and wrote the manuscript. G.H. and D.H.T. prepared the manuscript.

Corresponding author

Correspondence to Gerta Hoxhaj.

Ethics declarations

Competing interests

R.J.D. is an advisor for Agios Pharmaceuticals and Vida Ventures. All other authors declare no competing interests.

Additional information

Peer review information Nature Metabolism thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: George Caputa.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 NADK2-deficient cells require proline for cell proliferation.

a, A549 and K562 ∆NADK2 cells stably reconstituted with either empty vector (Vec) or NADK2 were injected subcutaneously into athymic nude mice. Tumour growth curves are shown as average of all tumours from the data shown in Fig. 1c,d. Data are presented as mean ± SEM from 7 tumors (A549) or 3 or 4 tumours (K562). *P < 0.05 for pairwise comparisons calculated using a one-sided Student’s t-test. b, Immunoblots and cell proliferation of wild-type or single cell-derived knockout cells of NADK in HEK-293E cells grown in DMEM with 10% serum. Proliferation rate was assessed 72 h post-plating and normalized to Day 0. c, Relative proliferation rate was assessed in three consecutive days from wild-type or isogenic ∆NADK2 cells stably expressing either empty vector, NADK2 or NADK. Immunoblots for NADK, NADK2 and β-actin are shown. d, Relative proliferation rate as in (b) from isogenic ∆NADK2 HeLa cells stably expressing either empty vector or NADK2. Cells were grown in 10% dialyzed serum or supplemented with oleate (0.1 mM). e, Relative proliferation rate as in (b) from wild-type or ∆NADK2 HeLa cells. Cells were grown in 10% dialyzed serum for 72 hours or supplemented with NAC (5 mM), nucleosides (inosine 0.1 mg/ml uridine, 0.1 mg/ml), non-essential amino acid (NEAA) mixture (1X), pyruvate (10 mM) or aspartate (10 mM). f, Relative proliferation rate as in (b) from isogenic ∆NADK2 K562 cells stably expressing either empty vector or NADK2 and supplemented with the indicated individual non-essential amino acids at concentration present in human plasma-like medium (HPLM). g, Relative proliferation rate as in (b) from isogenic ∆NADK2 HEK-293E cells stably expressing either empty vector or NADK2, and supplemented with the indicated individual non-essential amino acids at 10X concentration present in human plasma-like medium (HPLM). Related to Fig. 1f. h, Relative proliferation rate as in (b) from HCT116 cells with stable shRNA-mediated knockdown of NADK2 grown in the presence or absence of proline (2 mM). i, Normalized peak areas of mitochondrial NAD + (M + 4), NADP + (M + 4) and NADPH (M + 4) from labeling with 13C3-15N-nicotinamide are shown. ∆NADK2 HEK293E cells stably expressing HA-Mito were stably reconstituted with either empty vector or NADK2. HEK-293E cells expressing (Myc-Mito) were used as a negative control (1-Ctrl). HA-tagged mitochondria were isolated from equal amount of protein for each condition and metabolites were analyzed by targeted LC-MS/MS. Data are presented as the mean ± SD (b-i) from n = 4 of biologically independent samples for (b), n = 3 for (c,g,h,i), n = 12 for (d), n = 3–9 for (e), n = 3–5 for (f) and are representative of at least two independent experiments. *P < 0.05, **P < 0.01, ***P < 0.001 for comparisons calculated using a two-sided Student’s t-test for (b) and with one-way ANOVA test and Tukey’s post-hoc test for (c-i).

Source data

Extended Data Fig. 2 NADK2-deficient tumors display reduced proline levels.

a,b, Immunoblots and peak areas of proline and other amino acid are shown from A549 (a) and K562 (b) xenograft tumours that are NADK2-deficient (blue) or that express NADK2 from tumors in Fig. 1c,d. Each condition represents four tumors, and levels of NADK2 are assessed by immunoblotting and shown below the graphs. Data are presented as the mean ± SD from n = 4 of biologically independent samples. **P < 0.01 for comparisons was calculated using a two-sided Student’s t-test.

Source data

Extended Data Fig. 3 Glutamine-dependent proline synthesis is dependent on NADK2 (Data supporting Fig. 5).

a, Schematic of 13C5-glutamine labelling. b, Fractional abundance (%) of glutamine (M + 5) from experiment presented in Fig. 5b. c, Fractional abundance (%) of glutamine (M + 5) from experiment presented in Fig. 5c. d, Fractional abundance (%) of glutamine (M + 5), glutamate (M + 5) and proline (M + 5) from isogenic ∆NADK2 A549 cells stably expressing either empty vector (-) or NADK2 cDNA and labeled for 3 hours with 13C5-glutamine. Wildtype counterparts of each cell line are shown as controls. e, Fractional abundance (%) of glutamine (M + 5), glutamate (M + 5) and proline (M + 5) from isogenic ∆NADK2 K562 cells stably expressing either empty vector (-) or NADK2 cDNA and labeled for 3 hours with 13C5-glutamine. Wildtype counterparts of each cell line are shown as controls. f, Immunoblots from HCT116 cells stably expressing a control shRNA (Ctrl), NADK2 shRNA, or two shRNAs against P5CS. g, Fractional abundance (%) of glutamine (M + 5), glutamate (M + 5) and proline (M + 5) from HCT116 cells stably expressing a control shRNA (Ctrl) or two shRNAs against P5CS. Immunoblots are shown in (f). h, Fractional abundance (%) of glutamine (M + 5), glutamate (M + 5) and proline (M + 5) from HCT116 cells stably expressing a control shRNA (Ctrl) or an shRNA against NADK2. Immunoblots are shown in (f). Data are presented as the mean ± SD from n = 4 of biologically independent samples for (b-e) and n = 3 or 4 for (g,h) and are representative of at least two independent experiments. *P < 0.05, **P < 0.01, ***P < 0.001 for comparisons was calculated using a two-sided Student’s t-test for (h) and with one-way ANOVA test and Tukey’s post-hoc test for (b-e,g).

Source data

Extended Data Fig. 4 NADK2 regulated proline synthesis for cell growth. Data supporting Fig. 5.

a, Immunoblots of NADK2 and proline biosynthesis genes shown for wild-type or isogenic ∆NADK2 HEK293E cells stably expressing either empty vector or NADK2 grown in DMEM supplemented with 10% serum in the presence or absence of proline (0.2 mM). Data are representative of at least two independent experiments. b, Immunoblots as in (a) for wild-type or isogenic ∆NADK2 A549 cells stably expressing either empty vector or NADK2 grown in DMEM supplemented with 10% serum in the presence or absence of proline (0.2 mM). Data are representative of at least two independent experiments. c, Immunoblot and fractional abundance (%) of glutamine (M + 5) from experiment presented in Fig. 2d. d, Schematic showing the sequence conservation of D161 among NADK2 orthologs across different species. e, Fractional abundance (%) of glutamine (M + 5) from experiment presented in Fig. 5e. f, Fractional abundance (%) of glutamine (M + 5) from experiment presented in Fig. 5f. g, Relative proliferation rate as in (Fig. 5g), but from isogenic ∆NADK2 HEK293E cells stably expressing either empty vector or NADK2. Cells were grown in 10% dialyzed serum for 72 hours or supplemented with ornithine (0.5 mM), dimethyl α-ketoglutarate (0.25 mM), or with ornithine (0.5 mM) and dimethyl α-ketoglutarate (0.25 mM). h, Normalized peak areas of ornithine (M + 7) from 3 hours labeling with 13C5-15N2-ornithine are shown from experiment presented in Fig. 5i. Data are presented as the mean ± SD from n = 4 of biologically independent samples for (c), n = 3 for (e-h) and are representative of at least two independent experiments. *P < 0.05, **P < 0.01 for comparisons calculated using a two-sided Student’s t-test for (c,h) and with one-way ANOVA test and Tukey’s post-hoc test for (e-g).

Source data

Extended Data Fig. 5 Proline does not affect the NADK2-dependent regulation of ROS levels.

a, Relative proliferation in ∆NADK2 HeLa cells cultured in DMEM with 10% dialyzed serum for 72 hours in the presence or absence of proline (2 mM) or PRODH inhibitor L-THFA (5 mM). Data is normalized to cells grown in the presence of proline. b, Relative proliferation as in (a) in HeLa ∆NADK2 cells reconstituted with NADK2. c, Schematic of putative functions of proline axis mediating ATP generation or defense against ROS. d,e, Mean fluorescence intensity for CellRox Green staining (ROS) in ∆NADK2 HeLa (d) or HEK-293E (e) cells stably expressing either empty vector or NADK2 cultured in 10% dialyzed serum in the presence or absence of proline (2 mM). f,g, GSH, GSSG and GSH/GSSG ratio quantified from ∆NADK2 HeLa (d) or HEK-293E (e) cells cultured in 10% dialyzed serum in the presence or absence of proline (2 mM). h,i, Extracellular Acidification Rate (ECAR) for ∆NADK2 HeLa (e) or HEK-293E (f) cells stably expressing either empty vector or NADK2 cultured in the presence or absence of proline (2 mM). Wildtype counterparts are shown (Supporting Fig. 6). Data are presented as the mean ± SD from n = 3 of biologically independent samples for (a,b), n = 4 for (d,e,f,g), n = 11 or 12 for (h), and n = 9–11 for (i), and are representative of at least two independent experiments. **P < 0.01, ***P < 0.001 for comparisons calculated using a two-sided Student’s t-test for (f,g) and with one-way ANOVA test and Tukey’s post-hoc test for (a,b,d,e,h,i).

Source data

Extended Data Fig. 6 NADK2 loss results in impairment of cell cycle progression.

a, Cell cycle profiles (histograms) at indicated time points after release from G1 phase arrest induced by double-thymidine block, from ∆NADK2 HeLa cells stably expressing either empty vector or WT NADK2, cultured in the presence or absence of proline (0.2 mM) as indicated. Data are analyzed using the FlowJo’s Watson Pragmatic cell cycle platform algorithm and are representative of at least two independent experiments performed in duplicates or tripicates. b, Cell cycle profiles from asynchronous ∆NADK2 HeLa cells stably expressing either empty vector or WT NADK2, cultured in the presence or absence of proline (0.2 mM) as indicated. Biological duplicates are shown. Data are analyzed using the FlowJo’s Watson Pragmatic cell cycle platform algorithm and are representative of at least two independent experiments performed in duplicates or triplicates.

Source data

Extended Data Fig. 7 NADK2 regulates nucleotide synthesis (Data supporting Fig. 7).

a, Schematic of 13C6-glucose labelling. b, Schematic of 3-13C-serine labeling. c, Fractional abundance (%) of Serine (M + 1), 10-Formyl-THF (M + 1), and dTMP (M + 1) from isogenic ∆NADK2 HEK-293E cells stably expressing either empty vector or NADK2 cDNA and labeled for 6 hours with 3-13C-serine. d, Relative incorporation of radiolabel from 14C-glycine, 14C-aspartate, or 3H-uridine (6 hours labelling) from isogenic ∆NADK2 HEK-293E cells stably expressing either empty vector (-) or NADK2 cDNA grown in the presence or absence of proline (0.2 mM). e, Relative incorporation of radiolabel from 3H-uridine (6 hours labelling) from isogenic ∆NADK2 HeLa, or K562 cells stably expressing either empty vector or NADK2 cDNA grown in the presence or absence of proline (0.2 mM). Performed in parallel with experiment shown in Fig. 7c (HeLa) and Fig. 7d (K562). Data are presented as the mean ± SD from n = 3–4 of biologically independent samples (c,d,e) and are representative of at least two independent experiments. **P < 0.01, ***P < 0.001 for comparisons calculated using a two-sided Student’s t-test for (c) and with one-way ANOVA test and Tukey’s post-hoc test for (d,e). f, Immunoblots of pentose pathway enzymes (TKT, TALDO, PGD, G6PD) and nucleotide biosynthesis genes (PPAT, GART) shown for isogenic ΔNADK2 HeLa, K562 or HEK-293E cells stably expressing either empty vector or NADK2, grown in DMEM supplemented with 10% serum in the presence or absence of proline (0.2 mM) for 48 hours. Data are representative of two independent experiments.

Source data

Extended Data Fig. 8 Proline availability regulates transcript levels of multiple nucleotide biosynthesis genes. (Data supporting Fig. 7).

a,b, Transcript levels are shown for the indicated nucleotide biosynthesis genes from isogenic ΔNADK2 HeLa (a), or K562 (b) cells stably expressing either empty vector or NADK2 grown in DMEM supplemented with 10% serum in the presence or absence of proline (0.2 mM). Data are presented as the mean ± SEM from =3 of biologically independent samples that were each measured in technical triplicates. *P < 0.05, **P < 0.01 for comparisons calculated using one-way ANOVA test and Tukey’s post-hoc test.

Source data

Supplementary information

Supplementary Information

Supplementary Tables 1–3 and gating strategy for Extended Data Fig. 6

Reporting Summary

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 1

Unprocessed western blots.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 5

Unprocessed western blots.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 7

Statistical source data.

Source Data Fig. 7

Unprocessed western blots.

Source Data Fig. 8

Statistical source data.

Source Data Fig. 8

Unprocessed western blots.

Source Data Extended Data Fig. 1

Statistical source data.

Source Extended Data Fig. 1

Unprocessed western blots.

Source Data Extended Data Fig. 2

Statistical source data.

Source Extended Data Fig. 2

Unprocessed western blots.

Source Data Extended Data Fig. 3

Statistical source data.

Source Extended Data Fig. 3

Unprocessed western blots.

Source Data Extended Data Fig. 4

Statistical source data.

Source Extended Data Fig. 4

Unprocessed western blots.

Source Data Extended Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 7

Statistical source data.

Source Extended Data Fig. 7

Unprocessed western blots.

Source Data Extended Data Fig. 8

Statistical source data.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tran, D.H., Kesavan, R., Rion, H. et al. Mitochondrial NADP+ is essential for proline biosynthesis during cell growth. Nat Metab 3, 571–585 (2021). https://doi.org/10.1038/s42255-021-00374-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s42255-021-00374-y

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer