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A proton relay enhances H2O2 sensitivity of GAPDH to facilitate metabolic adaptation

Abstract

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is sensitive to reversible oxidative inactivation by hydrogen peroxide (H2O2). Here we show that H2O2 reactivity of the active site thiolate (C152) is catalyzed by a previously unrecognized mechanism based on a dedicated proton relay promoting leaving group departure. Disruption of the peroxidatic reaction mechanism does not affect the glycolytic activity of GAPDH. Therefore, specific and separate mechanisms mediate the reactivity of the same thiolate nucleophile toward H2O2 and glyceraldehyde 3-phosphate, respectively. The generation of mutants in which the glycolytic and peroxidatic activities of GAPDH are comprehensively uncoupled allowed for a direct assessment of the physiological relevance of GAPDH H2O2 sensitivity. Using yeast strains in which wild-type GAPDH was replaced with H2O2-insensitive mutants retaining full glycolytic activity, we demonstrate that H2O2 sensitivity of GAPDH is a key component of the cellular adaptive response to increased H2O2 levels.

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Figure 1: C156 is dispensable for glycolysis, yet essential for efficient C152 oxidation.
Figure 2: Lack of C156 impairs S-glutathionylation of C152.
Figure 3: Computational chemistry suggests a mechanism for C152 oxidation by H2O2.
Figure 4: Site-directed mutagenesis supports the proton-shuttle mechanism.
Figure 5: GAPDH oxidation sensitivity contributes to cellular oxidative stress resistance.
Figure 6: A compensatory mutation restores oxidation sensitivity in the C156S mutant.

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References

  1. Baty, J.W., Hampton, M.B. & Winterbourn, C.C. Proteomic detection of hydrogen peroxide-sensitive thiol proteins in Jurkat cells. Biochem. J. 389, 785–795 (2005).

    Article  CAS  Google Scholar 

  2. Brandes, N., Schmitt, S. & Jakob, U. Thiol-based redox switches in eukaryotic proteins. Antioxid. Redox Signal. 11, 997–1014 (2009).

    Article  CAS  Google Scholar 

  3. Poole, L.B., Karplus, P.A. & Claiborne, A. Protein sulfenic acids in redox signaling. Annu. Rev. Pharmacol. Toxicol. 44, 325–347 (2004).

    Article  CAS  Google Scholar 

  4. Winterbourn, C.C. & Hampton, M.B. Thiol chemistry and specificity in redox signaling. Free Radic. Biol. Med. 45, 549–561 (2008).

    Article  CAS  Google Scholar 

  5. Ferrer-Sueta, G. et al. Factors affecting protein thiol reactivity and specificity in peroxide reduction. Chem. Res. Toxicol. 24, 434–450 (2011).

    Article  CAS  Google Scholar 

  6. Nagy, P. et al. Model for the exceptional reactivity of peroxiredoxins 2 and 3 with hydrogen peroxide: a kinetic and computational study. J. Biol. Chem. 286, 18048–18055 (2011).

    Article  CAS  Google Scholar 

  7. Winterbourn, C.C. Reconciling the chemistry and biology of reactive oxygen species. Nat. Chem. Biol. 4, 278–286 (2008).

    Article  CAS  Google Scholar 

  8. Dickinson, B.C. & Chang, C.J. Chemistry and biology of reactive oxygen species in signaling or stress responses. Nat. Chem. Biol. 7, 504–511 (2011).

    Article  CAS  Google Scholar 

  9. Delaunay, A., Pflieger, D., Barrault, M.B., Vinh, J. & Toledano, M.B. A thiol peroxidase is an H2O2 receptor and redox-transducer in gene activation. Cell 111, 471–481 (2002).

    Article  CAS  Google Scholar 

  10. Sobotta, M.C. et al. Peroxiredoxin-2 and STAT3 form a redox relay for H2O2 signaling. Nat. Chem. Biol. 10.1038/nchembio.1695 (24 November 2014).

  11. Gupta, V. & Carroll, K.S. Sulfenic acid chemistry, detection and cellular lifetime. Biochim. Biophys. Acta 1840, 847–875 (2014).

    Article  CAS  Google Scholar 

  12. Stone, J.R. An assessment of proposed mechanisms for sensing hydrogen peroxide in mammalian systems. Arch. Biochem. Biophys. 422, 119–124 (2004).

    Article  CAS  Google Scholar 

  13. Seidler, N.W. GAPDH: Biological Properties and Diversity Vol. 985 (Springer, 2013).

  14. Little, C. & O'Brien, P.J. Mechanism of peroxide-inactivation of the sulphydryl enzyme glyceraldehyde-3-phosphate dehydrogenase. Eur. J. Biochem. 10, 533–538 (1969).

    Article  CAS  Google Scholar 

  15. Maller, C., Schröder, E. & Eaton, P. Glyceraldehyde 3-phosphate dehydrogenase is unlikely to mediate hydrogen peroxide signaling: studies with a novel anti-dimedone sulfenic acid antibody. Antioxid. Redox Signal. 14, 49–60 (2011).

    Article  CAS  Google Scholar 

  16. Nakajima, H. et al. Glyceraldehyde-3-phosphate dehydrogenase aggregate formation participates in oxidative stress-induced cell death. J. Biol. Chem. 284, 34331–34341 (2009).

    Article  CAS  Google Scholar 

  17. Schuppe-Koistinen, I., Moldéus, P., Bergman, T. & Cotgreave, I.A. S-thiolation of human endothelial cell glyceraldehyde-3-phosphate dehydrogenase after hydrogen peroxide treatment. Eur. J. Biochem. 221, 1033–1037 (1994).

    Article  CAS  Google Scholar 

  18. Jenkins, J.L. & Tanner, J.J. High-resolution structure of human d-glyceraldehyde-3-phosphate dehydrogenase. Acta Crystallogr. D Biol. Crystallogr. 62, 290–301 (2006).

    Article  Google Scholar 

  19. Cowan-Jacob, S.W., Kaufmann, M., Anselmo, A.N., Stark, W. & Grütter, M.G. Structure of rabbit-muscle glyceraldehyde-3-phosphate dehydrogenase. Acta Crystallogr. D Biol. Crystallogr. 59, 2218–2227 (2003).

    Article  Google Scholar 

  20. Reis, M. et al. The catalytic mechanism of glyceraldehyde 3-phosphate dehydrogenase from Trypanosoma cruzi elucidated via the QM/MM approach. Phys. Chem. Chem. Phys. 15, 3772–3785 (2013).

    Article  CAS  Google Scholar 

  21. Yun, M., Park, C.-G., Kim, J.-Y. & Park, H.-W. Structural analysis of glyceraldehyde 3-phosphate dehydrogenase from Escherichia coli: direct evidence of substrate binding and cofactor-induced conformational changes. Biochemistry 39, 10702–10710 (2000).

    Article  CAS  Google Scholar 

  22. Ralser, M. et al. Dynamic rerouting of the carbohydrate flux is key to counteracting oxidative stress. J. Biol. 6, 10 (2007).

    Article  Google Scholar 

  23. Tanner, J.J., Hecht, R.M. & Krause, K.L. Determinants of enzyme thermostability observed in the molecular structure of Thermus aquaticus d-glyceraldehyde-3-phosphate dehydrogenase at 2.5 Å resolution. Biochemistry 35, 2597–2609 (1996).

    Article  CAS  Google Scholar 

  24. Mukherjee, S., Dutta, D., Saha, B. & Das, A.K. Crystal structure of glyceraldehyde-3-phosphate dehydrogenase 1 from methicillin-resistant Staphylococcus aureus MRSA252 provides novel insights into substrate binding and catalytic mechanism. J. Mol. Biol. 401, 949–968 (2010).

    Article  CAS  Google Scholar 

  25. Beutler, E. Red Cell Metabolism: a Manual of Biochemical Methods (Grune & Stratton, 1984).

  26. Neuhoff, V., Arold, N., Taube, D. & Ehrhardt, W. Improved staining of proteins in polyacrylamide gels including isoelectric focusing gels with clear background at nanogram sensitivity using Coomassie Brilliant Blue G-250 and R-250. Electrophoresis 9, 255–262 (1988).

    Article  CAS  Google Scholar 

  27. Perkins, D.N., Pappin, D.J., Creasy, D.M. & Cottrell, J.S. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551–3567 (1999).

    Article  CAS  Google Scholar 

  28. Case, D.A. et al. AMBER 11 (University of California–San Francisco, 2010).

  29. Hornak, V. et al. Comparison of multiple Amber force fields and development of improved protein backbone parameters. Proteins 65, 712–725 (2006).

    Article  CAS  Google Scholar 

  30. Polgár, L. Ion-pair formation as a source of enhanced reactivity of the essential thiol group of d-glyceraldehyde-3-phosphate dehydrogenase. Eur. J. Biochem. 51, 63–71 (1975).

    Article  Google Scholar 

  31. Walker, R.C., de Souza, M.M., Mercer, I.P., Gould, I.R. & Klug, D.R. Large and fast relaxations inside a protein:calculation and measurement of reorganization energies in alcohol dehydrogenase. J. Phys. Chem. B 106, 11658–11665 (2002).

    Article  CAS  Google Scholar 

  32. Jorgensen, W.L., Chandrasekhar, J., Madura, J.D., Impey, R.W. & Klein, M.L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983).

    Article  CAS  Google Scholar 

  33. Berendsen, H.J.C., Postma, J.P.M., van Gunsteren, W.F., DiNola, A. & Haak, J.R. Molecular dynamics with coupling to an external bath. J. Chem. Phys. 81, 3684–3690 (1984).

    Article  CAS  Google Scholar 

  34. Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys. 126, 014101 (2007).

    Article  Google Scholar 

  35. Darden, T., York, D. & Pedersen, L. Particle mesh Ewald: An Nlog(N) method for Ewald sums in large systems. J. Chem. Phys. 98, 10089–10092 (1993).

    Article  CAS  Google Scholar 

  36. Essmann, U. et al. A smooth particle mesh Ewald method. J. Chem. Phys. 103, 8577–8593 (1995).

    Article  CAS  Google Scholar 

  37. Lambrakos, S.G., Boris, J.P., Oran, E.S., Chandrasekhar, I. & Nagumo, M. A modified shake algorithm for maintaining rigid bonds in molecular dynamics simulations of large molecules. J. Comput. Phys. 85, 473–486 (1989).

    Article  Google Scholar 

  38. Roe, D.R. & Cheatham, T.E. PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data. J. Chem. Theory Comput. 9, 3084–3095 (2013).

    Article  CAS  Google Scholar 

  39. Pettersen, E.F. et al. UCSF Chimera—a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004).

    Article  CAS  Google Scholar 

  40. Lang, P.T. et al. DOCK 6: combining techniques to model RNA-small molecule complexes. RNA 15, 1219–1230 (2009).

    Article  CAS  Google Scholar 

  41. Frisch, M.J. et al. Gaussian 03 (Gaussian, Inc., 2004).

  42. Stewart, J.J.P. MOPAC 2012 (Stewart Computational Chemistry, Colorado Springs, Colorado, USA, 2012).

  43. Klamt, A. & Schüürmann, G. COSMO: a new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient. J. Chem. Soc., Perkin Trans. 2 799–805 (1993).

  44. Tomasi, J., Mennucci, B. & Cammi, R. Quantum mechanical continuum solvation models. Chem. Rev. 105, 2999–3093 (2005).

    Article  CAS  Google Scholar 

  45. Janke, C. et al. A versatile toolbox for PCR-based tagging of yeast genes: new fluorescent proteins, more markers and promoter substitution cassettes. Yeast 21, 947–962 (2004).

    Article  CAS  Google Scholar 

  46. de Castro, E. et al. ScanProsite: detection of PROSITE signature matches and ProRule-associated functional and structural residues in proteins. Nucleic Acids Res. 34, W362–W365 (2006).

    Article  CAS  Google Scholar 

  47. UniProt Consortium. Activities at the universal protein resource (UniProt). Nucleic Acids Res. 42, D191–D198 (2014).

Download references

Acknowledgements

T.P.D. is supported by the German Research Foundation (SFB 1036, SPP 1710). F.G. is supported by the Klaus Tschira Foundation. D.P. was supported by a PhD scholarship from the Helmholtz International Graduate School for Cancer Research. A.K.B. was supported by the Heidelberg University BIOMS program. P.N. is grateful for financial support from FP7-PEOPLE-2010-RG (Marie Curie International Reintegration Grant; grant no. PIRG08-GA-2010-277006), the Hungarian National Science Foundation (OTKA; grant no.: K 109843) and the EurocanPlatform project. T. Ruppert (DKFZ-ZMBH Alliance) is acknowledged for performing MS analysis. K. Ballagó and G. Kuntz are acknowledged for their technical assistance.

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D.P. and T.P.D. conceived the project. D.P. performed and analyzed most experiments. A.K.B. and F.G. designed and performed computational chemistry calculations. B.M. designed yeast experiments. E.D., K.V.L. and P.N. designed and performed kinetic experiments. All authors analyzed the data, discussed the results and contributed to the writing of the manuscript.

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Correspondence to Tobias P Dick.

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Supplementary Results, Supplementary Figures 1–9 and Supplementary Tables 1 and 2. (PDF 15625 kb)

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Peralta, D., Bronowska, A., Morgan, B. et al. A proton relay enhances H2O2 sensitivity of GAPDH to facilitate metabolic adaptation. Nat Chem Biol 11, 156–163 (2015). https://doi.org/10.1038/nchembio.1720

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