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:

Membrane-anchored HDCR nanowires drive hydrogen-powered CO2 fixation

Nature volume 607, pages 823–830 (2022)Cite this article

Subjects

Abstract

Filamentous enzymes have been found in all domains of life, but the advantage of filamentation is often elusive1. Some anaerobic, autotrophic bacteria have an unusual filamentous enzyme for CO2 fixation—hydrogen-dependent CO2 reductase (HDCR)2,3—which directly converts H2 and CO2 into formic acid. HDCR reduces CO2 with a higher activity than any other known biological or chemical catalyst4,5, and it has therefore gained considerable interest in two areas of global relevance: hydrogen storage and combating climate change by capturing atmospheric CO2. However, the mechanistic basis of the high catalytic turnover rate of HDCR has remained unknown. Here we use cryo-electron microscopy to reveal the structure of a short HDCR filament from the acetogenic bacterium Thermoanaerobacter kivui. The minimum repeating unit is a hexamer that consists of a formate dehydrogenase (FdhF) and two hydrogenases (HydA2) bound around a central core of hydrogenase Fe-S subunits, one HycB3 and two HycB4. These small bacterial polyferredoxin-like proteins oligomerize through their C-terminal helices to form the backbone of the filament. By combining structure-directed mutagenesis with enzymatic analysis, we show that filamentation and rapid electron transfer through the filament enhance the activity of HDCR. To investigate the structure of HDCR in situ, we imaged T. kivui cells with cryo-electron tomography and found that HDCR filaments bundle into large ring-shaped superstructures attached to the plasma membrane. This supramolecular organization may further enhance the stability and connectivity of HDCR to form a specialized metabolic subcompartment within the cell.

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: Cryo-EM structure of a short HDCR filament.
Fig. 2: Molecular connectivity in the repeating unit of the HDCR filament.
Fig. 3: Filamentation is mediated by the C-terminal helices of HycB3 and HycB4, enabling increased HDCR activity.
Fig. 4: An electron nanowire forms the central spine of the HDCR filament.
Fig. 5: Bundles of HDCR filaments bind to the plasma membrane in native T. kivui cells.

Similar content being viewed by others

Data availability

Cryo-EM maps, as well as cryo-ET subtomogram averages and cellular tomograms are available in the Electron Microscopy Data Bank (EMDB) with the accession codes EMD-14169 (cryo-EM map), EMD- 15053 (subtomogram average of HDCR), EMD-15054 (subtomogram average of T. kivui ribosomes), EMD-15055 (Fig. 5b tomogram) and EMD-15056 (Fig. 5a tomogram). Raw electron tomography data are available in the Electron Microscopy Public Image Archive (EMPIAR-11058). The atomic model of HDCR is available in the PDB (7QV7). Structural and sequence data used for comparison with HDCR subunits are available in the PDB (3C8Y, iron hydrogenase from Clostridium pasteurianum; 1H0H, W-containing formate dehydrogenase from D. gigas). Source data are provided with this paper.

References

  1. Park, C. K. & Horton, N. C. Structures, functions, and mechanisms of filament forming enzymes: a renaissance of enzyme filamentation. Biophys. Rev. 11, 927–994 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Schuchmann, K. & Müller, V. Direct and reversible hydrogenation of CO2 to formate by a bacterial carbon dioxide reductase. Science 342, 1382–1385 (2013).

    Article  CAS  PubMed  ADS  Google Scholar 

  3. Schwarz, F. M., Schuchmann, K. & Müller, V. Hydrogenation of CO2 at ambient pressure catalyzed by a highly active thermostable biocatalyst. Biotechnol. Biofuels 11, 237 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Sordakis, K. et al. Homogeneous catalysis for sustainable hydrogen storage in formic acid and alcohols. Chem. Rev. 118, 372–433 (2018).

    Article  CAS  PubMed  Google Scholar 

  5. Müller, V. New horizons in acetogenic conversion of one-carbon substrates and biological hydrogen storage. Trends Biotechnol. 37, 1344–1354 (2019).

    Article  PubMed  CAS  Google Scholar 

  6. Scheffers, B. R. et al. The broad footprint of climate change from genes to biomes to people. Science 354, aaf7671 (2016).

    Article  PubMed  CAS  Google Scholar 

  7. Pecl, G. T. et al. Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).

    Article  PubMed  CAS  Google Scholar 

  8. DeWeerdt, S. Sea change. Nature 550, S54–S58 (2017).

    Article  CAS  PubMed  ADS  Google Scholar 

  9. Masson-Delmotte, V. et al. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2021).

  10. Ripple, W. J. et al. World scientists' warning to humanity: a second notice. Bioscience 67, 1026–1028 (2017).

    Article  Google Scholar 

  11. Rand, D. A. J. & Dell, R. M. Hydrogen Energy: Challenges and Prospects (Royal Society of Chemistry, 2007).

  12. Chu, S. & Majumdar, A. Opportunities and challenges for a sustainable energy future. Nature 488, 294–303 (2012).

    Article  CAS  PubMed  ADS  Google Scholar 

  13. Fukuzumi, S. Bioinspired energy conversion systems for hydrogen production and storage. Eur. J. Inorg. Chem. 2008, 1351–1362 (2008).

    Article  CAS  Google Scholar 

  14. Joo, F. Breakthroughs in hydrogen storage—formic acid as a sustainable storage material for hydrogen. ChemSusChem 1, 805–808 (2008).

    Article  CAS  PubMed  Google Scholar 

  15. Loges, B., Boddien, A., Gärtner, F., Junge, H. & Beller, M. Catalytic generation of hydrogen from formic acid and its derivatives: useful hydrogen storage materials. Top. Catal. 53, 902–914 (2010).

    Article  CAS  Google Scholar 

  16. Mellmann, D., Sponholz, P., Junge, H. & Beller, M. Formic acid as a hydrogen storage material—development of homogeneous catalysts for selective hydrogen release. Chem. Soc. Rev. 45, 3954–3988 (2016).

    Article  CAS  PubMed  Google Scholar 

  17. Eppinger, J. & Huang, K.-W. Formic acid as a hydrogen energy carrier. ACS Energy Lett. 2, 188–195 (2016).

    Article  CAS  Google Scholar 

  18. Enthaler, S., von Langermann, J. & Schmidt, T. Carbon dioxide and formic acid—the couple for environmental-friendly hydrogen storage? Energy Environ. Sci. 3, 1207–1217 (2010).

    Article  CAS  Google Scholar 

  19. Agarwal, A. S., Zhai, Y., Hill, D. & Sridhar, N. The electrochemical reduction of carbon dioxide to formate/formic acid: engineering and economic feasibility. ChemSusChem 4, 1301–1310 (2011).

    Article  CAS  PubMed  Google Scholar 

  20. Pereira, I. A. An enzymatic route to H2 storage. Science 342, 1329–1330 (2013).

    Article  CAS  PubMed  ADS  Google Scholar 

  21. Preuster, P., Papp, C. & Wasserscheid, P. Liquid organic hydrogen carriers (LOHCs): Toward a hydrogen-free hydrogen economy. Acc. Chem. Res. 50, 74–85 (2017).

    Article  CAS  PubMed  Google Scholar 

  22. Li, H. et al. Integrated electromicrobial conversion of CO2 to higher alcohols. Science 335, 1596 (2012).

    Article  CAS  PubMed  ADS  Google Scholar 

  23. Yishai, O., Lindner, S. N., Gonzalez de la Cruz, J., Tenenboim, H. & Bar-Even, A. The formate bio-economy. Curr. Opin. Chem. Biol. 35, 1–9 (2016).

    Article  CAS  PubMed  Google Scholar 

  24. Pinske, C. & Sargent, F. Exploring the directionality of Escherichia coli formate hydrogenlyase: a membrane-bound enzyme capable of fixing carbon dioxide to organic acid. MicrobiologyOpen 5, 721–737 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wang, W. H., Himeda, Y., Muckerman, J. T., Manbeck, G. F. & Fujita, E. CO2 hydrogenation to formate and methanol as an alternative to photo- and electrochemical CO2 reduction. Chem. Rev. 115, 12936–12973 (2015).

    Article  CAS  PubMed  Google Scholar 

  26. Matubayasi, N. & Nakahara, M. Hydrothermal reactions of formaldehyde and formic acid: free-energy analysis of equilibrium. J. Chem. Phys. 122, 074509 (2005).

    Article  PubMed  ADS  CAS  Google Scholar 

  27. Kottenhahn, P., Schuchmann, K. & Müller, V. Efficient whole cell biocatalyst for formate-based hydrogen production. Biotechnol. Biofuels 11, 93 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Schwarz, F. M. & Müller, V. Whole-cell biocatalysis for hydrogen storage and syngas conversion to formate using a thermophilic acetogen. Biotechnol. Biofuels 13, 32 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Schuchmann, K., Vonck, J. & Müller, V. A bacterial hydrogen-dependent CO2 reductase forms filamentous structures. FEBS J. 283, 1311–1322 (2016).

    Article  CAS  PubMed  Google Scholar 

  30. Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  31. Peters, J. W., Lanzilotta, W. N., Lemon, B. J. & Seefeldt, L. C. X-ray crystal structure of the Fe-only hydrogenase (Cpl) from Clostridium pasteurianum to 1.8 angstrom resolution. Science 282, 1853–1858 (1998).

    Article  CAS  PubMed  ADS  Google Scholar 

  32. Maia, L. B., Moura, I. & Moura, J. J. G. Molybdenum and tungsten-containing formate dehydrogenases: aiming to inspire a catalyst for carbon dioxide utilization. Inorganica Chim. Acta 455, 350–363 (2017).

    Article  CAS  Google Scholar 

  33. Dong, G. & Ryde, U. Reaction mechanism of formate dehydrogenase studied by computational methods. J. Biol. Inorg. Chem. 23, 1243–1254 (2018).

    Article  CAS  PubMed  Google Scholar 

  34. Niks, D. & Hille, R. Molybdenum- and tungsten-containing formate dehydrogenases and formylmethanofuran dehydrogenases: structure, mechanism, and cofactor insertion. Protein Sci. 28, 111–122 (2019).

    Article  CAS  PubMed  Google Scholar 

  35. Maia, L. B., Moura, I. & Moura, J. J. G. in Enzymes for Solving Humankind's Problems: Natural and Artificial Systems in Health, Agriculture, Environment and Energy (eds Moura, J. J. G., Moura, I. & Maia, L. B.) 29–81 (Springer, 2021).

  36. Raaijmakers, H. et al. Gene sequence and the 1.8 Å crystal structure of the tungsten-containing formate dehydrogenase from Desulfovibrio gigas. Structure 10, 1261–1272 (2002).

    Article  CAS  PubMed  Google Scholar 

  37. Page, C. C., Moser, C. C., Chen, X. & Dutton, P. L. Natural engineering principles of electron tunnelling in biological oxidation–reduction. Nature 402, 47–52 (1999).

    Article  CAS  PubMed  ADS  Google Scholar 

  38. Basen, M., Geiger, I., Henke, L. & Müller, V. A genetic system for the thermophilic acetogenic bacterium Thermoanaerobacter kivui. Appl. Environ. Microbiol. 84, e02210–e02217 (2018).

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  39. Jain, S., Dietrich, H. M., Müller, V. & Basen, M. Formate is required for growth of the thermophilic acetogenic bacterium Thermoanaerobacter kivui lacking hydrogen-dependent carbon dioxide reductase (HDCR). Front. Microbiol. 11, 59 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Esteve-Núñez, A., Sosnik, J., Visconti, P. & Lovley, D. R. Fluorescent properties of c-type cytochromes reveal their potential role as an extracytoplasmic electron sink in Geobacter sulfurreducens. Environ. Microbiol. 10, 497–505 (2008).

    Article  PubMed  CAS  Google Scholar 

  41. Bewley, K. D., Ellis, K. E., Firer-Sherwood, M. A. & Elliott, S. J. Multi-heme proteins: Nature's electronic multi-purpose tool. Biochim. Biophys. Acta 1827, 938–948 (2013).

    Article  CAS  PubMed  Google Scholar 

  42. Sturm, G. et al. A dynamic periplasmic electron transfer network enables respiratory flexibility beyond a thermodynamic regulatory regime. ISME J. 9, 1802–1811 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Schaffer, M. et al. Optimized cryo-focused ion beam sample preparation aimed at in situ structural studies of membrane proteins. J. Struct. Biol. 197, 73–82 (2017).

    Article  CAS  PubMed  Google Scholar 

  44. Asano, S., Engel, B. D. & Baumeister, W. In situ cryo-electron tomography: a post-reductionist approach to structural biology. J. Mol. Biol. 428, 332–343 (2016).

    Article  CAS  PubMed  Google Scholar 

  45. Bäuerlein, F. J. B. & Baumeister, W. Towards visual proteomics at high resolution. J. Mol. Biol. 433, 167187 (2021).

    Article  PubMed  CAS  Google Scholar 

  46. Schuchmann, K. & Müller, V. Autotrophy at the thermodynamic limit of life: a model for energy conservation in acetogenic bacteria. Nat. Rev. Microbiol. 12, 809–821 (2014).

    Article  CAS  PubMed  Google Scholar 

  47. Schoelmerich, M. C. & Müller, V. Energy conservation by a hydrogenase-dependent chemiosmotic mechanism in an ancient metabolic pathway. Proc. Natl Acad. Sci. USA 116, 6329–6334 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Schwarz, F. M., Moon, J., Oswald, F. & Müller, V. Biological hydrogen storage and release through multiple cycles of bi-directional hydrogenation of CO2 to formic acid in a single process unit. Joule 6, 1304–1319 (2022).

  49. Debabov, V. G. Acetogens: biochemistry, bioenergetics, genetics, and biotechnological potential. Microbiology 90, 273–297 (2021).

    Article  CAS  Google Scholar 

  50. Roger, M., Reed, T. C. P. & Sargent, F. Harnessing Escherichia coli for bio-based production of formate under pressurized H2 and CO2 gases. Appl. Environ. Microbiol. 87, e00299–00221 (2021).

    Article  CAS  PubMed Central  ADS  Google Scholar 

  51. Mastronarde, D. N. Automated electron microscope tomography using robust prediction of specimen movements. J. Struct. Biol. 152, 36–51 (2005).

    Article  PubMed  Google Scholar 

  52. Biyani, N. et al. Focus: the interface between data collection and data processing in cryo-EM. J. Struct. Biol. 198, 124–133 (2017).

    Article  CAS  PubMed  Google Scholar 

  53. Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Rohou, A. & Grigorieff, N. CTFFIND4: fast and accurate defocus estimation from electron micrographs. J. Struct. Biol. 192, 216–221 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Zhang, K. Gctf: real-time CTF determination and correction. J. Struct. Biol. 193, 1–12 (2016).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  56. Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–296 (2017).

    Article  CAS  PubMed  Google Scholar 

  57. Punjani, A., Zhang, H. & Fleet, D. J. Non-uniform refinement: adaptive regularization improves single-particle cryo-EM reconstruction. Nat. Methods 17, 1214–1221 (2020).

    Article  CAS  PubMed  Google Scholar 

  58. Tan, Y. Z. et al. Addressing preferred specimen orientation in single-particle cryo-EM through tilting. Nat. Methods 14, 793–796 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Emsley, P. & Cowtan, K. Coot: model-building tools for molecular graphics. Acta Crystallogr. D 60, 2126–2132 (2004).

    Article  PubMed  CAS  Google Scholar 

  60. Afonine, P. V. et al. Real-space refinement in PHENIX for cryo-EM and crystallography. Acta Crystallogr. D 74, 531–544 (2018).

    Article  CAS  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  62. Moriarty, N. W., Grosse-Kunstleve, R. W. & Adams, P. D. electronic Ligand Builder and Optimization Workbench (eLBOW): a tool for ligand coordinate and restraint generation. Acta Crystallogr. D 65, 1074–1080 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Chen, V. B. et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr. D 66, 12–21 (2010).

    Article  CAS  PubMed  Google Scholar 

  64. Delano, W. L. The PyMOL Molecular Graphics System (Schrödinger, 2002).

  65. Goddard, T. D. et al. UCSF ChimeraX: meeting modern challenges in visualization and analysis. Protein Sci. 27, 14–25 (2018).

    Article  CAS  PubMed  Google Scholar 

  66. Shaw, A. J., Hogsett, D. A. & Lynd, L. R. Natural competence in Thermoanaerobacter and Thermoanaerobacterium species. Appl. Environ. Microbiol. 76, 4713–4719 (2010).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  67. Benner, P. Proteinproduktion im Thermophilen, Acetogenen Bakterium Thermoanaerobacter kivui. BSc thesis, Goethe Univ. (2016).

  68. Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).

    Article  CAS  PubMed  Google Scholar 

  69. Bradford, M. M. A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of proteine-dye binding. Anal. Biochem. 72, 248–254 (1976).

    Article  CAS  PubMed  Google Scholar 

  70. Wolff, G. et al. Mind the gap: micro-expansion joints drastically decrease the bending of FIB-milled cryo-lamellae. J. Struct. Biol. 208, 107389 (2019).

    Article  PubMed  Google Scholar 

  71. Hagen, W. J. H., Wan, W. & Briggs, J. A. G. Implementation of a cryo-electron tomography tilt-scheme optimized for high resolution subtomogram averaging. J. Struct. Biol. 197, 191–198 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Wan, W. williamnwan/TOMOMAN: TOMOMAN v.08042020 https://doi.org/10.5281/zenodo.4110737 (Zenodo, 2020).

  73. Grant, T. & Grigorieff, N. Measuring the optimal exposure for single particle cryo-EM using a 2.6 Å reconstruction of rotavirus VP6. eLife 4, e06980 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  74. Mastronarde, D. N. & Held, S. R. Automated tilt series alignment and tomographic reconstruction in IMOD. J. Struct. Biol. 197, 102–113 (2017).

    Article  PubMed  Google Scholar 

  75. Kremer, J. R., Mastronarde, D. N. & McIntosh, J. R. Computer visualization of three-dimensional image data using IMOD. J. Struct. Biol. 116, 71–76 (1996).

    Article  CAS  PubMed  Google Scholar 

  76. Buchholz, T., Jordan, M., Pigino, G. & Jug, F. Cryo-CARE: Content-aware image restoration for cryo-transmission electron microscopy data. In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019) 502–506 (IEEE, 2019).

  77. Martinez-Sanchez, A., Garcia, I., Asano, S., Lucic, V. & Fernandez, J. J. Robust membrane detection based on tensor voting for electron tomography. J. Struct. Biol. 186, 49–61 (2014).

    Article  PubMed  Google Scholar 

  78. Wan, W. williamnwan/STOPGAP: STOPGAP v.0.7.1 https://doi.org/10.5281/zenodo.3973664 (Zenodo, 2020).

  79. Turoňová, B., Schur, F. K. M., Wan, W. & Briggs, J. A. G. Efficient 3D-CTF correction for cryo-electron tomography using NovaCTF improves subtomogram averaging resolution to 3.4 Å. J. Struct. Biol. 199, 187–195 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. Pintilie, G. D., Zhang, J., Goddard, T. D., Chiu, W. & Gossard, D. C. Quantitative analysis of cryo-EM density map segmentation by watershed and scale-space filtering, and fitting of structures by alignment to regions. J. Struct. Biol. 170, 427–438 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Harauz, G. & van Heel, M. Exact filters for general geometry three dimensional reconstruction. Optik 73, 146–156 (1986).

    Google Scholar 

  82. Rosenthal, P. B. & Henderson, R. Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy. J. Mol. Biol. 333, 721–745 (2003).

    Article  CAS  PubMed  Google Scholar 

  83. Grant, T., Rohou, A. & Grigorieff, N. cisTEM, user-friendly software for single-particle image processing. eLife 7, e35383 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Qu, K. et al. Structure and architecture of immature and mature murine leukemia virus capsids. Proc. Natl Acad. Sci. USA 115, E11751–E11760 (2018).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

Download references

Acknowledgements

We thank D. Bollschweiler and T. Schäfer at the MPIB cryo-EM facility for single-particle cryo-EM data acquisition, J. Zarzycki for help with model building, M. Demulder for help with FIB milling and H. van den Hoek, F. Beck, P. Erdmann, S. Khavnekar and W. Wan for scripts and advice with cryo-ET analysis. We are grateful to E. Conti, J. Plitzko and W. Baumeister for access to state-of-the-art FIB and transmission electron microscopy instrumentation; to P. Benner and M. Basen for their gift of pPB5 and for discussions; and to L. Ribaric for help in preparing pLR2, pLR2c, pLR3b and pLR4. Calculations were performed at the Max Planck Institute for Biochemistry computing cluster in Martinsried, Germany, and at the sciCORE (http://scicore.unibas.ch/) scientific computing center at the University of Basel. J.M.S. acknowledges the DFG for early career support by an Emmy Noether grant (SCHU 3364/1-1). Work from the V.M. laboratory was supported by the European Research Council (Acetogens, grant agreement no. 741791). Work from the B.D.E. laboratory was supported by a DFG grant (EN 1194/1–1, part of FOR 2092), Helmholtz Munich and the University of Basel. H.M.D. was funded by a fellowship from Deutsche Bundesstiftung Umwelt (DBU) (PhD. grant no. 20016/446). R.D.R. acknowledges funding from the Alexander von Humboldt Foundation and a non-stipendiary fellowship from EMBO.

Author information

Author notes

  1. These authors contributed equally: Helge M. Dietrich, Ricardo D. Righetto

Authors and Affiliations

  1. Molecular Microbiology & Bioenergetics, Institute of Molecular Biosciences, Johann Wolfgang Goethe University, Frankfurt am Main, Germany

    Helge M. Dietrich, Anuj Kumar, Raphael Trischler, Fabian M. Schwarz & Volker Müller

  2. Helmholtz Pioneer Campus, Helmholtz Munich, Neuherberg, Germany

    Ricardo D. Righetto, Wojciech Wietrzynski & Benjamin D. Engel

  3. Biozentrum, University of Basel, Basel, Switzerland

    Ricardo D. Righetto, Wojciech Wietrzynski & Benjamin D. Engel

  4. CryoEM of Molecular Machines, SYNMIKRO Research Center and Department of Chemistry, Philipps-University, Marburg, Germany

    Anuj Kumar, Sandra K. Schuller & Jan M. Schuller

  5. Department of Molecular Structural Biology, Max Planck Institute of Biochemistry, Martinsried, Germany

    Jonathan Wagner

Authors
  1. Helge M. Dietrich
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ricardo D. Righetto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Anuj Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wojciech Wietrzynski
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Raphael Trischler
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sandra K. Schuller
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jonathan Wagner
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Fabian M. Schwarz
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Benjamin D. Engel
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Volker Müller
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Jan M. Schuller
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

H.M.D., B.D.E., J.M.S. and V.M. designed and coordinated the experiments. H.M.D., R.T. and F.M.S. expressed and purified the proteins. H.M.D. and R.T. carried out enzymatic assays. S.K.S. and J.M.S. collected and processed cryo-EM data. A.K., S.K.S. and J.M.S. built and refined models. H.M.D., R.D.R., A.K., J.M.S. and V.M. analysed and interpreted the functional and structural data. W.W. and J.W. performed FIB milling and cryo-ET data acquisition. R.D.R. and J.W. processed and analysed the cryo-ET data. A.K. and J.W. performed the negative-stain imaging. J.M.S., B.D.E. and V.M. wrote the manuscript together with all of the other authors.

Corresponding authors

Correspondence to Benjamin D. Engel, Volker Müller or Jan M. Schuller.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks Alexey Amunts and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

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

Extended data figures and tables

Extended Data Fig. 1 Cryo-EM data collection and analysis.

a, A representative cryo-EM micrograph (n = 33,853) collected on a FEI Titan Krios microscope (scale bar: 50 nm), operated at 300 kV and equipped with a K3 camera. b, Reference-free 2D class averages revealing the short HDCR filament in multiple orientations. c, Overview of the cryo-EM data-processing scheme. d, Angular distribution of the particles used for the final round of refinement. e, Plot showing the global resolution and sphericity of the final HDCR reconstruction, calculated using the “Remote 3DFSC Processing Server” web interface58. A sphericity of 0.939 indicates an isotropic particle orientation. f, Local resolution as calculated by CryoSPARC mapped on the refined density (left: bottom and side view, right: cut-open view of central section).

Extended Data Fig. 2 Filament bundling of purified HDCR used for cryo-EM and negative staining.

a–d, Longer HDCR filaments were occasionally observed in cryo-EM micrographs of the purified HDCR preparation. These filaments generally grouped together as bundles with varying filament length, impeding structural analysis. Representative images from 33,853 micrographs collected. Micrograph recording was performed as described in Extended Data Fig. 1. Scale bar: 50 nm. e–f, Representative negative-stain images of HDCR_His from F2 of Fig. 3f (n = 8), showing large filament bundles. Scale bars: 100 nm.

Extended Data Fig. 3 Model quality.

a, Structural models of the enzymatic active subunits in their electron density. FdhF domain IV is flexible (see Extended Data Fig. 5). The same colours are used as in Fig. 1. b, Representative regions of the HDCR complex and surrounding electron density maps are shown. Subunits and residue numbers are specified. Snapshots are shown for the density of both folded and cofactor binding regions.

Extended Data Fig. 4 Structural conservation of HydA2.

a, Structural model of HydA2. b, Superposition of HydA2 (blue) with the closest homolog [FeFe]-hydrogenase from Clostridium pasteurianum and zoom-in of the active site. c, Fit of the H-cluster (PDB: 3C8Y) in the electron density. d, Sequence alignment of HydA2 with the [FeFe]-hydrogenase CpI from Clostridium pasteurianum. Conserved residues are highlighted with colour, with darker shades of blue indicating high conservation. This alignment shows high conservation of the cap domain. Functional and cofactor-coordinating residues are marked according to the legend on the right side, revealing a full conservation of H-cluster coordination.

Extended Data Fig. 5 Structural conservation of FdhF.

a, Structural model of domains I-III of FdhF as built from the cryo-EM density. Close-up of the [4Fe4S]-cluster fitted into its map (mesh), demonstrating map quality. b, Superposition of FdhF (green) with the tungsten-containing formate dehydrogenase from D. gigas (pink, PDB: 1H0H). Close-up of the tungsten and pterin guanine dinucleotide binding site reveals high structural conservation. Fit of the W-bisPGD cofactors (1H0H) in the electron density. c, Composite model of FdhF: domains I-III were built from the cryo-EM density (as in panel a), and domain IV as well as the W-bisPGD cofactors were derived from homology. d, Sequence alignment of FdhF with the tungsten-containing formate dehydrogenase from D. gigas. Conserved residues are highlighted, with darker shades of blue indicating high conservation. This alignment shows that all domains are highly conserved. Functional and cofactor-coordinating residues are marked according to the legend on the right side, revealing conservation of W-bisPGD cofactor coordination. For more details on conserved W-bisPGD coordinating amino acids, see also Supplementary Table 2.

Extended Data Fig. 6 HDCR_His complements the native HDCR enzyme activity.

a, Purified HDCR (10 µg) from wild-type T. kivui (HDCR native) and from the overproduction strain HDCR_His have identical protein subunits. b, Isolated native HDCR and the HDCR_His tested for H2 evolution from formate and formate production from H2 + CO2. Data for “HDCR native” are reproduced from a previous study3. Hydrogen production from formate (150 mM) catalysed by 10 µg isolated HDCR_His. Formate production as described before, but H2 + CO2 (80:20 [v:v], 1.1 x 105 Pa) was used as a substrate. c, Hydrogen production from formate (150 mM) catalysed by 0.3 mg of cytoplasmic fractions of WT (HDCR native) and HDCR_His T. kivui strains. All data points are mean ± s.e.m., taken from 3 biologically independent replicates, each with 3 technical replicates. Statistical analysis was performed using one-way analysis of variance (ANOVA) with comparative Tukey post-hoc test (significance level ***p = 0.001).

Source data

Extended Data Fig. 7 Catalytic properties of HDCR variants.

a-d, Characterization of the pH- and temperature-dependence of HDCR native (squares) and HDCR_His (circles). a and c, Methylviologen-dependent hydrogenase activity with H2 or b and d, formate dehydrogenase activity with formate as electron donor. Data for HDCR native are reproduced from a previous study3. 0.03 µg (H2:MV-oxidoreductase activity) or 3 µg (formate:MV-oxidoreductase activity) of HDCR_His were incubated in reaction buffer at 64 °C. 10 mM methylviologen was used as an electron acceptor, and reduction of methylviologen was monitored at 604 nm. MV, methylviologen. e-f, Functionality of catalytical subunits in HDCR variants. e, Methylviologen-dependent hydrogenase activity with H2 or f, formate dehydrogenase activity with formate as an electron donor. 3 µg (H2:MV-oxidoreductase activity) or 30 µg (formate:MV-oxidoreductase activity) of cytoplasmic fractions containing HDCR variants were incubated in reaction buffer at 64 °C. 10 mM methylviologen was used as an electron acceptor, and reduction of methylviologen was monitored at 604 nm. 100 % corresponds to the activity of the complete HDCR_His complex (H2:MV-oxidoreductase activity 301 µmol min−1 mg−1; formate:MV-oxidoreductase activity 40 µmol min−1 mg−1). MV, methylviologen. g) Hydrogen production from formate of selected HDCR variants. h) Formate production from H2 + CO2 of selected HDCR variants. HDCR_His was defined as 100 % relative enzyme activity (hydrogen evolution from formate, 83 µmol min−1 mg−1; formate production from H2 + CO2, 25 µmol min−1 mg−1). All data points are mean ± s.e.m., taken from 3 (a–g) or 1 (h) biologically independent replicates, each with 3 (e,f,h) or 2 (a,b,c,d,g) technical replicates. Statistical analysis was performed using one-way analysis of variance (ANOVA) with comparative Tukey post-hoc test (significance level ***p = 0.001). For further methods details, see the Supplementary Information.

Source data

Extended Data Fig. 8 Cryo-ET of wild-type and Δhdcr mutant T. kivui cells confirms the identity of HDCR.

a–f, Slices through cryo-tomograms of wild-type (WT) T. kivui cells containing HDCR filament bundles (yellow arrowheads). HDCR filaments were observed in 22 of n = 34 WT tomograms. g–l, Slices through cryo-tomograms of mutant T. kivui cells in which the genes coding for HDCR proteins were deleted (Δhdcr). No filaments were observed in n = 34 Δhdcr tomograms. Slice thickness: 7 nm.

Extended Data Fig. 9 Overview of HDCR subtomogram averaging, and helical pitch comparison between in vitro and in situ structures.

a, Processing flowchart used for HDCR subtomogram averaging in situ. For additional details, see Methods. b, Fourier shell correlation (FSC) curves from the final subtomogram average (displayed in Fig. 5g). c, comparison of observed helical pitch in vitro (98.5 nm with rise: 68.4 Å, twist: 25°) and in situ (289.5 nm with rise: 67.8 Å, twist: 8.43°).

Extended Data Table 1 Cryo- EM data collection, refinement and validation statistics
Full size table

Supplementary information

Supplementary Information

Supplementary file containing additional information about HDCR subunit interaction, further method details, and the impact of filamentation for HDCR enzymes. Supplementary Tables 1–5 contain detailed information about cofactor coordination in HDCR, as well as primers, plasmids and strains used in this study. Supplementary Figure 1 includes uncropped polyacrylamide gels. The Supplementary Information also includes legends for Supplementary Videos and Supplementary References.

Reporting Summary

Peer Review File

Supplementary Video 1

Supplementary Video 2

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dietrich, H.M., Righetto, R.D., Kumar, A. et al. Membrane-anchored HDCR nanowires drive hydrogen-powered CO2 fixation. Nature 607, 823–830 (2022). https://doi.org/10.1038/s41586-022-04971-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-022-04971-z

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing Microbiology

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

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Microbiology