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.

  • Protocol
  • Published:

NMR protein structure determination in living E. coli cells using nonlinear sampling

Nature Protocols volume 5, pages 1051–1060 (2010)Cite this article

Subjects

Abstract

The cell is a crowded environment in which proteins interact specifically with other proteins, nucleic acids, cofactors and ligands. Atomic resolution structural explanation of proteins functioning in this environment is a main goal of biochemical research. Recent improvements to nuclear magnetic resonance (NMR) hardware and methodology allow the measurement of high-resolution heteronuclear multidimensional NMR spectra of macromolecules in living cells (in-cell NMR). In this study, we describe a protocol for the stable isotope (13C, 15N and 2H) labeling and structure determination of proteins overexpressed in Escherichia coli cells exclusively on the basis of information obtained in living cells. The protocol combines the preparation of the protein in E. coli cells, the rapid measurement of the three-dimensional (3D) NMR spectra by nonlinear sampling of the indirectly acquired dimensions, structure calculation and structure refinement. Under favorable circumstances, this in-cell NMR approach can provide high-resolution 3D structures of proteins in living environments. The protocol has been used to solve the first 3D structure of a protein in living cells for the putative heavy metal-binding protein TTHA1718 from Thermus thermophilus HB8 overexpressed in E. coli cells. As no protein purification is necessary, a sample for in-cell NMR measurements can be obtained within 2–3 d. With the nonlinear sampling scheme, the duration of each 3D experiment can be reduced to 2–3 h. Once chemical shift assignments and NOESY peak lists have been prepared, structure calculation with the program CYANA and energy refinement can be completed in less than 1 h on a powerful computer system.

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

Figure 1: Rapid acquisition of 3D NMR spectra of proteins in living E. coli cells.
Figure 2: 2D 1H-15N or 1H-13C HSQC spectra of TTHA1718 in living E. coli cells.
Figure 3: 13C(F1)-1HN(F3) or 1H(F1)-1HN(F3) cross-sections corresponding to the amide 15N chemical shift of Lys30 (120.06 p.p.m.) from 3D HNCA, HN(CO)CA, CBCANH, CBCA(CO)NH, HN(CA)CO, HNCO, HBHA(CBCACO)NH, H(CCCO)NH and (H)CC(CO)NH spectra (black) used for backbone and side-chain resonance assignments of TTHA1718 in living E. coli cells.
Figure 4: Collection of nuclear Overhauser effect-derived distance restraints in TTHA1718 in living E. coli cells.
Figure 5: NMR solution structure of TTHA1718 in living E. coli cells.

Similar content being viewed by others

References

  1. Ellis, R.J. Macromolecular crowding: obvious but underappreciated. Trends Biochem. Sci. 26, 597–604 (2001).

    Article  CAS  Google Scholar 

  2. Pielak, G.J. et al. Protein nuclear magnetic resonance under physiological conditions. Biochemistry 48, 226–234 (2009).

    Article  CAS  Google Scholar 

  3. Sakakibara, D. et al. Protein structure determination in living cells by in-cell NMR spectroscopy. Nature 458, 102–105 (2009).

    Article  CAS  Google Scholar 

  4. Serber, Z. & Dotsch, V. In-cell NMR spectroscopy. Biochemistry 40, 14317–14323 (2001).

    Article  CAS  Google Scholar 

  5. Serber, Z., Corsini, L., Durst, F. & Dötsch, V. In-cell NMR spectroscopy. Method. Enzymol. 394, 17–41 (2005).

    Article  CAS  Google Scholar 

  6. Serber, Z. et al. Investigating macromolecules inside cultured and injected cells by in-cell NMR spectroscopy. Nat. Protoc. 1, 2701–2709 (2006).

    Article  CAS  Google Scholar 

  7. Burz, D.S., Dutta, K., Cowburn, D. & Shekhtman, A. Mapping structural interactions using in-cell NMR spectroscopy (STINT-NMR). Nat. Methods 3, 91–93 (2006).

    Article  CAS  Google Scholar 

  8. Burz, D.S., Dutta, K., Cowburn, D. & Shekhtman, A. In-cell NMR for protein-protein interactions (STINT-NMR). Nat. Protoc. 1, 146–152 (2006).

    Article  CAS  Google Scholar 

  9. Reckel, S., Hänsel, R., Löhr, F. & Dötsch, V. In-cell NMR spectroscopy. Prog. Nucl. Mag. Res. Sp. 51, 91–101 (2007).

    Article  CAS  Google Scholar 

  10. Selenko, P. & Wagner, G. Looking into live cells with in-cell NMR spectroscopy. J. Struct. Biol. 158, 244–253 (2007).

    Article  CAS  Google Scholar 

  11. Serber, Z. et al. High-resolution macromolecular NMR spectroscopy inside living cells. J. Am. Chem. Soc. 123, 2446–2447 (2001).

    Article  CAS  Google Scholar 

  12. Serber, Z., Ledwidge, R., Miller, S.M. & Dötsch, V. Evaluation of parameters critical to observing proteins inside living Escherichia coli by in-cell NMR spectroscopy. J. Am. Chem. Soc. 123, 8895–8901 (2001).

    Article  CAS  Google Scholar 

  13. Wieruszeski, J.M., Bohin, A., Bohin, J.P. & Lippens, G. In vivo detection of the cyclic osmoregulated periplasmic glucan of Ralstonia solanacearum by high-resolution magic angle spinning NMR. J. Magn. Reson. 151, 118–123 (2001).

    Article  CAS  Google Scholar 

  14. Selenko, P., Serber, Z., Gade, B., Ruderman, J. & Wagner, G. Quantitative NMR analysis of the protein G B1 domain in Xenopus laevis egg extracts and intact oocytes. Proc. Natl. Acad. Sci. USA 103, 11904–11909 (2006).

    Article  CAS  Google Scholar 

  15. Sakai, T. et al. In-cell NMR spectroscopy of proteins inside Xenopus laevis oocytes. J. Biomol. NMR 36, 179–188 (2006).

    Article  CAS  Google Scholar 

  16. Bodart, J.F. et al. NMR observation of Tau in Xenopus oocytes. J. Magn. Reson. 192, 252–257 (2008).

    Article  CAS  Google Scholar 

  17. Inomata, K. et al. High-resolution multi-dimensional NMR spectroscopy of proteins in human cells. Nature 458, 106–109 (2009).

    Article  CAS  Google Scholar 

  18. Ogino, S. et al. Observation of NMR signals from proteins introduced into living mammalian cells by reversible membrane permeabilization using a pore-forming toxin, streptolysin O. J. Am. Chem. Soc. 131, 10834–10835 (2009).

    Article  CAS  Google Scholar 

  19. Barna, J.C.J., Laue, E.D., Mayger, M.R., Skilling, J. & Worrall, S.J.P. Exponential sampling, an alternative method for sampling in two-dimensional NMR experiments. J. Magn. Reson. 73, 69–77 (1987).

    CAS  Google Scholar 

  20. Schmieder, P., Stern, A.S., Wagner, G. & Hoch, J.C. Improved resolution in triple-resonance spectra by nonlinear sampling in the constant-time domain. J. Biomol. NMR 4, 483–490 (1994).

    Article  CAS  Google Scholar 

  21. Rovnyak, D. et al. Accelerated acquisition of high resolution triple-resonance spectra using non-uniform sampling and maximum entropy reconstruction. J. Magn. Reson. 170, 15–21 (2004).

    Article  CAS  Google Scholar 

  22. Rosen, M.K. et al. Selective methyl group protonation of perdeuterated proteins. J. Mol. Biol. 263, 627–636 (1996).

    Article  CAS  Google Scholar 

  23. Serber, Z. et al. Methyl groups as probes for proteins and complexes in in-cell NMR experiments. J. Am. Chem. Soc. 126, 7119–7125 (2004).

    Article  CAS  Google Scholar 

  24. Güntert, P. Automated NMR protein structure calculation. Prog. Nucl. Mag. Res. Sp. 43, 105–125 (2003).

    Article  Google Scholar 

  25. Williams, S.P., Haggie, P.M. & Brindle, K.M. 19F NMR measurements of the rotational mobility of proteins in vivo. Biophys. J. 72, 490–498 (1997).

    Article  CAS  Google Scholar 

  26. Laue, E.D., Mayger, M.R., Skilling, J. & Staunton, J. Reconstruction of phase sensitive 2D NMR spectra by maximum entropy. J. Magn. Reson. 68, 14–29 (1986).

    CAS  Google Scholar 

  27. Herrmann, T., Güntert, P. & Wüthrich, K. Protein NMR structure determination with automated NOE assignment using the new software CANDID and the torsion angle dynamics algorithm DYANA. J. Mol. Biol. 319, 209–227 (2002).

    Article  CAS  Google Scholar 

  28. Güntert, P., Mumenthaler, C. & Wüthrich, K. Torsion angle dynamics for NMR structure calculation with the new program DYANA. J. Mol. Biol. 273, 283–298 (1997).

    Article  Google Scholar 

  29. Cornilescu, G., Delaglio, F. & Bax, A. Protein backbone angle restraints from searching a database for chemical shift and sequence homology. J. Biomol. NMR 13, 289–302 (1999).

    Article  CAS  Google Scholar 

  30. Cornell, W.D. et al. A second generation force field for the simulation of proteins, nucleic acids, and organic molecules. J. Am. Chem. Soc. 117, 5179–5197 (1995).

    Article  CAS  Google Scholar 

  31. Luginbühl, P., Güntert, P., Billeter, M. & Wüthrich, K. The new program OPAL for molecular dynamics simulations and energy refinements of biological macromolecules. J. Biomol. NMR 8, 136–146 (1996).

    Article  Google Scholar 

  32. Koradi, R., Billeter, M. & Güntert, P. Point-centered domain decomposition for parallel molecular dynamics simulation. Comput. Phys. Commun. 124, 139–147 (2000).

    Article  CAS  Google Scholar 

  33. Hoch, J.C. & Stern, A.S. NMR Data Processing (Wiley-Liss, New York, 1996).

  34. Kraulis, P.J. ANSIG: a program for the assignment of protein 1H 2D NMR spectra by interactive computer graphics. J. Magn. Reson. 84, 627–633 (1989).

    CAS  Google Scholar 

  35. Kraulis, P.J., Domaille, P.J., Campbell-Burk, S.L., Van Aken, T. & Laue, E.D. Solution structure and dynamics of Ras p21-GDP determined by heteronuclear three- and four-dimensional NMR spectroscopy. Biochemistry 33, 3515–3531 (1994).

    Article  CAS  Google Scholar 

  36. Vranken, W.F. et al. The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins 59, 687–696 (2005).

    Article  CAS  Google Scholar 

  37. Johnson, B.A. & Blevins, R.A. NMR view: a computer program for the visualization and analysis of NMR data. J. Biomol. NMR 4, 603–614 (1994).

    Article  CAS  Google Scholar 

  38. Johnson, B.A. Using NMRView to visualize and analyze the NMR spectra of macromolecules. Methods Mol. Biol. 278, 313–352 (2004).

    CAS  PubMed  Google Scholar 

  39. Bartels, C., Xia, T., Billeter, M., Güntert, P. & Wüthrich, K. The program XEASY for computer-supported NMR spectral analysis of biological macromolecules. J. Biomol. NMR 6, 1–10 (1995).

    Article  CAS  Google Scholar 

  40. Shen, Y., Delaglio, F., Cornilescu, G. & Bax, A. TALOS+: a hybrid method for predicting protein backbone torsion angles from NMR chemical shifts. J. Biomol. NMR 44, 213–223 (2009).

    Article  CAS  Google Scholar 

  41. Jaravine, V.A. & Orekhov, V.Y. Targeted acquisition for real-time NMR spectroscopy. J. Am. Chem. Soc. 128, 13421–13426 (2006).

    Article  CAS  Google Scholar 

  42. Jaravine, V., Ibraghimov, I. & Orekhov, V.Y. Removal of a time barrier for high-resolution multidimensional NMR spectroscopy. Nat. Methods 3, 605–607 (2006).

    Article  CAS  Google Scholar 

  43. Marion, D. Fast acquisition of NMR spectra using Fourier transform of non-equispaced data. J. Biomol. NMR 32, 141–150 (2005).

    Article  CAS  Google Scholar 

  44. Kazimierczuk, K., Zawadzka, A., Kozminski, W. & Zhukov, I. Random sampling of evolution time space and Fourier transform processing. J. Biomol. NMR 36, 157–168 (2006).

    Article  CAS  Google Scholar 

  45. Takeda, M., Ikeya, T., Güntert, P. & Kainosho, M. Automated structure determination of proteins with the SAIL-FLYA NMR method. Nat. Protoc. 2, 2896–2902 (2007).

    Article  CAS  Google Scholar 

  46. Thorstenson, Y.R., Zhang, Y., Olson, P.S. & Mascarenhas, D. Leaderless polypeptides efficiently extracted from whole cells by osmotic shock. J. Bacteriol. 179, 5333–5339 (1997).

    Article  CAS  Google Scholar 

  47. Gardy, J.L. et al. PSORT-B: improving protein subcellular localization prediction for Gram-negative bacteria. Nucleic Acids Res. 31, 3613–3617 (2003).

    Article  CAS  Google Scholar 

  48. Gardy, J.L. et al. PSORTb v.2.0: expanded prediction of bacterial protein subcellular localization and insights gained from comparative proteome analysis. Bioinformatics 21, 617–623 (2005).

    Article  CAS  Google Scholar 

  49. Nielsen, H., Engelbrecht, J., Brunak, S. & von Heijne, G. Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites. Protein Eng. 10, 1–6 (1997).

    Article  CAS  Google Scholar 

  50. Bendtsen, J.D., Nielsen, H., von Heijne, G. & Brunak, S. Improved prediction of signal peptides: SignalP 3.0. J. Mol. Biol. 340, 783–795 (2004).

    Article  Google Scholar 

  51. Li, C. et al. Differential dynamical effects of macromolecular crowding on an intrinsically disordered protein and a globular protein: implications for in-cell NMR spectroscopy. J. Am. Chem. Soc. 130, 6310–6311 (2008).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank Professor Seiki Kuramitsu for providing the plasmid encoding TTHA1718. This work was supported in part by the CREST program of the Japan Science and Technology Agency (JST), the Molecular Ensemble Program of RIKEN, Grants-in-Aid for Scientific Research of Priority Areas from the Japanese Ministry of Education, Sports, Culture, Science, and Technology on 'Molecular Soft Interactions Regulating Membrane Interface of Biological Systems' and 'Molecular Science for Supra Functional Systems—Development of Advanced Methods for Exploring Elementary Process', and by the Volkswagen Foundation.

Author information

Authors and Affiliations

  1. Department of Chemistry, Tokyo Metropolitan University, Hachioji, Tokyo, Japan

    Teppei Ikeya, Atsuko Sasaki, Daisuke Sakakibara, Yoshiki Shigemitsu, Junpei Hamatsu, Tomomi Hanashima, Masaki Mishima, Peter Güntert & Yutaka Ito

  2. Center for Biomolecular Magnetic Resonance, Institute of Biophysical Chemistry, Goethe University, Frankfurt am Main, Germany

    Teppei Ikeya & Peter Güntert

  3. CREST, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan

    Atsuko Sasaki, Daisuke Sakakibara, Yoshiki Shigemitsu, Junpei Hamatsu, Masaki Mishima, Masahiro Shirakawa & Yutaka Ito

  4. Cellular and Molecular Biology Laboratory, RIKEN, Wako-shi, Saitama, Japan

    Masatoshi Yoshimasu

  5. Department of Life Science, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, Yokohama, Kanagawa, Japan

    Nobuhiro Hayashi

  6. Research Group for Bio-Supramolecular Structure-Function, RIKEN, Yokohama, Kanagawa, Japan

    Tsutomu Mikawa & Yutaka Ito

  7. Biometal Science Laboratory, RIKEN, Sayo-gun, Hyogo, Japan

    Tsutomu Mikawa & Yutaka Ito

  8. Department of Biochemistry, University of Cambridge, Cambridge, UK

    Daniel Nietlispach

  9. Bruker BioSpin, Yokohama, Kanagawa, Japan

    Markus Wälchli

  10. Division of Molecular and Cellular Biology, Faculty of Biomedical and Life Sciences, University of Glasgow, Glasgow, UK

    Brian O Smith

  11. Department of Molecular Engineering, Graduate School of Engineering, Kyoto University, Nishikyo-Ku, Kyoto, Japan

    Masahiro Shirakawa

  12. Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany

    Peter Güntert

Authors
  1. Teppei Ikeya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Atsuko Sasaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Daisuke Sakakibara
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yoshiki Shigemitsu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Junpei Hamatsu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tomomi Hanashima
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Masaki Mishima
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Masatoshi Yoshimasu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Nobuhiro Hayashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Tsutomu Mikawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Daniel Nietlispach
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Markus Wälchli
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Brian O Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Masahiro Shirakawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Peter Güntert
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Yutaka Ito
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

B.O.S., M.S., P.G. and Y.I. designed the research and wrote the article. T.I. developed the protocol for structure calculation and refinement. A.S., D.S., J.H., T.H., M.Y., N.H. and T.M. developed the protocols, including sample preparation and characterization, data acquisition and resonance assignment. Y.S., M.M., D.N. and M.W. contributed the protocol development for rapid NMR data acquisition and MaxEnt processing.

Corresponding author

Correspondence to Yutaka Ito.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ikeya, T., Sasaki, A., Sakakibara, D. et al. NMR protein structure determination in living E. coli cells using nonlinear sampling. Nat Protoc 5, 1051–1060 (2010). https://doi.org/10.1038/nprot.2010.69

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2010.69

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

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

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