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Metal-free ribonucleotide reduction powered by a DOPA radical in Mycoplasma pathogens

Naturevolume 563pages416420 (2018) | Download Citation

Abstract

Ribonucleotide reductase (RNR) catalyses the only known de novo pathway for the production of all four deoxyribonucleotides that are required for DNA synthesis1,2. It is essential for all organisms that use DNA as their genetic material and is a current drug target3,4. Since the discovery that iron is required for function in the aerobic, class I RNR found in all eukaryotes and many bacteria, a dinuclear metal site has been viewed as necessary to generate and stabilize the catalytic radical that is essential for RNR activity5,6,7. Here we describe a group of RNR proteins in Mollicutes—including Mycoplasma pathogens—that possess a metal-independent stable radical residing on a modified tyrosyl residue. Structural, biochemical and spectroscopic characterization reveal a stable 3,4-dihydroxyphenylalanine (DOPA) radical species that directly supports ribonucleotide reduction in vitro and in vivo. This observation overturns the presumed requirement for a dinuclear metal site in aerobic ribonucleotide reductase. The metal-independent radical requires new mechanisms for radical generation and stabilization, processes that are targeted by RNR inhibitors. It is possible that this RNR variant provides an advantage under metal starvation induced by the immune system. Organisms that encode this type of RNR—some of which are developing resistance to antibiotics—are involved in diseases of the respiratory, urinary and genital tracts. Further characterization of this RNR family and its mechanism of cofactor generation will provide insight into new enzymatic chemistry and be of value in devising strategies to combat the pathogens that utilize it. We propose that this RNR subclass is denoted class Ie.

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Data availability

Structures and crystallographic data have been deposited in the Protein Data Bank with the following codes: DOPA-active form, 6GP2; inactive form, 6GP3. All other data can be obtained from the corresponding author upon reasonable request.

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References

  1. 1.

    Hofer, A., Crona, M., Logan, D. T. & Sjöberg, B.-M. DNA building blocks: keeping control of manufacture. Crit. Rev. Biochem. Mol. Biol. 47, 50–63 (2012).

  2. 2.

    Nordlund, P. & Reichard, P. Ribonucleotide reductases. Annu. Rev. Biochem. 75, 681–706 (2006).

  3. 3.

    Mannargudi, M. B. & Deb, S. Clinical pharmacology and clinical trials of ribonucleotide reductase inhibitors: is it a viable cancer therapy? J. Cancer Res. Clin. Oncol. 143, 1499–1529 (2017).

  4. 4.

    Aye, Y., Li, M., Long, M. J. C. & Weiss, R. S. Ribonucleotide reductase and cancer: biological mechanisms and targeted therapies. Oncogene 34, 2011–2021 (2015).

  5. 5.

    Brown, N. C., Eliasson, R., Reichard, P. & Thelander, L. Nonheme iron as a cofactor in ribonucleotide reductase from E. coli. Biochem. Biophys. Res. Commun. 30, 522–527 (1968).

  6. 6.

    Lundin, D., Berggren, G., Logan, D. T. & Sjöberg, B.-M. The origin and evolution of ribonucleotide reduction. Life (Basel) 5, 604–636 (2015).

  7. 7.

    Huang, M., Parker, M. J. & Stubbe, J. Choosing the right metal: case studies of class I ribonucleotide reductases. J. Biol. Chem. 289, 28104–28111 (2014).

  8. 8.

    Nordlund, P., Sjöberg, B. M. & Eklund, H. Three-dimensional structure of the free radical protein of ribonucleotide reductase. Nature 345, 593–598 (1990).

  9. 9.

    Uhlin, U. & Eklund, H. Structure of ribonucleotide reductase protein R1. Nature 370, 533–539 (1994).

  10. 10.

    Stubbe, J., Nocera, D. G., Yee, C. S. & Chang, M. C. Y. Radical initiation in the class I ribonucleotide reductase: long-range proton-coupled electron transfer? Chem. Rev. 103, 2167–2202 (2003).

  11. 11.

    Cotruvo, J. A. & Stubbe, J. Class I ribonucleotide reductases: metallocofactor assembly and repair in vitro and in vivo. Annu. Rev. Biochem. 80, 733–767 (2011).

  12. 12.

    Högbom, M. Metal use in ribonucleotide reductase R2, di-iron, di-manganese and heterodinuclear—an intricate bioinorganic workaround to use different metals for the same reaction. Metallomics 3, 110–120 (2011).

  13. 13.

    Högbom, M. et al. The radical site in chlamydial ribonucleotide reductase defines a new R2 subclass. Science 305, 245–248 (2004).

  14. 14.

    Jiang, W. et al. A manganese(IV)/iron(III) cofactor in Chlamydia trachomatis ribonucleotide reductase. Science 316, 1188–1191 (2007).

  15. 15.

    Berggren, G., Lundin, D. & Sjöberg, B.-M. in Encyclopedia of Inorganic and Bioinorganic Chemistry (ed. Scott, R. A.) https://doi.org/10.1002/9781119951438.eibc2480 (American Cancer Society, 2017).

  16. 16.

    Rozman Grinberg, I. et al. Novel ATP-cone-driven allosteric regulation of ribonucleotide reductase via the radical-generating subunit. eLife 7, e31529 (2018).

  17. 17.

    Rose, H. et al. Structural basis for superoxide activation of Flavobacterium johnsoniae class I ribonucleotide reductase and for radical initiation by its dimanganese cofactor. Biochemistry 57, 2679–2693 (2018).

  18. 18.

    Cotruvo, J. A. Jr, Stich, T. A., Britt, R. D. & Stubbe, J. Mechanism of assembly of the dimanganese-tyrosyl radical cofactor of class Ib ribonucleotide reductase: enzymatic generation of superoxide is required for tyrosine oxidation via a Mn(III)Mn(IV) intermediate. J. Am. Chem. Soc. 135, 4027–4039 (2013).

  19. 19.

    Boal, A. K., Cotruvo, J. A. Jr, Stubbe, J. & Rosenzweig, A. C. Structural basis for activation of class Ib ribonucleotide reductase. Science 329, 1526–1530 (2010).

  20. 20.

    Berggren, G., Duraffourg, N., Sahlin, M. & Sjöberg, B.-M. Semiquinone-induced maturation of Bacillus anthracis ribonucleotide reductase by a superoxide intermediate. J. Biol. Chem. 289, 31940–31949 (2014).

  21. 21.

    Martin, J. E. & Imlay, J. A. The alternative aerobic ribonucleotide reductase of Escherichia coli, NrdEF, is a manganese-dependent enzyme that enables cell replication during periods of iron starvation. Mol. Microbiol. 80, 319–334 (2011).

  22. 22.

    Roca, I., Torrents, E., Sahlin, M., Gibert, I. & Sjöberg, B.-M. NrdI essentiality for class Ib ribonucleotide reduction in Streptococcus pyogenes. J. Bacteriol. 190, 4849–4858 (2008).

  23. 23.

    Hammerstad, M., Hersleth, H.-P., Tomter, A. B., Røhr, A. K. & Andersson, K. K. Crystal structure of Bacillus cereus class Ib ribonucleotide reductase di-iron NrdF in complex with NrdI. ACS Chem. Biol. 9, 526–537 (2014).

  24. 24.

    Land, E. J. & Porter, G. Primary photochemical processes in aromatic molecules. Part 7.—spectra and kinetics of some phenoxyl derivatives. Trans. Faraday Soc. 59, 2016–2026 (1963).

  25. 25.

    Sahlin, M. et al. Magnetic interaction between the tyrosyl free radical and the antiferromagnetically coupled iron center in ribonucleotide reductase. Biochemistry 26, 5541–5548 (1987).

  26. 26.

    Ehrenberg, A. & Reichard, P. Electron spin resonance of the iron-containing protein B2 from ribonucleotide reductase. J. Biol. Chem. 247, 3485–3488 (1972).

  27. 27.

    Thelander, L., Larsson, B., Hobbs, J. & Eckstein, F. Active site of ribonucleoside diphosphate reductase from Escherichia coli. Inactivation of the enzyme by 2′-substituted ribonucleoside diphosphates. J. Biol. Chem. 251, 1398–1405 (1976).

  28. 28.

    Eliasson, R., Pontis, E., Eckstein, F. & Reichard, P. Interactions of 2′-modified azido- and haloanalogs of deoxycytidine 5′-triphosphate with the anaerobic ribonucleotide reductase of Escherichia coli. J. Biol. Chem. 269, 26116–26120 (1994).

  29. 29.

    Sjöberg, B. M., Gräslund, A. & Eckstein, F. A substrate radical intermediate in the reaction between ribonucleotide reductase from Escherichia coli and 2′-azido-2′-deoxynucleoside diphosphates. J. Biol. Chem. 258, 8060–8067 (1983).

  30. 30.

    Seyedsayamdost, M. R. & Stubbe, J. Site-specific replacement of Y356 with 3,4-dihydroxyphenylalanine in the β2 subunit of E. coli ribonucleotide reductase. J. Am. Chem. Soc. 128, 2522–2523 (2006).

  31. 31.

    Sjöberg, B. M., Reichard, P., Gräslund, A. & Ehrenberg, A. The tyrosine free radical in ribonucleotide reductase from Escherichia coli. J. Biol. Chem. 253, 6863–6865 (1978).

  32. 32.

    Hood, M. I. & Skaar, E. P. Nutritional immunity: transition metals at the pathogen–host interface. Nat. Rev. Microbiol. 10, 525–537 (2012).

  33. 33.

    Eddy, S. R. Accelerated profile HMM searches. PLoS Comput. Biol. 7, e1002195 (2011).

  34. 34.

    Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).

  35. 35.

    Do, C. B., Mahabhashyam, M. S. P., Brudno, M. & Batzoglou, S. ProbCons: probabilistic consistency-based multiple sequence alignment. Genome Res. 15, 330–340 (2005).

  36. 36.

    Criscuolo, A. & Gribaldo, S. BMGE (Block Mapping and Gathering with Entropy): a new software for selection of phylogenetic informative regions from multiple sequence alignments. BMC Evol. Biol. 10, 210 (2010).

  37. 37.

    Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).

  38. 38.

    Loderer, C. et al. A unique cysteine-rich zinc finger domain present in a majority of class II ribonucleotide reductases mediates catalytic turnover. J. Biol. Chem. 292, 19044–19054 (2017).

  39. 39.

    Kabsch, W. XDS. Acta Crystallogr. D 66, 125–132 (2010).

  40. 40.

    McCoy, A. J. et al. Phaser crystallographic software. J. Appl. Crystallogr. 40, 658–674 (2007).

  41. 41.

    Andersson, M. E. et al. Structural and mutational studies of the carboxylate cluster in iron-free ribonucleotide reductase R2. Biochemistry 43, 7966–7972 (2004).

  42. 42.

    Adams, P. D. et al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D 66, 213–221 (2010).

  43. 43.

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

  44. 44.

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

  45. 45.

    Krissinel, E. & Henrick, K. Secondary-structure matching (SSM), a new tool for fast protein structure alignment in three dimensions. Acta Crystallogr. D 60, 2256–2268 (2004).

  46. 46.

    Sjöberg, B. M., Reichard, P., Gräslund, A. & Ehrenberg, A. Nature of the free radical in ribonucleotide reductase from Escherichia coli. J. Biol. Chem. 252, 536–541 (1977).

  47. 47.

    Reijerse, E., Lendzian, F., Isaacson, R. & Lubitz, W. A tunable general purpose Q-band resonator for CW and pulse EPR/ENDOR experiments with large sample access and optical excitation. J. Magn. Reson. 214, 237–243 (2012).

  48. 48.

    Franke, D. et al. ATSAS 2.8: a comprehensive data analysis suite for small-angle scattering from macromolecular solutions. J. Appl. Crystallogr. 50, 1212–1225 (2017).

  49. 49.

    Konarev, P. V., Volkov, V. V., Sokolova, A. V., Koch, M. H. J. & Svergun, D. I. PRIMUS: A Windows PC-based system for small-angle scattering data analysis. J. Appl. Crystallogr. 36, 1277–1282 (2003).

  50. 50.

    Franke, D. & Svergun, D. I. DAMMIF, a program for rapid ab-initio shape determination in small-angle scattering. J. Appl. Crystallogr. 42, 342–346 (2009).

  51. 51.

    Volkov, V. V. & Svergun, D. I. Uniqueness of ab initio shape determination in small-angle scattering. J. Appl. Crystallogr. 36, 860–864 (2003).

  52. 52.

    Svergun, D., Barberato, C. & Koch, M. H. CRYSOL - a program to evaluate X-ray solution scattering of biological macromolecules from atomic coordinates. J. Appl. Crystallogr. 28, 768–773 (1995).

  53. 53.

    Sielaff, M. et al. Evaluation of FASP, SP3, and iST protocols for proteomic sample preparation in the low microgram range. J. Proteome Res. 16, 4060–4072 (2017).

  54. 54.

    Hughes, C. S. et al. Ultrasensitive proteome analysis using paramagnetic bead technology. Mol. Syst. Biol. 10, 757 (2014).

  55. 55.

    Eng, J. K., McCormack, A. L. & Yates, J. R. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5, 976–989 (1994).

  56. 56.

    Na, S., Bandeira, N. & Paek, E. Fast multi-blind modification search through tandem mass spectrometry. Mol. Cell Proteomics 11, M111.010199 (2012).

  57. 57.

    Chambers, M. C. et al. A cross-platform toolkit for mass spectrometry and proteomics. Nat. Biotechnol. 30, 918–920 (2012).

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Acknowledgements

We would like to acknowledge the foundational contributions of the late P. Reichard to the RNR field. We thank J. Imlay for the gift of the E. coli (∆nrdAB, ∆nrdEF) strain, K. Andersson and M. Hammerstad for the pET-22bBcnrdF plasmid and E. Torrents for the pBAD18 plasmid. Financial support to M.H. was provided by the Swedish Research Council (2017-04018), the European Research Council (HIGH-GEAR 724394), and the Knut and Alice Wallenberg Foundation (Wallenberg Academy Fellows (2012.0233 and 2017.0275)); to B.-M.S. by the Swedish Research Council (2016-01920), the Swedish Cancer Foundation (CAN 2016/670), and the Wenner-Gren Foundations; and to N.C. by the Australian Research Council (FT140100834) and the Max Planck Society. We thank the Diamond Light Source for beamtime (proposals mx11265 and mx15806) and particularly the staff from beamlines I24 and B21.

Reviewer information

Nature thanks C. Dealwis, M. Fontecave and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Author notes

  1. These authors contributed equally: Vivek Srinivas, Hugo Lebrette

Affiliations

  1. Department of Biochemistry and Biophysics, Stockholm University, Arrhenius Laboratories for Natural Sciences, Stockholm, Sweden

    • Vivek Srinivas
    • , Hugo Lebrette
    • , Daniel Lundin
    • , Margareta Sahlin
    • , Michael Lerche
    • , Britt-Marie Sjöberg
    •  & Martin Högbom
  2. Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr, Mülheim an der Ruhr, Germany

    • Yuri Kutin
  3. Cancer Proteomics Mass Spectrometry, Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, Solna, Sweden

    • Jürgen Eirich
    •  & Rui M. M. Branca
  4. Research School of Chemistry, Australian National University, Canberra, Australian Capital Territory, Australia

    • Nicholas Cox
  5. Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    • Martin Högbom

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Contributions

B.-M.S. and M.H. conceived and led the study. D.L. performed bioinformatics. V.S. carried out cloning and generated operon constructs. V.S. and H.L. performed protein production, in vivo and in vitro activity assays, TXRF analysis, crystallography and sample preparation for all other methods. Y.K., M.S. and N.C. performed spectroscopy. M.L. performed SAXS experiments. J.E. and R.M.M.B. performed mass spectrometry. All authors were involved in experiment design and data analysis. M.H. wrote the manuscript with substantial input from all authors.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Martin Högbom.

Extended data figures and tables

  1. Extended Data Fig. 1 Unrooted maximum-likelihood phylogeny of representative NrdF (RNR subclass Ib radical-generating subunit) sequences.

    All RefSeq NrdF sequences were clustered at 75% identity to reduce redundancy and a maximum-likelihood phylogeny was estimated. Sequences with non-canonical amino acids in the positions involved in coordinating the metal centre of the enzyme formed a well-supported clan in the NrdF2 group of sequences. We identified two variants, one in which three of the glutamates were replaced by glutamine, serine and lysine (NrdF2.QSK) and the other in which they were replaced by valine, proline and lysine (NrdF2.VPK). Both variants thus have a substitution of a lysine for the normally metal-bridging glutamine (residue 213 in M. florum NrdF2.VPK). Together, the two variants form a well-supported (96% bootstrap support) clan in the phylogeny inside the NrdF2 diversity. The NrdF2.VPK clan seems to be derived from the NrdF2.QSK clan. Behind the sequences in the tree are a set of sequences that are more than 75% identical to each represented sequence. The VPK and QSK sequences in the phylogeny represent 138 and 182 sequences in RefSeq, respectively.

  2. Extended Data Fig. 2 Small-angle X-ray scattering characterization of the MfR2–NrdI complex.

    Solution scattering data for MfR2 (left) and MfR2 incubated with MfNrdI (right). a, Experimental solution scattering profiles (black spheres) for MfR2 alone and incubated with MfNrdI superimposed with the theoretical scattering profile of the MfR2 crystal structure (red line) and the theoretical scattering profile from the homology model based on the E. coli R2-NrdI complex structure (blue line). Theoretical scattering curves and goodness of fit values were calculated using CRYSOL. b, Guinier fit and p(r) function of MfR2 alone and incubated with MfNrdI. The fit to the data are shown as an orange line. The shift in invariant parameters Rg and Dmax indicate that an increase in dimensions occurred as MfR2 was incubated with MfNrdI. Radius of gyration statistics were derived from 60 data points within the Guinier region for MfR2 and 55 for MfNrdI–MfR2. c, Ab initio models (calculated using DAMMIF) of both MfR2 alone and with NrdI (grey surface) overlaid with the crystal structure of MfR2 (left) and the homology model based on the E. coli R2–NrdI complex structure model (right).

  3. Extended Data Fig. 3 Metal analysis and radical generation in the presence of a chelator.

    a, Representative TXRF spectra measured for MfR2 (blue, at 664 µM) and Fe-reconstituted class Ia EcR2 (orange, at 635 µM), on the 5–10 keV energy range. The spectra have been scaled using the peak size of the Ga internal standard and offset slightly in the y direction for clarity. K-level X-ray emission lines are indicated with arrows. For elements, in which both Kα and Kβ lines are present, they are specified. Otherwise, arrows indicate Kα lines. Experiments were repeated three times. b, Concentrations of Mn, Fe, Co, Ni, Cu and Zn were measured in the active MfR2, MfNrdI and MfR1 protein solutions and in their respective buffers, as well as in a solution of E. coli class Ia R2 protein reconstituted with Fe in vitro. Mean concentrations and s.d. of measurements on three independently prepared samples for each sample are reported. The concentrations were converted to metal-to-protein molar ratio. The measurements show that none of the MfRNR proteins contain a substantial amount of metal, as opposed to EcR2a which, as expected, contains in the order of two metal ions per monomer also after a desalting step. Buffer 1 is the buffer system used for MfR2; that is, 25 mM HEPES-Na pH 7, 50 mM NaCl. Buffer 2 is the buffer system used for MfR1 and MfNrdI; that is, 25 mM Tris-HCl pH 8, 50 mM NaCl. The protein purification involves a nickel-affinity step, which is probably the reason for nickel being the dominant metal species in the sample. c, HPLC-based in vitro assays show that RNR activity can be restored after MfR2 is quenched by hydroxyurea. MfR2 is regenerated by the addition of MfNrdI followed by redox cycling with dithionite- and oxygen-containing buffer (green) (see main Fig. 2d). Reactivation and activity are observed also in the presence of a metal chelator (EDTA 0.3 mM, blue). Addition of extra metals (0.2 mM of each Mn, Fe, Co, Ni, Cu, Zn) does not improve the activity recovery (pink).

  4. Extended Data Fig. 4 Mass spectrometric characterization of intact proteins.

    Intact protein mass spectra obtained from purified MfR2 proteins. Inactive protein (top) and active protein (bottom). Insets represent the decharged and deisotoped mass as calculated by the program Protein Deconvolution (version 4.0) using the ReSpect algorithm therein. The result from the deconvolution of n = 30 consecutive scans in one LC–MS run per protein form is shown. Each protein form was analysed in duplicate LC–MS runs. Protein intact masses are given as mean ± s.d. The s.d. was 1.4 Da for the inactive protein and 2 Da for the active form. The results show that the active protein is 17 ± 2 Da heavier than the inactive MfR2.

  5. Extended Data Fig. 5 MS2 fragmentation spectra of peptides with oxidized tyrosine.

    a, c, Annotated MS2 fragmentation spectra and respective theoretical fragment ion tables of the doubly charged precursor ion 661.8458 m/z corresponding to peptide VAVHARSY(+15.995)GSIF (a) and the doubly charged precursor ion 458.7279 m/z corresponding to peptide ARSY(+15.995)GSIF (c) both with the oxidized (+16) Y126 residue. The peptides shown in a and c were obtained by proteolytic digestion of the active form of the MfR2 protein with chymotrypsin and pepsin, respectively. The mass error is typically less than 0.01 m/z, in accordance with the high resolution used (15,000). Errors in p.p.m. are indicated for the corresponding fragment ions when detected. Among the fragment ions observed, the most relevant are the b7 and b8 ions for the peptide shown in a. The experimental m/z values, the annotation, theoretical m/z values and p.p.m. errors are shown in b, including the peaks for the corresponding isotope envelope. In d the Y(+O) immonium ion for c is shown, demonstrating that Tyr126 is modified by a mass of +15.995 and the absence of the corresponding immonium ion for the unmodified Y. Four independent experiments per peptidase treatment were performed, confirming the modified peptide sequences shown. Figures are taken from one representative experiment.

  6. Extended Data Fig. 6 Radical stability and isotope labelling.

    a, Superimposed UV–vis absorption spectra at time points between 0 and 400 min. Inset, absorbance at 383 nm at 0, 4, 129, 140, 210 and 400 min. Experiments were repeated three times. b, X-band spectra of the radical observed in collected cells grown in minimal medium supplemented with deuterated amino acids. EDTA (0.5 mM) was added before induction. From top: non-labelled tyrosine, β,β-d2 tyrosine, 3,5-d2 tyrosine, indole-d5 tryptophan and d5 glycine. The doublet signal collapses to a singlet when β,β-deuterated tyrosine is incorporated in the protein. Furthermore, the additional coupling to the remaining 3 or 5 proton in the 3,5-d2 tyrosine grown cells disappears, which is also in line with the radical being tyrosine-derived. Finally, the exclusion of tryptophan and glycine as source for the observed radical is evident from the two lower traces in the figure, which are identical to the top spectrum. Five independent cultures were grown, each including one of the indicated deuterated amino acids. Spectra were recorded at 100 K in a nitrogen-flow system. The spectra have been normalized to the same double integrals; that is, the same number of spins in the cavity.

  7. Extended Data Fig. 7 EPR and ENDOR characterization.

    See Supplementary Information. a, Q-band ENDOR and HYSCORE spectra of the spectral region in which an 14N hyperfine coupling should be observed. Experimental parameters are listed in Methods. b, Full multifrequency (X-band, top left; Q-band, bottom left) EPR dataset and corresponding field dependent Q-band ENDOR spectra (right). Experimental parameters are listed in Methods. The red dashed lines represent a simultaneous simulation of all datasets using the spin Hamiltonian formalism. Simulation parameters are listed in Supplementary Table 1. c, Inferred orientation (θ1, θ2) of the Cβ protons relative to the phenoxyl radical ring plane as determined by the dihedral angle (ϕ) between the ring plane (C1) and Cα. d, Candidates proposed for the MfR2 radical species, see Supplementary Information. All ENDOR measurements were repeated at a second microwave frequency (W-band) giving similar results. Pulse EPR and ENDOR measurements represent extensive data accumulations or averages. EPR: 300 averages (6 scans/50 shots). ENDOR: 600 averages (600 scans/1 shot).

  8. Extended Data Fig. 8 EPR saturation.

    EPR saturation behaviour of the MfR2 radical at 103 and 298 K. Saturation curves at different temperatures determine the microwave power at half saturation P1/2. The temperature dependence of P1/2 gives information about possible relaxing transition metals in the vicinity of the radical. A fast-relaxing metal site will give a higher P1/2 than an isolated radical. The microwave saturation behaviour of the MfR2 is similar to that for an irradiated tyrosine solution. Here we evaluate P1/2 ≈ 0.6 mW at 103 K and P1/2 ≈ 30 mW at 298 K for MfR2. This can be compared to irradiated Tyr with P1/2 ≈ 0.4 mW at 93 K and E. coli Tyr with P1/2 ≈ 150 mW at 106 K and not possible to saturate at 298 K.

  9. Extended Data Fig. 9 Primers and operon construct.

    a, Primers used in this study. b, Construction of the M. florum class Ie RNR operon.

  10. Extended Data Table 1 Data collection and refinement statistics

Supplementary information

  1. Supplementary Information

    This file contains supplementary text; which includes supplementary tables 1-3.

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https://doi.org/10.1038/s41586-018-0653-6

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