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:

Computational identification of a systemic antibiotic for Gram-negative bacteria

Nature Microbiology volume 7, pages 1661–1672 (2022)Cite this article

Subjects

Abstract

Discovery of antibiotics acting against Gram-negative species is uniquely challenging due to their restrictive penetration barrier. BamA, which inserts proteins into the outer membrane, is an attractive target due to its surface location. Darobactins produced by Photorhabdus, a nematode gut microbiome symbiont, target BamA. We reasoned that a computational search for genes only distantly related to the darobactin operon may lead to novel compounds. Following this clue, we identified dynobactin A, a novel peptide antibiotic from Photorhabdus australis containing two unlinked rings. Dynobactin is structurally unrelated to darobactins, but also targets BamA. Based on a BamA-dynobactin co-crystal structure and a BAM-complex-dynobactin cryo-EM structure, we show that dynobactin binds to the BamA lateral gate, uniquely protruding into its β-barrel lumen. Dynobactin showed efficacy in a mouse systemic Escherichia coli infection. This study demonstrates the utility of computational approaches to antibiotic discovery and suggests that dynobactin is a promising lead for drug development.

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: Schematic overview of the workflow.
Fig. 2: Phylogenetic tree of rSAM-SPASM enzymes.
Fig. 3: Identification of dynobactin A from P. australis.
Fig. 4: Dynobactin A binds BamA lateral gate.
Fig. 5: Efficacy of dynobactin A.

Similar content being viewed by others

Data availability

Data supporting the findings of this study are available within the paper and its

Supplementary Information, and have been submitted to publicly available databases. Crystal structures are available through PDB: microED dynobactin A structure (7T3H), BamA:dynobactin A X-ray co-crystal (7R1V), BAM complex:dynobactin A cryo-EM (7R1W, EMD-14242). Any other data or datasets from the current study are available upon reasonable request to the corresponding authors.

References

  1. Brown, E. D. & Wright, G. D. Antibacterial drug discovery in the resistance era. Nature 529, 336–343 (2016).

    Article  CAS  PubMed  Google Scholar 

  2. Lewis, K. The science of antibiotic discovery. Cell 181, 29–45 (2020).

    Article  CAS  PubMed  Google Scholar 

  3. Ling, L. L. et al. A new antibiotic kills pathogens without detectable resistance. Nature 517, 455–459 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Tacconelli, E. et al. Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis. Lancet Infect. Dis. 18, 318–327 (2018).

    Article  PubMed  Google Scholar 

  5. Zgurskaya, H. I., Rybenkov, V. V., Krishnamoorthy, G. & Leus, I. V. Trans-envelope multidrug efflux pumps of Gram-negative bacteria and their synergism with the outer membrane barrier. Res. Microbiol. 169, 351–356 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Richter, M. F. et al. Predictive compound accumulation rules yield a broad-spectrum antibiotic. Nature 545, 299–304 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Parker, E. N. et al. Implementation of permeation rules leads to a FabI inhibitor with activity against Gram-negative pathogens. Nat. Microbiol. 5, 67–75 (2020).

    Article  CAS  PubMed  Google Scholar 

  8. Gavrish, E. et al. Lassomycin, a ribosomally synthesized cyclic peptide, kills Mycobacterium tuberculosis by targeting the ATP-dependent protease ClpC1P1P2. Chem. Biol. 21, 509–518 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Quigley, J. et al. Novel antimicrobials from uncultured bacteria acting against Mycobacterium tuberculosis. mBio https://doi.org/10.1128/mBio.01516-20 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Shahsavari, N. et al. A silent operon of Photorhabdus luminescens encodes a prodrug mimic of GTP. mBio https://doi.org/10.1128/mbio.00700-22 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Leimer, N. et al. A selective antibiotic for lyme disease. Cell https://doi.org/10.1016/j.cell.2021.09.011 (2021).

    Article  PubMed  Google Scholar 

  12. Crawford, J. M. & Clardy, J. Bacterial symbionts and natural products. Chem. Commun. 47, 7559–7566 (2011).

    Article  CAS  Google Scholar 

  13. Tobias, N. J., Shi, Y. M. & Bode, H. B. Refining the natural product repertoire in entomopathogenic bacteria. Trends Microbiol. 26, 833–840 (2018).

    Article  CAS  PubMed  Google Scholar 

  14. Imai, Y. et al. A new antibiotic selectively kills Gram-negative pathogens. Nature 576, 459–464 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Kaur, H. et al. The antibiotic darobactin mimics a beta-strand to inhibit outer membrane insertase. Nature 593, 125–129 (2021).

    Article  CAS  PubMed  Google Scholar 

  16. Rutledge, P. J. & Challis, G. L. Discovery of microbial natural products by activation of silent biosynthetic gene clusters. Nat. Rev. Microbiol. 13, 509–523 (2015).

    Article  CAS  PubMed  Google Scholar 

  17. Hover, B. M. et al. Culture-independent discovery of the malacidins as calcium-dependent antibiotics with activity against multidrug-resistant Gram-positive pathogens. Nat. Microbiol. 3, 415–422 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Stokes, J. M. et al. A deep learning approach to antibiotic discovery. Cell 180, 688–702.e13 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    Article  CAS  PubMed  Google Scholar 

  20. Santos-Aberturas, J. et al. Uncovering the unexplored diversity of thioamidated ribosomal peptides in Actinobacteria using the RiPPER genome mining tool. Nucleic Acids Res. 47, 4624–4637 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7, 539 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Grell, T. A., Goldman, P. J. & Drennan, C. L. SPASM and twitch domains in S-adenosylmethionine (SAM) radical enzymes. J. Biol. Chem. 290, 3964–3971 (2015).

    Article  CAS  PubMed  Google Scholar 

  23. Montalbán-López, M. et al. New developments in RiPP discovery, enzymology and engineering. Nat. Prod. Rep. 38, 130–239 (2021).

    Article  PubMed  Google Scholar 

  24. Akiva, E. et al. The structure–function linkage database. Nucleic Acids Res. 42, D521–D530 (2014).

    Article  CAS  PubMed  Google Scholar 

  25. Grove, T. L., Lee, K. H., St Clair, J., Krebs, C. & Booker, S. J. In vitro characterization of AtsB, a radical SAM formylglycine-generating enzyme that contains three [4Fe-4S] clusters. Biochemistry 47, 7523–7538 (2008).

    Article  CAS  PubMed  Google Scholar 

  26. Goldman, P. J. et al. X-ray structure of an AdoMet radical activase reveals an anaerobic solution for formylglycine posttranslational modification. Proc. Natl Acad. Sci. USA 110, 8519–8524 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Zhang, Q., Mo, T., Ding, W., Han, Y. & Deng, Z. The research on post-translational modification of RiPPs Xye catalyzed by CyFE PacB. Synth. Biol. J. https://doi.org/10.12211/2096-8280.2021-080 (2021).

    Article  Google Scholar 

  28. Vesth, T. et al. Veillonella, firmicutes: microbes disguised as gram negatives. Stand. Genom. Sci. 9, 431–448 (2013).

    Article  Google Scholar 

  29. Antunes, L. C. et al. Phylogenomic analysis supports the ancestral presence of LPS-outer membranes in the Firmicutes. eLife 5, e14589 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Wang, M. et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat. Biotechnol. 34, 828–837 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Jones, C. G. et al. The CryoEM method MicroED as a powerful tool for small molecule structure determination. ACS Cent. Sci. 4, 1587–1592 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Haupert, L. M. & Simpson, G. J. Screening of protein crystallization trials by second order nonlinear optical imaging of chiral crystals (SONICC). Methods 55, 379–386 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Nguyen, T. Q. N. et al. Post-translational formation of strained cyclophanes in bacteria. Nat. Chem. 12, 1042–1053 (2020).

    Article  CAS  PubMed  Google Scholar 

  34. Matsunaga, S. & Fusetani, N. Theonellamides AE, cytotoxic bicyclic peptides, from a marine sponge Theonella sp. J. Org. Chem. 60, 1177–1181 (1995).

    Article  CAS  Google Scholar 

  35. Nicolet, Y. Structure–function relationships of radical SAM enzymes. Nat. Catal. 3, 337–350 (2020).

    Article  CAS  Google Scholar 

  36. Benjdia, A., Balty, C. & Berteau, O. Radical SAM enzymes in the biosynthesis of ribosomally synthesized and post-translationally modified peptides (RiPPs). Front. Chem. 5, 87 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Yu, D. et al. An efficient recombination system for chromosome engineering in Escherichia coli. Proc. Natl Acad. Sci. USA 97, 5978–5983 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Datsenko, K. A. & Wanner, B. L. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc. Natl Acad. Sci. USA 97, 6640–6645 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Kaur, H. et al. Identification of conformation-selective nanobodies against the membrane protein insertase BamA by an integrated structural biology approach. J. Biomol. NMR https://doi.org/10.1007/s10858-019-00250-8 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Rath, P. et al. High-throughput screening of BAM inhibitors in native membrane environment. Nat. Commun. Preprint at https://doi.org/10.21203/rs.3.rs-1465417/v1 (2022).

  41. Kloser, A., Laird, M., Deng, M. & Misra, R. Modulations in lipid A and phospholipid biosynthesis pathways influence outer membrane protein assembly in Escherichia coli K‐12. Mol. Microbiol. 27, 1003–1008 (1998).

    Article  CAS  PubMed  Google Scholar 

  42. Koronakis, V., Sharff, A., Koronakis, E., Luisi, B. & Hughes, C. Crystal structure of the bacterial membrane protein TolC central to multidrug efflux and protein export. Nature 405, 914–919 (2000).

    Article  CAS  PubMed  Google Scholar 

  43. Webber, M. A. & Piddock, L. J. The importance of efflux pumps in bacterial antibiotic resistance. J. Antimicrob. Chemother. 51, 9–11 (2003).

    Article  CAS  PubMed  Google Scholar 

  44. Jaffe, A., Chabbert, Y. A. & Semonin, O. Role of porin proteins OmpF and OmpC in the permeation of beta-lactams. Antimicrob. Agents Chemother. 22, 942–948 (1982).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Srinivas, N. et al. Peptidomimetic antibiotics target outer-membrane biogenesis in Pseudomonas aeruginosa. Science 327, 1010–1013 (2010).

    Article  CAS  PubMed  Google Scholar 

  46. Silver, L. L. A Gestalt approach to Gram-negative entry. Bioorg. Med. Chem. 24, 6379–6389 (2016).

    Article  CAS  PubMed  Google Scholar 

  47. Konovalova, A., Kahne, D. E. & Silhavy, T. J. Outer membrane biogenesis. Annu. Rev. Microbiol. 71, 539–556 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Melchers, M. J. et al. Pharmacokinetics and pharmacodynamics of murepavadin in neutropenic mouse models. Antimicrob. Agents Chemother. 63, e01699–01618 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Luther, A. et al. Chimeric peptidomimetic antibiotics against Gram-negative bacteria. Nature 576, 452–458 (2019).

    Article  CAS  PubMed  Google Scholar 

  50. Hart, E. M. et al. A small-molecule inhibitor of BamA impervious to efflux and the outer membrane permeability barrier. Proc. Natl Acad. Sci. USA 116, 21748–21757 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Storek, K. M. et al. Monoclonal antibody targeting the beta-barrel assembly machine of Escherichia coli is bactericidal. Proc. Natl Acad. Sci. USA 115, 3692–3697 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Johnston, C. W. et al. Assembly and clustering of natural antibiotics guides target identification. Nat. Chem. Biol. 12, 233–239 (2016).

    Article  CAS  PubMed  Google Scholar 

  53. O’Shea, R. & Moser, H. E. Physicochemical properties of antibacterial compounds: implications for drug discovery. J Med. Chem. 51, 2871–2878 (2008).

    Article  PubMed  Google Scholar 

  54. Nikaido, H. Molecular basis of bacterial outer membrane permeability revisited. Microbiol. Mol. Biol. Rev. 67, 593–656 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Lundquist, K., Bakelar, J., Noinaj, N. & Gumbart, J. C. C-terminal kink formation is required for lateral gating in BamA. Proc. Natl Acad. Sci. USA 115, E7942–E7949 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Sayers, E. W. et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 49, D10–D17 (2021).

    Article  CAS  PubMed  Google Scholar 

  57. Groß, S. et al. Improved broad-spectrum antibiotics against Gram-negative pathogens via darobactin biosynthetic pathway engineering. Chem. Sci. 12, 11882–11893 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Okonechnikov, K., Golosova, O., Fursov, M. & Team, U. Unipro UGENE: a unified bioinformatics toolkit. Bioinformatics 28, 1166–1167 (2012).

    Article  CAS  PubMed  Google Scholar 

  59. Luft, J. R. et al. A deliberate approach to screening for initial crystallization conditions of biological macromolecules. J. Struct. Biol. 142, 170–179 (2003).

    Article  CAS  PubMed  Google Scholar 

  60. Zhao, J. et al. A simple pressure-assisted method for MicroED specimen preparation. Nat. Commun. 12, 5036 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Kabsch, W. X. D. S. Acta Crystallogr. D 66, 125–132 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Sheldrick, G. M. SHELXT - integrated space-group and crystal-structure determination. Acta Crystallogr. A 71, 3–8 (2015).

    Article  Google Scholar 

  63. Fujii, K., Ikai, Y., Oka, H. & Suzuki, M. & Harada, K. A nonempirical method using LC/MS for determination of the absolute configuration of constituent amino acids in a peptide: combination of Marfey’s method with mass spectrometry and its practical application. Anal. Chem. 69, 5146–5151 (1997).

    Article  CAS  Google Scholar 

  64. Bibow, S., Bohm, R., Modaresi, S. M. & Hiller, S. Detergent titration as an efficient method for NMR resonance assignments of membrane proteins in lipid-bilayer nanodiscs. Anal. Chem. 92, 7786–7793 (2020).

    Article  CAS  PubMed  Google Scholar 

  65. Lee, W., Tonelli, M. & Markley, J. L. NMRFAM-SPARKY: enhanced software for biomolecular NMR spectroscopy. Bioinformatics 31, 1325–1327 (2015).

    Article  PubMed  Google Scholar 

  66. Hartmann, J. B., Zahn, M., Burmann, I. M., Bibow, S. & Hiller, S. Sequence-specific solution NMR assignments of the beta-barrel insertase BamA to monitor its conformational ensemble at the atomic level. J. Am. Chem. Soc. 140, 11252–11260 (2018).

    Article  CAS  PubMed  Google Scholar 

  67. Evans, P. R. & Murshudov, G. N. How good are my data and what is the resolution? Acta Crystallogr. D 69, 1204–1214 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  70. Schuttelkopf, A. W. & van Aalten, D. M. PRODRG: a tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallogr. D 60, 1355–1363 (2004).

    Article  PubMed  Google Scholar 

  71. Adams, P. D. et al. PHENIX: building new software for automated crystallographic structure determination. Acta Crystallogr. D 58, 1948–1954 (2002).

    Article  PubMed  Google Scholar 

  72. 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 

  73. 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 

  74. Pettersen, E. F. et al. UCSF ChimeraX: structure visualization for researchers, educators, and developers. Protein Sci. 30, 70–82 (2021).

    Article  CAS  PubMed  Google Scholar 

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

    Article  PubMed  Google Scholar 

  76. 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 

  77. 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 

  78. 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 

  79. Thoma, J. et al. Protein-enriched outer membrane vesicles as a native platform for outer membrane protein studies. Commun. Biol. 1, 23 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Hagan, C. L., Kim, S. & Kahne, D. Reconstitution of outer membrane protein assembly from purified components. Science 328, 890–892 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Photorhabdus australis isolates were kindly shared by N. Waterfield at the University of Warwick as well as by A. Thanwisai from Naresuan University.

Crystallization screening at the National Crystallization Center at HWI was supported through NIH grant R24GM141256.

B.-K.Y. thanks L. M. Henling for fruitful discussions. The microED data were collected at the Caltech cryo-EM facility. We thank S. Chen for assistance and the Beckman Institute for their generous support of the cryo-EM facility and the Molecular Observatory at Caltech;

the Korea Basic Science Institute, Ochang, Korea, for providing NMR (900 MHz) data;

the staff of beamlines X06DA and X06SA at the Paul Scherrer Institute, Villigen, Switzerland, for support with crystallographic data collection; and the BioEM lab of the University of Basel for support with cryo-EM data acquisition. Calculations were performed at sciCORE (http://scicore.unibas.ch/) scientific computing core facility at the University of Basel.

This project was supported by the National Institutes of Health grant P01 AI118687 (K.L.), the Swiss National Science Foundation grants 177084 (T.M.) and 187170 (S.H.), and the National Center of Competence in Research AntiResist (180541).

Author information

Author notes

  1. These authors contributed equally: Ryan D. Miller, Akira Iinishi, Seyed Majed Modaresi, Byung-Kuk Yoo.

Authors and Affiliations

  1. Antimicrobial Discovery Center, Department of Biology, Northeastern University, Boston, MA, USA

    Ryan D. Miller, Akira Iinishi, Thomas D. Curtis, Patrick J. Lariviere, Libang Liang, Sangkeun Son, Samantha Nicolau, Rachel Bargabos, Madeleine Morrissette, Michael F. Gates, Norman Pitt, Samantha Niles, Blake Karavas, Meghan Ghiglieri & Kim Lewis

  2. Biozentrum, University of Basel, Basel, Switzerland

    Seyed Majed Modaresi, Roman P. Jakob, Parthasarathi Rath, Timm Maier & Sebastian Hiller

  3. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA

    Byung-Kuk Yoo & Douglas C. Rees

  4. Beckman Institute, California Institute of Technology, Pasadena, CA, USA

    Andrey G. Malyutin & Jens T. Kaiser

  5. National Crystallization Center, Hauptman-Woodward Medical Research Institute, Buffalo, NY, USA

    Sarah E. J. Bowman

  6. Howard Hughes Medical Institute, California Institute of Technology, Pasadena, CA, USA

    Douglas C. Rees

Authors
  1. Ryan D. Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Akira Iinishi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Seyed Majed Modaresi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Byung-Kuk Yoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Thomas D. Curtis
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Patrick J. Lariviere
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Libang Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Sangkeun Son
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Samantha Nicolau
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Rachel Bargabos
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Madeleine Morrissette
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Michael F. Gates
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Norman Pitt
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Roman P. Jakob
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Parthasarathi Rath
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Timm Maier
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Andrey G. Malyutin
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Jens T. Kaiser
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Samantha Niles
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Blake Karavas
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Meghan Ghiglieri
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Sarah E. J. Bowman
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Douglas C. Rees
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Sebastian Hiller
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Kim Lewis
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

K.L. conceptualized the project; R.D.M., A.I., S.M.M., B.-K.Y., D.C.R., S.H. and K.L. developed the methodology; R.D.M., A.I., S.M.M., B.K.-Y., T.D.C., P.J.L., L.L., S.S., S.N., R.B., M.M., M.F.G., N.P., R.P.J., P.R., T.M., A.G.M., J.T.K., S.N., B.K., M.G., S.B. conducted the investigations; R.D.M., S.M.M., S.H. and K.L. wrote the manuscript; D.C.R., S.H. and K.L. acquired funding; and D.C.R., S.H. and K.L. supervised the project.

Corresponding authors

Correspondence to Sebastian Hiller or Kim Lewis.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Microbiology thanks Paul Hergenrother 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

Extended Data Fig. 1 Compound and Operon structures.

Shown are darobactin and putatively-related cyclophane RiPP products (dynobactin A, xenorceptide), BamA-targeting synthetic molecule (MRL-494), and theonellamide G which contains an unusual histidine Nε2 to alanine β-carbon linkage, similar to dynobactin histidine Nε2 to tyrosine β-carbon linkage.

Extended Data Fig. 2 Rapid identification of target metabolites.

Total ion chromatogram (TIC) and Escherichia coli MG1655 activity assay. Panels A-C correspond to C18 (A), PFP (B), and Phenyl (C) columns applied to a 0.1% (v/v) formic acid in water:acetonitrile gradient condition. Panels (D), (E), and (F) correspond to the same columns applied to a 0.1% (v/v) formic acid in water:methanol condition. Timeslice fractions which inhibit E. coli growth are indicated by highlighted boxes containing a ‘+’ symbol. (G) Summary of networked masses in antimicrobial ion exchange fraction. (H) Structure of biologically-active metabolites purified from Photorhabdus australis with GNPS network relationship to the dominant metabolite (dynobactin A).

Extended Data Fig. 3 CryoEM microED structure determination.

MicroED data collection and analysis of 19 independent crystals of dynobactin A yielded structure, further details are elaborated within Methods. (A) Bright-field TEM image of dynobactin crystals (Scale bar: 5 μm). (B) Electron diffraction pattern with resolution ring at 0.95 Å. (C) 2D crystal packing arrangements of dynobactin. The intramolecular hydrogen bonds are shown as dashed lines for the top two molecules. The crystallographic b axis is parallel to the vertical direction of the figure. (D) Dynobactin A shows flexible conformations. Left shows superimposition dynobactin A microED structure (straight) and the dynobactin A structure observed in co-crystal with target BamA (bent). Right panels depict individual structures side-by-side. Separation of the two macrocycle rings in dynobactin A allows for free rotation about 4 bonds, creating an approximate 90° kink in the dynobactin A structure.

Extended Data Fig. 4 Dynobactin Secondary Structural Confirmations.

Full NMR assignment available in Supplementary Table 4. (A) 1H NMR spectrum (900 MHz, D2O). (B) 13C NMR spectrum (225 MHz, D2O). (C) 2D NMR spectra recorded in D2O (top left HSQC, top right DQF-COSY, bottom left HMBC, bottom right ROESY). (D) Key 2D NMR correlations in D2O and DMSO-d6. (E) Retention times (tR, min) of FDLA derivatives from dynobactin A Marfey’s analysis.

Extended Data Fig. 5 Target identification and resistance mutations.

BamA crystal structure (green) with labeled resistance mutation sites identified in this paper: (A) front view of lateral gate and (B) view of the barrel lumen from the periplasmic side (underside). Sites identified which gave resistance to both compounds are labeled in blue, and a mutation site which gives resistance to only dynobactin A is labeled in magenta. (C) Table listing MICs for bacteria from the previously described darobactin-resistance evolution experiment15, the isolated dynobactin-resistant mutants from this study, and other E. coli strains with outer membrane deficiencies (that is porin or efflux knockouts).

Extended Data Fig. 6 Unique features of dynobactin A binding.

(A) Comparison of the co-crystal structure of BamA-β with bound darobactin A (PDB:7NRF) and with bound dynobactin A (this work). In the close-up panels, W810 is highlighted in red. (B) Comparison of the orientation of the compound relative to strand β16 of BamA in the two structures. The bulky C-terminal extension of dynobactin A displaces the C-terminus of BamA further into the barrel lumen, with residue W810 becoming flexibly disordered (C) Selected region of a 2D [15N,1H]-TROSY spectrum of BamA-β in LDAO micelles upon titration with dynobactin A. Tentative assignment for indole W810 is indicated. (D) Affinity measurements of darobactins and dynobactin A to BamA-β via Surface Plasmon Resonance, sensorgrams and the corresponding steady-state affinity plots show dynobactin A binds one order of magnitude tighter to BamA-barrel than the darobactins. (E) Efficacy of the compounds in inhibiting BAM-mediated folding in native outer membrane vesicles (OMVs) (data are presented as mean values ± SD, n = 2). Fitting of these data resulted in IC50 values of 30 ± 6 nM, 48 ± 8 nM, and 16 ± 2 nM for darobactin A, darobactin B and dynobactin A with a 95% confidence interval, respectively.

Extended Data Fig. 7 Cryo-EM and X-ray structure comparison of dynobactin A-bound BamA.

(A) X-ray crystal structure of BamA-β with bound dynobactin A at 2.5 Å resolution. Zoomed-in panels highlight specific residues involved in the interaction. (B) Hydrophobic interaction between V5 of dynobactin A to the side chains of F428 and I430 of BamA in the co-crystal structure. (C) Interaction between W1 of dynobactin A and BamA. (D) Superimposition of the X-ray and cryo-EM structures (β-strand 1 only). The comparison shows a high degree of similarity in the conformation of dynobactin A between the cryo-EM and X-ray structure.

Extended Data Fig. 8 Solution NMR spectroscopy of BamA-β interacting with dynobactin A.

(A) 2D [15N,1H]-TROSY spectra of apo BamA-β in LDAO micelles (green) overlaid with BamA-β with 1.0 eq of dynobactin A (magenta). Zoomed-in panels show selected resonances. Tentatively assigned W810 is indicated with a frame on the spectrum. (B) 2D [15N,1H]-TROSY spectra of BamA-β in a titration experiment with increasing concentration of dynobactin A, as indicated, from black to red. (C) NMR spectrum of mutant W810F to confirm the assignment of W810.

Extended Data Fig. 9 Time-lapse microscopy of E. coli undergoing dynobactin A treatment.

E. coli MG1655 cells were spotted onto a 1.5% agarose pad containing dynobactin A (8x MIC), the membrane stain FM4-64 10 μg mL-1 (false-colored in magenta), and membrane permeabilization stain Sytox Green 0.5 μM (false-colored in green). Cells were incubated at 37 °C in a thermostatic chamber and imaged every 15 minutes under the microscope. The panels and selected time points were chosen to best represent the population of E. coli MG1655 undergoing dynobactin A treatment. White arrows indicate representative examples of membrane blebbing; orange arrows indicate examples of swelling or cell lysis. Scale bars, 5 μm. This experiment is representative of two biologically-independent experiments performed, each showing similar results.

Extended Data Table 1 Strains screened with putative RTEs
Full size table

Supplementary information

Supplementary Information

Supplementary Notes, Figs. 1 and 2, and Tables 1–8.

Reporting Summary

Peer Review File

Rights and permissions

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

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Miller, R.D., Iinishi, A., Modaresi, S.M. et al. Computational identification of a systemic antibiotic for Gram-negative bacteria. Nat Microbiol 7, 1661–1672 (2022). https://doi.org/10.1038/s41564-022-01227-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41564-022-01227-4

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research