Dynamics of an LPS translocon induced by substrate and an antimicrobial peptide

Abstract

Lipopolysaccharide (LPS) transport to the outer membrane (OM) is a crucial step in the biogenesis of microbial surface defenses. Although many features of the translocation mechanism have been elucidated, molecular details of LPS insertion via the LPS transport (Lpt) OM protein LptDE remain elusive. Here, we integrate native MS with hydrogen–deuterium exchange MS and molecular dynamics simulations to investigate the influence of substrate and peptide binding on the conformational dynamics of LptDE. Our data reveal that LPS induces opening of the LptD β-taco domain, coupled with conformational changes on β-strands adjacent to the putative lateral exit gate. Conversely, an antimicrobial peptide, thanatin, stabilizes the β-taco, thereby preventing LPS transport. Our results illustrate that LPS insertion into the OM relies on concerted opening movements of both the β-barrel and β-taco domains of LptD, and suggest a means for developing antimicrobial therapeutics targeting this essential process in Gram-negative ESKAPE pathogens.

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Fig. 1: Schematic of the LPS transport system and native mass spectrometry (nMS) analysis of LptDE, Re-LPS and thanatin.
Fig. 2: Conformational dynamics of LPS-bound LptDE.
Fig. 3: Conformational dynamics of thanatin-bound LptDE.
Fig. 4: Conformational dynamics of LptDE in the presence of both LPS and thanatin.
Fig. 5: Schematic of LptDE-mediated LPS insertion in the OM.

Data availability

Data supporting the findings of this study are available from the corresponding authors upon reasonable request. HDX-MS raw data and the HDX data tables have been deposited to the ProteomeXchange Consortium via the PRIDE60 partner repository with the dataset identifier PXD021743.

The structural models employed in this study are accessible through the PDB (https://www.rcsb.org/) under accession nos. 5IV9 (KpLptDE), 5XO4 (thanatin), 2R1A (EcLptA), 6GD5 (EcLptA–thanatin complex) and 4Q35 (SfLptDE). Source data are provided with this paper.

References

  1. 1.

    Whitfield, C. & Trent, M. S. Biosynthesis and export of bacterial lipopolysaccharides. Ann. Rev. Biochem. 83, 99–128 (2014).

    CAS  PubMed  Google Scholar 

  2. 2.

    Okuda, S., Sherman, D. J., Silhavy, T. J., Ruiz, N. & Kahne, D. Lipopolysaccharide transport and assembly at the outer membrane: the PEZ model. Nat. Rev. Microbiol. 14, 337–345 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Ruiz, N., Kahne, D. & Silhavy, T. J. Transport of lipopolysaccharide across the cell envelope: the long road of discovery. Nat. Rev. Microbiol. 7, 677–683 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Luo, Q. et al. Structural basis for lipopolysaccharide extraction by ABC transporter LptB2FG. Nat. Struct. Mol. Biol. 24, 469–474 (2017).

    CAS  PubMed  Google Scholar 

  5. 5.

    Li, Y., Orlando, B. J. & Liao, M. Structural basis of lipopolysaccharide extraction by the LptB2FGC complex. Nature 567, 486–490 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Tang, X. et al. Cryo-EM structures of lipopolysaccharide transporter LptB2FGC in lipopolysaccharide or AMP-PNP-bound states reveal its transport mechanism. Nat. Commun. 10, 4175 (2019).

    PubMed  PubMed Central  Google Scholar 

  7. 7.

    Owens, T. W. et al. Structural basis of unidirectional export of lipopolysaccharide to the cell surface. Nature 567, 550–553 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Villa, R. et al. The Escherichia coli Lpt transenvelope protein complex for lipopolysaccharide export is assembled via conserved structurally homologous domains. J. Bacteriol. 195, 1100–1108 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Chng, S. S., Ruiz, N., Chimalakonda, G., Silhavy, T. J. & Kahne, D. Characterization of the two-protein complex in Escherichia coli responsible for lipopolysaccharide assembly at the outer membrane. Proc. Natl Acad. Sci. USA 107, 5363–5368 (2010).

    CAS  PubMed  Google Scholar 

  10. 10.

    Freinkman, E., Chng, S. S. & Kahne, D. The complex that inserts lipopolysaccharide into the bacterial outer membrane forms a two-protein plug-and-barrel. Proc. Natl Acad. Sci. USA 108, 2486–2491 (2011).

    CAS  PubMed  Google Scholar 

  11. 11.

    Qiao, S., Luo, Q., Zhao, Y., Zhang, X. C. & Huang, Y. Structural basis for lipopolysaccharide insertion in the bacterial outer membrane. Nature 511, 108–111 (2014).

    CAS  PubMed  Google Scholar 

  12. 12.

    Dong, H. et al. Structural basis for outer membrane lipopolysaccharide insertion. Nature 511, 52–56 (2014).

    CAS  PubMed  Google Scholar 

  13. 13.

    Botos, I. et al. Structural and functional characterization of the LPS transporter LptDE from Gram-negative pathogens. Structure 24, 965–976 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Li, X., Gu, Y., Dong, H., Wang, W. & Dong, C. Trapped lipopolysaccharide and LptD intermediates reveal lipopolysaccharide translocation steps across the Escherichia coli outer membrane. Sci. Rep. 5, 11883 (2015).

    PubMed  PubMed Central  Google Scholar 

  15. 15.

    Gu, Y. et al. Lipopolysaccharide is inserted into the outer membrane through an intramembrane hole, a lumen gate, and the lateral opening of LptD. Structure 23, 496–504 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    World Health Organization. Global Priority List of Antibiotic-resistant Bacteria to Guide Research, Discovery, and Development of New Antibiotics (WHO, 2017); http://www.who.int/medicines/publications/global-priority-list-antibiotic-resistant-bacteria/en/

  17. 17.

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

    CAS  PubMed  Google Scholar 

  18. 18.

    Andolina, G. et al. A peptidomimetic antibiotic interacts with the periplasmic domain of LptD from Pseudomonas aeruginosa. ACS Chem. Biol. 13, 666–675 (2018).

    CAS  PubMed  Google Scholar 

  19. 19.

    Werneburg, M. et al. Inhibition of lipopolysaccharide transport to the outer membrane in Pseudomonas aeruginosa by peptidomimetic antibiotics. ChemBioChem 13, 1767–1775 (2012).

    CAS  PubMed  Google Scholar 

  20. 20.

    Fehlbaum, P. et al. Structure–activity analysis of thanatin, a 21-residue inducible insect defense peptide with sequence homology to frog skin antimicrobial peptides. Proc. Natl Acad. Sci. USA 93, 1221–1225 (1996).

    CAS  PubMed  Google Scholar 

  21. 21.

    Vetterli, S. U. et al. Thanatin targets the intermembrane protein complex required for lipopolysaccharide transport in Escherichia coli. Sci. Adv. 4, eaau2634 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Bolla, J. R. et al. Direct observation of the influence of cardiolipin and antibiotics on lipid II binding to MurJ. Nat. Chem. 10, 363–371 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Fiorentino, F., Bolla, J. R., Mehmood, S. & Robinson, C. V. The different effects of substrates and nucleotides on the complex formation of ABC transporters. Structure 27, 651–659 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Yen, H. Y. et al. PtdIns(4,5)P2 stabilizes active states of GPCRs and enhances selectivity of G-protein coupling. Nature 559, 423–427 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Bolla, J. R., Howes, A. C., Fiorentino, F. & Robinson, C. V. Assembly and regulation of the chlorhexidine-specific efflux pump AceI. Proc. Natl Acad. Sci. USA 117, 17011–17018 (2020).

    CAS  PubMed  Google Scholar 

  26. 26.

    Martens, C. et al. Direct protein–lipid interactions shape the conformational landscape of secondary transporters. Nat. Commun. 9, 4151 (2018).

    PubMed  PubMed Central  Google Scholar 

  27. 27.

    Nielsen, A. K. et al. Substrate-induced conformational dynamics of the dopamine transporter. Nat. Commun. 10, 2714 (2019).

    PubMed  PubMed Central  Google Scholar 

  28. 28.

    Landreh, M. et al. Integrating mass spectrometry with MD simulations reveals the role of lipids in Na+/H+ antiporters. Nat. Commun. 8, 13993 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Skinner, J. J. et al. Benchmarking all-atom simulations using hydrogen exchange. Proc. Natl Acad. Sci. USA 111, 15975–15980 (2014).

    CAS  PubMed  Google Scholar 

  30. 30.

    Persson, F. & Halle, B. How amide hydrogens exchange in native proteins. Proc. Natl Acad. Sci. USA 112, 10383–10388 (2015).

    CAS  PubMed  Google Scholar 

  31. 31.

    Laganowsky, A., Reading, E., Hopper, J. T. & Robinson, C. V. Mass spectrometry of intact membrane protein complexes. Nat. Protoc. 8, 639–651 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Raetz, C. R. et al. Kdo2-Lipid A of Escherichia coli, a defined endotoxin that activates macrophages via TLR-4. J. Lipid Res. 47, 1097–1111 (2006).

    CAS  PubMed  Google Scholar 

  33. 33.

    Xie, R., Taylor, R. J. & Kahne, D. Outer membrane translocon communicates with inner membrane ATPase to stop lipopolysaccharide transport. J. Am. Chem. Soc. 140, 12691–12694 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Bolla, J. R. et al. A mass-spectrometry-based approach to distinguish annular and specific lipid binding to membrane proteins. Angew. Chem. Int. Ed. 59, 3523–3528 (2020).

    CAS  Google Scholar 

  35. 35.

    Masson, G. R. et al. Recommendations for performing, interpreting and reporting hydrogen deuterium exchange mass spectrometry (HDX-MS) experiments. Nat. Methods 16, 595–602 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Lundquist, K. P. & Gumbart, J. C. Presence of substrate aids lateral gate separation in LptD. Biochim. Biophys. Acta Biomembr. 1862, 183025 (2020).

    CAS  PubMed  Google Scholar 

  37. 37.

    Merkle, P. S. et al. Substrate-modulated unwinding of transmembrane helices in the NSS transporter LeuT. Sci. Adv. 4, eaar6179 (2018).

    PubMed  PubMed Central  Google Scholar 

  38. 38.

    Zhou, J. et al. Conformational dynamics of 1-deoxy-d-xylulose 5-phosphate synthase on ligand binding revealed by H/D exchange MS. Proc. Natl Acad. Sci. USA 114, 9355–9360 (2017).

    CAS  PubMed  Google Scholar 

  39. 39.

    Jefferys, E., Sands, Z. A., Shi, J., Sansom, M. S. P. & Fowler, P. W. Alchembed: a computational method for incorporating multiple proteins into complex lipid geometries. J. Chem. Theory Comput. 11, 2743–2754 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Bonomi, M. et al. PLUMED: a portable plugin for free-energy calculations with molecular dynamics. Comput. Phys. Commun. 180, 1961–1972 (2009).

    CAS  Google Scholar 

  41. 41.

    Robert, X. & Gouet, P. Deciphering key features in protein structures with the new ENDscript server. Nucleic Acids Res. 42, W320–W324 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Tomasek, D. et al. Structure of a nascent membrane protein as it folds on the BAM complex. Nature 583, 473–478 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Hernandez, H. & Robinson, C. V. Determining the stoichiometry and interactions of macromolecular assemblies from mass spectrometry. Nat. Protoc. 2, 715–726 (2007).

    CAS  PubMed  Google Scholar 

  44. 44.

    Marty, M. T. et al. Bayesian deconvolution of mass and ion mobility spectra: from binary interactions to polydisperse ensembles. Anal. Chem. 87, 4370–4376 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Cubrilovic, D. et al. Determination of protein–ligand binding constants of a cooperatively regulated tetrameric enzyme using electrospray mass spectrometry. ACS Chem. Biol. 9, 218–226 (2014).

    CAS  PubMed  Google Scholar 

  46. 46.

    Guttman, M. et al. Tuning a high transmission ion guide to prevent gas-phase proton exchange during H/D exchange MS analysis. J. Am. Soc. Mass Spectrom. 27, 662–668 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Lau, A. M. C., Ahdash, Z., Martens, C. & Politis, A. Deuteros: software for rapid analysis and visualization of data from differential hydrogen deuterium exchange-mass spectrometry. Bioinformatics 35, 3171–3173 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Weis, D. D., Engen, J. R. & Kass, I. J. Semi-automated data processing of hydrogen exchange mass spectra using HX-Express. J. Am. Soc. Mass Spectrom. 17, 1700–1703 (2006).

    CAS  PubMed  Google Scholar 

  49. 49.

    Guttman, M., Weis, D. D., Engen, J. R. & Lee, K. K. Analysis of overlapped and noisy hydrogen/deuterium exchange mass spectra. J. Am. Soc. Mass Spectrom. 24, 1906–1912 (2013).

    CAS  PubMed  Google Scholar 

  50. 50.

    Konermann, L., Pan, J. & Liu, Y. H. Hydrogen exchange mass spectrometry for studying protein structure and dynamics. Chem. Soc. Rev. 40, 1224–1234 (2011).

    CAS  PubMed  Google Scholar 

  51. 51.

    Thompson, J. D., Higgins, D. G. & Gibson, T. J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22, 4673–4680 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52.

    Wiederstein, M. & Sippl, M. J. TopMatch-web: pairwise matching of large assemblies of protein and nucleic acid chains in 3D. Nucleic Acids Res. 48, W31–W35 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Abraham, M. J. et al. GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2, 19–25 (2015).

    Google Scholar 

  54. 54.

    Monticelli, L. et al. The MARTINI coarse-grained force field: extension to proteins. J. Chem. Theory Comput. 4, 819–834 (2008).

    CAS  PubMed  Google Scholar 

  55. 55.

    Wassenaar, T. A., Ingólfsson, H. I., Böckmann, R. A., Tieleman, D. P. & Marrink, S. J. Computational lipidomics with insane: a versatile tool for generating custom membranes for molecular simulations. J. Chem. Theory Comput. 11, 2144–2155 (2015).

    CAS  PubMed  Google Scholar 

  56. 56.

    Stansfeld, P. J. & Sansom, M. S. P. From coarse grained to atomistic: a serial multiscale approach to membrane protein simulations. J. Chem. Theory Comput. 7, 1157–1166 (2011).

    CAS  PubMed  Google Scholar 

  57. 57.

    Best, R. B. et al. Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ1 and χ2 dihedral angles. J. Chem. Theory Comput. 8, 3257–3273 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58.

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

    PubMed  Google Scholar 

  59. 59.

    Michaud-Agrawal, N., Denning, E. J., Woolf, T. B. & Beckstein, O. MDAnalysis: a toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. 32, 2319–2327 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Perez-Riverol, Y. et al. The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res. 47, D442–D450 (2020).

    Google Scholar 

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Acknowledgements

Research in C.V.R.’s laboratory is supported by a Medical Research Council program grant (MR/N020413/1), a European Research Council Advanced Grant ENABLE (695511) and a Wellcome Trust Senior Investigator Award (104633/Z/14/Z). Research in P.J.S.’s laboratory is funded by Wellcome (208361/Z/17/Z), the MRC (MR/S009213/1) and BBSRC (BB/P01948X/1, BB/R002517/1 and BB/S003339/1). This project made use of time on ARCHER and JADE, granted via the UK High-End Computing Consortium for Biomolecular Simulation (HECBioSim). P.J.S. acknowledges Athena at HPC Midlands+, funded by the EPSRC under grant no. EP/P020232/1 and the University of Warwick Scientific Computing Research Technology Platform for computational access. F.F. holds a SABS CDT studentship supported by the EPSRC and MRC (EP/L016044/1). J.B.S. is supported by the Oxford interdisciplinary DTP and the Biotechnology and Biological Sciences Research Council (BBSRC) (BB/M011224/1). We also thank S. Roy (University of Oxford) for his help with HDX-MS data analysis and rendering.

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Authors

Contributions

F.F., J.R.B., P.J.S. and C.V.R. designed the research. F.F. expressed and purified the protein samples and performed all nMS measurements. F.F. and J.R.B. analyzed nMS data. F.F. and X.Q. collected HDX-MS data. F.F. analyzed and interpreted HDX-MS data with the help of X.Q., J.R.B. and S.M. J.B.S. performed the MD simulations with the assistance of P.J.S., who modeled the initial substrate-bound LptDE states with B.M.-W. J.B.S. analyzed MD simulations data with the help of R.A.C., C.K.C. and P.J.S. F.F., J.B.S., R.A.C., C.K.C., J.R.B., P.J.S. and C.V.R. wrote the manuscript. All authors discussed the results and commented on the manuscript.

Corresponding authors

Correspondence to Jani R. Bolla or Phillip J. Stansfeld or Carol V. Robinson.

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C.V.R. is a co-founder and consultant at OMass Therapeutics. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Detergent competition experiments to assess LptDE lipid binding.

LptDE (5 μM, left) in 0.5% (w/v) C8E4 was mixed with 10 μM Re-LPS (a, orange adducts), POPG (b, red adducts) or CDL (c, magenta adducts). The protein-lipid mixture was then supplemented with increasing concentrations of n-nonyl-β-D-glucopyranoside (NG). Detergent addition decreases POPG and CDL binding, but has no pronounced effect on Re-LPS.

Extended Data Fig. 2 Thanatin binding efficiency and effect on Re-LPS binding.

a, Mass spectra recorded for solutions of LptDE (5 μM) with increasing concentrations of thanatin (green adducts). b, Mass spectra of Re-LPS-bound LptDE supplemented with 1 μM thanatin (as described in Fig. 1d) with a focus on the 16+ charge state showing the presence of the 2:1 Re-LPS:thanatin complex, particularly at higher Re-LPS concentration. c, Quantification of the total amount of Re-LPS bound to LptDE in the absence or in the presence of thanatin (related to Fig. 1d). Error bars represent s.d. (n = 3). d, Thanatin-first nMS analysis: LptDE (5 μM) was initially mixed with thanatin and then supplemented with Re-LPS (10 μM).

Extended Data Fig. 3 Sequence coverage of LptDE.

68 peptides covering 70.5% of LptD sequence a, and 17 peptides covering 87.4% of LptE b, were identified following digestion with immobilized pepsin.

Extended Data Fig. 4 Representative mass spectra for peptides showing EX1/EXX kinetics.

Mass spectra are shown for apo-LptDE, LPS, thanatin or LPS + thanatin states. Two binomial isotopic envelopes produced the best fit for the spectra yielding low- (green) and high-mass (light blue) populations. The sums of the two binomial distributions are shown in red. a, Peptide 66-92. b, Peptide 105-115. c, Peptide 116-19. d, Peptide 119-129. e, Peptide 130-141. f, Peptide 171-179.

Extended Data Fig. 5 Monoexponential fitting of the high-mass population in peptides showing EX1 kinetics.

Extracted relative abundances of high- mass populations plotted as a function of labeling time and fitted to a single exponential function with a variable intercept and plateau (to account for the lack of saturation seen in most peptides) to obtain the rate of translation from the low-mass population to the high-mass population (kop) and the half-life of the low mass population (t1/2). The apo state is indicated in purple, LPS-bound state in orange, thanatin-bound state in green, and LPS + thanatin state in maroon. Standard deviations are plotted as error bars (nbiological = 2; ntechnical = 3) but are in some instances too small to be visible. In the case of thanatin-bound state and LPS + thanatin state kinetic values could not be extracted because of poor fitting (the increase of high-mass population is incremental given the slow kinetics). In these cases, the dotted line is included only for visual guidance.

Extended Data Fig. 6 Re-LPS contacts and position within the β-taco.

a, Average percentage occupancy of Re-LPS contacts made with the β-taco with a 4 Å cut-off. These contacts have been compared to those made by the detergent in the SfLptD structure (PDB ID: 4Q35; marked by an asterisk) and found that 90% of residues which interact with detergent. b, Top: Kernel density estimate (KDE) of the center of mass (COM) position between the five replicates indicate minimal diffusion over the course of the simulation. Middle: Partial density of Re-LPS across the β-taco demonstrating consistent and rigid contact across the domain, this implies that the Re-LPS bound within the β-taco does not have enough simulation time to sample the entire soluble domain in different binding poses, which would account for the discrepancy in deprotected coverage across this domain when compared to HDX-MS (Supplementary Fig. 15). Bottom: reference cartoon structure of β-taco to compare with above plot axes.

Extended Data Fig. 7 Re-LPS contact mapped onto LptDE.

a, Average Re-LPS contacts mapped onto cartoon representations of LptDE. b, Residues interacting with the three Re-LPS lipids referenced in Fig. 2c (Re-LPS(1-3)) are shown in stick representation. c, C-terminal strand of the β-taco is in contact with the bilayer (Supplementary Fig. 15c). d, Ile186 and Phe187 are in transient contact with the Re-LPS lipids engaged with the lateral putative exit gate of the β-barrel. The open gate causes Re-LPS lipids (shown in yellow and pink) to be laterally pulled into the β-barrel sinking them into the inner leaflet of the and allowing the tails to interact with the C-terminal strand of the β-taco. This may suggest how Re-LPS gets laterally extruded into the OM during the translocation process.

Extended Data Fig. 8 Re-LPS distance plots.

Top: snapshot of the key lipid interactions between Re-LPS and the lateral gate peptide (232-251). Bottom: Plots measuring the distance from the geometric center of the peptide (232-251) to the geometric center of the lipids. Data plotted as the average of five repeats throughout the course of the simulation, standard deviation shaded gray.

Extended Data Fig. 9 Sequence and structure alignments of KpLptD and EcLptA.

a, Sequence alignment between KpLptD and EcLptA. Red color indicates conserved residues, yellow indicates highly similar residues. Circles indicate crucial residues for LptA-thanatin interaction. Blue color represents van-der-Waals interactions while green represents ionic bridges and H-bonds. b, Structure alignment of LptD (PDB ID: 5IV9) with apo-LptA (PDB ID: 2R1A). The RMSD is equal to 1.48 Å over 115 Cα.

Extended Data Fig. 10 Evaluation of LptD-thanatin interaction stability.

a, RMSD of thanatin docked to the bottom (i) of the β-jellyroll in its closed conformation compared to being docked to the top (ii) where standard deviation is colored gray. b, Right: schematic showing the orientation of the β-taco vector drawn through Cα of residues Asp33 and Pro190, where x, y displacement is shown as red arrows. Right: x,y displacement of the β-taco vector mapped relative to the origin 0.0, 0.0 (defined as the original position of β-taco in the crystal structure) comparing the conformation space sampled of the apo-β-taco against when thanatin is docked to the (i) bottom and (ii) top of the β-taco.

Supplementary information

Supplementary Information

Supplementary Figs. 1–18 and Tables 1–5.

Reporting Summary

Supplementary Video

Morph of LptDE complex. Morph between the closed conformation of the complex and the open conformation of the complex, with disulfide bonds between cysteines at the β-taco (Cys7, Cys149) and the β-barrel (Cys696, Cys697) shown as spheres.

Source data

Source Data Fig. 2

HDX-MS data used to create deuterium uptake plots for apo and LPS-bound protein and to map the difference in relative deuterium uptake (LPS - apo) onto LptD structure.

Source Data Figs. 3 and 4

HDX-MS data used to create deuterium uptake plots for apo, thantin-bound and LPS + thanatin bound protein and to map the difference in relative deuterium uptake (ligand bound - apo) onto LptD structure.

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Fiorentino, F., Sauer, J.B., Qiu, X. et al. Dynamics of an LPS translocon induced by substrate and an antimicrobial peptide. Nat Chem Biol 17, 187–195 (2021). https://doi.org/10.1038/s41589-020-00694-2

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