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.

De novo phasing with X-ray laser reveals mosquito larvicide BinAB structure

Abstract

BinAB is a naturally occurring paracrystalline larvicide distributed worldwide to combat the devastating diseases borne by mosquitoes. These crystals are composed of homologous molecules, BinA and BinB, which play distinct roles in the multi-step intoxication process, transforming from harmless, robust crystals, to soluble protoxin heterodimers, to internalized mature toxin, and finally to toxic oligomeric pores. The small size of the crystals—50 unit cells per edge, on average—has impeded structural characterization by conventional means. Here we report the structure of Lysinibacillus sphaericus BinAB solved de novo by serial-femtosecond crystallography at an X-ray free-electron laser. The structure reveals tyrosine- and carboxylate-mediated contacts acting as pH switches to release soluble protoxin in the alkaline larval midgut. An enormous heterodimeric interface appears to be responsible for anchoring BinA to receptor-bound BinB for co-internalization. Remarkably, this interface is largely composed of propeptides, suggesting that proteolytic maturation would trigger dissociation of the heterodimer and progression to pore formation.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: De novo phasing of SFX data collected from nanocrystals of L. sphaericus BinAB.
Figure 2: BinA and BinB folds and carbohydrate-binding modules.
Figure 3: BinAB dimer assembly is weakened by proteolysis.
Figure 4: pH sensing in BinAB crystals.

Accession codes

Primary accessions

Protein Data Bank

Data deposits

Atomic coordinates and structure factors have been deposited in the Protein Data Bank under accession codes 5FOY (pH 7 structure), 5FOZ (pH 10 structure) and 5G37 (pH 5 structure).

References

  1. Moreira, L. A. et al. A Wolbachia symbiont in Aedes aegypti limits infection with dengue, Chikungunya, and Plasmodium. Cell 139, 1268–1278 (2009)

    Article  PubMed  Google Scholar 

  2. Alphey, N., Bonsall, M. B. & Alphey, L. Combining pest control and resistance management: synergy of engineered insects with Bt crops. J. Econ. Entomol. 102, 717–732 (2009)

    Article  PubMed  Google Scholar 

  3. Federici, B. A., Park, H.-W. & Bideshi, D. K. Overview of the basic biology of Bacillus thuringiensis with emphasis on genetic engineering of bacterial larvicides for mosquito control. Open Toxinology J. 3, 83–100 (2010)

    Article  CAS  Google Scholar 

  4. Fang, W. et al. Development of transgenic fungi that kill human malaria parasites in mosquitoes. Science 331, 1074–1077 (2011)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  5. Worrall, E. & Fillinger, U. Large-scale use of mosquito larval source management for malaria control in Africa: a cost analysis. Malar. J. 10, 338 (2011)

    Article  PubMed  PubMed Central  Google Scholar 

  6. Darboux, I., Nielsen-LeRoux, C., Charles, J.-F. & Pauron, D. The receptor of Bacillus sphaericus binary toxin in Culex pipiens (Diptera: Culicidae) midgut: molecular cloning and expression. Insect Biochem. Mol. Biol. 31, 981–990 (2001)

    Article  CAS  PubMed  Google Scholar 

  7. Berry, C. et al. Genetic determinants of host ranges of Bacillus sphaericus mosquito larvicidal toxins. J. Bacteriol. 175, 510–518 (1993)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Srisucharitpanit, K. et al. Crystal structure of BinB: a receptor binding component of the binary toxin from Lysinibacillus sphaericus. Proteins 82, 2703–2712 (2014)

    Article  CAS  PubMed  Google Scholar 

  9. Opota, O. et al. Bacillus sphaericus binary toxin elicits host cell autophagy as a response to intoxication. PLoS One 6, e14682 (2011)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  10. Liang, M. et al. The Coherent X-ray Imaging instrument at the Linac coherent light source. J. Synchrotron Radiat. 22, 514–519 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. DePonte, D. P. et al. SEM imaging of liquid jets. Micron 40, 507–509 (2009)

    Article  CAS  PubMed  Google Scholar 

  12. Sierra, R. G. et al. Nanoflow electrospinning serial femtosecond crystallography. Acta Crystallogr. D Biol. Crystallogr. 68, 1584–1587 (2012)

    Article  CAS  Google Scholar 

  13. Hattne, J. et al. Accurate macromolecular structures using minimal measurements from X-ray free-electron lasers. Nat. Methods 11, 545–548 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Uervirojnangkoorn, M. et al. Enabling X-ray free electron laser crystallography for challenging biological systems from a limited number of crystals. eLife 4, 05421 (2015)

    Article  Google Scholar 

  15. Broadwell, A. H. & Baumann, P. Proteolysis in the gut of mosquito larvae results in further activation of the Bacillus sphaericus toxin. Appl. Environ. Microbiol. 53, 1333–1337 (1987)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  16. Cokmus, C., Davidson, E. W. & Cooper, K. Electrophysiological effects of Bacillus sphaericus binary toxin on cultured mosquito cells. J. Invertebr. Pathol. 69, 197–204 (1997)

    Article  CAS  PubMed  Google Scholar 

  17. Melton, J. A., Parker, M. W., Rossjohn, J., Buckley, J. T. & Tweten, R. K. The identification and structure of the membrane-spanning domain of the Clostridium septicum alpha toxin. J. Biol. Chem. 279, 14315–14322 (2004)

    Article  CAS  PubMed  Google Scholar 

  18. Degiacomi, M. T. et al. Molecular assembly of the aerolysin pore reveals a swirling membrane-insertion mechanism. Nat. Chem. Biol. 9, 623–629 (2013)

    Article  CAS  PubMed  Google Scholar 

  19. Yamashita, K. et al. Crystal structure of the octameric pore of staphylococcal γ-hemolysin reveals the β-barrel pore formation mechanism by two components. Proc. Natl Acad. Sci. USA 108, 17314–17319 (2011)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  20. Schwartz, J. L. et al. Permeabilization of model lipid membranes by Bacillus sphaericus mosquitocidal binary toxin and its individual components. J. Membr. Biol. 184, 171–183 (2001)

    Article  CAS  PubMed  Google Scholar 

  21. Ponstingl, H., Henrick, K. & Thornton, J. M. Discriminating between homodimeric and monomeric proteins in the crystalline state. Proteins 41, 47–57 (2000)

    Article  CAS  PubMed  Google Scholar 

  22. Lawrence, M. C. & Colman, P. M. Shape complementarity at protein/protein interfaces. J. Mol. Biol. 234, 946–950 (1993)

    Article  CAS  PubMed  Google Scholar 

  23. Oei, C., Hindley, J. & Berry, C. Binding of purified Bacillus sphaericus binary toxin and its deletion derivatives to Culex quinquefasciatus gut: elucidation of functional binding domains. J. Gen. Microbiol. 138, 1515–1526 (1992)

    Article  CAS  PubMed  Google Scholar 

  24. Klapper, M. H. The independent distribution of amino acid near neighbor pairs into polypeptides. Biochem. Biophys. Res. Commun. 78, 1018–1024 (1977)

    Article  CAS  PubMed  Google Scholar 

  25. Chiu, E. et al. Structural basis for the enhancement of virulence by viral spindles and their in vivo crystallization. Proc. Natl Acad. Sci. USA 112, 3973–3978 (2015). 10.1073/pnas.1418798112

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  26. Barends, T. R. M. et al. De novo protein crystal structure determination from X-ray free-electron laser data. Nature 505, 244–247 (2014)

    Article  ADS  CAS  PubMed  Google Scholar 

  27. Yamashita, K. et al. An isomorphous replacement method for efficient de novo phasing for serial femtosecond crystallography. Sci. Rep. 5, 14017 (2015)

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  28. Fukuda, Y. et al. Redox-coupled proton transfer mechanism in nitrite reductase revealed by femtosecond crystallography. Proc. Natl Acad. Sci. USA 113, 2928–2933 (2016)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  29. Nakamura, T. et al. Sugar-binding sites of the HA1 subcomponent of Clostridium botulinum type C progenitor toxin. J. Mol. Biol. 376, 854–867 (2008)

    Article  CAS  PubMed  Google Scholar 

  30. Mancheño, J. M., Tateno, H., Goldstein, I. J., Martínez-Ripoll, M. & Hermoso, J. A. Structural analysis of the Laetiporus sulphureus hemolytic pore-forming lectin in complex with sugars. J. Biol. Chem. 280, 17251–17259 (2005)

    Article  PubMed  CAS  Google Scholar 

  31. Park, H. W., Ge, B., Bauer, L. S. & Federici, B. A. Optimization of Cry3A yields in Bacillus thuringiensis by use of sporulation-dependent promoters in combination with the STAB-SD mRNA sequence. Appl. Environ. Microbiol. 64, 3932–3938 (1998)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sawaya, M. R. et al. Protein crystal structure obtained at 2.9 Å resolution from injecting bacterial cells into an X-ray free-electron laser beam. Proc. Natl Acad. Sci. USA 111, 12769–12774 (2014)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. Park, H.-W. et al. Recombinant larvicidal bacteria with markedly improved efficacy against culex vectors of West Nile virus. Am. J. Trop. Med. Hyg. 72, 732–738 (2005)

    Article  CAS  PubMed  Google Scholar 

  34. Bourgouin, C., Delécluse, A., de la Torre, F. & Szulmajster, J. Transfer of the toxin protein genes of Bacillus sphaericus into Bacillus thuringiensis subsp. israelensis and their expression. Appl. Environ. Microbiol. 56, 340–344 (1990)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  35. Park, H.-W., Hice, R. H. & Federici, B. A. Effect of promoters and plasmid copy number on Cyt1A synthesis and crystal assembly in Bacillus thuringiensis. Curr. Microbiol. 72, 33–40 (2016)

    Article  CAS  PubMed  Google Scholar 

  36. Wu, D. & Federici, B. A. A 20-kilodalton protein preserves cell viability and promotes CytA crystal formation during sporulation in Bacillus thuringiensis. J. Bacteriol. 175, 5276–5280 (1993)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Miyatake, H., Hasegawa, T. & Yamano, A. New methods to prepare iodinated derivatives by vaporizing iodine labelling (VIL) and hydrogen peroxide VIL (HYPER-VIL). Acta Crystallogr. D Biol. Crystallogr. 62, 280–289 (2006)

    Article  PubMed  CAS  Google Scholar 

  38. Weierstall, U., Spence, J. C. H. & Doak, R. B. Injector for scattering measurements on fully solvated biospecies. Rev. Sci. Instrum. 83, 035108 (2012)

    Article  ADS  CAS  PubMed  Google Scholar 

  39. Sauter, N. K., Hattne, J., Grosse-Kunstleve, R. W. & Echols, N. New Python-based methods for data processing. Acta Crystallogr. D Biol. Crystallogr. 69, 1274–1282 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Sheldrick, G. M. A short history of SHELX. Acta Crystallogr. A 64, 112–122 (2008)

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Langer, G., Cohen, S. X., Lamzin, V. S. & Perrakis, A. Automated macromolecular model building for X-ray crystallography using ARP/wARP version 7. Nat. Protocols 3, 1171–1179 (2008)

    Article  CAS  PubMed  Google Scholar 

  43. Winn, M. D. et al. Overview of the CCP4 suite and current developments. Acta Crystallogr. D Biol. Crystallogr. 67, 235–242 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Terwilliger, T. C. SOLVE and RESOLVE: automated structure solution and density modification. Methods Enzymol. 374, 22–37 (2003)

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  47. Blanc, E. et al. Refinement of severely incomplete structures with maximum likelihood in BUSTER-TNT. Acta Crystallogr. D Biol. Crystallogr. 60, 2210–2221 (2004)

    Article  CAS  PubMed  Google Scholar 

  48. Ursby, T. & Bourgeois, D. Improved estimation of structure-factor difference amplitudes from poorly accurate data. Acta Crystallogr. A 53, 564–575 (1997)

    Article  Google Scholar 

  49. Brunger, A. T. Version 1.2 of the crystallography and NMR system. Nat. Protocols 2, 2728–2733 (2007)

    Article  CAS  PubMed  Google Scholar 

  50. Colletier, J.-P. et al. Shoot-and-Trap: use of specific x-ray damage to study structural protein dynamics by temperature-controlled cryo-crystallography. Proc. Natl Acad. Sci. USA 105, 11742–11747 (2008)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  51. Olsson, M. H. M., Søndergaard, C. R., Rostkowski, M. & Jensen, J. H. PROPKA3: Consistent treatment of internal and surface residues in empirical pKa predictions. J. Chem. Theory Comput. 7, 525–537 (2011)

    Article  CAS  PubMed  Google Scholar 

  52. Dolinsky, T. J., Nielsen, J. E., McCammon, J. A. & Baker, N. A. PDB2PQR: an automated pipeline for the setup of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Res. 32, W665–W667 (2004)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. The PyMOL Molecular Graphics System, Version 1.8 Schrödinger, LLC

  54. Zeldin, O. B., Gerstel, M. & Garman, E. F. RADDOSE-3D : time- and space-resolved modelling of dose in macromolecular crystallography. J. Appl. Cryst. 46, 1225–1230 (2013)

    Article  CAS  Google Scholar 

  55. Cole, A. Absorption of 20-eV to 50,000-eV Electron Beams in Air and Plastic. Radiat. Res. 38, 7–33 (1969)

    Article  ADS  CAS  PubMed  Google Scholar 

  56. Singkhamanan, K., Promdonkoy, B., Chaisri, U. & Boonserm, P. Identification of amino acids required for receptor binding and toxicity of the Bacillus sphaericus binary toxin. FEMS Microbiol. Lett. 303, 84–91 (2010)

    Article  CAS  PubMed  Google Scholar 

  57. Kelker, M. S. et al. Structural and biophysical characterization of Bacillus thuringiensis insecticidal proteins Cry34Ab1 and Cry35Ab1. PLoS One 9, e112555 (2014)

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  58. De Colibus, L. et al. Structures of lysenin reveal a shared evolutionary origin for pore-forming proteins and its mode of sphingomyelin recognition. Structure 20, 1498–1507 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Waterhouse, A. M., Procter, J. B., Martin, D. M. A., Clamp, M. & Barton, G. J. Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics 25, 1189–1191 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. McCoy, A. J., Chandana Epa, V. & Colman, P. M. Electrostatic complementarity at protein/protein interfaces. J. Mol. Biol. 268, 570–584 (1997)

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We acknowledge the help of the following people during data collection: S. Lee, J. Koralek, R. Shoeman, S. Botha, B. Doak and O. Zeldin. We thank A. Volveda for advice regarding sequence-wise Fourier difference map integration; J. Brooks-Bartlett and E. Garman for help with dose calculations; and M. Weik for discussions and continuing support. We thank the HCIA program of HHMI, the W.M. Keck Foundation (grant 2843398), the NIH (grant AG-029430), National Science Foundation (grant MCB 0958111) and DOE (DE-FC02-02ER63421) (to D.S.E.), the France Alzheimer Foundation (FA-AAP-2013-65-101349) and the Agence Nationale de la Recherche (ANR-12-BS07-0008-03) (to J.-P.C.), NIH grants GM095887 and GM102520 for data-processing methods (to N.K.S.), and NIH grant AI45817 (to B.A.F.). Support by the CNRS (PEPS-SASLELX-2013, PEPS-SASLELX-2014) funded travel to LCLS. Use of the LCLS at SLAC National Accelerator Laboratory, is supported by the US Department of Energy, Office of Science, and Office of Basic Energy Sciences under contract no. DE-AC02-76SF00515. The CXI instrument was funded by the Linac Coherent Light Source Ultrafast Science Instruments project, itself funded by the DOE Office of Basic Energy Sciences. Parts of the sample injector used at LCLS for this research were funded by the National Institutes of Health, P41GM103393, formerly P41RR001209.

Author information

Authors and Affiliations

Authors

Contributions

J.-P.C., M.R.S., M.G., J.A.R., D.C., B.A.F. and D.S.E designed and coordinated the project. M.G. carried out the in vivo production of BinAB nano-crystals. H.-W.P., D.K.B. and B.A.F. engineered bacterial strains to produce enlarged BinAB crystals. R.H.H. and H.-W.P. performed toxicity assays. R.H.H. designed the mutagenesis protocol. D.K.B. performed crystal solubilization assays. M.R.S. performed heavy atom derivatizations. J.-P.C., M.R.S., J.A.R., D.C., A.S.B., T.M.-C., S.B., G.J.W., M.M., D.P.D., R.G.S., H.L., J.E.K., M.S.H., N.C., M.U. and N.K.S. acquired and processed data. J.-P.C. and M.R.S carried out the MIRAS and MR phasing, and built and refined the atomic models. R.G.S. and H.L. developed the MESH-on-a-stick injector. J.-P.C., M.R.S., and D.S.E prepared the manuscript with input from M.G., J.A.R., D.C., A.S.B., T.M.-C., R.G.S., M.S.H., A.T.B., B.A.F., and N.K.S.

Corresponding authors

Correspondence to Jacques-Philippe Colletier or David S. Eisenberg.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks C. Berry, H. Chapman and P. Wang for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Data collection and heavy-atom substructure determinations.

a, The ‘MESH-on-a-stick’ sample injector configuration (see Methods). In the three panels, the yellow X below the capillary indicates the X-ray path into the page. The middle panel shows a closer view of the injector tip; the right panel shows an on-axis view of the sample injecting during the experiment. b, Our choice of X-ray wavelength for diffraction and MIRAS phasing was a compromise between maximizing the heavy atom anomalous signals, f″, as indicated by the curves for each element, and maximizing the number of data sets collected in the time allotted for the experiment. The grey bar corresponds to the wavelength we used, 1.41 Å. c, Difference Patterson maps calculated at 2.8 Å resolution. Sharpening (−5.0 Å2) was applied to Hg and VIL maps. Coefficients for the PCMBS and VIL maps were obtained from both isomorphous and anomalous differences. The Gd difference Patterson map was calculated from anomalous differences only. Contours start at the 1.5σ level and continue at 0.5σ intervals. Peaks corresponding to vectors between heavy atoms stand out as high peaks, up to 7.5σ. d, Heavy-atom sites were located successfully for each of the three derivatives using the program SHELXD. We compared the quality of potential heavy-atom substructure solutions obtained from two sources of heavy-atom signal: single wavelength anomalous dispersion (SAD, red) and a combination of anomalous dispersion and isomorphous differences (SIRAS, blue). Ten-thousand independent trials were performed for each derivative and signal source. Each dot in the scatter plots indicates the quality of an individual substructure solution. The vertical axis, labelled CCall, indicates the consistency between the potential solution and the diffraction data as the correlation coefficient between normalized structure factors, Ecalc and Eobs. The horizontal axis, labelled PATFOM (Patterson figure of merit), indicates the consistency between the observed difference Patterson map and that predicted by the potential solution. Successful substructure determination is suggested by the appearance of a sharp separation between two populations of potential solutions: a cluster with lower values of CCall and PATFOM (incorrect solutions) and a cluster with higher values (correct solutions). Such is the case for all the trials performed, except for VIL using the SAD signal, where only a single population of solutions is observed. Evidently, the SAD signal was insufficient for accurate location of iodine sites. For VIL, we relied on the accuracy of sites obtained from the SIRAS signal. In most cases, the SIRAS (blue) signal is stronger than the SAD signal (red), indicating good isomorphism between native and derivative data sets. Only in the case of GdCl3 does the SAD signal appear to be better than the SIRAS signal. The histograms in the right column indicate the number of potential substructure solutions with given values of CFOM (combined figure of merit). The histograms recapitulate the trends observed in the scatter plots. e, The correlation coefficient (CCiso) measures the agreement and Riso measures the discrepancy between the native structure factors and those of each of the derivatives. Each of our three derivative data sets shows isomorphism with the native data set up to 2.8 Å resolution.

Extended Data Figure 2 Structure solution and model building.

a, Evidence for choosing the correct hand of heavy atom substructures. We illustrate here the two types of comparison we used for choosing the correct hand of the heavy-atom substructures: (1) comparisons of the quality of the SIRAS and SAD phased maps (upper three panels) and (2) comparisons of the heights of anomalous difference Fourier peaks (lower three panels). These comparisons are made between maps calculated in opposite hands; the correct hand is indicated by the individual with higher positive values. The disparity in values (Δ) is indicated on the vertical axes of the graphs. Greater |Δ| values indicate a stronger phasing power and more reliable choice of hand. There are six comparisons shown for each of the three heavy derivatives: PCMBS (mercury) in red, GdCl3 (gadolinium) in blue, and VIL (iodide) in green. The top three panels illustrate the percent difference between hands in the mean figure of merit (Mean-FOM), the pseudo-free correlation coefficient (Pseudo-free CC) of the density-modified map, and the correlation coefficient of the trace (Trace-CC) as reported by ShelxE. The sites and phases were obtained from SIRAS signal for mercury and iodide, and from SAD signal for Gd. The most probable solvent content is ~59%, corresponding to one BinAB complex per asymmetric unit. However, we note conflicting choices of hand indicated by fluctuations in the sign of Δ accompanying small variations in the solvent content used in the density modification step (horizontal axes). We found that the difference Fourier maps (lower three panels) offered a stronger and more consistent indication of the choice of hand even when the statistics from SIRAS and SAD phased maps themselves differed little between hands. In these panels, SIRAS phases from the each heavy atom (3 columns) were used to compute three anomalous difference Fourier maps, using as coefficients, the anomalous differences from each derivative (rows 4–6). The value Δ corresponds to the height of the highest peak in the map computed in the original hand minus the corresponding peak in the map computed in the inverted hand. The graphs show that for all three derivatives, the original hand choice was correct (indicated by positive Δ), consistent across choices of solvent content (all Δ have the same sign within a graph), and consistent across sources of anomalous differences (all Δ have the same sign within a column). b, Automated tracing and model-building. Phases from the three derivatives were combined using SOLVE44 (see Methods). The hands which we decided on during the phasing step (a) were specified as ‘known’ to phenix.autosol. We then used RESOLVE44 (see Methods) to trace the density and build a model. The upper and lower panels show the progress of model building, depending on whether anomalous and isomorphous differences were combined from all derivatives (upper panel) or mixed phases (that is, anomalous and isomorphous differences from PCMBS and VIL, and anomalous differences from the Gd derivative) (lower panel). Each panel shows scatter plots of Rfree, Rfactor, number of residues built and number of residues placed in sequence as a function of the number of cycles. The use of mixed phases allowed us to obtain a better model, faster (lower panel). c, Electron density maps at various stages of model building. From left to right, the panels illustrate progressive improvement in map and model at two representative regions of BinAB (upper versus lower panels). The number of residues built (including residues without side chains) is noted at each stage, as well as the number of protein atoms built. The quality of the maps at each stage is reported as a correlation coefficient with the map obtained from the final model. Approximately 60% of the total atoms in BinAB were built automatically. d, Comparison of BinA and BinB structures. Superposition of BinA (lighter colours) and BinB (darker colours) shows similarity between molecules, which superimpose with an r.m.s.d. of 1.7 Å over 329 pairs of α-carbons. The ‘face’ view displays the surface involved in the BinA–BinB dimer interface, and the barrel subdomain of the trefoil is oriented towards the viewer. The back view displays the outward faces of the molecules, with the putative carbohydrate binding modules, in the cap subdomain, oriented towards the viewer. One of the largest structural differences is located in a surface loop on the back face, in the trefoil domain (blue). In BinB, a disulfide bond (Cys67–Cys161, yellow sticks) pins a surface loop (residues 60–74) away from the opening in the trefoil domain (open), whereas in BinA, the analogous loop (residues 34–46) is stabilized by a different disulfide bond (Cys31–Cys47, yellow sticks) to take a conformation that covers the opening in the trefoil domain (closed). e, Structure-based sequence alignment of BinA, BinB, and cry35Ab1. The secondary structures of BinA and BinB are shown above the sequences. Heterodimer contacts and cleavage sites are noted.

Extended Data Figure 3 Trefoil domains of BinA and BinB.

a, Structural relationships among trefoil domains illustrated by a phylogenetic tree plot. Four of the structures used for comparison were identified from a structural similarity search through the Protein Data Bank conducted by the Dali server (using BinA residues 6–156 as the probe). The top four hits occupy the top half of the plot (3AH1, 3VT2, 2E4M, and 4JP0) and include the deadly toxin, ricin (3VT2). The remaining structures chosen for comparison (1W3G and 3ZXG) were selected based on their membership in the aerolysin family of toxins, of which BinA and BinB are members. That is, these are trefoils covalently linked to aerolysin-type pore-forming domains. These are highlighted in blue text and include another insecticidal protein from B. thuringiensis, Cry35Ab1 (4JP0). Note that BinA and BinB are nearly as distant from each other as they are from the closest homologues, haemagglutinin, ricin, and Cry35Ab1. Carbohydrate molecules are shown in sticks where coordinates are available. Notable loop insertions in BinA and BinB are coloured in orange and magenta, respectively. b, Carbohydrate-binding modules of BinA and BinB display different levels of structural integrity. No carbohydrates were included or observed in the crystals structure of BinAB. To investigate the structural integrity of the putative carbohydrate-binding pockets of BinAB, we superimposed coordinates of lectin (1W3G) and haemagglutinin (3AH1). The crystal structures illustrated in the left column are carbohydrate complexes chosen for their structural similarity to BinAB. Some modules appear competent for carbohydrate binding, such as the β- and γ-modules of BinA and the β-module of BinB. Others show steric clash (yellow starburst), such as the α-module of BinA and the β-module of BinB, which could be overcome by allowing adjustments in torsion angles. Notably, the α-module of BinB is completely occluded by the insertion in its sequence (magenta) and stapled shut by a disulphide bond. In addition to the canonical α-, β- and γ-binding modules, 3AH1 displays another weakly bound carbohydrate marked site IIIA (bottom panel). This site is illustrated here because its superimposed coordinates lie adjacent to Y150 in BinB. The Y150A mutation causes complete loss of receptor binding56.

Extended Data Figure 4 Pore-forming domains (PFD) of BinA and BinB.

a, Topology of the aerolysin family of pore-forming toxins. These share a core topology composed of five antiparallel β-strands and a putative membrane-spanning segment (green). PDB ID codes are included in parentheses. For clarity, we exclude from this illustration any accessory domains outside the pore-forming module (PFM) of these toxins. The PFM is divided into two subdomains: a β-sheet subdomain at one end (above the horizontal grey line) and a β-sandwich subdomain at the opposite end (below the horizontal grey line). The length, twist, and number of strands vary between toxins. Also, the putative membrane-spanning segment (green) varies widely in secondary structure. However, in all cases this putative membrane-spanning segment is located between the second and third strands, suggesting that these toxins might share a common mechanism of pore formation. b, Members of the aerolysin family that also contain a β-trefoil domain like BinAB. These are: Cry35Ab1 toxin from B. thuringiensis (4jp0)57, lysenin, a haemolytic toxin from the earthworm Eisenia fetida (3zxg)58, and a pore-forming lectin from the mushroom Laetiporus suphureus (1w3g)30. c, Amphipathicity is evident in the sequence of the putative transmembrane (TM) subdomains of BinA and BinB. The observed secondary structures of BinA and BinB are shown above the sequence alignment. The range of the transmembrane subdomain is coloured yellow. Amino acids are coloured by hydrophobicity according to the scale given at the bottom. Note the alternating hydrophobic–hydrophilic pattern is especially prominent in the N-terminal half of the transmembrane subdomain. This pattern is consistent with the proposal of an oligomeric membrane-spanning β-barrel. The figure was made using the program Jalview59.

Extended Data Figure 5 Overview and analysis of molecular interfaces in the BinAB crystal.

a, Overview of the six molecular interfaces involving BinA in the BinAB crystal. The reference copy of the BinA molecule is depicted as a beige molecular surface and its six neighbouring molecules are shown as cartoon ribbons (upper panels). Face and back views (left and right panels) reveal opposite surfaces of the BinA molecule. The largest interface is with BinB (x,y,z) which is shown most clearly in the face view (left panels) in dark blue. It is the only interface of the six that is large enough to stretch over most of the length of the molecule. In all views, the pseudo-two-fold axis relating BinA and BinB is in a vertical orientation (black line in upper panels). The areas of contact are illustrated on the BinA molecular surface (middle panels) in colours corresponding to the cartoon ribbons (upper panels). BinA molecules and surfaces are shown in beige shades; BinB molecules and surfaces are shown in blue-green shades. The pie chart shows the relative amount of total BinA surface area buried by each of the six crystal contacts and the remainder, which is solvent exposed. b, Overview of the eight molecular interfaces involving BinB in the BinAB crystal. The reference copy of the BinB molecule is depicted as a dark blue molecular surface and its eight neighbouring molecules are shown as cartoon ribbons (upper panels). Face and back views (left and right panels) reveal opposite surfaces of the BinB molecule. The largest interface is with BinA (x,y,z), shown most clearly in the face view (left panels) in beige. It is the only interface of the eight that is large enough to stretch over most of the length of the molecule. In all views, the pseudo-two-fold axis relating BinA and BinB is in a vertical orientation (black line in upper panels). The areas of contact are illustrated on the BinA molecular surface (middle panels) in colours corresponding to the cartoon ribbons (upper panels). BinA molecules and surfaces are shown in amber shades; BinB molecules and surfaces are shown in blue-green shades. The pie chart shows the relative amounts of total BinB surface area buried by each of the eight crystal contacts and the remainder, which is solvent exposed. c, Distribution of the BinA–BinB interface area over its subdomains. The pie charts in the upper half show the area contributions to the principal BinA–BinB interface from each of the five named regions: trefoil domain, transmembrane subdomain, sheet subdomain, sandwich subdomain, and combined N- and C-terminal propeptides. The lower charts show analogous contributions on a per-residue basis. That is, the area contributed by each region is divided by the total number of residues comprising that region. These pie charts emphasize the role of the transmembrane subdomain in the dimer interface, perhaps to restrain this subdomain from inserting into a membrane until after the BinAB dimer dissociates. Notably, the higher efficiency of pore formation of BinA compared to BinB20 correlates with the greater protection of its transmembrane domain (12.5 Å2 buried per residue versus 6.5 Å2 buried per residue) in the dimer.

Extended Data Figure 6 Detailed views of the molecular interfaces in the BinAB crystal.

ag, BinA and BinB are shown as green and cyan ribbon diagrams, respectively. The C-terminal propeptide of BinB (residues 396–448) is highlighted in blue, while the N-terminal (residues 1–10) and C-terminal (residues 354–367) propeptides of BinA are shown in dark green. Contacting residues are shown as sticks. Polar interactions within a 3.6-Å cut-off are highlighted by yellow dashes. The contacts illustrated in panels ag are detailed in Supplementary Tables 3–9, respectively. a, Molecular contacts between BinA (x,y,z) (green) and BinB (x,y,z) (cyan), that is, within the biological dimer. A large part of this interface involves the C-terminal propeptide of BinB. b, Molecular contacts between BinA (x,y,z) (green) and BinA (x + 1/2, −y + 1/2, −z) (lime green). c, Molecular contacts between BinA (x,y,z) (green) and BinB (x − 1/2, −y + 1/2, −z) (cyan). This interface involves the propeptide of BinB (residues 396–448). d, Molecular contacts between BinA (x,y,z) (green) and BinB (−x + 2, y − 1/2, −z + 1/2) (cyan). This interface involves the propeptide of BinB (residues 396–448). e, Molecular contacts between BinA (x,y,z) (green) and BinB (−x + 5/2, −y, −z + 1/2) (cyan). f, Molecular contacts between BinB (x,y,z) (cyan) and BinB (−x + 2, y − 1/2, −z + 1/2) (teal). A small part of this interface involves the propeptide of BinB (residues 396–448). g, Molecular contacts between BinB (x,y,z) (cyan) and BinB (x, y − 1, z) (teal).

Extended Data Figure 7 Electrostatic complementarity, tyrosine distribution, predicted electrostatic changes upon pH elevation and crystal solubilisation assays.

a, b, Electrostatic surface complementarity of the BinA–BinB interface. At pH 7.0 (a), complementary charges are notable between the BinA electrostatic surface potential (top) and the BinB electrostatic surface potential (bottom). The complementarity in potential is highlighted by the vertical arrows connecting adjacent patches on opposing surfaces of the interface. At pH 10.5 (b), deprotonation of tyrosine and increased negative charge on acid residues causes a reduction in electrostatic complementarity from 0.37 to 0.29 (ref. 60). All panels depict the BinA surface of the BinAB dimer interface. In the upper panels of a and b, this surface is coloured by electrostatic surface potential of BinA; in the lower panels, this surface is coloured by electrostatic surface potential of BinB. Residues lining the interface (sticks) are labelled with colour corresponding to the domain to which it belongs. The colour scheme is as described in Extended Data Fig. 2a. BinA residues are labelled in the upper panel. BinB residues are labelled in the lower panel. In all panels, the pseudo-two-fold axis relating BinA and BinB is in a vertical orientation (black line in Fig. 3a, lower panel). c, Distribution of tyrosine residues in the BinAB dimer. Of the total 49 tyrosine residues, 48 are ordered in the crystal structure. Of these, 20% are located in the dimer interface, which itself accounts for only 10% of the total molecular surface. Thus, the distribution of tyrosine residues is slightly more concentrated on the dimer interface compared to the remainder of the BinAB surface. Tyrosines outside the dimer interface are probably more prone to deprotonation than those within the dimer interface, due to differences in solvent accessibility. d, e, Electrostatic potential map of BinA and BinB. The surface of the BinAB dimer is depicted coloured by the electrostatic surface potential of BinA on the left, and by that of BinB on the right. In d, the regions of BinA (left) and BinB (right) that participate in the dimer interface are highlighted. In e, the external surface of the dimer is highlighted. In both d and e, the upper and lower panels show the electrostatic surface potentials of BinA (left) and BinB (right) at pH 7 and pH 10.5, respectively. f, Alkaline-induced crystal dissolution is delayed for the BinA D22N mutant compared to the wild type. Our structural data suggested that BinA Asp22 was an important pH sensor for triggering crystal dissolution at the high pH characteristic of the mosquito midgut. We reasoned that a D22N mutation in BinA would render the crystal less sensitive to pH by stabilizing a hydrogen bond with the BinB C-terminal carboxylate. We constructed a BinA D22N mutant and measured solubility of BinA D22N–BinB crystals at pH 10, collecting three data points for each time point. We found that its solubility in vitro decreased by 30% between 30 and 90 min at pH 10 compared to wild-type crystals, but not at pH 7 (individual measurements are plotted to indicate the range of variation). After 90 min, crystals of wild-type BinAB and BinA D22N–BinB are completely dissolved. This delay in crystal dissolution up to the 90-min time point is an important difference because in the fourth-instar Culex larvae, the larval feeding rate from the time particles are ingested until they are digested and exit the hindgut is 30 min (indicated by grey shading). Hence, the 60-min delay that we see in our experiments with D22N is long enough to contribute to the striking loss of toxicity of more than 20-fold at the LC95 level (Supplementary Table 13). These results are consistent with the model of Asp22 serving as a pH sensor for crystallization.

Extended Data Figure 8 Comparison of FopHiFopHj maps obtained from crystals receiving different X-ray doses suggests that the structural changes observed are due to pH change and not radiation damage.

af, The pH 5 and pH 10 data sets were collected with a ~500-fold higher dose than the pH 7 data set, raising the concern that some of the peaks in the FopH10FopH7, φpH7 map result from radiation damage, most notably those observed on disulfides. Panels ad show, for each of the four regions identified as highly sensitive to pH elevation in Fig. 4c–f, the six possible FopHjFopHi, φpHi maps calculated from the pH 5, pH 7 and pH 10 data sets and structures. Panels e and f show these maps around the disulfides of BinA (e) and BinB (f). BinA and BinB are shown as cartoons, coloured by subdomain, as in Fig. 4. The cartoons range in colour from pale to medium to dark, signifying the pH values 5, 7, and 10, respectively. Consistent with the hypothesis that a 500-fold difference in dose causes no major structural change, we see a lack of peaks in the FopH5FopH7, φpH7 map (Riso = 0.26) around disulfides (e, f) and other pH-sensitive residues (ad). Consistent with the hypothesis that the peaks observed in the FopH10FopH7, φpH7 map (Riso = 0.23) are caused by pH change, these peaks are reproduced in the FopH10FopH5, φpH5 and FopH5FopH10, φpH10 maps (Riso = 0.35). We interpret this pattern of peaks as implying movement of the disulfide bonds rather than their disruption. This movement accompanies pH-sensitive rigid-body motion of the trefoil domains (Extended Data Fig. 9). g, h, Peaks stronger than ± 3.5σ were integrated contiguously in the FopH10FopH7, φpH7 (upper panels) and FopH5FopH7, φpH7 maps (lower panels) and then assigned to the closest residue. The secondary structures of BinA (g) and BinB (h) are shown as cartoons, coloured by subdomain as in Fig. 4. The background of the sequence is also coloured by subdomain. The sequence-wise integration of the FopH10FopH7, φpH7 map reveals that BinB is more affected by the pH elevation than BinA, and in both chains, the trefoil is more affected than the pore-forming domain. The propeptide and transmembrane regions of both proteins are also sensitive to pH elevation. Peaks in the FopH5FopH7, φpH7 map (lower panels) are smaller in magnitude and concentrated in the trefoil domain of BinA and the C-terminal propeptide of BinB. They correspond to side-chain reorientation rather than increased dynamics or domain motion (Extended Data Fig. 9). The marked difference in pattern between the FopH10FopH7, φpH7 and FopH5FopH7, φpH7 map integrations is consistent with the hypothesis that the peaks observed in these maps are not due to radiation damage, but rather to pH-induced conformational changes.

Extended Data Figure 9 Conformational changes in the BinAB dimer upon pH elevation from 7 to 10.

ad, Distance difference matrices (DDMs) calculated between the pH 7 (reference) structure and either the pH 10 or the pH 5 structure. Blue and red indicate decreases and increases in Cα–Cα distances in the pH 10 or pH 5 structures as compared to the pH 7 structure, respectively. The secondary structures of BinA (ac) and BinB (a, b, d) are recapitulated by cartoons on the side or the diagonal of the DDMs. These cartoons are coloured by subdomain as in Fig. 4. a, Intermolecular (BinA versus BinB) DDM between the pH 10 and the pH 7 structures. This DDM illustrates that the BinAB dimer contracts upon pH elevation, with the two trefoil domains coming closer to one another. This might be due to electrostatic repulsion at crystal contact zone 5 (Fig. 4e, Extended Data Fig. 6e and Supplementary Table 7), which involves the trefoils of BinA and BinB from two symmetry-related dimers. b, Intermolecular (BinA versus BinB) DDM between the pH 5 and the pH 7 structures. The pH 5 structure is overall slightly more compact than the pH 7 structure but shows no major conformational changes. c, d, Intramolecular DDMs of BinA (c) and BinB (d). Changes in Cα–Cα distances between the pH 10 and the pH 7 structures are reported below the diagonal, while those between the pH 7 and the pH 5 structures are shown above the diagonal. The pH 5 and pH 7 structures of BinA (c) and BinB (d) are overall similar, with only the BinA loop Ile110–Arg120 and BinB loop Lys175–Ser184 showing a noticeable difference in conformation. In contrast, the pH 10 structures of BinA (c) and BinB (d) appear more compact. On the local level, striking conformational changes are observed upon pH elevation in the N-terminal propeptide of BinA, in loops Ile110–Thr120 (trefoil) and Asn341–Tyr345 (PFD) of BinA, and in loop Lys175–Ser184 (trefoil) of BinB. The increase in compactness is due to the trefoil domain coming closer to the PFD in both BinA and BinB. BinA loop Ile110–Thr120 appears sensitive to both increases and decreases in pH. e, f, Porcupine plots depicting differences between structures of BinAB for pH 7 versus pH 5 (green arrows) and pH 7 versus pH 10 (red arrows). The pH 7 structure of BinAB is shown, coloured by subdomain as in Fig. 4. The movement of Cα atoms is indicated by arrows on the ribbon representation, with the magnitude of motions illustrated by length of arrows exaggerated by 2.5 Å to increase visibility (for all atoms that move by more than 0.1 Å). e, View of the BinAB dimer, in an orientation similar to Fig. 4b. As compared to Fig. 3a, b, this view is rotated by 180° around the vertical axis. f, View from the top of the trefoil domains; this face of the BinAB dimer is presumably that interacting with the apical membrane of larvae midgut cells. The view in f is 90° apart from that in e.

Extended Data Table 1 Data collection, phasing and refinement statistics

Supplementary information

Supplementary Information

This file contains a Supplementary Discussion and additional references. (PDF 591 kb)

Supplementary Tables

This file contains Supplementary Tables 1-14. (PDF 1822 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Colletier, JP., Sawaya, M., Gingery, M. et al. De novo phasing with X-ray laser reveals mosquito larvicide BinAB structure. Nature 539, 43–47 (2016). https://doi.org/10.1038/nature19825

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature19825

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

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