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Continuous evolution of Bacillus thuringiensis toxins overcomes insect resistance

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The Bacillus thuringiensis δ-endotoxins (Bt toxins) are widely used insecticidal proteins in engineered crops that provide agricultural, economic, and environmental benefits. The development of insect resistance to Bt toxins endangers their long-term effectiveness. Here we have developed a phage-assisted continuous evolution selection that rapidly evolves high-affinity protein–protein interactions, and applied this system to evolve variants of the Bt toxin Cry1Ac that bind a cadherin-like receptor from the insect pest Trichoplusia ni (TnCAD) that is not natively bound by wild-type Cry1Ac. The resulting evolved Cry1Ac variants bind TnCAD with high affinity (dissociation constant Kd = 11–41 nM), kill TnCAD-expressing insect cells that are not susceptible to wild-type Cry1Ac, and kill Cry1Ac-resistant T. ni insects up to 335-fold more potently than wild-type Cry1Ac. Our findings establish that the evolution of Bt toxins with novel insect cell receptor affinity can overcome insect Bt toxin resistance and confer lethality approaching that of the wild-type Bt toxin against non-resistant insects.

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Figure 1: Protein-binding PACE.
Figure 2: Protein-binding PACE selection development and stringency modulation.
Figure 3: Continuous evolution of Cry1Ac variants that bind the T. ni cadherin receptor.
Figure 4: Characterization of consensus-evolved Cry1Ac variants.
Figure 5: Characterization of stabilized evolved Cry1Ac variants reveals potently enhanced activity.

Change history

  • 03 April 2016

    In the AOP version of this Article, Extended Data Fig. 4 was duplicated and Extended Data Fig. 2 was missing; this has now been corrected.


  1. 1

    Prado, J. R. et al. Genetically engineered crops: from idea to product. Annu. Rev. Plant Biol. 65, 769–790 (2014)

    CAS  Article  Google Scholar 

  2. 2

    Pardo-López, L., Soberón, M. & Bravo, A. Bacillus thuringiensis insecticidal three-domain Cry toxins: mode of action, insect resistance and consequences for crop protection. FEMS Microbiol. Rev. 37, 3–22 (2013)

    Article  Google Scholar 

  3. 3

    James, C. Global Status of Commercialized Biotech/GM Crops: 2014. ISAAA Brief No. 49 (International Service for the Acquisition of Agri-biotech Applications, 2014)

  4. 4

    Tabashnik, B. E., Brévault, T. & Carrière, Y. Insect resistance to Bt crops: lessons from the first billion acres. Nature Biotechnol. 31, 510–521 (2013)

    CAS  Article  Google Scholar 

  5. 5

    Adang, M. J., Crickmore, N. & Jurat-Fuentes, J. L. Diversity of Bacillus thuringiensis crystal toxins and mechanism of action. Adv. Insect Physiol. 47, 39–87 (2014)

    Article  Google Scholar 

  6. 6

    Esvelt, K. M., Carlson, J. C. & Liu, D. R. A system for the continuous directed evolution of biomolecules. Nature 472, 499–503 (2011)

    CAS  ADS  Article  Google Scholar 

  7. 7

    Dickinson, B. C., Leconte, A. M., Allen, B., Esvelt, K. M. & Liu, D. R. Experimental interrogation of the path dependence and stochasticity of protein evolution using phage-assisted continuous evolution. Proc. Natl Acad. Sci. USA 110, 9007–9012 (2013)

    CAS  ADS  Article  Google Scholar 

  8. 8

    Leconte, A. M. et al. A population-based experimental model for protein evolution: effects of mutation rate and selection stringency on evolutionary outcomes. Biochemistry 52, 1490–1499 (2013)

    CAS  Article  Google Scholar 

  9. 9

    Carlson, J. C., Badran, A. H., Guggiana-Nilo, D. A. & Liu, D. R. Negative selection and stringency modulation in phage-assisted continuous evolution. Nature Chem. Biol. 10, 216–222 (2014)

    CAS  Google Scholar 

  10. 10

    Dickinson, B. C., Packer, M. S., Badran, A. H. & Liu, D. R. A system for the continuous directed evolution of proteases rapidly reveals drug-resistance mutations. Nature Commun . 5, 5352 (2014)

    CAS  ADS  Article  Google Scholar 

  11. 11

    Hubbard, B. P. et al. Continuous directed evolution of DNA-binding proteins to improve TALEN specificity. Nature Methods 12, 939–942 (2015)

    CAS  Article  Google Scholar 

  12. 12

    Badran, A. H. & Liu, D. R. Development of potent in vivo mutagenesis plasmids with broad mutational spectra. Nature Commun . 6, 8425 (2015)

    CAS  ADS  Article  Google Scholar 

  13. 13

    Dove, S. L. & Hochschild, A. Conversion of the omega subunit of Escherichia coli RNA polymerase into a transcriptional activator or an activation target. Genes Dev. 12, 745–754 (1998)

    CAS  Article  Google Scholar 

  14. 14

    Wojcik, J. et al. A potent and highly specific FN3 monobody inhibitor of the Abl SH2 domain. Nature Struct. Mol. Biol . 17, 519–527 (2010)

    CAS  Article  Google Scholar 

  15. 15

    Gómez, I. et al. Role of receptor interaction in the mode of action of insecticidal Cry and Cyt toxins produced by Bacillus thuringiensis . Peptides 28, 169–173 (2007)

    Article  Google Scholar 

  16. 16

    Fabrick, J. A. & Tabashnik, B. E. Binding of Bacillus thuringiensis toxin Cry1Ac to multiple sites of cadherin in pink bollworm. Insect Biochem. Mol. Biol. 37, 97–106 (2007)

    CAS  Article  Google Scholar 

  17. 17

    Wu, Y. D. Detection and mechanisms of resistance evolved in insects to cry toxins from Bacillus thuringiensis . Adv. Insect Physiol. 47, 297–342 (2014)

    Article  Google Scholar 

  18. 18

    Xie, R. et al. Single amino acid mutations in the cadherin receptor from Heliothis virescens affect its toxin binding ability to Cry1A toxins. J. Biol. Chem. 280, 8416–8425 (2005)

    CAS  Article  Google Scholar 

  19. 19

    Hua, G., Jurat-Fuentes, J. L. & Adang, M. J. Bt-R1a extracellular cadherin repeat 12 mediates Bacillus thuringiensis Cry1Ab binding and cytotoxicity. J. Biol. Chem. 279, 28051–28056 (2004)

    CAS  Article  Google Scholar 

  20. 20

    Nagamatsu, Y., Koike, T., Sasaki, K., Yoshimoto, A. & Furukawa, Y. The cadherin-like protein is essential to specificity determination and cytotoxic action of the Bacillus thuringiensis insecticidal CryIAa toxin. FEBS Lett. 460, 385–390 (1999)

    CAS  Article  Google Scholar 

  21. 21

    Peng, D., Xu, X., Ye, W., Yu, Z. & Sun, M. Helicoverpa armigera cadherin fragment enhances Cry1Ac insecticidal activity by facilitating toxin-oligomer formation. Appl. Microbiol. Biotechnol. 85, 1033–1040 (2010)

    CAS  Article  Google Scholar 

  22. 22

    Eren, A. M. et al. Oligotyping: differentiating between closely related microbial taxa using 16S rRNA gene data. Methods Ecol. Evol . 4, 1111–1119 (2013)

    Article  Google Scholar 

  23. 23

    Chougule, N. P. et al. Retargeting of the Bacillus thuringiensis toxin Cyt2Aa against hemipteran insect pests. Proc. Natl Acad. Sci. USA 110, 8465–8470 (2013)

    CAS  ADS  Article  Google Scholar 

  24. 24

    Fujii, Y. et al. Affinity maturation of Cry1Aa toxin to the Bombyx mori cadherin-like receptor by directed evolution. Mol. Biotechnol. 54, 888–899 (2013)

    CAS  Article  Google Scholar 

  25. 25

    Tiewsiri, K. & Wang, P. Differential alteration of two aminopeptidases N associated with resistance to Bacillus thuringiensis toxin Cry1Ac in cabbage looper. Proc. Natl Acad. Sci. USA 108, 14037–14042 (2011)

    CAS  ADS  Article  Google Scholar 

  26. 26

    Baxter, S. W. et al. Parallel evolution of Bacillus thuringiensis toxin resistance in Lepidoptera. Genetics 189, 675–679 (2011)

    CAS  Article  Google Scholar 

  27. 27

    Zhang, X., Tiewsiri, K., Kain, W., Huang, L. & Wang, P. Resistance of Trichoplusia ni to Bacillus thuringiensis toxin Cry1Ac is independent of alteration of the cadherin-like receptor for Cry toxins. PLoS ONE 7, e35991 (2012)

    CAS  ADS  Article  Google Scholar 

  28. 28

    Wang, P. et al. Mechanism of resistance to Bacillus thuringiensis toxin Cry1Ac in a greenhouse population of the cabbage looper, Trichoplusia ni . Appl. Environ. Microbiol. 73, 1199–1207 (2007)

    CAS  Article  Google Scholar 

  29. 29

    Song, X., Kain, W., Cassidy, D. & Wang, P. Resistance to Bacillus thuringiensis toxin Cry2Ab in Trichoplusia ni is conferred by a novel genetic mechanism. Appl. Environ. Microbiol. 81, 5184–5195 (2015)

    CAS  Article  Google Scholar 

  30. 30

    Carrière, Y., Crickmore, N. & Tabashnik, B. E. Optimizing pyramided transgenic Bt crops for sustainable pest management. Nature Biotechnol. 33, 161–168 (2015)

    Article  Google Scholar 

  31. 31

    Tabashnik, B. E. et al. Efficacy of genetically modified Bt toxins against insects with different genetic mechanisms of resistance. Nature Biotechnol. 29, 1128–1131 (2011)

    CAS  Article  Google Scholar 

  32. 32

    Fu, C., Donovan, W. P., Shikapwashya-Hasser, O., Ye, X. & Cole, R. H. Hot Fusion: an efficient method to clone multiple DNA fragments as well as inverted repeats without ligase. PLoS ONE 9, e115318 (2014)

    ADS  Article  Google Scholar 

  33. 33

    Lund, A. M. et al. A versatile system for USER cloning-based assembly of expression vectors for mammalian cell engineering. PLoS ONE 9, e96693 (2014)

    ADS  Article  Google Scholar 

  34. 34

    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nature Methods 9, 357–359 (2012)

    CAS  Article  Google Scholar 

  35. 35

    Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009)

    PubMed  PubMed Central  Google Scholar 

  36. 36

    Garrison, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. Preprint at (2012)

  37. 37

    Chaisson, M. J. & Tesler, G. Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory. BMC Bioinformatics 13, 238 (2012)

    CAS  Article  Google Scholar 

  38. 38

    Tan, Y. & Donovan, W. P. Deletion of aprA and nprA genes for alkaline protease A and neutral protease A from Bacillus thuringiensis: effect on insecticidal crystal proteins. J. Biotechnol. 84, 67–72 (2001)

    CAS  Article  Google Scholar 

  39. 39

    Donovan, W. P. et al. Amino acid sequence and entomocidal activity of the P2 crystal protein. An insect toxin from Bacillus thuringiensis var. kurstaki. J. Biol. Chem. 263, 561–567 (1988)

    CAS  PubMed  Google Scholar 

  40. 40

    Nallamsetty, S. et al. Efficient site-specific processing of fusion proteins by tobacco vein mottling virus protease in vivo and in vitro. Protein Expr. Purif. 38, 108–115 (2004)

    CAS  Article  Google Scholar 

  41. 41

    Baum, J. A. et al. Cotton plants expressing a hemipteran-active Bacillus thuringiensis crystal protein impact the development and survival of Lygus hesperus (Hemiptera: Miridae) nymphs. J. Econ. Entomol. 105, 616–624 (2012)

    CAS  Article  Google Scholar 

  42. 42

    Kain, W. C. et al. Inheritance of resistance to Bacillus thuringiensis Cry1Ac toxin in a greenhouse-derived strain of cabbage looper (Lepidoptera: Noctuidae). J. Econ. Entomol. 97, 2073–2078 (2004)

    CAS  Article  Google Scholar 

  43. 43

    Abbott, W. S. A method of computing the effectiveness of an insecticide. 1925. J. Am. Mosq. Control Assoc. 3, 302–303 (1987)

    CAS  PubMed  Google Scholar 

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This work was supported by National Institutes of Health/National Institute of Biomedical Imaging and Bioengineering R01EB022376, DARPA HR0011-11-2-0003, DARPA N66001-12-C-4207, the Howard Hughes Medical Institute, and the US Department of Agriculture National Institute of Food and Agriculture and Agricultural Research Service Biotechnology Risk Assessment Grant Program 2012-33522-19791. A.H.B. was supported by the Harvard Chemical Biology Program and a National Science Foundation Graduate Research Fellowship. We are grateful to J. Carlson, J. Nageotte, D. Rappoli, J.-L. Kouadio, M. Zheng, J. Milligan, M. Huang, Z. Du, X. Zhou, E. Kraft, and J. Wang for their assistance.

Author information




A.H.B. designed the research, performed experiments, analysed data, and wrote the manuscript. D.R.L. designed and supervised the research and wrote the manuscript. V.M.G. and T.M. designed the initial Cry1Ac/TBR3 pair for evolution in PACE. V.M.G. designed and supervised the research on the evaluation of evolved and stabilized Cry1Ac variants. V.M.G. and P.V. designed stabilized Cry1Ac variants. Q.H. performed protein purification and in vitro binding analysis, and analysed data. M.M.K. performed the insect cell-based assays. W.K., P.W., and A.M.N. performed insect diet bioassays using evolved Cry1Ac variants. A.E. and F.M. designed and validated the Cry1Ac-binding TBR3 mutant. K.H.T. analysed high-throughput sequencing data. All of the authors contributed to editing the manuscript.

Corresponding author

Correspondence to David R. Liu.

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Competing interests

The authors have filed a provisional patent application on the PACE system and related improvements.

Extended data figures and tables

Extended Data Figure 1 Bacterial two-hybrid component validation and optimization.

a, Plasmids encoding an IPTG-inducible λ cI–SH2 cassette (‘DBD’) and an ATc-inducible activator-HA4 cassette (‘activator’) were co-transformed into the E. coli S1030 host strain and induced using either or both small molecules. T4 AsiA-mediated transcriptional activation required low-level expression of the σ70 (R541C/F563Y/L607P) mutant to alleviate AsiA toxicity. Use of RpoZ as the activation domain showed the greatest degree of transcriptional activation (~17-fold). b, DNA-binding domain variation shows that multivalent phage repressors yield a greater degree of transcriptional activation than the monomeric zinc finger Zif268. c, Transcriptional activation from a combination of the λcI DNA binding domain and RpoZ transcriptional activator was evaluated using several previously evolved protein–protein interactions involving either monobodies or DARPins, showing the generality of binding interaction detection. Error bars, s.d. of at least three independent biological replicates.

Extended Data Figure 2 Optimization of the PlacZ promoter for improved sensitivity and dynamic range.

a, Promoter and DNA-binding domain combinations tested during PlacZ optimization, showing uninduced and induced levels of absorbance-normalized luminescence. The SH2/HA4 interaction pair was used in all cases. The fold activation in each case was calculated as the ratio of the induced and uninduced luciferase expression signals. b, Graphical representation of the data in a, showing the wide distribution of promoter background levels and degrees of transcriptional activation. In a and b, the red and green dots indicate the starting (Plac62) and final (PlacZ-opt) promoter/DNA-binding domain combinations, respectively. Each data point in b reflects the average of at least three independent biological replicates.

Extended Data Figure 3 Bacterial two-hybrid optimization.

a, Inducer titration of the interacting fusion proteins driving the two-hyrbid system. The black and green lines represent the uninduced (0 μM IPTG) and induced (1 μM IPTG) levels of IPTG-inducible 434cI–SH2 expression, while ATc induces expression of the rpoZ–HA4 cassette. In subsequent graphs and assays, the expression level resulting from the IPTG-inducible Plac promoter was measured by western blot and approximated using a constitutive promoter to reduce experimental variability. b, Degree of transcriptional activation using HA4 monobody mutants correlated with known binding affinities. The highest levels of activation resulted from Kd = low nanomolar affinities, while weak affinities in the Kd = low micromolar range could still be detected. c, Relationship between DNA-binding domain multivalency state (monomeric, dimeric, or tetrameric DNA-binding domain fused to the SH2 domain) and transcriptional activation resulting from the SH2/HA4 interaction, with higher multivalency states yielding greater activation levels. d, RBS modification enables robust modulation of the relative activation levels from the PlacZ-opt promoter using the SH2/HA4 interaction. e, Operator–promoter binding site spacing strongly affects transcriptional activation levels; 434cI binding at 61 base pairs upstream of the PlacZ-opt promoter resulted in the most robust activation. f, Linker extension to include one, two, or three G4S motifs result in reduced activation levels using the SH2/HA4 interacting pair. g, Phage plaque formation as a function of target protein multivalency. ‘No operator’ indicates a scrambled 434cI operator control accessory plasmid; ‘phage control’ indicates an accessory plasmid in which the phage shock promoter (activated by phage infection) drives gene III expression. h, Co-crystal structure of the ABL1 SH2 (blue) bound to the HA4 monobody (red), highlighting the interaction of HA4 Y87 (red spheres) with key residues of the phosophotyrosine-binding pocket (blue spheres) of the SH2 domain (Protein Data Bank accession number 3K2M). The phosphate ion is shown in orange at the interaction interface. i, Apparent binding activity of mutants of the HA4 monobody at position 87. Tyrosine, tryptophan, and phenylalanine are tolerated at position 87 and enable protein–protein interaction by bacterial two-hybrid assay. Error bars, s.d. of at least three independent biological replicates.

Extended Data Figure 4 Choice of Cry1Ac and TnTBR3 fragments used in PACE.

a, Protein sequence alignment of known Cry1Ac-binding motifs from cadherin receptors in several lepidopteran species, as well as the cadherin receptor from T. ni (TnCAD). The toxin-binding region (TBR; shown in red) of the known Cry1Ac-binding motifs differs from TnCAD at seven positions (shown in blue). Mutation of three residues in the TnCAD TBR (M1433F, L1436S, and D1437A) to resemble the corresponding positions of the cadherin-receptor TBRs yielded the evolutionary stepping-stone target TnTBR3. b, Schematic representations of the Cry1Ac and T. ni TBR3/CAD full-length receptors and fragments tested in this study. The red stars in the TnTBR3 variants represent the three mutations introduced into TnCAD to generate TnTBR3. c, Transcriptional activation assay using Cry1Ac and TnTBR3 fragments shows that the greatest degree of transcriptional activation resulted from full-length Cry1Ac together with TBR3 fragment 3 (TnTBR3-F3). RpoZ–Cry1Ac and 434cI–TnTBR3 fusions were used in all cases. d, Overnight phage enrichment assays using selection phages that encode either kanamycin resistance (KanR) only or KanR together with RpoZ–Cry1Ac. Compared with the KanR-only selection phage, the RpoZ–Cry1Ac selection phage enriches >26,000-fold overnight. e, Continuous propagation assays in the PACE format using either the KanR-only selection phage or the RpoZ–Cry1Ac selection phage show that the moderate affinity of Cry1Ac for TnTBR3 allows phage propagation at low flow rates (≤1.5 lagoon volumes per hour).

Extended Data Figure 5 Single-clone sequencing and evolved Cry1Ac characterization after PACE using the bacterial two-hybrid luminescence reporter.

a, Coding mutations of the tested RpoZ–Cry1Ac clones at the end of each of the four segments of PACE. Consensus mutations are coloured according to the segment in which they became highly enriched in the population (Fig. 3a). Mutations coloured in black were observed at low abundance (≤5% of sequenced clones). b, Mutational dissection of the consensus mutations from the first segment of PACE reveals the requirement for both D384Y and S404C to achieve high-level transcriptional activation using the TnTBR3-F3 target. Mutations listed in red occurred in the RpoZ activation domain, whereas mutations listed in blue occurred in the Cry1Ac domain. Error bars, s.d. of at least three independent biological replicates. c, Structure of wild-type Cry1Ac (Protein Data Bank accession number 4ARX) showing the positions of the evolved consensus mutations. The colours correspond to the PACE segments shown in Fig. 3 during which the mutations became highly abundant.

Extended Data Figure 6 High-throughput DNA sequencing of PACE Cry1Ac selection phage libraries.

The number of reads mapped to the wild-type rpoZ–Cry1Ac reference sequence using (a) Pacific Biosciences (PacBio) or (b) Illumina sequencing. Time points are coloured according to the corresponding segment of the PACE experiment (Fig. 3a). c, In general, most PacBio reads aligned to the wt rpoZ–Cry1Ac reference sequence were found to cluster around ~2,200 base pairs, corresponding to the size of the full-length fusion gene and indicating high-quality sequencing reads. d, Illumina high-throughput sequencing yielded several high-quality single nucleotide polymorphisms across all time points. The corresponding mutations are shown in e.

Extended Data Figure 7 Insect diet bioassay activity of PACE-evolved Cry1Ac variants against various agricultural pests.

Two consensus and three stabilized PACE-evolved Cry1Ac variants were tested for activity in eleven pests: a, C. includes (soybean looper); b, Heliothis virescens (tobacco budworm); c, Helicoverpa zea (corn earworm); d, Plutella xylostella (diamondback moth); e, Agrotis ipsilon (black cutworm); f, Spodoptera frugiperda (fall armyworm); g, Anticarsia gemmatalis (velvetbean caterpillar); h, Diatraea saccharalis (sugarcane borer); Spodoptera eridania (southern armyworm); Leptinotarsa decemlineata (Colorado potato beetle); and Lygus lineolaris (tarnished plant bug). Stabilized variants showed enhanced activity in C. includens and H. virescens compared with wild-type Cry1Ac, and comparable activity to wild-type Cry1Ac in H. zea, P. xylostella, A. ipsilon, S. frugiperda, A. gemmatalis, and D. saccharalis. No activity was observed for any of the Cry1Ac variants at any tested dose for S. eridania, L. decemlineata, or L. lineolaris. No insect larvae mortality was observed for S. frugiperda, although high toxin doses greatly stunted growth.

Extended Data Figure 8 Comparison of cadherin receptor sequence identity.

The percentage sequence identity using the full-length cadherin receptor (a) or fragment used for directed evolution experiments (b) for insects tested in Extended Data Fig. 7. Numbers in parentheses denote the number of identical amino acids between the two receptors. In general, mortality and stunting data from diet bioassays correlate with cadherin receptor sequence identity.

Extended Data Table 1 Insect bioassays against susceptible and resistant T. ni
Extended Data Table 2 Plasmids used in this work

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Badran, A., Guzov, V., Huai, Q. et al. Continuous evolution of Bacillus thuringiensis toxins overcomes insect resistance. Nature 533, 58–63 (2016).

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