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Biocontainment of genetically modified organisms by synthetic protein design

Nature volume 518, pages 55–60 (2015)Cite this article

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A Corrigendum to this article was published on 23 September 2015

Abstract

Genetically modified organisms (GMOs) are increasingly deployed at large scales and in open environments. Genetic biocontainment strategies are needed to prevent unintended proliferation of GMOs in natural ecosystems. Existing biocontainment methods are insufficient because they impose evolutionary pressure on the organism to eject the safeguard by spontaneous mutagenesis or horizontal gene transfer, or because they can be circumvented by environmentally available compounds. Here we computationally redesign essential enzymes in the first organism possessing an altered genetic code (Escherichia coli strain C321.ΔA) to confer metabolic dependence on non-standard amino acids for survival. The resulting GMOs cannot metabolically bypass their biocontainment mechanisms using known environmental compounds, and they exhibit unprecedented resistance to evolutionary escape through mutagenesis and horizontal gene transfer. This work provides a foundation for safer GMOs that are isolated from natural ecosystems by a reliance on synthetic metabolites.

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Figure 1: Computational design of NSAA-dependent essential proteins.
Figure 2: Escape frequencies and doubling times of auxotrophic strains.
Figure 3: Structural specificity at designed UAG positions in eight NSAA-dependent enzymes correlates with escape frequencies.
Figure 4: Competition between synthetic auxotroph escapees and prototrophic E. coli.
Figure 5: Synthetic auxotrophy and genomic recoding reduce HGT-mediated escape.

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Protein Data Bank

Data deposits

Atomic coordinates and structure factors for the reported crystal structure have been deposited in the Protein Data Bank under accession number 4OUD.

References

  1. Moe-Behrens, G. H., Davis, R. & Haynes, K. A. Preparing synthetic biology for the world. Front. Microbiol. 4, 5 (2013)

    Article  PubMed  PubMed Central  Google Scholar 

  2. Molin, S. et al. Conditional suicide system for containment of bacteria and plasmids. Nature Biotechnol. 5, 1315–1318 (1987)

    Article  CAS  Google Scholar 

  3. Li, Q. & Wu, Y.-J. A fluorescent, genetically engineered microorganism that degrades organophosphates and commits suicide when required. Appl. Microbiol. Biotechnol. 82, 749–756 (2009)

    Article  CAS  PubMed  Google Scholar 

  4. Curtiss, R., III Biological containment and cloning vector transmissibility. J. Infect. Dis. 137, 668–675 (1978)

    Article  CAS  PubMed  Google Scholar 

  5. Ronchel, M. C. & Ramos, J. L. Dual system to reinforce biological containment of recombinant bacteria designed for rhizoremediation. Appl. Environ. Microbiol. 67, 2649–2656 (2001)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Wright, O., Delmans, M., Stan, G. B. & Ellis, T. GeneGuard: a modular plasmid system designed for biosafety. ACS Synth. Biol. http://dx.doi.org/doi:10.1021/sb500234s (13 May 2014)

  7. Knudsen, S. et al. Development and testing of improved suicide functions for biological containment of bacteria. Appl. Environ. Microbiol. 61, 985–991 (1995)

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Pasotti, L., Zucca, S., Lupotto, M., Cusella De Angelis, M. G. & Magni, P. Characterization of a synthetic bacterial self-destruction device for programmed cell death and for recombinant proteins release. J. Biol. Eng. 5, 8 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Lajoie, M. J. et al. Genomically recoded organisms expand biological functions. Science 342, 357–360 (2013)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  10. Xie, J., Liu, W. & Schultz, P. G. A genetically encoded bidentate, metal-binding amino acid. Angew. Chem. 46, 9239–9242 (2007)

    Article  CAS  Google Scholar 

  11. Renfrew, P. D., Choi, E. J., Bonneau, R. & Kuhlman, B. Incorporation of noncanonical amino acids into Rosetta and use in computational protein-peptide interface design. PLoS ONE 7, e32637 (2012)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  12. Baba, T. et al. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol. Syst. Biol. 2, 2006.0008 (2006)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Wu, H. C. & Wu, T. C. Isolation and characterization of a glucosamine-requiring mutant of Escherichia coli K-12 defective in glucosamine-6-phosphate synthetase. J. Bacteriol. 105, 455–466 (1971)

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Carr, P. A. et al. Enhanced multiplex genome engineering through co-operative oligonucleotide co-selection. Nucleic Acids Res. (2012)

  15. Berman, H. M. et al. The Protein Data Bank. Nucleic Acids Res. 28, 235–242 (2000)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  16. Wang, H. H. et al. Programming cells by multiplex genome engineering and accelerated evolution. Nature 460, 894–898 (2009)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  17. Shannon, C. E. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423 (1948)

    Article  MathSciNet  MATH  Google Scholar 

  18. saiSree, L., Reddy, M. & Gowrishankar, J. IS186 insertion at a hot spot in the lon promoter as a basis for lon protease deficiency of Escherichia coli B: identification of a consensus target sequence for IS186 transposition. J. Bacteriol. 183, 6943–6946 (2001)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Tomoyasu, T., Mogk, A., Langen, H., Goloubinoff, P. & Bukau, B. Genetic dissection of the roles of chaperones and proteases in protein folding and degradation in the Escherichia coli cytosol. Mol. Microbiol. 40, 397–413 (2001)

    Article  CAS  PubMed  Google Scholar 

  20. Steidler, L. et al. Biological containment of genetically modified Lactococcus lactis for intestinal delivery of human interleukin 10. Nature Biotechnol. 21, 785–789 (2003)

    Article  CAS  Google Scholar 

  21. Smillie, C. S. et al. Ecology drives a global network of gene exchange connecting the human microbiome. Nature 480, 241–244 (2011)

    Article  ADS  CAS  PubMed  Google Scholar 

  22. Wollman, E. L., Jacob, F. & Hayes, W. Conjugation and genetic recombination in Escherichia coli K-12. Cold Spring Harb. Symp. Quant. Biol. 21, 141–162 (1956)

    Article  CAS  PubMed  Google Scholar 

  23. Mukai, T. et al. Codon reassignment in the Escherichia coli genetic code. Nucleic Acids Res. 38, 8188–8195 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Kortemme, T., Morozov, A. V. & Baker, D. An orientation-dependent hydrogen bonding potential improves prediction of specificity and structure for proteins and protein–protein complexes. J. Mol. Biol. 326, 1239–1259 (2003)

    Article  CAS  PubMed  Google Scholar 

  25. Malyshev, D. A. et al. A semi-synthetic organism with an expanded genetic alphabet. Nature 509, 385–388 (2014)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  26. Schmidt, M. & de Lorenzo, V. Synthetic constructs in/for the environment: managing the interplay between natural and engineered Biology. FEBS Lett. 586, 2199–2206 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Benson, D. A., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J. & Wheeler, D. L. GenBank. Nucleic Acids Res. 33, D34–D38 (2005)

    Article  CAS  PubMed  Google Scholar 

  28. UniProt Consortium. Update on activities at the Universal Protein Resource (UniProt) in 2013. Nucleic Acids Res. 41, D43–D47 (2013)

  29. Chaudhury, S., Lyskov, S. & Gray, J. J. PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta. Bioinformatics 26, 689–691 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Fraczkiewicz, R. & Braun, W. Exact and efficient analytical calculation of the accessible surface areas and their gradients for macromolecules. J. Comput. Chem. 19, 319–333 (1998)

    Article  CAS  Google Scholar 

  31. Zhu, H., Fraczkiewicz, R. & Braun, W. Solvent Accessible Surface Areas, Atomic Solvation Energies, and Their Gradients for Macromolecules http://curie.utmb.edu/area_man.html (2012)

    Google Scholar 

  32. Kuhlman, B. & Baker, D. Native protein sequences are close to optimal for their structures. Proc. Natl Acad. Sci. USA 97, 10383–10388 (2000)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. Gregg, C. J. et al. Rational optimization of tolC as a powerful dual selectable marker for genome engineering. Nucleic Acids Res. 42, 4779–4790 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nature Methods 6, 343–345 (2009)

    Article  CAS  PubMed  Google Scholar 

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

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  37. Isaacs, F. J. et al. Precise manipulation of chromosomes in vivo enables genome-wide codon replacement. Science 333, 348–353 (2011)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  38. Otwinowski, Z. & Minor, W. in Methods in Enzymology Vol. 276 (ed Carter, C. W. Jr ) 307–326 (Academic, 1997)

    Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  40. Brünger, A. T. et al. Crystallography & NMR system: a new software suite for macromolecular structure determination. Acta Crystallogr. D 54, 905–921 (1998)

    PubMed  Google Scholar 

  41. Eggertsson, G. & Soll, D. Transfer ribonucleic acid-mediated suppression of termination codons in Escherichia coli. Microbiol. Rev. 52, 354–374 (1988)

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Fadrosh, D. W. et al. An improved dual-indexing approach for multiplexed 16S rRNA gene sequencing on the Illumina MiSeq platform. Microbiome 2, 6 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

  43. Rohland, N. & Reich, D. Cost-effective, high-throughput DNA sequencing libraries for multiplexed target capture. Genome Res. 22, 939–946 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zerbino, D. R. & Birney, E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 18, 821–829 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Young, T. S., Ahmad, I., Yin, J. A. & Schultz, P. G. An enhanced system for unnatural amino acid mutagenesis in E. coli. J. Mol. Biol. 395, 361–374 (2010)

    Article  CAS  PubMed  Google Scholar 

  46. Lutz, R. & Bujard, H. Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. Nucleic Acids Res. 25, 1203–1210 (1997)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Tolonen, A. C., Chilaka, A. C. & Church, G. M. Targeted gene inactivation in Clostridium phytofermentans shows that cellulose degradation requires the family 9 hydrolase Cphy3367. Mol. Microbiol. 74, 1300–1313 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank D. Renfrew for help with NSAA modelling in Rosetta, D. Goodman and R. Chari for sequence analysis assistance, M. Napolitano for advice on Lon-mediated escape assays, J. Teramoto and B. Wanner for the pJTE2 jumpstart plasmid, and F. Isaacs for manuscript comments. D.J.M. is a Howard Hughes Medical Institute Fellow of the Life Sciences Research Foundation. M.J.L. was supported by a US Department of Defense National Defense Science and Engineering Graduate Fellowship. M.T.M. was supported by a Doctoral Study Award from the Canadian Institutes of Health Research. The research was supported by Department of Energy Grant DE-FG02-02ER63445.

Author information

Author notes

  1. Daniel J. Mandell and Marc J. Lajoie: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Genetics, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Daniel J. Mandell, Marc J. Lajoie, Michael T. Mee, Gleb Kuznetsov, Julie E. Norville, Christopher J. Gregg & George M. Church

  2. Program in Chemical Biology, Harvard University, Cambridge, 02138, Massachusetts, USA

    Marc J. Lajoie

  3. Department of Biomedical Engineering, Boston University, Boston, 02215, Massachusetts, USA

    Michael T. Mee

  4. Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, 98109, Washington, USA

    Ryo Takeuchi & Barry L. Stoddard

  5. Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, 02115, Massachusetts, USA

    George M. Church

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Contributions

D.J.M., M.J.L., M.T.M. and G.M.C. conceived the project and designed the study, with D.J.M. as computational lead and M.J.L. as experimental lead. D.J.M. computationally designed synthetic auxotrophs, performed strain engineering, characterized escape frequencies and fitness of synthetic auxotrophs, performed western blot analyses and prepared samples for mass spectrometry and X-ray crystallography. M.J.L. performed strain engineering, performed site-saturation mutagenesis at UAG positions, performed whole-genome sequencing of escapees, validated escape mechanisms and assessed HGT by conjugation. M.T.M. measured escape frequencies and fitness of natural metabolic auxotrophs, performed competition assays and assessed HGT by conjugation. R.T. and B.L.S. crystallized tyrS.d7 and determined the X-ray structure. G.K. analysed whole-genome sequencing data of escapees. J.E.N. and C.J.G. developed the tdk selection protocol. D.J.M., M.J.L. and M.T.M. wrote the paper.

Corresponding author

Correspondence to George M. Church.

Ethics declarations

Competing interests

Harvard has filed a provisional patent application. G.M.C. is a founder of Enevolv Inc. and Gen9bio. Other potentially relevant financial interests are listed at http://arep.med.harvard.edu/gmc/tech.html.

Extended data figures and tables

Extended Data Figure 1 bipA dependence in synthetic auxotrophs.

Prototrophic and synthetic auxotrophic strains were grown in titrations of bipA and monitored in a microplate reader (Methods). Media for all bipA concentrations contained SDS, chloramphenicol and arabinose. Doubling times for three technical replicates are shown. Positive and negative error bars are s.e.m. Growth was undetectable for synthetic auxotrophs at 0.00 μM, 0.01 μM and 0.10 μM bipA, as well as 0.50 μM bipA for adk.d6_tyrS.d8.

Extended Data Figure 2 Mass spectrometry of NSAA-dependent enzymes.

Mass spectrometry was performed and peptide spectrum matches (PSMs) were obtained as described in the Methods. Data sets were culled of minor contaminant PSMs and re-searched with SEQUEST against adk.d6, tyrS.d7 and tyrS.d8 sequences without taking into account enzyme specificity. To interrogate the sequences for bipA, tryptophan and leucine, the amino acid at the bipA position was given the mass of leucine and searches were performed with differential modifications of +110.01565 and +72.99525 to account for the masses of bipA and tryptophan, respectively. In all samples, only bipA, and not leucine or tryptophan, was detected at these positions. The PSM for adk.d6 is shown. Peptides observed to contain bipA are LVEYHQMTAP[bipA]IGYVSK (adk.d6), AQYV[bipA]AEQVTR (tyrS.d7) and AQYV[bipA]AEQATR (tyrS.d8).

Extended Data Figure 3 Crystal structure of tyrS.d7.

a, Overall structure of the redesigned enzyme. The N-terminal domain (residues 4–330) that catalyses tyrosine activation, the carboxy-terminal tRNA-binding domain (residues 350–424) and their connecting region are coloured cyan, blue and yellow, respectively. The residues 232–241 are disordered (dash line). b, Comparison between the C-terminal tRNA recognition domains of tyrS.d7 (blue) and of Thermus thermophilus TyrS (orange; PDB code 1H3E). The residues 352–442 of the hyperthermophilic TyrS are shown. c, The N-terminal domain of the engineered protein is superposed on the crystal structure of its parental enzyme (green; PDB code 1X8X). The KMSKS loop of the parental enzyme is highlighted in magenta. d, Tyrosine molecule bound to tyrS.d7. An electron density map of l-tyrosine is shown as a grey mesh (2Fo − Fc contoured at 1.2σ; top panel). A tyrosine and the surrounding protein fold of tyrS.d7 (cyan) are very similar to those of the wild-type TyrS structure (green; bottom panel).

Extended Data Figure 4 Western blot analysis of tyrS.d7 variants.

Variants of tyrS.d7 with leucine or tryptophan at the bipA position were expressed as GST fusions under identical conditions and analysed by western blot (Methods). Soluble protein content was quantified by densitometry and normalized to GAPDH. Mutating bipA to leucine or tryptophan reduced soluble TyrS levels by 2.5- or 2.1-fold, respectively (P < 0.05 by two-tailed unpaired Student’s t-test with unequal variances). Three technical replicates were performed; a representative image is shown. Positive error bars are s.e.m.

Extended Data Figure 5 Population selection dynamics for canonical amino acid substitutions at designed UAG positions.

For each plot, degenerate MAGE oligonucleotides were used to create a population of cells in which the UAG codon was mutated to all 64 codons. Codon substitutions leading to survival in the absence of bipA were selected by growth in LBL media without bipA and arabinose supplementation. Aliquots of the culture population were taken at 1 h, 4 h, confluence 1 (once the culture reached confluence), confluence 2 (after regrowth of a 100-fold dilution of confluence 1) and confluence 3 (after regrowth of a 100-fold dilution of confluence 2). The amino acid identity at the bipA position was probed by targeted Illumina sequencing. Residual bipA-containing proteins were expected to remain active until intracellular protein turnover cleared them from the cell, making the 1-h time point a reasonable representation of initial diversity present in the population. These data show the relative fitness of amino acid substitutions in a given protein variant; relative fitness across multiple protein variants cannot be accurately assessed from these data.

Extended Data Figure 6 Natural metabolites can circumvent auxotrophies.

a–d, Synthetic auxotrophs of pgk can be complemented by pyruvate or succinate. Strains were cultured in LBL in the presence of pyruvate, succinate, glucose or bipA (10 µM) and monitored by kinetic growth. The single-enzyme synthetic auxotroph pgk.d4 (a) grows similarly to prototrophic C321.ΔA (b) in the presence of pyruvate and succinate, but not glucose. Synthetic auxotrophs of adk (c) and tyrS (d) grow robustly in bipA but cannot be complemented by pyruvate or succinate. Growth of pgk.d4 and adk.d6 in glucose after 1,000 min is due to mutational escape (loss of bipA dependence). e, The synthetic auxotroph parental strain (C321.ΔA), a second prototrophic MG1655-derived strain (EcNR1), and three natural auxotroph derivatives of EcNR1 were grown in LBL supplemented with 166.66 ml l−1 bacterial lysate (Teknova). Growth curves are shown with doubling times ± one standard deviation of three technical replicates next to the labels. The conditions fully complement the metabolic auxotrophy of EcNR1.ΔthyA, which doubles as robustly as prototrophic EcNR1. Strains lacking the asd gene (EcNR1.Δasd and the EcNR1.ΔasdΔthyA double knockout) show more impairment but enter exponential growth with doubling times of 91 to 137 min, respectively. f, g, Single- (f) and double-enzyme (g) synthetic auxotrophies are not complemented by natural products in rich media or bacterial lysate. h, When the Δasd auxotrophy is combined with double-enzyme synthetic auxotrophies the natural products are no longer sufficient to support growth. No growth is indicated by an asterisk in f–h.

Extended Data Figure 7 Analysis of the A70V mutation as an escape mechanism for tyrS.d8.

a, The X-ray structure of tyrS.d7 is shown; tyrS.d8 varies by the single mutation V307A. BipA303, A70 and their neighbouring side chains are shown in stick representation, with bipA303 and A70 coloured orange. The bound tyrosine substrate is shown in spacefill. The A70V mutation (white sticks) may stabilize the catalytic domain when bipA is replaced by natural amino acids by tightly packing with neighbouring side chains including V108. b, Escape frequencies on non-permissive media for three separately constructed tyrS.d8 A70V strains are shown for days 1 through 4. Although escapees are growth-impaired in the absence of bipA (Supplementary Table 10), all cells form colonies after 5 days, suggesting that A70V confers 100% survival on non-permissive media. Positive error bars indicate s.e.m.

Extended Data Figure 8 Conjugal escape frequencies of synthetic auxotrophs.

Single-, double- and triple-enzyme auxotrophs were assayed to determine the frequency of escape by HGT and recombination from a prototrophic donor as described in the Methods. These results highlight the benefit of having multiple auxotrophies distributed throughout the genome. Notably, scaling from a single synthetic auxotrophy to three distributed auxotrophies results in a reduction of conjugal escape by at least two orders of magnitude. Positive error bars indicate standard deviation.

Extended Data Table 1 Data collection and refinement statistics
Full size table
Extended Data Table 2 Cost per litre of culture for commonly used NSAAs
Full size table

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Mandell, D., Lajoie, M., Mee, M. et al. Biocontainment of genetically modified organisms by synthetic protein design. Nature 518, 55–60 (2015). https://doi.org/10.1038/nature14121

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