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.

Genetic circuit design automation with Cello 2.0

Abstract

Cells interact with their environment, communicate among themselves, track time and make decisions through functions controlled by natural regulatory genetic circuits consisting of interacting biological components. Synthetic programmable circuits used in therapeutics and other applications can be automatically designed by computer-aided tools. The Cello software designs the DNA sequences for programmable circuits based on a high-level software description and a library of characterized DNA parts representing Boolean logic gates. This process allows for design specification reuse, modular DNA part library curation and formalized circuit transformations based on experimental data. This protocol describes Cello 2.0, a freely available cross-platform software written in Java. Cello 2.0 enables flexible descriptions of the logic gates’ structure and their mathematical models representing dynamic behavior, new formal rules for describing the placement of gates in a genome, a new graphical user interface, support for Verilog 2005 syntax and a connection to the SynBioHub parts repository software environment. Collectively, these features expand Cello’s capabilities beyond Escherichia coli plasmids to new organisms and broader genetic contexts, including the genome. Designing circuits with Cello 2.0 produces an abstract Boolean network from a Verilog file, assigns biological parts to each node in the Boolean network, constructs a DNA sequence and generates highly structured and annotated sequence representations suitable for downstream processing and fabrication, respectively. The result is a sequence implementing the specified Boolean function in the organism and predictions of circuit performance. Depending on the size of the design space and users’ expertise, jobs may take minutes or hours to complete.

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

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Basic software architecture of Cello 2.0.
Fig. 2: NOR gate architectures.
Fig. 3: Visualization of gate model and function definitions.
Fig. 4: A selection of Eugene rules and circuits that satisfy or violate the rules.
Fig. 5: The Verilog editor and input and output selection panes in the GUI.
Fig. 6: The results view in the GUI.
Fig. 7: An XNOR gate designed in all five libraries available in Cello 2.0.
Fig. 8: The expected results of a case study aiming at designing the circuit 0×01 (three-input AND gate) using the SC1C1G1T1 library.

Data availability

The data that support the findings of this study (i.e., standard UCF libraries, input sensor files and output device files) are openly available at https://doi.org/10.5281/zenodo.4676314.

Code availability

Code for Cello 2.0 is divided among various openly available repositories. The core circuit design module is available at https://doi.org/10.5281/zenodo.4676314, the code for the web application is available at https://doi.org/10.5281/zenodo.4676310 and the source code of the GUI (which is compiled into the webapp) is available at https://doi.org/10.5281/zenodo.4676300. A file (in .zip format), containing all the source code in the version used in the study, associated test data, parameters and documentation, is openly available at https://publication-artifacts.s3.amazonaws.com/cellov2.zip. The source code is openly distributed in accordance with Boston University’s Data Protection Standards (https://www.bu.edu/policies/data-protection-standards/pdf/) and under the MIT license at https://opensource.org/licenses/MIT.

References

  1. Cheng, A. A. & Lu, T. K. Synthetic biology: an emerging engineering discipline. Annu. Rev. Biomed. Eng. 14, 155–178 (2012).

    CAS  Article  Google Scholar 

  2. Khalil, A. S. & Collins, J. J. Synthetic biology: applications come of age. Nat. Rev. Genet. 11, 367–379 (2010).

    CAS  Article  Google Scholar 

  3. Endy, D. Foundations for engineering biology. Nature 438, 449–453 (2005).

    CAS  Article  Google Scholar 

  4. Bueso, Y. F. & Tangney, M. Synthetic biology in the driving seat of the bioeconomy. Trends Biotechnol. 35, 373–378 (2017).

    Article  Google Scholar 

  5. Purnick, P. E. & Weiss, R. The second wave of synthetic biology: from modules to systems. Nat. Rev. Mol. Cell Biol. 10, 410–422 (2009).

    CAS  Article  Google Scholar 

  6. Mano, M. M. R. & Ciletti, M. D. Digital Design: With an Introduction to the Verilog HDL, VHDL, and SystemVerilog (Pearson, 2018).

  7. Rabaey, J. M., Chandrakasan, A. P. & Nikolić, B. Digital Integrated Circuits: A Design Perspective (Prentice Hall, 2008).

  8. Oliveira, S. M. D. et al. Temperature-dependent model of multi-step transcription initiation in Escherichia coli based on live single-cell measurements. PLoS Comput. Biol. https://doi.org/10.1371/journal.pcbi.1005174 (2016).

  9. Tabor, J. J. et al. A synthetic genetic edge detection program. Cell 137, 1272–1281 (2009).

    Article  Google Scholar 

  10. Stephens, K. & Bentley, W. E. Synthetic biology for manipulating quorum sensing in microbial consortia. Trends Microbiol. 28, 633–643 (2020).

    CAS  Article  Google Scholar 

  11. Brophy, J. A. N. & Voigt, C. A. Principles of genetic circuit design. Nat. Methods 11, 508–520 (2014).

    CAS  Article  Google Scholar 

  12. Nielsen, A. A. K. et al. Genetic circuit design automation. Science 352, aac7341 (2016).

  13. Hasty, J., McMillen, D. & Collins, J. J. Engineered gene circuits. Nature 420, 224–230 (2002).

    CAS  Article  Google Scholar 

  14. Andrews, L. B., Nielsen, A. A. K. & Voigt, C. A. Cellular checkpoint control using programmable sequential logic. Science 361, eaap8987 (2018).

  15. Bilitchenko, L. et al. Eugene—a domain specific language for specifying and constraining synthetic biological parts, devices, and systems. PLoS ONE 6, e18882 (2011).

    CAS  Article  Google Scholar 

  16. Woodruff, L. B. et al. Registry in a tube: multiplexed pools of retrievable parts for genetic design space exploration. Nucleic Acids Res. 45, 1553–1565 (2017).

    CAS  PubMed  Google Scholar 

  17. Hossain, A. et al. Automated design of thousands of nonrepetitive parts for engineering stable genetic systems. Nat. Biotechnol. 38, 1466–1475 (2020).

    CAS  Article  Google Scholar 

  18. Huynh, L., Tsoukalas, A., Köppe, M. & Tagkopoulos, I. SBROME: a scalable optimization and module matching framework for automated biosystems design. ACS Synth. Biol. 2, 263–273 (2013).

    CAS  Article  Google Scholar 

  19. Yaman, F., Bhatia, S., Adler, A., Densmore, D. & Beal, J. Automated selection of synthetic biology parts for genetic regulatory networks. ACS Synth. Biol. 1, 332–344 (2012).

    CAS  Article  Google Scholar 

  20. Beal, J., Lu, T. & Weiss, R. Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks. PLoS ONE 6, e22490 (2011).

    CAS  Article  Google Scholar 

  21. Czar, M. J., Cai, Y. & Peccoud, J. Writing DNA with GenoCADTM. Nucleic Acids Res. 37, W40–W47 (2009).

    CAS  Article  Google Scholar 

  22. Chen, J., Densmore, D., Ham, T. S., Keasling, J. D. & Hillson, N. J. DeviceEditor visual biological CAD canvas. J. Biol. Eng. 6, 1–12 (2012).

    Article  Google Scholar 

  23. Roehner, N. & Myers, C. J. Directed acyclic graph-based technology mapping of genetic circuit models. ACS Synth. Biol. 3, 543–555 (2014).

    CAS  Article  Google Scholar 

  24. Salis, H. M. The ribosome binding site calculator. Methods Enzymol. 498, 19–42 (2011).

    CAS  Article  Google Scholar 

  25. Rodrigo, G., Carrera, J. & Jaramillo, A. Genetdes: automatic design of transcriptional networks. Bioinformatics 23, 1857–1858 (2007).

    CAS  Article  Google Scholar 

  26. Wilson, E. H., Macklin, C., & Platt, D. Engineering genomes with genotype specification language. in Synthetic Biology 373–398 (Humana Press, 2018).

  27. Pedersen, M. & Phillips, A. Towards programming languages for genetic engineering of living cells. J. R. Soc. Interface 6, S437–S450 (2009).

    CAS  Article  Google Scholar 

  28. Wolf, C. Yosys Open Synthesis Suite (2016).

  29. Vaidyanathan, P. et al. A framework for genetic logic synthesis. Proc. IEEE 103, 2196–2207 (2015).

    Article  Google Scholar 

  30. Roehner, N. et al. Sharing structure and function in biological design with SBOL 2.0. ACS Synth. Biol. 5, 498–506 (2016).

    CAS  Article  Google Scholar 

  31. McLaughlin, J. A. et al. SynBioHub: a standards-enabled design repository for synthetic biology. ACS Synth. Biol. 7, 682–688 (2018).

    CAS  Article  Google Scholar 

  32. Shin, J., Zhang, S., Der, B. S., Nielsen, A. A. & Voigt, C. A. Programming Escherichia coli to function as a digital display. Mol. Syst. Biol. 16, e9401 (2020).

    CAS  Article  Google Scholar 

  33. Der, B. S. et al. DNAplotlib: programmable visualization of genetic designs and associated data. ACS Synth. Biol. 6, 1115–1119 (2017).

    CAS  Article  Google Scholar 

  34. Häkkinen, A., Oliveira, S. M. D., Neeli-Venkata, R. & Ribeiro, A. S. Transcription closed and open complex formation coordinate expression of genes with a shared promoter region. J. R. Soc. Interface 16, 20190507 (2019).

    Article  Google Scholar 

  35. Park, Y., Espah Borujeni, A., Gorochowski, T. E., Shin, J. & Voigt, C. A. Precision design of stable genetic circuits carried in highly-insulated E. coli genomic landing pads. Mol. Syst. Biol. 16, e9584 (2020).

    CAS  Article  Google Scholar 

  36. Taketani, M. et al. Genetic circuit design automation for the gut resident species Bacteroides thetaiotaomicron. Nat. Biotechnol. 38, 962–969 (2020).

    CAS  Article  Google Scholar 

  37. Chen, Y. et al. Genetic circuit design automation for yeast. Nat. Microbiol. 5, 1349–1360 (2020).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

This work was supported by funding from DARPA award FA8750-17-C-0229 ‘Synergistic Discovery and Design (SD2)’ (D.D., C.A.V., C.J.M., T.S.J. and S.M.D.O.), DARPA award HR011-12-C-0067 ‘Living Foundries: 1000 Molecules’ (C.A.V), US Department of Energy award DE-SC0018368 (C.A.V.), NSF Synthetic Biology Engineering Research Center SA5284-11210 (C.A.V.) and NSF Grant No. 1522074 ‘The Living Computing Project’ (D.D., C.J.M., T.S.J. and S.M.D.O.). The authors also acknowledge the support of William Jackson from D.D.’s CIDAR Lab in providing programming assistance and reviewing the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

C.A.V. and D.D. conceived and supervised the project. C.J.M. provided supervision and technical assistance with SBOL and SynBioHub integrations. S.M.D.O assisted with input files and UCF designs and preparation. T.S.J. wrote the Cello 2.0 software. All authors read and revised the manuscript.

Corresponding author

Correspondence to Douglas Densmore.

Ethics declarations

Competing interests

D.D. and C.A.V. are co-founders of Asimov. Asimov is a company that uses software to engineer biology.

Peer review

Peer review information

Nature Protocols thanks Mark Isalan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Key references using this protocol

Nielsen, A. et al. Science 352, aac7341 (2016): https://doi.org/10.1126/science.aac7341

Chen, Y. et al. Nat. Microbiol. 5, 1349–1360 (2020): https://doi.org/10.1038/s41564-020-0757-2

Vaidyanathan, P. et al. Proc. IEEE 11, 2196–2207 (2015): https://doi.org/10.1109/JPROC.2015.2443832

Key data used in this protocol

Taketani, M. et al. Nat. Biotechnol. 38, 962–969 (2020): https://doi.org/10.1038/s41587-020-0468-5

Supplementary information

Supplementary Information

Supplementary Manual, Supplementary Listings 1–35 and Supplementary Figs. 1–6.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Jones, T.S., Oliveira, S.M.D., Myers, C.J. et al. Genetic circuit design automation with Cello 2.0. Nat Protoc 17, 1097–1113 (2022). https://doi.org/10.1038/s41596-021-00675-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41596-021-00675-2

Further reading

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

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing