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Partitioning of a 2-bit hash function across 66 communicating cells

Nature Chemical Biology volume 21, pages 268–279 (2025)Cite this article

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Abstract

Powerful distributed computing can be achieved by communicating cells that individually perform simple operations. Here, we report design software to divide a large genetic circuit across cells as well as the genetic parts to implement the subcircuits in their genomes. These tools were demonstrated using a 2-bit version of the MD5 hashing algorithm, which is an early predecessor to the cryptographic functions underlying cryptocurrency. One iteration requires 110 logic gates, which were partitioned across 66 Escherichia coli strains, requiring the introduction of a total of 1.1 Mb of recombinant DNA into their genomes. The strains were individually experimentally verified to integrate their assigned input signals, process this information correctly and propagate the result to the cell in the next layer. This work demonstrates the potential to obtain programable control of multicellular biological processes.

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Fig. 1: Multicellular implementation of the MD5 circuit.
Fig. 2: Logic gates and cell−cell communication used to build subcircuits.
Fig. 3: Division of the 2-bit MD5 circuit into subcircuits.
Fig. 4: Multicellular computation of the 2-bit MD5 circuit.

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Data availability

Sequences for strains and plasmids used in this work are included in the Supplementary Information file. GenBank files of full constructs for each subcircuit can be found at https://doi.org/10.5281/zenodo.13247698 ref. 121. Additional data are available from the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

Cello 2.1 is available at cellocad.org and can be accessed via Google account. All files for Cello 2.1 can be found at https://github.com/CIDARLAB/Cello-v2-1-Core/tree/main/library. The script used to simulate the MD5 algorithm can be found at https://github.com/VoigtLab/MD5_Circuit. The manual for Cello 2.1 is provided as Supplementary Software.

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Acknowledgements

We thank J. Roberts (Boston University) and S. Oliveira (North Carolina A&T State University) for their help in developing Cello 2.1. This work was supported by funding from the National Science Foundation SemiSynBio program awards CCF-1807575 (J.P., J.S., C.A.V.) and CCF-1849588 (W.C., E.D.S., C.A.V.); DARPA Synergistic Discovery and Design program (SD2) award FA8750-17-C-0229 (J.P., J.S., C.A.V.); an award from the Schmidt Innovation Fellows Program (J.P., J.S., C.A.V.); Air Force Office of Scientific Research award FA9550-22-1-0316 (W.C., E.D.S); National Science Foundation award 2211040 (Y.Z., D.D.) and National Science Foundation’s Semiconductor Synthetic Biology for Information Storage and Retrieval award 2027045 (C.K., W.Z.H.).

Author information

Author notes

  1. These authors contributed equally: Jai P. Padmakumar, Jessica J. Sun.

Authors and Affiliations

  1. MIT Microbiology Program, Massachusetts Institute of Technology, Cambridge, MA, USA

    Jai P. Padmakumar & Christopher A. Voigt

  2. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Jai P. Padmakumar, Jessica J. Sun & Christopher A. Voigt

  3. Department of Bioengineering, Northeastern University, Boston, MA, USA

    William Cho & Eduardo D. Sontag

  4. Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA

    Yangruirui Zhou, Christopher Krenz & Douglas Densmore

  5. Department of Computer Science, Boston University, Boston, MA, USA

    Woo Zhong Han

  6. Biological Design Center, Boston University, Boston, MA, USA

    Douglas Densmore

  7. Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA

    Eduardo D. Sontag

Authors
  1. Jai P. Padmakumar
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  2. Jessica J. Sun
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  3. William Cho
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  4. Yangruirui Zhou
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  5. Christopher Krenz
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  6. Woo Zhong Han
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  7. Douglas Densmore
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  8. Eduardo D. Sontag
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  9. Christopher A. Voigt
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Contributions

J.P., J.S. and C.A.V. conceived the study and designed the experiments. J.P. and J.S. performed the experiments and analyzed the data. W.C., Y.Z., D.D. and E.S. implemented the partitioning and edge coloring algorithm. C.K., W.Z.H. and D.D. developed Cello 2.1. J.P., J.S. and C.A.V. wrote the manuscript.

Corresponding author

Correspondence to Christopher A. Voigt.

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The authors declare no competing interests.

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Peer review information

Nature Chemical Biology thanks Irene Otero-Muras, Xiao-Jun Tian and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1−16, Gate Datasheets, Subcircuit Datasheets, Tables 1−11, Methods and Software.

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Supplementary Data

Source data for supplementary figures.

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Source Data Fig. 1

Data for Fig. 1d.

Source Data Fig. 2

Data for Fig. 2c−e,g.

Source Data Fig. 3

Data for Fig. 3d,e.

Source Data Fig. 4

Data for Fig. 4b.

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Padmakumar, J.P., Sun, J.J., Cho, W. et al. Partitioning of a 2-bit hash function across 66 communicating cells. Nat Chem Biol 21, 268–279 (2025). https://doi.org/10.1038/s41589-024-01730-1

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