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Bioelectronic control of a microbial community using surface-assembled electrogenetic cells to route signals

Nature Nanotechnology volume 16, pages 688–697 (2021)Cite this article

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Abstract

We developed a bioelectronic communication system that is enabled by a redox signal transduction modality to exchange information between a living cell-embedded bioelectronics interface and an engineered microbial network. A naturally communicating three-member microbial network is ‘plugged into’ an external electronic system that interrogates and controls biological function in real time. First, electrode-generated redox molecules are programmed to activate gene expression in an engineered population of electrode-attached bacterial cells, effectively creating a living transducer electrode. These cells interpret and translate electronic signals and then transmit this information biologically by producing quorum sensing molecules that are, in turn, interpreted by a planktonic coculture. The propagated molecular communication drives expression and secretion of a therapeutic peptide from one strain and simultaneously enables direct electronic feedback from the second strain, thus enabling real-time electronic verification of biological signal propagation. Overall, we show how this multifunctional bioelectronic platform, termed a BioLAN, reliably facilitates on-demand bioelectronic communication and concurrently performs programmed tasks.

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Fig. 1: Information flow through an electronically interfaced biological network.
Fig. 2: Peroxide-driven electrogenetic control.
Fig. 3: Contribution of electrochemical generation and bacterial consumption rates to hydrogen peroxide flux simulated at an electrode.
Fig. 4: Assembly of electrogenetic cells onto gold surfaces via peptide surface display.
Fig. 5: Electronic information flow through an engineered two-member community.
Fig. 6: BioLAN function.

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Data availability

The datasets that support the findings of this study are available at https://figshare.com/s/30bcc0241826827d12f4. Source data are provided with this paper.

Code availability

The MATLAB code for the models used in this study is available from the corresponding author upon request.

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Acknowledgements

Partial support of this work was provided by DTRA (HDTRA1-19-0021), NSF (DMREF 1435957, ECCS 1807604, CBET 1805274), the National Institutes of Health (R21EB024102) and the Office of Naval Research (N0001417WX01318, N0001418WX01042). This work was also supported by the Office of the Under Secretary of Defense for Research and Engineering (USD(R&E)) through the Applied Research for Advancement of S&T Priorities (ARAP) Program on Synthetic Biology for Military Environments (SBME).

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  1. These authors contributed equally: Jessica L. Terrell, Tanya Tschirhart.

Authors and Affiliations

  1. U.S. Army Combat Capabilities Development Command (DEVCOM)—Army Research Laboratory, Adelphi, MD, USA

    Jessica L. Terrell, Justin P. Jahnke, Hong Dong & Dimitra N. Stratis-Cullum

  2. Center for Biomolecular Science and Engineering, U.S. Naval Research Laboratory, Washington, DC, USA

    Tanya Tschirhart & Gary Vora

  3. Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA

    Kristina Stephens, Yi Liu, Maria Pozo, Ryan McKay, Chen Yu Tsao, Hsuan-Chen Wu, Gregory F. Payne & William E. Bentley

  4. Fischell Institute for Biomedical Devices, University of Maryland, College Park, MD, USA

    Kristina Stephens, Ryan McKay, Chen Yu Tsao, Gregory F. Payne & William E. Bentley

  5. Institute for Bioscience and Biotechnology Research, University of Maryland, College Park, MD, USA

    Kristina Stephens, Yi Liu, Ryan McKay, Chen Yu Tsao, Hsuan-Chen Wu, Gregory F. Payne & William E. Bentley

  6. U.S. Army Combat Capabilities Development Command (DEVCOM)—Army Research Laboratory, Aberdeen, MD, USA

    Margaret M. Hurley

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Contributions

J.L.T., T.T., Y.L., C.Y.T., H.-C.W., G.V., G.F.P., D.N.S.-C. and W.E.B. were involved with the conception and design of the work. J.L.T., T.T., K.S., R.M. and M.P. were involved with engineering strains used in this work. J.L.T., T.T., J.P.J., K.S. and H.D. were involved with data acquisition and interpretation. J.P.J. and M.M.H. were involved with computational kinetic studies and protein modelling, respectively. J.L.T., T.T., J.P.J., G.F.P., D.N.S.-C. and W.E.B. were involved with writing and documentation of the work.

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Correspondence to William E. Bentley.

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Peer review information Nature Nanotechnology thanks Ada Poon 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 Methods, Figs. 1–15, Tables 1–8 and references.

Source data

Source Data Fig. 2

Statistical source data and R code.

Source Data Fig. 3

Model data and corresponding MATLAB-generated figures.

Source Data Fig. 4

Protein sequence, unprocessed images, statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

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Terrell, J.L., Tschirhart, T., Jahnke, J.P. et al. Bioelectronic control of a microbial community using surface-assembled electrogenetic cells to route signals. Nat. Nanotechnol. 16, 688–697 (2021). https://doi.org/10.1038/s41565-021-00878-4

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