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A hybrid transistor with transcriptionally controlled computation and plasticity

Author

Listed:
  • Yang Gao

    (University of Texas at Austin)

  • Yuchen Zhou

    (University of Texas at Austin
    University of Texas at Austin)

  • Xudong Ji

    (Northwestern University
    Northwestern University)

  • Austin J. Graham

    (University of Texas at Austin
    University of California San Francisco)

  • Christopher M. Dundas

    (University of Texas at Austin
    Stanford University)

  • Ismar E. Miniel Mahfoud

    (University of Texas at Austin)

  • Bailey M. Tibbett

    (University of Texas at Austin)

  • Benjamin Tan

    (University of Texas at Austin
    University of Texas at Austin)

  • Gina Partipilo

    (University of Texas at Austin)

  • Ananth Dodabalapur

    (University of Texas at Austin
    University of Texas at Austin)

  • Jonathan Rivnay

    (Northwestern University
    Northwestern University)

  • Benjamin K. Keitz

    (University of Texas at Austin)

Abstract

Organic electrochemical transistors (OECTs) are ideal devices for translating biological signals into electrical readouts and have applications in bioelectronics, biosensing, and neuromorphic computing. Despite their potential, developing programmable and modular methods for living systems to interface with OECTs has proven challenging. Here we describe hybrid OECTs containing the model electroactive bacterium Shewanella oneidensis that enable the transduction of biological computations to electrical responses. Specifically, we fabricated planar p-type OECTs and demonstrated that channel de-doping is driven by extracellular electron transfer (EET) from S. oneidensis. Leveraging this mechanistic understanding and our ability to control EET flux via transcriptional regulation, we used plasmid-based Boolean logic gates to translate biological computation into current changes within the OECT. Finally, we demonstrated EET-driven changes to OECT synaptic plasticity. This work enables fundamental EET studies and OECT-based biosensing and biocomputing systems with genetically controllable and modular design elements.

Suggested Citation

  • Yang Gao & Yuchen Zhou & Xudong Ji & Austin J. Graham & Christopher M. Dundas & Ismar E. Miniel Mahfoud & Bailey M. Tibbett & Benjamin Tan & Gina Partipilo & Ananth Dodabalapur & Jonathan Rivnay & Ben, 2024. "A hybrid transistor with transcriptionally controlled computation and plasticity," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45759-1
    DOI: 10.1038/s41467-024-45759-1
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    References listed on IDEAS

    as
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