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Published May 2016 | Published + Submitted
Journal Article Open

A population-based temporal logic gate for timing and recording chemical events


Engineered bacterial sensors have potential applications in human health monitoring, environmental chemical detection, and materials biosynthesis. While such bacterial devices have long been engineered to differentiate between combinations of inputs, their potential to process signal timing and duration has been overlooked. In this work, we present a two‐input temporal logic gate that can sense and record the order of the inputs, the timing between inputs, and the duration of input pulses. Our temporal logic gate design relies on unidirectional DNA recombination mediated by bacteriophage integrases to detect and encode sequences of input events. For an E. coli strain engineered to contain our temporal logic gate, we compare predictions of Markov model simulations with laboratory measurements of final population distributions for both step and pulse inputs. Although single cells were engineered to have digital outputs, stochastic noise created heterogeneous single‐cell responses that translated into analog population responses. Furthermore, when single‐cell genetic states were aggregated into population‐level distributions, these distributions contained unique information not encoded in individual cells. Thus, final differentiated sub‐populations could be used to deduce order, timing, and duration of transient chemical events.

Additional Information

© 2016 The Authors. Published under the terms of the CC BY 4.0 license. This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Received 27 October 2015; Revised 6 April 2016; Accepted 10 April 2016. Published online: May 17, 2016. The authors would like to thank J. Bonnet and D. Endy for the initial plasmids used in this work, S. Sanchez for critical assistance in automation and liquid handling, D. Perez for flow cytometry assistance, and C. Hayes for discussions. V.H. is supported by the U.S. Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. Y.H. is supported by JSPS Fellowship for Research Abroad. Research supported in part by the Institute for Collaborative Biotechnologies through grant W911NF-09-0001 from the U.S. Army Research Office. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. Author contributions: VH conceived of the circuit design, constructed the necessary experimental strains, performed experimental work and data analysis, ran model simulations, and wrote the manuscript. YH developed the stochastic model and derived the mathematical results. PWKR provided feedback and guidance on data analysis and interpretation. RMM provided feedback and guidance on overall project vision, circuit design, and interpretation of results. The authors declare that they have no conflict of interest.

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Published - 869.full.pdf

Submitted - 029967.full.pdf


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