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      Synthetic circuits integrating logic and memory in living cells.

      Nature biotechnology
      Artificial Cells, Computer Storage Devices, Computers, Molecular, Equipment Design, Equipment Failure Analysis, Escherichia coli, genetics, Genetic Engineering, methods, Signal Processing, Computer-Assisted, instrumentation, Synthetic Biology, Systems Integration

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          Abstract

          Logic and memory are essential functions of circuits that generate complex, state-dependent responses. Here we describe a strategy for efficiently assembling synthetic genetic circuits that use recombinases to implement Boolean logic functions with stable DNA-encoded memory of events. Application of this strategy allowed us to create all 16 two-input Boolean logic functions in living Escherichia coli cells without requiring cascades comprising multiple logic gates. We demonstrate long-term maintenance of memory for at least 90 cell generations and the ability to interrogate the states of these synthetic devices with fluorescent reporters and PCR. Using this approach we created two-bit digital-to-analog converters, which should be useful in biotechnology applications for encoding multiple stable gene expression outputs using transient inputs of inducers. We envision that this integrated logic and memory system will enable the implementation of complex cellular state machines, behaviors and pathways for therapeutic, diagnostic and basic science applications.

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          Most cited references22

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          Synthetic gene networks that count.

          Synthetic gene networks can be constructed to emulate digital circuits and devices, giving one the ability to program and design cells with some of the principles of modern computing, such as counting. A cellular counter would enable complex synthetic programming and a variety of biotechnology applications. Here, we report two complementary synthetic genetic counters in Escherichia coli that can count up to three induction events: the first, a riboregulated transcriptional cascade, and the second, a recombinase-based cascade of memory units. These modular devices permit counting of varied user-defined inputs over a range of frequencies and can be expanded to count higher numbers.
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            Programmed population control by cell-cell communication and regulated killing.

            De novo engineering of gene circuits inside cells is extremely difficult, and efforts to realize predictable and robust performance must deal with noise in gene expression and variation in phenotypes between cells. Here we demonstrate that by coupling gene expression to cell survival and death using cell-cell communication, we can programme the dynamics of a population despite variability in the behaviour of individual cells. Specifically, we have built and characterized a 'population control' circuit that autonomously regulates the density of an Escherichia coli population. The cell density is broadcasted and detected by elements from a bacterial quorum-sensing system, which in turn regulate the death rate. As predicted by a simple mathematical model, the circuit can set a stable steady state in terms of cell density and gene expression that is easily tunable by varying the stability of the cell-cell communication signal. This circuit incorporates a mechanism for programmed death in response to changes in the environment, and allows us to probe the design principles of its more complex natural counterparts.
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              Engineered bacteriophage targeting gene networks as adjuvants for antibiotic therapy.

              Antimicrobial drug development is increasingly lagging behind the evolution of antibiotic resistance, and as a result, there is a pressing need for new antibacterial therapies that can be readily designed and implemented. In this work, we engineered bacteriophage to overexpress proteins and attack gene networks that are not directly targeted by antibiotics. We show that suppressing the SOS network in Escherichia coli with engineered bacteriophage enhances killing by quinolones by several orders of magnitude in vitro and significantly increases survival of infected mice in vivo. In addition, we demonstrate that engineered bacteriophage can enhance the killing of antibiotic-resistant bacteria, persister cells, and biofilm cells, reduce the number of antibiotic-resistant bacteria that arise from an antibiotic-treated population, and act as a strong adjuvant for other bactericidal antibiotics (e.g., aminoglycosides and beta-lactams). Furthermore, we show that engineering bacteriophage to target non-SOS gene networks and to overexpress multiple factors also can produce effective antibiotic adjuvants. This work establishes a synthetic biology platform for the rapid translation and integration of identified targets into effective antibiotic adjuvants.
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