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      A fast, robust, and tunable synthetic gene oscillator

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          Abstract

          One defining goal of synthetic biology is the development of engineering-based approaches that enable the construction of gene-regulatory networks according to “design specs” generated from computational modeling 16 . This approach provides a systematic framework for exploring how a given regulatory network generates a particular phenotypic behavior. Several fundamental gene circuits have been developed using this approach, including toggle switches 7 and oscillators 810 , and these have been applied in novel contexts such as triggered biofilm development 11 and cellular population control 12 . Here we describe an engineered genetic oscillator in Escherichia coli that is fast, robust, and persistent, with tunable oscillatory periods as fast as 13 minutes. The oscillator was designed using a previously modeled network architecture comprising linked positive and negative feedback loops 1, 13 . Using a microfluidic platform tailored for single-cell microscopy, we precisely control environmental conditions and monitor oscillations in individual cells through multiple cycles. Experiments reveal remarkable robustness and persistence of oscillations in the designed circuit; almost every cell exhibited large-amplitude fluorescence oscillations throughout observation runs. The oscillatory period can be tuned by altering inducer levels, temperature, and media source. Computational modeling demonstrates that the key design principle for constructing a robust oscillator is a time delay in the negative feedback loop, which can mechanistically arise from the cascade of cellular processes involved in forming a functional transcription factor. The positive feedback loop increases the robustness of the oscillations and allows for greater tunability. Examination of our refined model suggested the existence of a simplified oscillator design without positive feedback, and we construct an oscillator strain confirming this computational prediction.

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          Foundations for engineering biology.

          Drew Endy (2005)
          Engineered biological systems have been used to manipulate information, construct materials, process chemicals, produce energy, provide food, and help maintain or enhance human health and our environment. Unfortunately, our ability to quickly and reliably engineer biological systems that behave as expected remains quite limited. Foundational technologies that make routine the engineering of biology are needed. Vibrant, open research communities and strategic leadership are necessary to ensure that the development and application of biological technologies remains overwhelmingly constructive.
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            Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell.

            The physiological responses of cells to external and internal stimuli are governed by genes and proteins interacting in complex networks whose dynamical properties are impossible to understand by intuitive reasoning alone. Recent advances by theoretical biologists have demonstrated that molecular regulatory networks can be accurately modeled in mathematical terms. These models shed light on the design principles of biological control systems and make predictions that have been verified experimentally.
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              Synthetic biology: new engineering rules for an emerging discipline

              Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                18 September 2019
                29 October 2008
                27 November 2008
                14 October 2019
                : 456
                : 7221
                : 516-519
                Affiliations
                [1 ]Department of Bioengineering, University of California, San Diego, La Jolla, California, USA.
                [2 ]Institute for Nonlinear Science, University of California, San Diego, La Jolla, California, USA.
                Author notes
                [⋆]

                These authors contributed equally to this work.

                Author Contribution

                J.S., S.C., and M.R.B. contributed equally to this work. J.S. and J.H. designed the oscillator circuits, and J.S. constructed the circuits. S.C. performed the microscopy experiments, and J.S. and S.C. performed the flow cytometry experiments. S.C., L.S.T. and J.H. performed the single-cell data analysis. M.R.B., W.H.M., and L.S.T. performed the computational modeling. All authors wrote the manuscript.

                [3 ]Corresponding Author. Department of Bioengineering, University of California, San Diego, Mailcode 0412, La Jolla, CA 92093-0412, USA. Telephone: 858 822 3442. Fax: 858 534 5722. hasty@ 123456bioeng.ucsd.edu
                Article
                NIHMS68804
                10.1038/nature07389
                6791529
                18971928
                94b69890-4c4a-43dc-be97-37aa0e55df85

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