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      A synthetic Escherichia coli predator–prey ecosystem

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          Abstract

          We have constructed a synthetic ecosystem consisting of two Escherichia coli populations, which communicate bi-directionally through quorum sensing and regulate each other's gene expression and survival via engineered gene circuits. Our synthetic ecosystem resembles canonical predator–prey systems in terms of logic and dynamics. The predator cells kill the prey by inducing expression of a killer protein in the prey, while the prey rescue the predators by eliciting expression of an antidote protein in the predator. Extinction, coexistence and oscillatory dynamics of the predator and prey populations are possible depending on the operating conditions as experimentally validated by long-term culturing of the system in microchemostats. A simple mathematical model is developed to capture these system dynamics. Coherent interplay between experiments and mathematical analysis enables exploration of the dynamics of interacting populations in a predictable manner.

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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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            A synthetic multicellular system for programmed pattern formation.

            Subhayu Basu, Yoram Gerchman, Cynthia H Collins … (2005)
            Pattern formation is a hallmark of coordinated cell behaviour in both single and multicellular organisms. It typically involves cell-cell communication and intracellular signal processing. Here we show a synthetic multicellular system in which genetically engineered 'receiver' cells are programmed to form ring-like patterns of differentiation based on chemical gradients of an acyl-homoserine lactone (AHL) signal that is synthesized by 'sender' cells. In receiver cells, 'band-detect' gene networks respond to user-defined ranges of AHL concentrations. By fusing different fluorescent proteins as outputs of network variants, an initially undifferentiated 'lawn' of receivers is engineered to form a bullseye pattern around a sender colony. Other patterns, such as ellipses and clovers, are achieved by placing senders in different configurations. Experimental and theoretical analyses reveal which kinetic parameters most significantly affect ring development over time. Construction and study of such synthetic multicellular systems can improve our quantitative understanding of naturally occurring developmental processes and may foster applications in tissue engineering, biomaterial fabrication and biosensing.
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              Synthetic biology: new engineering rules for an emerging discipline

              Ernesto Andrianantoandro, Subhayu Basu, David K. Karig … (2006)
              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
                Journal ID (nlm-ta): Mol Syst Biol
                Title: Molecular Systems Biology
                Publisher: Nature Publishing Group
                ISSN (Electronic): 1744-4292
                Publication date Collection: 2008
                Publication date (Electronic): 15 April 2008
                Volume: 4
                Page: 187
                Affiliations
                [1 ]Department of Bioengineering, Stanford University and Howard Hughes Medical Institute, Stanford, CA, USA
                [2 ]Department of Applied Physics, California Institute of Technology, Pasadena, CA, USA
                [3 ]Department of Biomedical Engineering and Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA
                [4 ]Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA
                Author notes
                [a ]Department of Biomedical Engineering and Institute for Genome Sciences and Policy, Duke University, 101 Science Drive, Box 3382, Durham, NC 27708, USA. Tel.: +1 919 660 8408; Fax: +1 919 668 0795; you@ 123456duke.edu
                [*]

                Present address: Engineering Technologies Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA

                [†]

                Present address: SunFlare Co. Ltd., Shinjuku Hirose Bldg. 4–7, Yotsuya, Shinjuku-ku, Tokyo 160-0004, Japan

                [‡]

                Present address: Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA

                Article
                Publisher Item ID: msb200824
                DOI: 10.1038/msb.2008.24
                PMC ID: 2387235
                PubMed ID: 18414488
                SO-VID: 1f42808c-5bf9-4ccc-95ef-29ac8ecccb3b
                Copyright © Copyright © 2008, EMBO and Nature Publishing Group
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits distribution and reproduction in any medium, provided the original author and source are credited. Creation of derivative works is permitted but the resulting work may be distributed only under the same or similar licence to this one. This licence does not permit commercial exploitation without specific permission.

                History
                Date received : 27 November 2007
                Date accepted : 7 March 2008
                Page count
                Pages: 1
                Categories
                Subject: Report

                ScienceOpen disciplines: Quantitative & Systems biology
                Keywords: systems biology,microchemostat,quorum sensing,synthetic biology,microfluidics
                Data availability:
                ScienceOpen disciplines: Quantitative & Systems biology
                Keywords: systems biology, microchemostat, quorum sensing, synthetic biology, microfluidics

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