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      Modular cell biology: retroactivity and insulation

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          Abstract

          Modularity plays a fundamental role in the prediction of the behavior of a system from the behavior of its components, guaranteeing that the properties of individual components do not change upon interconnection. Just as electrical, hydraulic, and other physical systems often do not display modularity, nor do many biochemical systems, and specifically, genetic networks. Here, we study the effect of interconnections on the input–output dynamic characteristics of transcriptional components, focusing on a property, which we call ‘retroactivity', that plays a role analogous to non-zero output impedance in electrical systems. In transcriptional networks, retroactivity is large when the amount of transcription factor is comparable to, or smaller than, the amount of promoter-binding sites, or when the affinity of such binding sites is high. To attenuate the effect of retroactivity, we propose a feedback mechanism inspired by the design of amplifiers in electronics. We introduce, in particular, a mechanism based on a phosphorylation–dephosphorylation cycle. This mechanism enjoys a remarkable insulation property, due to the fast timescales of the phosphorylation and dephosphorylation reactions.

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          Most cited references44

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          Network motifs in the transcriptional regulation network of Escherichia coli

          Little is known about the design principles of transcriptional regulation networks that control gene expression in cells. Recent advances in data collection and analysis, however, are generating unprecedented amounts of information about gene regulation networks. To understand these complex wiring diagrams, we sought to break down such networks into basic building blocks. We generalize the notion of motifs, widely used for sequence analysis, to the level of networks. We define 'network motifs' as patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks. We applied new algorithms for systematically detecting network motifs to one of the best-characterized regulation networks, that of direct transcriptional interactions in Escherichia coli. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motif structure also allows an easily interpretable view of the entire known transcriptional network of the organism. This approach may help define the basic computational elements of other biological networks.
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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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              Evolution and tinkering.

              F Jacob (1977)
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                Author and article information

                Journal
                Mol Syst Biol
                Molecular Systems Biology
                Nature Publishing Group
                1744-4292
                2008
                12 February 2008
                : 4
                : 161
                Affiliations
                [1 ]Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
                [2 ]Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, MI, USA
                [3 ]Department of Mathematics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
                Author notes
                [a ]Department of Electrical Engineering and Computer Science, University of Michigan, 1301 Beal Avenue, Ann Arbor, MI 48109, USA. Tel.: +1-734-764-6581; Fax: +1-734-763-8041; ddv@ 123456umich.edu
                Article
                msb4100204
                10.1038/msb4100204
                2267736
                18277378
                664f8766-9aaf-4702-8eac-b4b197d9995e
                Copyright © 2008, EMBO and Nature Publishing Group

                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
                : 28 September 2007
                : 30 November 2007
                Page count
                Pages: 1
                Categories
                Article

                Quantitative & Systems biology
                feedback,singular perturbation,modularity,insulation
                Quantitative & Systems biology
                feedback, singular perturbation, modularity, insulation

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