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      Design of orthogonal genetic switches based on a crosstalk map of σs, anti-σs, and promoters

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          Abstract

          • Part mining was applied to characterize 86 extracytoplasmic function (ECF) σs, their promoters, and 62 anti-σs identified from the genomes of diverse bacteria.

          • A subset of 20 σs and promoters were found to be highly orthogonal to each other and can be used to build non-crossreacting switches in single cells.

          • The N- and C-terminal domains from σs from different subgroups can be recombined and recognize the corresponding chimeric promoter.

          • These parts functioned off-the-shelf in an E. coli host with minimal re-engineering and minimally affected host growth and gene expression.

          Abstract

          Cells react to their environment through gene regulatory networks. Network integrity requires minimization of undesired crosstalk between their biomolecules. Similar constraints also limit the use of regulators when building synthetic circuits for engineering applications. Here, we mapped the promoter specificities of extracytoplasmic function (ECF) σs as well as the specificity of their interaction with anti- σs. DNA synthesis was used to build 86 ECF σs (two from every subgroup), their promoters, and 62 anti- σs identified from the genomes of diverse bacteria. A subset of 20 σs and promoters were found to be highly orthogonal to each other. This set can be increased by combining the −35 and −10 binding domains from different subgroups to build chimeras that target sequences unrepresented in any subgroup. The orthogonal σs, anti- σs, and promoters were used to build synthetic genetic switches in Escherichia coli. This represents a genome-scale resource of the properties of ECF σs and a resource for synthetic biology, where this set of well-characterized regulatory parts will enable the construction of sophisticated gene expression programs.

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          Most cited references49

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          Multiple sigma subunits and the partitioning of bacterial transcription space.

          Promoter recognition in eubacteria is carried out by the initiation factor sigma, which binds RNA polymerase and initiates transcription. Cells have one housekeeping factor and a variable number of alternative sigma factors that possess different promoter-recognition properties. The cell can choose from its repertoire of sigmas to alter its transcriptional program in response to stress. Recent structural information illuminates the process of initiation and also shows that the two key sigma domains are structurally conserved, even among diverse family members. We use the sigma repertoire of Escherichia coli, Bacillus subtilis, Streptomyces coelicolor, and cyanobacteria to illustrate the different strategies utilized to organize transcriptional space using multiple sigma factors.
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            The third pillar of bacterial signal transduction: classification of the extracytoplasmic function (ECF) sigma factor protein family.

            The ability of a bacterial cell to monitor and adaptively respond to its environment is crucial for survival. After one- and two-component systems, extracytoplasmic function (ECF) sigma factors - the largest group of alternative sigma factors - represent the third fundamental mechanism of bacterial signal transduction, with about six such regulators on average per bacterial genome. Together with their cognate anti-sigma factors, they represent a highly modular design that primarily facilitates transmembrane signal transduction. A comprehensive analysis of the ECF sigma factor protein family identified more than 40 distinct major groups of ECF sigma factors. The functional relevance of this classification is supported by the sequence similarity and domain architecture of cognate anti-sigma factors, genomic context conservation, and potential target promoter motifs. Moreover, this phylogenetic analysis revealed unique features indicating novel mechanisms of ECF-mediated signal transduction. This classification, together with the web tool ECFfinder and the information stored in the Microbial Signal Transduction (MiST) database, provides a comprehensive resource for the analysis of ECF sigma factor-dependent gene regulation.
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              The complete genome sequence of Escherichia coli DH10B: insights into the biology of a laboratory workhorse.

              Escherichia coli DH10B was designed for the propagation of large insert DNA library clones. It is used extensively, taking advantage of properties such as high DNA transformation efficiency and maintenance of large plasmids. The strain was constructed by serial genetic recombination steps, but the underlying sequence changes remained unverified. We report the complete genomic sequence of DH10B by using reads accumulated from the bovine sequencing project at Baylor College of Medicine and assembled with DNAStar's SeqMan genome assembler. The DH10B genome is largely colinear with that of the wild-type K-12 strain MG1655, although it is substantially more complex than previously appreciated, allowing DH10B biology to be further explored. The 226 mutated genes in DH10B relative to MG1655 are mostly attributable to the extensive genetic manipulations the strain has undergone. However, we demonstrate that DH10B has a 13.5-fold higher mutation rate than MG1655, resulting from a dramatic increase in insertion sequence (IS) transposition, especially IS150. IS elements appear to have remodeled genome architecture, providing homologous recombination sites for a 113,260-bp tandem duplication and an inversion. DH10B requires leucine for growth on minimal medium due to the deletion of leuLABCD and harbors both the relA1 and spoT1 alleles causing both sensitivity to nutritional downshifts and slightly lower growth rates relative to the wild type. Finally, while the sequence confirms most of the reported alleles, the sequence of deoR is wild type, necessitating reexamination of the assumed basis for the high transformability of DH10B.
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                Author and article information

                Journal
                Mol Syst Biol
                Mol. Syst. Biol
                Molecular Systems Biology
                Nature Publishing Group
                1744-4292
                2013
                29 October 2013
                29 October 2013
                : 9
                : 702
                Affiliations
                [1 ]Department of Microbiology and Immunology, University of California San Francisco , San Francisco, CA, USA
                [2 ]Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology , Cambridge, MA, USA
                [3 ]Graduate Group in Biophysics, University of California San Francisco , San Francisco, CA, USA
                [4 ]Synthetic Biology Research and Development, Life Technologies , Carlsbad, CA, USA
                [5 ]Department of Cell and Tissue Biology, University of California San Francisco , San Francisco, CA, USA
                Author notes
                [a ]Department of Microbiology and Immunology, University of California San Francisco , 600 16th Street, San Francisco, CA 94158, USA. Tel.:+1 415 476 4161; Fax:+1 415 514 4080; cgrossucsf@ 123456gmail.com
                [b ]Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology , 500 Technology Square NE47-277, Cambridge, MA 02139, USA. Tel.:+1 617 324 4851; cavoigt@ 123456gmail.com
                [*]

                These authors contributed equally to this work

                Article
                msb201358
                10.1038/msb.2013.58
                3817407
                24169405
                6c532de8-86a8-4751-8ad5-8db2a8c59834
                Copyright © 2013, EMBO and Macmillan Publishers Limited

                This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/.

                History
                : 06 May 2013
                : 26 September 2013
                Categories
                Article

                Quantitative & Systems biology
                compiler,genetic circuit,part mining,synthetic biology,systems biology

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