A 'resource allocator' for transcription based on a highly fragmented T7 RNA polymerase

Thomas H. Segall-Shapiro, Adam J. Meyer, Andrew D. Ellington, Eduardo D. Sontag, Christopher A. Voigt

    Research output: Contribution to journalArticlepeer-review

    158 Scopus citations

    Abstract

    Synthetic genetic systems share resources with the host, including machinery for transcription and translation. Phage RNA polymerases (RNAPs) decouple transcription from the host and generate high expression. However, they can exhibit toxicity and lack accessory proteins (σ factors and activators) that enable switching between different promoters and modulation of activity. Here, we show that T7 RNAP (883 amino acids) can be divided into four fragments that have to be co-expressed to function. The DNA-binding loop is encoded in a C-terminal 285-aa 'σ fragment', and fragments with different specificity can direct the remaining 601-aa 'core fragment' to different promoters. Using these parts, we have built a resource allocator that sets the core fragment concentration, which is then shared by multiple σ fragments. Adjusting the concentration of the core fragment sets the maximum transcriptional capacity available to a synthetic system. Further, positive and negative regulation is implemented using a 67-aa N-terminal 'α fragment' and a null (inactivated) σ fragment, respectively. The α fragment can be fused to recombinant proteins to make promoters responsive to their levels. These parts provide a toolbox to allocate transcriptional resources via different schemes, which we demonstrate by building a system which adjusts promoter activity to compensate for the difference in copy number of two plasmids.

    Original languageEnglish (US)
    Article number742
    JournalMolecular Systems Biology
    Volume10
    Issue number7
    DOIs
    StatePublished - Jul 2014

    Keywords

    • T7 RNA polymerase
    • genetic circuit
    • resource allocation
    • split protein
    • synthetic biology

    ASJC Scopus subject areas

    • Information Systems
    • General Biochemistry, Genetics and Molecular Biology
    • General Immunology and Microbiology
    • General Agricultural and Biological Sciences
    • Computational Theory and Mathematics
    • Applied Mathematics

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