Reducing DNA context dependence in bacterial promoters

Variation in the DNA sequence upstream of bacterial promoters is known to affect the expression levels of the products they regulate, sometimes dramatically. While neutral synthetic insulator sequences have been found to buffer promoters from upstream DNA context, there are no established methods for designing effective insulator sequences with predictable effects on expression levels. We address this problem with Degenerate Insulation Screening (DIS), a novel method based on a randomized 36-nucleotide insulator library and a simple, high-throughput, flow-cytometry-based screen that randomly samples from a library of 436 potential insulated promoters. The results of this screen can then be compared against a reference uninsulated device to select a set of insulated promoters providing a precise level of expression. We verify this method by insulating the constitutive, inducible, and repressible promotors of a four transcriptional-unit inverter (NOT-gate) circuit, finding both that order dependence is largely eliminated by insulation and that circuit performance is also significantly improved, with a 5.8-fold mean improvement in on/off ratio.

[1]  Christopher A. Voigt,et al.  Principles of genetic circuit design , 2014, Nature Methods.

[2]  Jacob Beal,et al.  A Method for Fast, High-Precision Characterization of Synthetic Biology Devices , 2012 .

[3]  Joseph H. Davis,et al.  Design, construction and characterization of a set of insulated bacterial promoters , 2010, Nucleic acids research.

[4]  Timothy S. Ham,et al.  Design, implementation and practice of JBEI-ICE: an open source biological part registry platform and tools , 2012, Nucleic acids research.

[5]  David Tollervey,et al.  Coding-Sequence Determinants of Gene Expression in Escherichia coli , 2009, Science.

[6]  R. Gourse,et al.  UP element-dependent transcription at the Escherichia coli rrnB P1 promoter: positional requirements and role of the RNA polymerase alpha subunit linker. , 2001, Nucleic acids research.

[7]  Jacob Beal,et al.  Accurate predictions of genetic circuit behavior from part characterization and modular composition. , 2015, ACS synthetic biology.

[8]  G. Mitchison The regional rule for bacterial base composition. , 2005, Trends in genetics : TIG.

[9]  Jacob Beal,et al.  CIDAR MoClo: Improved MoClo Assembly Standard and New E. coli Part Library Enable Rapid Combinatorial Design for Synthetic and Traditional Biology. , 2016, ACS synthetic biology.

[10]  R. Ebright,et al.  Bacterial promoter architecture: subsite structure of UP elements and interactions with the carboxy-terminal domain of the RNA polymerase alpha subunit. , 1999, Genes & development.

[11]  Thomas M Lozanoski,et al.  BBF RFC 94: Type IIS Assembly for Bacterial Transcriptional Units: A Standardized Assembly Method for Building Bacterial Transcriptional Units Using the Type IIS Restriction Enzymes BsaI and BbsI , 2015 .

[12]  Jacob Beal,et al.  Model-driven engineering of gene expression from RNA replicons. , 2015, ACS synthetic biology.

[13]  Priscilla E. M. Purnick,et al.  The second wave of synthetic biology: from modules to systems , 2009, Nature Reviews Molecular Cell Biology.

[14]  R. Kwok Five hard truths for synthetic biology , 2010, Nature.

[15]  R. Weiss,et al.  Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks , 2011, PloS one.

[16]  Ernst Weber,et al.  A Modular Cloning System for Standardized Assembly of Multigene Constructs , 2011, PloS one.

[17]  A. Arkin,et al.  Contextualizing context for synthetic biology – identifying causes of failure of synthetic biological systems , 2012, Biotechnology journal.

[18]  Jacob Beal,et al.  Bioengineering and Biotechnology Review Article Bridging the Gap: a Roadmap to Breaking the Biological Design Barrier , 2022 .

[19]  Richard M. Murray,et al.  Modeling the effects of compositional context on promoter activity in an E. coli extract based transcription-translation system , 2014, 53rd IEEE Conference on Decision and Control.

[20]  Christopher A. Voigt,et al.  Genetic circuit design automation , 2016, Science.

[21]  Andrew Phillips,et al.  Towards programming languages for genetic engineering of living cells , 2009, Journal of The Royal Society Interface.

[22]  Vivek K. Mutalik,et al.  Composability of regulatory sequences controlling transcription and translation in Escherichia coli , 2013, Proceedings of the National Academy of Sciences.