Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks

Enoch Yeung¹, Aaron J Dy², Kyle B Martin³, Andrew H Ng⁴, Domitilla Del Vecchio⁵, James L Beck⁶, James J Collins⁷, Richard M Murray⁸

Affiliations

¹ Data Science and Analytics Group, Computational and Statistical Analytics Division, Pacific Northwest National Laboratory, Richland, WA, USA. Electronic address: enoch.yeung@pnnl.gov.
² Department of Biological Engineering, Institute for Medical Engineering & Science, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
³ Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
⁴ Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA.
⁵ Department of Mechanical Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁶ Department of Civil and Mechanical Engineering, California Institute of Technology, Pasadena, CA, USA.
⁷ Department of Biological Engineering, Institute for Medical Engineering & Science, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA; Harvard-MIT Program in Health Sciences and Technology, Cambridge, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Control & Dynamical Systems, Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.

PMID: 28734826
DOI: 10.1016/j.cels.2017.06.001

Free article

Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks

Enoch Yeung et al. Cell Syst. 2017.

Free article

. 2017 Jul 26;5(1):11-24.e12.

doi: 10.1016/j.cels.2017.06.001. Epub 2017 Jul 19.

Authors

Enoch Yeung¹, Aaron J Dy², Kyle B Martin³, Andrew H Ng⁴, Domitilla Del Vecchio⁵, James L Beck⁶, James J Collins⁷, Richard M Murray⁸

Affiliations

¹ Data Science and Analytics Group, Computational and Statistical Analytics Division, Pacific Northwest National Laboratory, Richland, WA, USA. Electronic address: enoch.yeung@pnnl.gov.
² Department of Biological Engineering, Institute for Medical Engineering & Science, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
³ Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
⁴ Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA.
⁵ Department of Mechanical Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁶ Department of Civil and Mechanical Engineering, California Institute of Technology, Pasadena, CA, USA.
⁷ Department of Biological Engineering, Institute for Medical Engineering & Science, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA; Harvard-MIT Program in Health Sciences and Technology, Cambridge, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Control & Dynamical Systems, Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.

PMID: 28734826
DOI: 10.1016/j.cels.2017.06.001

Abstract

Synthetic gene expression is highly sensitive to intragenic compositional context (promoter structure, spacing regions between promoter and coding sequences, and ribosome binding sites). However, much less is known about the effects of intergenic compositional context (spatial arrangement and orientation of entire genes on DNA) on expression levels in synthetic gene networks. We compare expression of induced genes arranged in convergent, divergent, or tandem orientations. Induction of convergent genes yielded up to 400% higher expression, greater ultrasensitivity, and dynamic range than divergent- or tandem-oriented genes. Orientation affects gene expression whether one or both genes are induced. We postulate that transcriptional interference in divergent and tandem genes, mediated by supercoiling, can explain differences in expression and validate this hypothesis through modeling and in vitro supercoiling relaxation experiments. Treatment with gyrase abrogated intergenic context effects, bringing expression levels within 30% of each other. We rebuilt the toggle switch with convergent genes, taking advantage of supercoiling effects to improve threshold detection and switch stability.

Keywords: compositional context; genetic context; supercoiling; synthetic biology; transcriptional regulation.

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Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks

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Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks

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