Interpretation of morphogen gradients by a synthetic bistable circuit

Paul K. Grant (), Gregory Szep, Om Patange, Jacob Halatek, Valerie Coppard, Attila Csikász-Nagy, Jim Haseloff, James C. W. Locke, Neil Dalchau and Andrew Phillips ()
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Paul K. Grant: Microsoft Research
Gregory Szep: Microsoft Research
Om Patange: University of Cambridge
Jacob Halatek: Microsoft Research
Valerie Coppard: Microsoft Research
Attila Csikász-Nagy: Randall Centre for Cell and Molecular Biophysics
Jim Haseloff: University of Cambridge
James C. W. Locke: Microsoft Research
Neil Dalchau: Microsoft Research
Andrew Phillips: Microsoft Research

Nature Communications, 2020, vol. 11, issue 1, 1-8

Abstract: Abstract During development, cells gain positional information through the interpretation of dynamic morphogen gradients. A proposed mechanism for interpreting opposing morphogen gradients is mutual inhibition of downstream transcription factors, but isolating the role of this specific motif within a natural network remains a challenge. Here, we engineer a synthetic morphogen-induced mutual inhibition circuit in E. coli populations and show that mutual inhibition alone is sufficient to produce stable domains of gene expression in response to dynamic morphogen gradients, provided the spatial average of the morphogens falls within the region of bistability at the single cell level. When we add sender devices, the resulting patterning circuit produces theoretically predicted self-organised gene expression domains in response to a single gradient. We develop computational models of our synthetic circuits parameterised to timecourse fluorescence data, providing both a theoretical and experimental framework for engineering morphogen-induced spatial patterning in cell populations.

Date: 2020
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DOI: 10.1038/s41467-020-19098-w

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