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Genetically engineered control of phenotypic structure in microbial colonies

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Bittihn,  Philip
Department of Living Matter Physics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Citation

Bittihn, P., Didovyk, A., Tsimring, L. S., & Hasty, J. (2020). Genetically engineered control of phenotypic structure in microbial colonies. Nature Microbiology, 5, 697-705. doi:10.1038/s41564-020-0686-0.


Cite as: http://hdl.handle.net/21.11116/0000-0007-50F4-B
Abstract
Rapid advances in cellular engineering have positioned synthetic biology to address therapeutic and industrial problems, but a substantial obstacle is the myriad of unanticipated cellular responses in heterogeneous real-world environments such as the gut, solid tumours, bioreactors or soil. Complex interactions between the environment and cells often arise through non-uniform nutrient availability, which generates bidirectional coupling as cells both adjust to and modify their local environment through phenotypic differentiation. Although synthetic spatial gene expression patternshave been explored under homogeneous conditions, the mutual interaction of gene circuits, growth phenotype and the environment remains a challenge. Here, we design gene circuits that sense and control phenotypic structure in microcolonies containing both growing and dormant bacteria. We implement structure modulation by coupling different downstream modules to a tunable sensor that leverages Escherichia coli’s stress response and is activated on growth arrest. One is an actuator module that slows growth and thereby alters nutrient gradients. Environmental feedback in this circuit generates robust cycling between growth and dormancy in the interior of the colony, as predicted by a spatiotemporal computational model. We also use the sensor to drive an inducible gating module for selective gene expression in non-dividing cells, which allows us to radically alter population structure by eliminating the dormant phenotype with a ‘stress-gated lysis circuit‘. Our results establish a strategy to leverage and control microbial colony structure for synthetic biology applications in complex environments.