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Gene expression control for synthetic patterning of bacterial populations and plants

The development of shape in multicellular organisms has intrigued human minds for millenia. Empowered by modern genetic techniques, molecular biologists are now striving to not only dissect developmental processes, but to exploit their modularity for the design of custom living systems used in bioproduction, remediation, and regenerative medicine. Currently, our capacity to harness this potential is fundamentally limited by a lack of spatiotemporal control over gene expression in multicellular systems. While several synthetic genetic circuits for control of multicellular patterning have been reported, hierarchical induction of gene expression domains has received little attention from synthetic biologists, despite its fundamental role in biological self-organization. In this thesis, I introduce the first synthetic genetic system implementing population-based AND logic for programmed hierarchical patterning of bacterial populations of Escherichia coli, and address fundamental prerequisites for implementation of an analogous genetic circuit into the emergent multicellular plant model Marchantia polymorpha. In both model systems, I explore the use of bacteriophage T7 RNA polymerase as a gene expression engine to control synthetic patterning across populations of cells. In E. coli, I developed a ratiometric assay of bacteriophage T7 RNA polymerase activity, which I used to systematically characterize different intact and split enzyme variants. I utilized the best-performing variant to build a three-color patterning system responsive to two different homoserine lactones. I validated the AND gate-like behavior of this system both in cell suspension and in surface culture. Then, I used the synthetic circuit in a membrane-based spatial assay to demonstrate programmed hierarchical patterning of gene expression across bacterial populations. To prepare the adaption of bacteriophage T7 RNA polymerase-driven synthetic patterning from the prokaryote E. coli to the eukaryote M. polymorpha, I developed a toolbox of genetic elements for spatial gene expression control in the liverwort: I analyzed codon usage across the transcriptome of M. polymorpha, and used insights gained to design codon-optimized fluorescent reporters successfully expressed from its nuclear and chloroplast genomes. For targeting of bacteriophage T7 RNA polymerase to these cellular compartments, I functionally validated nuclear localization signals and chloroplast transit peptides. For spatiotemporal control of bacteriophage T7 RNA polymerase in M. polymorpha, I characterized spatially restricted and inducible promoters. For facilitated posttranscriptional processing of target transcripts, I functionally validated viral enhancer sequences in M. polymorpha. Taking advantage of this genetic toolbox, I introduced inducible nuclear-targeted bacteriophage T7 RNA polymerase into M. polymorpha. I showed implementation of the bacteriophage T7 RNA polymerase/PT7 expression system accompanied by hypermethylation of its target nuclear transgene. My observations suggest operation of efficient epigenetic gene silencing in M. polymorpha, and guide future efforts in chassis engineering of this multicellular plant model. Furthermore, my results encourage utilization of spatiotemporally controlled bacteriophage T7 RNA polymerase as a targeted silencing system for functional genomic studies and morphogenetic engineering in the liverwort. Taken together, the work presented enhances our capacity for spatiotemporal gene expression control in bacterial populations and plants, facilitating future efforts in synthetic morphogenesis for applications in synthetic biology and metabolic engineering.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:725569
Date January 2017
CreatorsBoehm, Christian Reiner
ContributorsHaseloff, Jim ; Smith, Alison
PublisherUniversity of Cambridge
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttps://www.repository.cam.ac.uk/handle/1810/267842

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