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Thesis

Patterned delivery of chemical signals from 3D-printed synthetic tissues

Abstract:
Patterns of chemical signals are ubiquitous in nature, driving a multitude of biological phenomena, such as wound healing, morphogenesis, axon guidance, quorum sensing and bacterial interference competition. To date, there are limited means to engineer patterned gradients of chemical signals with high spatio-temporal resolution. Here, I develop 3D-printed synthetic tissues as a versatile platform to deliver chemical signals in a patterned manner to guide gene expression. For this, I designed an interface comprising droplet-hydrogel bilayers (DHBs) between synthetic tissues and bacterium-laden hydrogels. I showcase how release dynamics can be precisely tuned to induce patterned gene expression in Escherichia coli. Furthermore, I integrate an additional layer of control by designing modules of synthetic tissues, which allow for triggered release of the chemical signal at a controlled point in time. I present means to both minimize compartment size and cause the reversible growth of synthetic tissues to overcome limitations of the current 3D printing setup. By using temperature-driven shrunken synthetic tissues, I achieve patterned control over gene expression with spatial resolution of ≈ 50 µm. Furthermore, I show the system’s versatility by guiding micrometer-sized patterned DNA damage in susceptible bacterial cells. Lastly, I create synthetic tissues bounded by lipid bilayers that fully function in aqueous solution and allow for the delivery of a chemical signal towards eukaryotic cells (HEK293) to induce gene expression.

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Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Sub department:
Chemistry Research Laboratory
Oxford college:
University College
Role:
Author
ORCID:
0000-0003-2708-0170

Contributors

Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Sub department:
Chemistry Research Laboratory
Research group:
Bayley group
Oxford college:
Hertford College
Role:
Supervisor
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
St Catherine's College
Role:
Examiner
ORCID:
0000-0003-3371-5929
Institution:
Heidelberg University
Role:
Examiner


More from this funder
Funder identifier:
https://ror.org/04qy50a03


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Language:
English
Deposit date:
2026-04-17
ARK identifier:

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