Self-healing living materials based on Turing pattern engineering in microbial cells
Abstract
Self-organizing patterns and structures are abundant in biological systems (e.g. zebra stripes, hair, bone and brain structures), but how these can be engineered remains elusive. Following the physicist Richard Feynman#s mantra, #What I cannot create,I do not understand,# here we propose to build on theoretical work to build robust living systems that can carry out such functions, including self-healing after damage; numerous applications are apparent in nanotechnology, self-assembly, and tissue engineering. In breakthrough works in the middle of the 20th century, the great mathematician Alan Turing proposed molecular mechanisms of how patterns can emerge in chemical and biological systems, which may explain skin patterns (e.g. zebra stripes) and limb formation (bone structures) during embryonic development. The simplest Turing model is a mathematical construct consisting of two molecular species (a two-node network), with one slowly diffusing activator and one rapidly diffusing inhibitor. These self-organize to potentially lead to periodic lateral inhibition, leading to a static wave pattern of gene expression - a Turing pattern (TP). Despite being found in natural systems, such as in growing digits in the hand, human hair follicle spacing, teeth spacing, and in synthetic chemical systems, no one has yet been able to engineer robust regular-repeat TPs from first principles, using biological components. Here we will first carry out a large-scale screening of conditions and mutants to establish how to consistently obtain Turing patterns from a non-classical Turing network that we identified computationally. We have already shown that this network can generate gene expression patterns in colonies of microbial cells, and we will build on this to get more robust, tunable patterns. A central prediction of Turing patterns is that they should repair themselves when damaged and we will test this to obtain self-healing patterns. Finally, we will move beyond toy systems that use fluorescent reporter proteins and will explore outputs based on materials that have potential real-world downstream applications. For example, the Turing output will ultimately be coupled to laying down ordered biomaterials. This will result in a new technology based on self-organizing, self-healing living materials, grown in microbial cells.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 13, 2023
- Source ID
- N629092312099
Entities
People
- Mark Isalan
Organizations
- Imperial College London
- Office of Naval Research
- United States Navy