Design and modelling of an engineered bacteria-based, pressure-sensitive soil. (24th May 2018)

• Record Type: Journal Article
• Authors: Dade-Robertson, Martyn; Mitrani, Helen; Corral, Javier Rodriguez; Zhang, Meng; Hernan, Luis; Guyet, Aurelie; Wipat, Anil
• Is Part Of: Bioinspiration & biomimetics. Volume 13:Number 4(2018:Dec.)
• Publication Date: 2018-05-24
• Subjects: responsive materials -- material based computation -- biological sensors -- synthetic biology -- cementation -- computational modelling; Biomimetics -- Periodicals; Biomedical materials -- Periodicals; Medical innovations -- Periodicals; Biomedical engineering -- Periodicals; 600
• DOI: 10.1088/1748-3190/aabe15
• Languages: English
• ISSNs: 1748-3182

Abstract

Abstract: In this paper, we describe the first steps in the design of a synthetic biological system based on the use of genetically modified bacteria to detect elevated pressures in soils and respond by cementing soil particles. Such a system might, for example, enable a self- constructed foundation to form in response to load using engineered bacteria which could be seeded and grown in the soils. This process would reduce the need for large-scale excavations and may be the basis for a new generation of self-assembling and responsive bio-based materials. A prototype computational model is presented which integrates experimental data from a pressure sensitive gene within Escherichia coli bacteria with geotechnical models of soil loading and pore water pressure. The results from the integrated model are visualised by mapping expected gene expression values onto the soil volume. We also use our experimental data to design a two component system where one type of bacteria acts as a sensor and signals to another material synthesis bacteria. The simulation demonstrates the potential of computational models which integrate multiple scales from macro stresses in soils to the expression of individual genes to inform new types of design process. The work also illustrates the combination of in silico (silicon based computing) computation with in vivo (in the living) computation.