Periodic Reporting for period 4 - SynBioBrain (Building biological computers from bacterial populations)
Période du rapport: 2022-11-01 au 2024-04-30
Biosensor development is a rapidly growing area with applications including healthcare diagnostics, the detection of harmful environmental agents, bioprocess monitoring, and agriculture. Using synthetic biology, we can now engineer bacteria into whole-cell biosensors where sensing, transduction and output occur within the living cell.
Living biosensors have many advantages over traditional approaches; they are cheap to manufacture, quick to develop and can detect certain compounds at very low concentrations. As we move towards more sophisticated applications, we want to detect multiple signals simultaneously and apply more complex information processing.
This project will construct biological computers formed from engineered bacterial populations that communicate using signalling molecules. Information from multiple biosensor inputs will be integrated and processed by the biocomputer. The output of the computations will be spatial patterning of colonies expressing fluorescent proteins at levels observable to the naked eye in normal light. We will create proof-of-principle multi-input biosensors that can monitor microbiota health in human samples.
Living biosensors have many advantages over traditional approaches; they are cheap to manufacture, quick to develop and can detect certain compounds at very low concentrations. As we move towards more sophisticated applications, we want to detect multiple signals simultaneously and apply more complex information processing.
This project will construct biological computers formed from engineered bacterial populations that communicate using signalling molecules. Information from multiple biosensor inputs will be integrated and processed by the biocomputer. The output of the computations will be spatial patterning of colonies expressing fluorescent proteins at levels observable to the naked eye in normal light. We will create proof-of-principle multi-input biosensors that can monitor microbiota health in human samples.
Work performed:
Developed new engineered sender and receiver strains that can emit signalling molecules and respond with different behaviours.
Developed new biosensor strains for gut-microbiota and cancer relevant metabolites including lactate, acetoacetate, reactive nitrogen species, pH and short chain fatty acids.
Developed robotic experimental protocols for plating colonies in a consistent and reproducible manner.
Built a mathematical model to describe the dynamics of colony growth and signal diffusion in solid media.
Devised the mathematical formalism to express arbitrary digital computations as arrangements of distributed colonies on solid media, together with algorithms for designing these systems.
Demonstrated simple two-input logic gate behaviour (OR, AND, XOR) using communicating bacterial colonies.
Developed new engineered sender and receiver strains that can emit signalling molecules and respond with different behaviours.
Developed new biosensor strains for gut-microbiota and cancer relevant metabolites including lactate, acetoacetate, reactive nitrogen species, pH and short chain fatty acids.
Developed robotic experimental protocols for plating colonies in a consistent and reproducible manner.
Built a mathematical model to describe the dynamics of colony growth and signal diffusion in solid media.
Devised the mathematical formalism to express arbitrary digital computations as arrangements of distributed colonies on solid media, together with algorithms for designing these systems.
Demonstrated simple two-input logic gate behaviour (OR, AND, XOR) using communicating bacterial colonies.
We expect to develop a system for arbitrary digital logic functions that can be printed onto a living bacterial chip. Given a set of biosensors, our chip can be reconfigured for different computations simply by plating the colonies in a different orientation. This is therefore extremely versatile, with the possible operations and applications growing as more and more bacterial biosensors become available.