We implemented a digital spatial computing approach based on morphogen gradients, where engineered bacterial colonies act as computational units. Each colony was programmed with a genetic circuit implementing a transfer function, focusing initially on high-pass and band-pass operations. Early prototypes used IPTG-inducible systems responsive to liquid droplets to validate the concept. Once feasibility was established, we transitioned to AHL-based quorum sensing circuits for inter-colony communication.
A key theoretical advance was demonstrating that any Boolean logic function can be decomposed into a set of output colonies, where the overall output is ON if any designated colony fluoresces. This was achieved by developing an algorithm that maps truth tables to spatial colony arrangements, enabling modular design of complex logic without additional genetic engineering.
To support design and optimization, we built two complementary mathematical models:
• A fast, reduced model for rapid exploration of candidate designs.
• A full reaction-diffusion model for detailed simulation and verification. These were integrated into a computational design platform, as described in Fedorec et al. (2024), allowing automated decomposition and simulation of logic circuits.
On the experimental side, we established automated protocols using an OpenTrons liquid-handling robot for precise colony placement on six-well agar plates. In collaboration with Loopbio, we developed a custom imaging system capable of real-time GFP fluorescence monitoring inside an incubator, enabling dynamic observation of spatial patterns.
We successfully constructed multi-input biosensors for metabolites including lactate, acetoacetate, arabinose, and propionate, integrating them into logic-based computational frameworks. These proof-of-principle systems demonstrated visible spatial patterning of fluorescent colonies under normal light, validating the concept of living biocomputers for multi-analyte sensing.
Exploitation and Dissemination:
The results have been disseminated through the publication in Nature Communications (Fedorec et al., 2024) and presentations at synthetic biology conferences. The design platform and protocols provide a foundation for future applications in diagnostics, environmental monitoring, and bioprocess control, with potential for open-source release to accelerate adoption.
