The main objective of BACTOCOM is to build a platform for biological engineering. Microbes may be thought of as biological "micro-machines" that process information about their own state and the world around them. By sensing their environment, certain bacteria are able to move in response to chemical signals, allowing them to seek out food, for example. They can also communicate with other bacteria, by leaving chemical trails, or by directly exchanging genetic information. We focus on this latter mechanism.
Parts of the internal "program" of a bacterial cell (encoded by its genes, and the connections between them) may be "reprogrammed" in order to persuade it to perform human-defined tasks. By introducing artificial "circuits" made up of genetic components, we may add new behaviours or modify existing functionality within the cell. Existing examples of this include a bacterial oscillator, which causes the cells to periodically flash, and cell-based pollution detectors that can spot arsenic in drinking water. The potential for bio-engineering is huge, but the process itself is made difficult by the noisy, "messy" nature of the underlying material. Bacteria are hard to engineer, as they rarely conform to the traditional model of a computer or device, with well-defined components laid out in a fixed design.
We intend to use the inherent randomness of natural processes to our advantage, by harnessing it as a framework for biological engineering. We begin with a large number of simple DNA-based components, taken from a well-understood toolbox, which may be pieced together inside the cell to form new genetic programs. A population of bacteria then absorbs these components, which may (or may not) affect their behaviour. Crucially, the core of our platform is made up of engineered microbes that can detect how well they are performing, according to some external measure, such as how well they can flash in time with light pulses.
By performing massively-parallel bacterial random search, we will quickly obtain functional devices without "top down" engineering. There are many potential benefits to this work, from both a biological and computing perspective. By "evolving" new functional structures, we gain insight into biological systems. This, in turn, may suggest new methods for silicon-based computing, in the way that both evolution and the brain have already done. This opens up applications in areas as diverse as environmental sensing and clean-up, medical diagnostics and therapeutics, energy and security.