Cells Are Plausible Targets for High-Level Spatial Languages

High level languages greatly increase the power of a programmer at the cost of programs that consume more resources than those written at a lower level of abstraction. This inefficiency is a major concern for the programming of biological systems: although advances in synthetic biology are beginning to allow bacteria to be programmed at an "assembly language\´\´ level, metabolic and chemical constraints currently place tight limits on the computational resources available. We find, however, that the semantics of the Proto spatial computing language appear to be a good match for engineered genetic regulatory networks, and particularly for describing the spatial differentiation necessary to construct tissues or organs. In this paper, we propose a mapping between Proto programs and standardized biological parts. We then demonstrate the plausibility of this mapping by applying it to a band detection program, finding that standard code optimization techniques can transform the inefficient program produced by the initial mapping into an efficient design equivalent to the Weiss laboratory\´s hand-designed band detector.