We report on a case study in synthetic biology, demonstrating the modeldriven
design of a self-powering electrochemical biosensor. An essential result of
the design process is a general template of a biosensor, which can be instantiated
to be adapted to specific pollutants. This template represents a gene expression network
extended by metabolic activity. We illustrate the model-based analysis of this
template using qualitative, stochastic and continuous Petri nets and related analysis
techniques, contributing to a reliable and robust design