We have constructed a synthetic ecosystem consisting of two Escherichia coli populations, which communicate bi-directionally through quorum sensing and regulate each other's gene expression and survival via engineered gene circuits. Our synthetic ecosystem resembles canonical predatorprey systems in terms of logic and dynamics. The predator cells kill the prey by inducing expression of a killer protein in the prey, while the prey rescue the predators by eliciting expression of an antidote protein in the predator. Extinction, coexistence and oscillatory dynamics of the predator and prey populations are possible depending on the operating conditions as experimentally validated by long-term culturing of the system in microchemostats. A simple mathematical model is developed to capture these system dynamics. Coherent interplay between experiments and mathematical analysis enables exploration of the dynamics of interacting populations in a predictable manner.

The genome sequence of T. parva shows remarkable differences from the other apicomplexan genomes sequenced to date. It provides significant improvements in our understanding of the metabolic capabilities of T. parva and a foundation for studying parasite-induced host cell transformation and constitutes a critical knowledge base for a pathogen of significance to agriculture in Africa. Mining of sequence data has already proved useful in the search for candidate vaccine antigens (3).

Biological research is experiencing an increasing focus on the application of knowledge rather than on its generation. Thanks to the increased understanding of cellular systems and technological advances, biologists are more frequently asking not only 'how can I understand the structure and behaviour of this biological system?', but also 'how can I apply that knowledge to generate novel functions in different biological systems or in other contexts?' Active pursuit of the latter has nurtured the emergence of synthetic biology. Here, we discuss the motivation behind, and foundational technologies enabling, the development of this nascent field. We examine some early successes and applications while highlighting the challenges involved. Finally, we consider future directions and mention non-scientific considerations that can influence the field's growth.