Microbes are currently being used to produce many valuable chemical compounds relevant to biotechnology, industry and medicine. Most of these processes utilize a single microbe to produce the desired product. However, the production (or degradation) of chemicals requiring the expression of many enzymes can lead to a large metabolic burden upon the organism, leading to suboptimal yields. As desired chemical processes become increasingly complex, employing multispecies cultures will both decrease the strain on a given organism and add additional levels of control. Naturally occurring microbial communities are composed of many species, each playing a specific role within the community. In the laboratory, synthetic microbial ecosystems could be designed wherein different chemical reactions are allocated to each microorganism. Synthetic biology aims to construct organisms with designed functions using naturally occurring component parts. This work has largely focused on engineering genetic regulatory networks with specific behaviors. Recent efforts have been made to extend these engineered networks to multicellular behaviors, in essence engineering simple communities. As a first step towards engineering microbial communities that carry out novel processes, we are developing high-throughput methods for identifying conditions under which the constituents of a community will coexist, without the addition of expensive chemicals such as antibiotics. We have focused on the role of resource competition under nutrient poor conditions and have found that the ratio of two bacterial species, Escherichia coli and Salmonella typhimurium, in a liquid co-culture can be varied through the addition of very inexpensive chemicals, essentially allowing us to tune the population structure of the community. Libraries of transcriptional reporters for each of the species have been employed to assess changes in gene expression under conditions that lead to differing community compositions. Analyzing changes to the transcriptome of each organism provides insight into how changes to the environment that affect community composition affect the physiology of each microorganism. As the individual components of the community are engineered to carry out specific tasks, our understanding of the physiological and transcriptional states of the microorganisms will guide our implementation of synthetic genetic networks for optimal enzyme production and community composition and stability.