Bacteria can form diverse community structures, called biofilms that include special characteristics such as spiral swirls on the surface of laboratory agar as well as in natural environments. Understanding how these microbial structures form is of fundamental importance, as bacteria predominantly function in the form of communities to impact the environment, agriculture, and human health. Understanding the design principles underlying the multi-scale organization of communities due to competition between members of the community is important, especially as competition is one of the major driving forces that influence how microbial communities organize themselves within a biofilm. An integrated understanding of bacterial competition and its roles in controlling spatial community structure will advance our basic knowledge about microbial ecology and facilitate new developments in the area of synthetic microbial biology. The research will also provide educational and training opportunities for girls in regional high schools and undergraduate institutions, particularly those underrepresented; simultaneously, it will engage larger research communities and the general public.
Bacterial competition is a major driving force that directs the emergence of diverse spatial community structures. Despite significant advances over decades of research, our understanding and predictive capability for the organization of competing communities remains limited, largely due to the multiscale coupling of the underlying molecular, cellular and ecological events. It is important to determine how the key molecular traits of competition, including its scale, variability and cost, determine the spatiotemporal structures of communities. To achieve this goal, synthetic E. coli consortia will be used as model systems for quantitative exploration; in parallel, a biophysical modeling platform for systematic survey and analysis will be developed. This project will yield a systems-level understanding of bacterial competition and community organization, thus providing critical implications for understanding microbial ecology and engineering artificial communities. More broadly, because of the rich nonlinear dynamics and emergent properties associated with bacterial communities, the planned work will further advance the fundamental knowledge of complex systems in general.
