Dynamic flux balance analysis for synthetic microbial communities

Synthetic Ecology of Microbes: Mathematical Models and Applications

As the indispensable role of natural microbial communities in many aspects of life on Earth is uncovered, the bottom-up engineering of synthetic microbial consortia with novel functions is becoming an attractive alternative to engineering single-species systems. Here, we summarize recent work on synthetic microbial communities with a particular emphasis on open challenges and opportunities in environmental sustainability and human health. We next provide a critical overview of mathematical approaches, ranging from phenomenological to mechanistic, to decipher the principles that govern the function, dynamics and evolution of microbial ecosystems. Finally, we present our outlook on key aspects of microbial ecosystems and synthetic ecology that require further developments, including the need for more efficient computational algorithms, a better integration of empirical methods and model-driven analysis, the importance of improving gene function annotation, and the value of a standardized library of well-characterized organisms to be used as building blocks of synthetic communities.

An Economic Framework of Microbial Trade

A large fraction of microbial life on earth exists in complex communities where metabolic exchange is vital. Microbes trade essential resources to promote their own growth in an analogous way to countries that exchange goods in modern economic markets. Inspired by these similarities, we developed a framework based on general equilibrium theory (GET) from economics to predict the population dynamics of trading microbial communities. Our biotic GET (BGET) model provides an a priori theory of the growth benefits of microbial trade, yielding several novel insights relevant to understanding microbial ecology and engineering synthetic communities. We find that the economic concept of comparative advantage is a necessary condition for mutualistic trade. Our model suggests that microbial communities can grow faster when species are unable to produce essential resources that are obtained through trade, thereby promoting metabolic specialization and increased intercellular exchange. Furthermore, we find that species engaged in trade exhibit a fundamental tradeoff between growth rate and relative population abundance, and that different environments that put greater pressure on group selection versus individual selection will promote varying strategies along this growth-abundance spectrum. We experimentally tested this tradeoff using a synthetic consortium of Escherichia coli cells and found the results match the predictions of the model. This framework provides a foundation to study natural and engineered microbial communities through a new lens based on economic theories developed over the past century.

Unraveling interactions in microbial communities - from co-cultures to microbiomes

Microorganisms do not exist in isolation in the environment. Instead, they form complex communities among themselves as well as with their hosts. Different forms of interactions not only shape the composition of these communities but also define how these communities are established and maintained. The kinds of interaction a bacterium can employ are largely encoded in its genome. This allows us to deploy a genomescale modeling approach to understand, and ultimately predict, the complex and intertwined relationships in which microorganisms engage. So far, most studies on microbial communities have been focused on synthetic co-cultures and simple communities. However, recent advances in molecular and computational biology now enable bottom up methods to be deployed for complex microbial communities from the environment to provide insight into the intricate and dynamic interactions in which microorganisms are engaged. These methods will be applicable for a wide range of microbial communities involved in industrial processes, as well as understanding, preserving and reconditioning natural microbial communities present in soil, water, and the human microbiome.