CH391L/S12/Synthetic Cooperation

Synthetic Cooperation

Through recent advances in synthetic biology that allow population level control of stability and dynamics, synthetic biologists are able to reliably control population composition and function. These advances give way to developing more complex ecosystems that can involve multiple microbials growing in consortium. These communities can achieve a variety of functions that may be difficult or impossible for a single microbe to perform on its own. By combining this with new techniques for computation and prediction, optimizing synthetic consortia to provide new methods in the field of bioprocessing, healthcare, and communication are possible.

Benefits

Synthetic consortia have a number of advantages over a single population that makes it beneficial to engineer new systems. Consortia are capable of more complex functions than are possible in individual populations. They also are more robust to environmental fluctuations such as nutrient depletion, invasion of foreign populations, and evolutionary mutations across generations. It is often difficult or impossible to engineer a single microbe to perform two or more tasks. This can be overcome by compartmentalizing the functions desired in different populations within the same culture. To achieve this the cells must be able to communicate with one another. This can accomplished by trading metabolites, as will be discussed later, or by exchange of dedicated molecular signals otherwise known as quorum sensing. This concept is discussed in detail here.

Challenges

Major challenges develop when trying to engineer multiple, interacting populations. Among these the most difficult aspect is control of populations over time. With natural, single populations, maintaining homeostasis is relatively simple, as members in the population typically do not out compete each other, nor do they exhaust their supply of resources. For multiple populations that are synthetically designed, this task become increasingly difficult. This is due to the tendency of genetic composition in these organisms to change over time as they adapt to their environments. To overcome this difficulty, the consortia should be designed such that members of the consortium can be re-introduced or eliminated as needed, and more importantly, be monitored over time.

The second challenge facing development of synthetic consortia is that gene transfer, at least in the case of natural microbials, is common. This issue needs to be taken into account to ensure the function of the community is not disrupted due to these changes. Another challenge is the ability to incorporate stable changes into the genomes of microbes that are not currently commonly engineered.

Finally, fine-tuning the performance of multiple populations will be an important barrier to overcome. To do this, techniques used for directed evolution that help optimize the behavior of single populations must be extended to multiple populations. Along with this, high-throughput screening and gene-chip assay procedures will aid in the design and evaluation of synthetic consortia.

Examples

Emergent Cooperation and Modeling Microbial Metabolism

Characterizing the behavior of microbes in co-culture is an important endeavor to explore. Wintermute et. al. attempts to create a generalized model of metabolic interaction that can account for metabolites exchanged in the co-culture, as well as the genotypic diversity of the strains involved. Ideally, such a model would not require biochemical characterization for each participant to function properly. To create this model, Wintermute et. al. used optimization-based techniques of flux balance that have been successful in the past to characterize metabolic systems of various species (((cite))). They extend this approach to higher-order systems that involve a model set of E. coli auxotrophs from the Keio collection. They selected 46 conditionally lethal auxotrophic E. coli. and by pairing them in minimal media, determination of which mutant strains cross-feed to survive is possible. They term this type of interaction as a synthetic mutualism in trans, or SMIT interaction. They chose their collection based on deletions that block a essential metabolite, which forces a strict dependency on an external supply of that metabolite. The strains were tagged by inserting plasmids expressing either mCherry or Venus fluorescent proteins and co-cultured together in pairs. This created a total of 1035 unique pairs. By using the growth of a given strain, they interpret the strain's relative level of cooperation.