Synthetic Biology Interdisciplinary Challenge 4
Designing communities of cells: How do we create communication and collaboration between cells to allow for specialization and division of labor?

Challenge Summary
Synthetic biology often focuses on engineering individual strains of microbial or other organisms to implement novel behaviors or metabolic functions in a cell autonomous manner. This approach, while powerful, appears to overlook one of the most basic aspects of biological systems: the ability of different species or cell types to interact with one another in order to generate behaviors that would be less feasible or impossible with a single genotype. In natural ecosystems, consortia of multiple species are commonplace, and many, perhaps most, species are non-culturable in isolation, requiring signals or nutrients from other species to grow.  Some metabolic functions may be more efficient when divided between strains, compared to when implemented in a single genotype.  Thus, multi-genotype/multi-cell type systems provide an opportunity for specialization and optimization not possible with homogenous cultures. Two examples of such optimization include the ability to compartmentalize different biosynthetic reactions in different cells that are chemically incompatible with each other, and the ability to create coherent structures that are dramatically larger than the size limit imposed by the dimensions of a cell.

Nevertheless, polycultures present a number of unique challenges compared to monocultures, such as engineering ecological stability (preventing one genotype from taking over the population).  Signaling between cells and populations is crucial to organize multiple populations.  Clearly, expanding synthetic biology to polyculture systems will require better understanding and control of basic ecological principles, signaling systems, determinants of evolutionary stability, population synchronization, and the constraints inherent in complex metabolic pathways.   In addition, problems inherent to all synthetic biology projects, such as uncertainty about the effects of a synthetic circuit on host growth rate, or uncertainty in biochemical parameters, could be even more challenging in the polyculture context. 

Here we will discuss the key issues, opportunities, and challenges that we will face in efforts to make use of the “parallelism” inherent in polyculture systems. 

Key Questions

• How can one engineer self-synchronizing populations, that behave coherently, despite cell-cell variability?
• How do we achieve effective cell communication over multiple length and time scales? For example, what are strategies for cell communication to nearest neighbors, over several cell layers and across an entire culture? How do we design cells to self organize into defined three-dimensional structures (Example: organs). Temporally, how do we synchronize cell cycles or metabolic states? 
• What kinds of metabolic processes are best carried out through the cooperative action of distinct strains, rather than consolidated in a single cell? 
• Are there advantages to spreading out metabolic functions even when the individual pathways involved are chemically compatible with each other? (Example: Chris Voigt’s research, http://www.voigtlab.ucsf.edu/.)
• What are optimal strategies for engineering ecological systems that maintain programmable population fractions?  How can such a system be made ecologically and evolutionarily stable, i.e. robust to invasion by “cheaters”? (Example: Alexander van Oudenaarden’s research, http://web.mit.edu/biophysics; and Wenying Shou’s COSMO, see reading reference below.)
• What applications might exist for controlled multi-population systems?
• Trojan horses: How do we engineer organisms that can invade and flourish in natural populations while altering the behavior of the affected organism/ecosystem in a controlled and desirable manner. (Example: Bruce Hay’s work on making elements that invade and spread through mosquito populations while making them resistant to malaria, www.its.caltech.edu/~haylab.)