Reprogramming synthetic microbial communities toward desirable states
Synthetic genetic circuits are the basis of bioengineering solutions in various industries, e.g., personalized cell therapeutics, transgenic plants for biofuels, textile, and food industries. Since individual species pose a limitation in the number of standard bio-parts to build increasing complexity and size genetic circuits, our lab investigates how large circuits can be proposed as interconnected multicellular small-in-size sub-circuits in microbial communities and their properties be used as design rules and means to predict desirable states precisely. Namely, using thermodynamic and kinetic models, we study how the variability of intrinsic variables of interspecies systems may impact community behavior.
Co-designing programmable microbial communities embedded into microfluidic chips
Microbial communities are highly complex in composition and, naturally, vary in space, time, and external contexts. Our lab investigates communication and gene expression variables influencing microbial community dynamics, functional activities, and spatial structure in controlled environmental contexts. Then, using fluidic-dynamic models with microfluidic properties and variables of microfluidic-based micro-environments, our lab studies the variability of such extrinsic variables and their impact on cell growth dynamics and community behavior. Finally, our lab aims to study what design rules can improve the predictive Co-design of synthetic communities and artificial microfluidic micro-environments for user-defined community behavior.
Engineering on-chip very-large programmable microbial communities with complex traits
Microfluidic-based screening platforms help find and characterize cell candidates with desired functions. For example, a library of cell-based biosensors that sense concentrations of heavy metals can be determined for a micro-environment while external variables are tested (e.g., inorganic metals and metal alloys). Depending on the complexity of the application, though, a community of cells may be required to perform a complex task. Other microfluidic devices that can sustain cell growth for long-term measurements are required in these cases, and many devices are available in academia and industry. Our lab investigates how microfluidic primitive properties (i.e., structure and dynamics) can be scalable to larger networks of primitives in a predictive way when implementing monolayer and multi-layer (with complex routing and microfluidic technology integration) fabrication approaches.