SURF 2018: Engineering metabolic cross-feeding relationships for robust microbial consortia
2018 SURF project description
- Mentor: Richard Murray
- Co-mentor: Rory Williams
Engineering metabolic cross-feeding relationships for robust microbial consortia Recent years have seen increased interest in both understanding the interactions governing the structure and dynamics of naturally occurring multi-species microbial communities, and implementing microbial consortia for bioremediation and bioprocessing. There are numerous potential advantages of using microbial consortia over a single species, including increased yield and efficiency through specialization of function, functional stability over a wider range of environmental conditions, and execution of metabolic functions not possible by a single organism alone. In selecting and designing microbial consortia, researches have harnessed existing microbial consortia, combined species with known metabolic function, and genetically engineered multiple species to cooperate in a single community. While more complex synthetic consortia may be more robust to environmental conditions, bottom-up design of many-membered consortia is yet challenging, in part due to our incomplete mechanistic understanding of natural complex consortia.
This SURF project will focus on the design and implementation of multi-species consortia which rely on metabolic cross-feeding. SURF students will model the dynamics of various community topologies across environmental conditions to characterize robustness, and utilize mutations inducing auxotrophy or overproduction of metabolites, and/or synthetic regulation of metabolite exchange to realize community structure(s). Communities may designed to be robust to variations of specific environmental conditions, and/or sensitive to variations in others. Through the identification of robust structures of metabolic interactions in multi-species communities, this project may help to elucidate consortia design principles, and to develop chassis for implementing circuits whose function is benefited or made possible through segregation across multiple distinct species.
Backround/skills: Genetics/biology courses, general microbiology techniques, molecular biology (PCR, cloning, etc.), Python.
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