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Computational design and analysis of modular cells for large libraries of exchangeable product synthesis modules
Institution:1. Department of Chemical and Biomolecular Engineering, The University of Tennessee, Knoxville, TN, United States;2. Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States;1. Department of Chemical and Biomolecular Engineering, United States;2. UTK-ORNL Joint Institute of Biological Science, United States;3. Bredesen Center for Interdisciplinary Research and Graduate Education, United States;4. Institute of Biomedical Engineering, The University of Tennessee, Knoxville, TN, United States;5. BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA;1. Bredesen Center for Interdisciplinary Research and Graduate Education, The University of Tennessee, Knoxville and Oak Ridge National Laboratory, Oak Ridge, TN, USA;2. BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA;3. Department of Chemical and Biomolecular Engineering, The University of Tennessee, Knoxville, TN, USA;4. Biosciecnes Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA;5. Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
Abstract:Microbial metabolism can be harnessed to produce a large library of useful chemicals from renewable resources such as plant biomass. However, it is laborious and expensive to create microbial biocatalysts to produce each new product. To tackle this challenge, we have recently developed modular cell (ModCell) design principles that enable rapid generation of production strains by assembling a modular (chassis) cell with exchangeable production modules to achieve overproduction of target molecules. Previous computational ModCell design methods are limited to analyze small libraries of around 20 products. In this study, we developed a new computational method, named ModCell-HPC, that can design modular cells for large libraries with hundreds of products with a highly-parallel and multi-objective evolutionary algorithm and enable us to elucidate modular design properties. We demonstrated ModCell-HPC to design Escherichia coli modular cells towards a library of 161 endogenous production modules. From these simulations, we identified E. coli modular cells with few genetic manipulations that can produce dozens of molecules in a growth-coupled manner with different types of fermentable sugars. These designs revealed key genetic manipulations at the chassis and module levels to accomplish versatile modular cells, involving not only in the removal of major by-products but also modification of branch points in the central metabolism. We further found that the effect of various sugar degradation on redox metabolism results in lower compatibility between a modular cell and production modules for growth on pentoses than hexoses. To better characterize the degree of compatibility, we developed a method to calculate the minimal set cover, identifying that only three modular cells are all needed to couple with all compatible production modules. By determining the unknown compatibility contribution metric, we further elucidated the design features that allow an existing modular cell to be re-purposed towards production of new molecules. Overall, ModCell-HPC is a useful tool for understanding modularity of biological systems and guiding more efficient and generalizable design of modular cells that help reduce research and development cost in biocatalysis.
Keywords:Modular cell design  Modular (chassis) cell  Production modules  Compatibility  ModCell  ModCell-HPC  Multiobjective optimization  Multiobjective evolutionary algorithm  Master-slave parallelization  Island parallelization  High performance computing
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