Collaborative Research: From genotype to fluxome to a comprehensive kinetic model of Escherichia coli

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Elucidating and quantifying the complexities of biological systems is of fundamental and practical interest to synthetic biologists and metabolic engineers. A useful approach to unraveling biological complexity is to observe the biological system under perturbed conditions, for example, by removing key cellular components such as genes. In this study, responses to gene knockouts in the model microorganism Escherichia coli will be investigated. By systematically measuring cellular responses to the removal of specific genes in central carbon metabolism a high-quality data set will be generated that will then be used to construct a predictive kinetic model. In addition to having significant value in advancing fundamental biological sciences, this model will provide a valuable new toolkit for industrial biotechnology. Additionally, this model will form the basis for the development of new and enhanced educational tools that will introduce high-school and college students to the biological systems at an early age. Developing a predictive kinetic model of cellular metabolism has been the desire of the scientific community for many decades. However, limitations in experimental approaches for measuring precise metabolic fluxes and the daunting task of estimating a large number of kinetic parameters in models of cellular metabolism have prevented its realization. In recent years, a number of major breakthroughs have been achieved that allow, for the first time, this long-standing task to be accomplished successfully. First, new experimental approached based on parallel 13C-labeling experiments have greatly improved the precision and accuracy of flux measurements. Second, the ensemble kinetic modeling approach was developed and validated for biological systems, which allows systematic construction of comprehensive kinetic models of cellular metabolism while limiting problems of parameter identifiability that have been a major concern in the past and have limited previous modeling approaches. In this project, metabolic flux redistribution in response to gene knockouts will be comprehensively assessed for a large number of E. coli knockout strains, both single gene and double knockouts, enabling the development of a comprehensive kinetic model of central metabolism. The proposed work will add to the scientific knowledge by: (1) generating extensive high-quality experimental data on metabolic fluxes for a large number of E. coli mutant strains using state-of-the-art 13C-flux analysis methods; (2) providing a comprehensive kinetic model of cellular metabolism for E. coli, an important academic and industrial microbe; (3) developing and implementing best practices, standards, procedures and tools for performing, documenting and sharing of 13C-flux analysis results and kinetic models; (4) building a framework to integrate multiple omics data sets within the ensemble modeling framework; (5) generating new knowledge and insights about the regulation of E. coli metabolism under glucose-rich and glucose-limited conditions.This award was co-funded by the Systems and Synthetic Biology (SSB) program in the Molecular and Cellular Biosciences (MCB) Division in the Biological Sciences Directorate and the Biotechnology and Biochemical Engineering (BBE) program of the Division of Chemical, Bioengineering, Environmental and Transport Systems (CBET) in the Engineering Directorate.