Catalytically Controlling the Reaction Pathways of Biomass-derived Oxygenate Molecules

Over the past 20 years, C-metabolic flux analysis (C-MFA) has emerged as the leading technology for accurate quantification of intracellular fluxes in microbial, mammalian and plant systems. Despite major advances in experimental, analytical and computational techniques, isotopic experiment design is often neglected for C-MFA. Optimal design of isotopic experiments is of central importance as it determines the resolving power of C-MFA, i.e. the precision with which fluxes can be estimated. Three experimental variables directly influence flux precision: (1) metabolite measurements, i.e. C-enrichments and concentrations; (2) isotopic tracers; and (3) experiment layout, i.e. single vs. parallel labeling experiments. Here, we present methodologies and metrics for optimal isotopic tracer selection, with emphasis on determining the optimal tracer for a single isotopic experiment or the best combination of tracers for multiple isotopic experiments conducted in parallel. First, we describe the development of a novel framework for rational tracer selection based on the Elementary Metabolite Unit (EMU). The strength of this approach is the decoupling of substrate labeling, i.e. the EMU basis vectors, from the dependence on free fluxes, i.e. the coefficients. We also demonstrate that flux observability inherently depends on the number of independent EMU basis vectors and the sensitivities of coefficients with respect to free fluxes. Furthermore, we apply this framework to a realistic network model of mammalian metabolism and determine two novel tracers that have not been previously considered for C-MFA of mammalian cells, i.e. [2,3,4,5,6-C]glucose and [3,4-C]glucose. Second, we describe the development of scoring metrics for global analysis of a network’s flux precision. Specifically, we develop a precision score, which accounts for the nonlinear confidence intervals for fluxes and does not introduce biasing due to normalization by the flux value. In addition, we propose a synergy score to estimate the flux information gain associated with conducting parallel labeling experiments as opposed to a single tracer experiment. Then, we utilize the scoring metrics to systematically evaluate in silico isotopic tracer designs for C-MFA in E. coli. In particular, we focus on tracer selection for two experiment layouts: (1) single tracer experiment, and (2) two parallel tracer experiments. We demonstrate the major improvement in flux precision that can result from careful selection of isotopic tracers for parallel labeling experiments. Lastly, we present an application of innovative tracer selection and parallel labeling experiments to probe biological questions. Specifically, parallel C-tracer experiments were performed in 3T3-L1 adipocytes to quantify the contributions of amino acids to fatty acid synthesis. Through isotopomer spectral analysis, we demonstrate that branched chain amino acid catabolism plays an important role in fatty acid synthesis. Also, we systematically determined the synthetic route of odd-chain fatty acids using novel GC-MS techniques. Furthermore, we provide evidence that suggests a methylmalonic acid shunt, which challenges the current understanding of propionate metabolism.