Integration of in silico Design and Experimental Evaluation for Creation of Microbial Cell Factories

Integration of in silico and experimental approaches is highly desired for creation of microbial cellfactories. Recently, on the basis of whole-genome information, the genome-scale metabolic reaction models (GSM) of cells have been reconstructed for many organisms. Using the GSMs, a reliable prediction of metabolic fluxes is possible by using Flux Balance Analysis (FBA). We reconstructed GSMs of industrially a useful microorganism Corynebacterium glutamicum [Shinfuku et al., 2009] and cyanobacterium Synechocystis sp. [Yoshikawa et al., 2011]. And then, the constructed GSMs are applied to prediction of metabolic fluxes under several environmental conditions and to design of genetic modification for valuable compounds production. A multiple deletion algorithm, FastPros [Ohno, 2013] and a non-native metabolite production design approach, ArtPathDesign [Chatsurachai et al., 2013] are also introduced.

         Metabolic flux analysis (MFA) based on quantification of ¹³C-labeling patterns of metabolites by mass spectroscopy (MS) is a powerful tool to quantify fluxes experimentally in a metabolic network of microorganisms. In this approach, after cells are cultivated using a ¹³C-labeled substrate, metabolites are extracted from the cells for use in MS analyses. Metabolic fluxes are determined using stoichiometric constraints coupled with extracellular measurements and ¹³C-labeling patterns of the metabolites. We experimentally determined metabolic fluxes of C. glutamicum and Synechocystis and analyzed states of metabolic pathways.. In Synechocystis sp., metabolic fluxes under different environmental conditions of photon and carbon source supply is analyzed. Combination of the these in silico and experimental flux analysis with other omics analyses such as transcriptomics and metabaolomics are also discussed.