Reconstruction And Application Of Spathaspora Passalidarum NRRL Y-27907 Genome-scale Metabolic Model

S. passalidarum NRRL Y-27907 is one of the lignocellulosic ethanol dominant strains, with a wide spectrum of carbon substrates. The strain could fermant glucose, xylose and cellobiose simultaneously under anaerobic and aerobic conditions. However it’s difficult to study the complex metabolic process on account of its non-clear metabolism. GSMM can provide an effective platform for a comprehensive analysis of the physiological matabolic function.In this study, a universal automatic refinement process of GSMM was developed based on Java, Perl, image processing algorithm and the weighted scoring mechanism. The automatic process was applied to build the GSMM of S. passalidarum NRRL Y-27907, and the major metabolic physiologies were analyzed subsequently. The main results included:(1)An automatic refinement process of GSMM which contains 3 aspects was proposed. Intergrating of hypertext transfer protocol and Htpp Client achieved site scripting semantics’ s automatic submission and analysis. KEGG online database and six subcellular prediction databases were studied for the process of auto-refinement. Moreover, it has proposed weighted scoring mechanism to analyze the results of subcellular prediction databases, while using image processing algorithm determine high credibility specific reaction. Then the GSMM of S. passalidarum NRRL Y-27907 named i XW790 was built automated with the process proposed.( 2) i XW790 model was applied to explore physiological metabolism of S. passalidarum NRRL Y-27907 and simulate cell growth phenotypes on three different carbon sources quantitatively. Matlab and Cobra algorithm pointed out the impact of oxygenation on ethanol production and the flux distribution of central metabolic pathway. Robustness analysis of oxygen demonstrated that the ethanol production could only be achieved under a relatively low dissolved oxygen condition. When the dissolved oxygen is greater than a specific value, ethanol would be oxidatded again and made a loss.(3)Opt Knock and flow balance analysis(FBA) predicted metabolic engineering method and fermentation optimization strategy that improved ethanol production on the basis of xylose fermentation ethanol mechanism. Opt Knock identified 3 candidate knockout targets(CYC1, ALA2, GDH3) all of which could improve the ethanol production showed by FBA analysis. GDH3 knockout type reached a highest 8.767 mmol·g DCW-1·h-1 ethanol growth with a 7.576% increasing compared to the control. FBA predicted that trace organic nitrogen sources could promote the synthesis of ethanol and proline addition brought a most improvement of 19.9%, reached 9.72 mmol·g DCW-1·h-1. With the addition of proline into the 3 knockout types, ethanol growth rate(GDH3) reached to 10.24 mmol·g DCW-1·h-1, increased by 26.38% compared to the wild type.(4)Minimized metabolic network was analyzed by the methodology, which was based on multi-objective genetic algorithm. Minimal genome for S. passalidarum NRRL Y-27907 growth on glucose, which provides insights into artifical synthetic cell.