Integration Of Regulatory And Metabolic Network And Its Application In Strain Design For Yeast

Transcriptional regulatory network and metabolic network are both critical research fields in systems biology.Regulatory network describes the interaction between transcriptional factors and target genes,while metabolic network is a collection of metabolites,biochemical reactions and enzymes.Constraint-based modeling,which is applied on metabolic network,is an important technique for predicting cellular phenotype.Based on these technologies,computational strain optimization algorithms aimed to provide rational guidance for design of engineering strains are developed.Recently,many related methods have been published.However,most of these methods only use pure metabolic network.Very fewer methods are able to utilize regulatory network to reveal the effects of transcriptional regulation on strain design.Based on our newly established method for integrating inferred regulatory network and metabolic network,we develop a strain design algorithm with a simulated annealing framework,which can identify strategies of up-regulation,down-regulation and knockout for both transcriptional factors and metabolic genes.We apply this method in yeast to simulate the synthesis of succinate and 2,3-butanediol and several solutions are obtained.Systematic evaluation and analysis for these solutions are carried out,including screening of essential genes and analysis of implementation cost based on paths.Finally,we compare our results with other methods and our advantages are proved.This project uses integrated method in systems biology for guiding optimization of metabolic pathways.It can provide important guidance for designing engineering strains and also has significant practical value in promoting the development of applications such as bioenergy.