Adding New Constraints to Incorporate Transcriptional Regulatory and Metabolic Networks of E.Coli on Binary Substrates

فاقد چكيده فارسي

Most of biotechnology industry researches deal with multi substrate environment because their desirable bacterial product obtain in such of these conditions and because of importance of diauxic growth for biotechnology industries, growth of Escherichia coli on binary mixtures of substituable substrates is simulated in this research. So, suitable prediction of bacterial phenotype in these situations is very important for researchers. Transcriptional regulation plays an important role in the diauxic growth systems. For this kind of simulation, there are many approaches to combine new methods like highthroughput data (transcriptomics, metabolomics, proteomics) with traditional biochemical investigations hence, microarray data of various perturbations in glucose minimal media of E. coli MG1655 is integrated with metabolic network and transcriptional regulatory network.. The results indicate that the algorithm improves the growth prediction compared with the previous approaches. The presented algorithm can properly predict the biomass concentration of E. coli growth on various binary substrates.