Multiplex Design of the Metabolic Network for Production of l-Homoserine in Escherichia coli

l-Homoserine, which is one of the few amino acids that is not produced on a large scale by microbial fermentation, plays a significant role in the synthesis of a series of valuable chemicals. In this study, systematic metabolic engineering was applied to target Escherichia coli W3110 for the production of l-homoserine. Initially, a basic l-homoserine producer was engineered through the strategies of overexpressing thrA (encoding homoserine dehydrogenase), removing the degradative and competitive pathways by knocking out metA (encoding homoserine O-succinyltransferase) and thrB (encoding homoserine kinase), reinforcing the transport system, and redirecting the carbon flux by deleting iclR (encoding the isocitrate lyase regulator). The resulting strain constructed by these strategies yielded 3.21 g/liter of l-homoserine in batch cultures. Moreover, based on CRISPR-Cas9/dCas9 (nuclease-dead Cas9)-mediated gene repression for 50 genes, the iterative genetic modifications of biosynthesis pathways improved the l-homoserine yield in a stepwise manner. The rational integration of glucose uptake and recovery of l-glutamate increased l-homoserine production to 7.25 g/liter in shake flask cultivation. Furthermore, the intracellular metabolic analysis further provided targets for strain modification by introducing the anaplerotic route afforded by pyruvate carboxylase to oxaloacetate formation, which resulted in accumulating 8.54 g/liter l-homoserine (0.33 g/g glucose, 62.4% of the maximum theoretical yield) in shake flask cultivation. Finally, a rationally designed strain gave 37.57 g/liter l-homoserine under fed-batch fermentation, with a yield of 0.31 g/g glucose. IMPORTANCE In this study, the bottlenecks that sequentially limit l-homoserine biosynthesis were identified and resolved, based on rational and efficient metabolic-engineering strategies, coupled with CRISPR interference (CRISPRi)-based systematic analysis. The metabolomics data largely expanded our understanding of metabolic effects and revealed relevant targets for further modification to achieve better performance. The systematic analysis strategy, as well as metabolomics analysis, can be used to rationally design cell factories for the production of highly valuable chemicals.