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[Construction and structural analysis of integrated cellular network of Corynebacterium glutamicum]. | LitMetric

AI Article Synopsis

  • Corynebacterium glutamicum is gaining traction as a key industrial microorganism due to advancements in genomics and genetic tools, although research on its metabolic regulation has lagged behind model organisms like E. coli.
  • The authors constructed an integrated cellular network for Corynebacterium by compiling data from public databases, resulting in a model with 1384 reactions, 1276 metabolites, and extensive transcriptional regulatory relationships.
  • A new method for extracting complex metabolic and regulatory networks was proposed, which showed more accuracy in reflecting the true functional network compared to traditional biochemical pathways, aiding in the understanding and design of high-yield amino acid production strains.

Article Abstract

Corynebacterium glutamicum is one of the most important traditional industrial microorganisms and receiving more and more attention towards a novel cellular factory due to the recently rapid development in genomics and genetic operation toolboxes for Corynebacterium. However, compared to other model organisms such as Escherichia coli, there were few studies on its metabolic regulation, especially a genome-scale integrated cellular network model currently missing for Corynebacterium, which hindered the systematic study of Corynebacterium glutamicum and large-scale rational design and optimization for strains. Here, by gathering relevant information from a number of public databases, we successfully constructed an integrated cellular network, which was composed of 1384 reactions, 1276 metabolites, 88 transcriptional factors and 999 pairs of transcriptional regulatory relationships. The transcriptional regulatory sub-network could be arranged into five layers and the metabolic sub-network presented a clear bow-tie structure. We proposed a new method to extract complex metabolic and regulatory sub-network for product-orientated study taking lysine biosynthesis as an example. The metabolic and regulatory sub-network extracted by our method was more close to the real functional network than the simplex biochemical pathways. The results would be greatly helpful for understanding the high-yielding biomechanism for amino acids and the re-design of the industrial strains.

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