4.5 Article

Metabolic evolution of Corynebacterium glutamicum for increased production of L-ornithine

Journal

BMC BIOTECHNOLOGY
Volume 13, Issue -, Pages -

Publisher

BIOMED CENTRAL LTD
DOI: 10.1186/1472-6750-13-47

Keywords

L-Ornithine; Corynebacterium glutamicum; Adaptive evolution; Metabolic engineering; Transcriptional level analysis

Funding

  1. National Natural Science Foundation of China [30970089, 20876181, 21276289]
  2. Natural Science Foundation of Guangdong Province [9351027501000003, S2011010001396]

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Background: L-ornithine is effective in the treatment of liver diseases and helps strengthen the heart. The commercial applications mean that efficient biotechnological production of L-ornithine has become increasingly necessary. Adaptive evolution strategies have been proven a feasible and efficient technique to achieve improved cellular properties without requiring metabolic or regulatory details of the strain. The evolved strains can be further optimised by metabolic engineering. Thus, metabolic evolution strategy was used for engineering Corynebacterium glutamicum to enhance L-ornithine production. Results: A C. glutamicum strain was engineered by using a combination of gene deletions and adaptive evolution with 70 passages of growth-based selection. The metabolically evolved C. glutamicum strain, named Delta APE6937R42, produced 24.1 g/L of L-ornithine in a 5-L bioreactor. The mechanism used by C. glutamicum Delta APE6937R42 to produce L-ornithine was investigated by analysing transcriptional levels of select genes and NADPH contents. The upregulation of the transcription levels of genes involved in the upstream pathway of glutamate biosynthesis and the elevated NADPH concentration caused by the upregulation of the transcriptional level of the ppnK gene promoted L-ornithine production in C. glutamicum Delta APE6937R42. Conclusions: The availability of NADPH plays an important role in L-ornithine production in C. glutamicum. Our results demonstrated that the combination of growth-coupled evolution with analysis of transcript abundances provides a strategy to engineer microbial strains for improving production of target compounds.

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