Literature DB >> 10103226

Homofermentative production of D- or L-lactate in metabolically engineered Escherichia coli RR1.

D E Chang1, H C Jung, J S Rhee, J G Pan.   

Abstract

We investigated metabolic engineering of fermentation pathways in Escherichia coli for production of optically pure D- or L-lactate. Several pta mutant strains were examined, and a pta mutant of E. coli RR1 which was deficient in the phosphotransacetylase of the Pta-AckA pathway was found to metabolize glucose to D-lactate and to produce a small amount of succinate by-product under anaerobic conditions. An additional mutation in ppc made the mutant produce D-lactate like a homofermentative lactic acid bacterium. When the pta ppc double mutant was grown to higher biomass concentrations under aerobic conditions before it shifted to the anaerobic phase of D-lactate production, more than 62.2 g of D-lactate per liter was produced in 60 h, and the volumetric productivity was 1.04 g/liter/h. To examine whether the blocked acetate flux could be reoriented to a nonindigenous L-lactate pathway, an L-lactate dehydrogenase gene from Lactobacillus casei was introduced into a pta ldhA strain which lacked phosphotransacetylase and D-lactate dehydrogenase. This recombinant strain was able to metabolize glucose to L-lactate as the major fermentation product, and up to 45 g of L-lactate per liter was produced in 67 h. These results demonstrate that the central fermentation metabolism of E. coli can be reoriented to the production of D-lactate, an indigenous fermentation product, or to the production of L-lactate, a nonindigenous fermentation product.

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Year:  1999        PMID: 10103226      PMCID: PMC91196     

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  18 in total

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  32 in total

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7.  Semi-industrial scale (30 m3) fed-batch fermentation for the production of D-lactate by Escherichia coli strain HBUT-D15.

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Review 9.  Minimizing acetate formation in E. coli fermentations.

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10.  Natural computation meta-heuristics for the in silico optimization of microbial strains.

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