Improving the production of acetyl-CoA-derived chemicals in Escherichia coli BL21(DE3) through iclR and arcA deletion

Liu, Min; Ding, Yamei; Chen, Hailin; Zhao, Zhe; Liu, Huizhou; Xian, Ming

doi:10.1186/s12866-016-0913-2

Cited by 36 publications

(25 citation statements)

References 39 publications

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“…The modification of glyoxylate shunt has been used to overcome acetate overflow and improve the production of acetyl-CoA-derived chemicals by deleting iclR in E. coli [9,[22][23][24]26]. In this study, the strain TWF056, TWF057, TWF058, TWF059, TWF060, TWF061, TWF062, TWF063, TWF064 and TWF065 were constructed by inserting the different part of attenuator region of thr operon, thrL, into the different native regulatory regions in front of iclR.…”

Section: Discussionmentioning

confidence: 99%

“…1), which encodes the three enzymes in the glyoxylate bypass [21]. The deletion of iclR in E. coli can improve production of phloroglucinol and 3-hydroxypropionate [22], produce succinate from acetate [23], and produce fumaric acid [24,25], ectoine [26] and fatty acids [27]. The metabolism regulator protein FadR represses the transcription of the fadBA operon, fadE, fadD, fadH, fadIJ operon, fadL and fadM, which involved in the fatty acid degradation [28].…”

Section: Introductionmentioning

confidence: 99%

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Expression regulation of multiple key genes to improve l-threonine in Escherichia coli

Zhao

Yang

et al. 2020

Microb Cell Fact

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Background: Escherichia coli is an important strain for l-threonine production. Genetic switch is a ubiquitous regulatory tool for gene expression in prokaryotic cells. To sense and regulate intracellular or extracellular chemicals, bacteria evolve a variety of transcription factors. The key enzymes required for l-threonine biosynthesis in E. coli are encoded by the thr operon. The thr operon could coordinate expression of these genes when l-threonine is in short supply in the cell. Results: The thrL leader regulatory elements were applied to regulate the expression of genes iclR, arcA, cpxR, gadE, fadR and pykF, while the threonine-activating promoters P cysH , P cysJ and P cysD were applied to regulate the expression of gene aspC, resulting in the increase of l-threonine production in an l-threonine producing E. coli strain TWF001. Firstly, different parts of the regulator thrL were inserted in the iclR regulator region in TWF001, and the best resulting strain TWF063 produced 16.34 g l-threonine from 40 g glucose after 30 h cultivation. Secondly, the gene aspC following different threonine-activating promoters was inserted into the chromosome of TWF063, and the best resulting strain TWF066 produced 17.56 g l-threonine from 40 g glucose after 30 h cultivation. Thirdly, the effect of expression regulation of arcA, cpxR, gadE, pykF and fadR was individually investigated on l-threonine production in TWF001. Finally, using TWF066 as the starting strain, the expression of genes arcA, cpxR, gadE, pykF and fadR was regulated individually or in combination to obtain the best strain for l-threonine production. The resulting strain TWF083, in which the expression of seven genes (iclR, aspC, arcA, cpxR, gadE, pykF, fadR and aspC) was regulated, produced 18.76 g l-threonine from 30 g glucose, 26.50 g l-threonine from 40 g glucose, or 26.93 g l-threonine from 50 g glucose after 30 h cultivation. In 48 h fed-batch fermentation, TWF083 could produce 116.62 g/L l-threonine with a yield of 0.486 g/g glucose and productivity of 2.43 g/L/h. Conclusion: The genetic engineering through the expression regulation of key genes is a better strategy than simple deletion of these genes to improve l-threonine production in E. coli. This strategy has little effect on the intracellular metabolism in the early stage of the growth but could increase l-threonine biosynthesis in the late stage.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Expression regulation of multiple key genes to improve l-threonine in Escherichia coli

Zhao

Yang

et al. 2020

Microb Cell Fact

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“…Acetyl‐CoA is involved in various biological processes and it serves as a platform chemical for producing various high‐value products, such as 1‐butanol (Dong et al, 2017; Ohtake et al, 2017), 3‐hydroxypropionate (Cheng, Jiang, Wu, Li, & Ye, 2016; Liu et al, 2017), polyhydroxyalkanoates (Zheng, Yuan, Yang, & Ma, 2017) and isoprenoids. Isoprenoids may be used for flavorings, biofuels, pharmaceuticals, vitamins (Wang, Zada, Wei, & Kim, 2017; Ward, Chatzivasileiou, & Stephanopoulos, 2018).…”

Section: Discussionmentioning

confidence: 99%

Metabolic engineering of E. coli for improving mevalonate production to promote NADPH regeneration and enhance acetyl‐CoA supply

Satowa

Fujiwara

Uchio

et al. 2020

Biotech & Bioengineering

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Microbial production of mevalonate from renewable feedstock is a promising and sustainable approach for the production of value‐added chemicals. We describe the metabolic engineering of Escherichia coli to enhance mevalonate production from glucose and cellobiose. First, the mevalonate‐producing pathway was introduced into E. coli and the expression of the gene atoB, which encodes the gene for acetoacetyl‐CoA synthetase, was increased. Then, the deletion of the pgi gene, which encodes phosphoglucose isomerase, increased the NADPH/NADP+ ratio in the cells but did not improve mevalonate production. Alternatively, to reduce flux toward the tricarboxylic acid cycle, gltA, which encodes citrate synthetase, was disrupted. The resultant strain, MGΔgltA‐MV, increased levels of intracellular acetyl‐CoA up to sevenfold higher than the wild‐type strain. This strain produced 8.0 g/L of mevalonate from 20 g/L of glucose. We also engineered the sugar supply by displaying β‐glucosidase (BGL) on the cell surface. When cellobiose was used as carbon source, the strain lacking gnd displaying BGL efficiently consumed cellobiose and produced mevalonate at 5.7 g/L. The yield of mevalonate was 0.25 g/g glucose (1 g of cellobiose corresponds to 1.1 g of glucose). These results demonstrate the feasibility of producing mevalonate from cellobiose or cellooligosaccharides using an engineered E. coli strain.

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“…aceA and aceB genes are at the same operon and have repressors encoded by iclR and fadR genes (Wilson and Malloy, 1987). In E. coli, the knock-out of iclR (isocitrate lyase regulator) increases the expression of aceA and aceB, with a consequent activation of the glyoxylate pathway, as shown in E. coli BL21 (Liu et al, 2017). The glyoxyate pathway can also be regulated by icd, which encodes for the isocitrate dehydrogenase, modulating the metabolic flux between the TCA cycle and the glyoxylate shunt.…”

Section: Impact Of Growth Rate On Central Carbon Metabolic Flux Distrmentioning

confidence: 97%

Mapping Salmonella typhimurium pathways using 13C metabolic flux analysis

Correia

Sargo

Silva

et al. 2019

Metabolic Engineering

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In the last years, Salmonella has been extensively studied not only due to its importance as a pathogen, but also as a host to produce pharmaceutical compounds. However, the full exploitation of Salmonella as a platform for bioproduct delivery has been hampered by the lack of information about its metabolism. Genome-scale metabolic models can be valuable tools to delineate metabolic engineering strategies as long as they closely represent the actual metabolism of the target organism. In the present study, a 13 C-MFA approach was applied to map the fluxes at the central carbon pathways of S. typhimurium LT2 growing at glucose-limited chemostat cultures. The experiments were carried out in a 2L bioreactor, using defined medium enriched with 20% 13 C-labeled glucose. Metabolic flux distributions in central carbon pathways of S. typhimurium LT2 were estimated using OpenFLUX2 based on the labeling pattern of biomass protein hydrolysates together with biomass composition. The results suggested that pentose phosphate is used to catabolize glucose, with minor fluxes through glycolysis. In silico simulations, using Optflux and pFBA as simulation method, allowed to study the performance of the genomescale metabolic model. In general, the accuracy of in silico simulations was improved by the superimposition of estimated intracellular fluxes to the existing genome-scale metabolic model, showing a better fitting to the experimental extracellular fluxes, whereas the intracellular fluxes of pentose phosphate and anaplerotic reactions were poorly described.

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Improving the production of acetyl-CoA-derived chemicals in Escherichia coli BL21(DE3) through iclR and arcA deletion

Cited by 36 publications

References 39 publications

Expression regulation of multiple key genes to improve l-threonine in Escherichia coli

Expression regulation of multiple key genes to improve l-threonine in Escherichia coli

Metabolic engineering of E. coli for improving mevalonate production to promote NADPH regeneration and enhance acetyl‐CoA supply

Mapping Salmonella typhimurium pathways using 13C metabolic flux analysis

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