Abstract:BackgroundRecent progress in production of various biofuel precursors and molecules, such as fatty acids, alcohols and alka(e)nes, is a significant step forward for replacing the fossil fuels with renewable fuels. A two-step process, where fatty acids from sugars are produced in the first step and then converted to corresponding biofuel molecules in the second step, seems more viable and attractive at this stage. We have engineered an Escherichia coli strain to take care of the second step for converting short… Show more
“…Most recently, one study has reported an engineered E. coli that carries a synthetic pathway consisting of Clostridium buk, ptb, and adhE2 for n-butanol production from butyrate (Mattam and Yazdani, 2013). Under the controlled fermenter condition, their E. coli strain grown on TB rich medium produces 1.85 g/L (25 mM) n-butanol from glycerol (5 g/L) and butyrate (2.2 g/L) at 100 h. To improve the production, a high cell density of the strain is used and the n-butanol titer reaches 4.4 g/L (60 mM) with consumption of 5.3 g/L butyrate at 24 h. In addition, there is around 4 g/L acetate production.…”
Section: N-butanol Production By Glucose and Butyrate Feedingmentioning
“…Most recently, one study has reported an engineered E. coli that carries a synthetic pathway consisting of Clostridium buk, ptb, and adhE2 for n-butanol production from butyrate (Mattam and Yazdani, 2013). Under the controlled fermenter condition, their E. coli strain grown on TB rich medium produces 1.85 g/L (25 mM) n-butanol from glycerol (5 g/L) and butyrate (2.2 g/L) at 100 h. To improve the production, a high cell density of the strain is used and the n-butanol titer reaches 4.4 g/L (60 mM) with consumption of 5.3 g/L butyrate at 24 h. In addition, there is around 4 g/L acetate production.…”
Section: N-butanol Production By Glucose and Butyrate Feedingmentioning
“…In another study, the butyrate-conversion strain (BUT-3EA) of E. coli was engineered by deleting ldhA, adhE, frdA, and pta genes and inserting native atoDA, acs and Clostridium adhE2 genes. The recombinant strain (BuT-3EA) was able to accumulate a titer of 6.2 g/L of 1-butanol using glucose and butyrate as a carbon sources [39], the titers were 1.5fold higher than the previously engineered strain using glycerol and butyrate as carbon sources [104].…”
Section: Elimination Of the Competitive Pathwaysmentioning
Background: Owing to the increase in energy consumption, fossil fuel resources are gradually depleting which has led to the growing environmental concerns; therefore, scientists are being urged to produce sustainable and ecofriendly fuels. Thus, there is a growing interest in the generation of biofuels from renewable energy resources using microbial fermentation. Main text: Butanol is a promising biofuel that can substitute for gasoline; unfortunately, natural microorganisms pose challenges for the economical production of 1-butanol at an industrial scale. The availability of genetic and molecular tools to engineer existing native pathways or create synthetic pathways have made non-native hosts a good choice for the production of 1-butanol from renewable resources. Non-native hosts have several distinct advantages, including using of cost-efficient feedstock, solvent tolerant and reduction of contamination risk. Therefore, engineering non-native hosts to produce biofuels is a promising approach towards achieving sustainability. This paper reviews the currently employed strategies and synthetic biology approaches used to produce 1-butanol in non-native hosts over the past few years. In addition, current challenges faced in using non-native hosts and the possible solutions that can help improve 1-butanol production are also discussed. Conclusion: Non-native organisms have the potential to realize commercial production of 1-butanol from renewable resources. Future research should focus on substrate utilization, cofactor imbalance, and promoter selection to boost 1-butanol production in non-native hosts. Moreover, the application of robust genetic engineering approaches is required for metabolic engineering of microorganisms to make them industrially feasible for 1-butanol production.
“…The zwf gene was amplified from E. coli DH5α genomic DNA and cloned in the pZS21mcs plasmid at KpnI and HindIII restriction sites to generate the pZF23 plasmid. Gene deletions in DH5α were achieved through the P1 transduction method (Fatma et al, 2016;Mattam and Yazdani, 2013;Munjal et al, 2012). The phage lysate was prepared and enriched by using the single gene knockout strain obtained from CGSC, and the targeted gene was replaced by an FRT flanked-kanamycin resistance cassette.…”
Section: Strain and Plasmid Constructionmentioning
confidence: 99%
“…Validation of the in silico findings required selection of a suitable E. coli host strain as the genetic background of the host makes a significant impact on the metabolite profiles (Liu et al, 2014;Mattam and Yazdani, 2013;Song et al, 2016). Therefore we compared hydrocarbon profiles in eight different E. coli strains, i.e., E. coli B, DH5α, M15, MG1655, BW25113, Top10, BL21, and JM109, by transforming them with plasmid pZS22 and found that DH5α showed the highest alkane production ( Fig.…”
Section: Implementation Of In Silico Finding Under In Vivo Conditionsmentioning
confidence: 99%
“…S6). Further, sequential knockouts of edd, pps, ldhA, aceA, poxB, ptaA and pflB were created in DH5α through phage transduction (Baba et al, 2006;Mattam and Yazdani, 2013). Gene knockouts were confirmed by PCR using external primers unique to the flanking regions of the genes (Table S1, Fig.…”
Section: Improvement In Long Chain Alkane Productionmentioning
Biologically-derived hydrocarbons are considered to have great potential as next-generation biofuels owing to the similarity of their chemical properties to contemporary diesel and jet fuels. However, the low yield of these hydrocarbons in biotechnological production is a major obstacle for commercialization. Several genetic and process engineering approaches have been adopted to increase the yield of hydrocarbon, but a model driven approach has not been implemented so far. Here, we applied a constraint-based metabolic modeling approach in which a variable demand for alkane biosynthesis was imposed, and co-varying reactions were considered as potential targets for further engineering of an E. coli strain already expressing cyanobacterial enzymes towards higher chain alkane production. The reactions that co-varied with the imposed alkane production were found to be mainly associated with the pentose phosphate pathway (PPP) and the lower half of glycolysis. An optimal modeling solution was achieved by imposing increased flux through the reaction catalyzed by glucose-6-phosphate dehydrogenase (zwf) and iteratively removing 7 reactions from the network, leading to an alkane yield of 94.2% of the theoretical maximum conversion determined by in silico analysis at a given biomass rate. To validate the in silico findings, we first performed pathway optimization of the cyanobacterial enzymes in E. coli via different dosages of genes, promoting substrate channelling through protein fusion and inducing substantial equivalent protein expression, which led to a 36-fold increase in alka(e)ne production from 2.8 mg/L to 102 mg/L. Further, engineering of E. coli based on in silico findings, including biomass constraint, led to an increase in the alka(e)ne titer to 425 mg/L (major components being 249 mg/L pentadecane and 160 mg/L heptadecene), a 148.6-fold improvement over the initial strain, respectively; with a yield of 34.2% of the theoretical maximum. The impact of model-assisted engineering was also tested for the production of long chain fatty alcohol, another commercially important molecule sharing the same pathway while differing only at the terminal reaction, and a titer of 1506 mg/L was achieved with a yield of 86.4% of the theoretical maximum. Moreover, the model assisted engineered strains had produced 2.54 g/L and 12.5 g/L of long chain alkane and fatty alcohol, respectively, in the bioreactor under fed-batch cultivation condition. Our study demonstrated successful implementation of a combined in silico modeling approach along with the pathway and process optimization in achieving the highest reported titers of long chain hydrocarbons in E. coli.
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