Fig 1.
Biosynthetic pathways for acrylic acid (AA) production from Glucose using 3-hydroxypropionate (3-HP) as an intermediary.
3-HP can be produced from glucose through three distinct pathways: glycerol (red arrows), malonyl-CoA (green arrows), and β-alanine (blue arrows). Furthermore, E. coli can also direct glycerol towards the central carbon metabolism, allowing it to be used as a carbon source.
Fig 2.
Simulation results for 3-hydroxypropionate (3-HP) production via the glycerol pathway.
(A) Glucose (GLCx) consumption and variation of extracellular 3-HP (3-HPx) over time; (B) Glycerol (GLYx) consumption and variation of 3-HPx over time.
Fig 3.
Simulation results for acrylic acid (AA) production via the glycerol pathway.
(A) Glucose (GLC) consumption and variation of extracellular AA (AAx) over time; (B) Variation of 3-hydroxypropionate (3-HP) concentration over time when using glucose as carbon source; (C) Glycerol (GLYx) consumption and variation of extracellular AAx over time; (D) Variation of 3-HP concentration over time when using glycerol as carbon source.
Table 1.
Literature review on 3-hydroxypropionate (3-HP) and acrylic acid (AA) production yields by the glycerol pathway in metabolically engineered Escherichia coli, and comparison with the yields predicted by the dynamic models using the same initial carbon concentration.
Fig 4.
Simulation results for 3-hydroxypropionate (3-HP) production via the malonyl-CoA pathway.
(A) Glucose (GLCx) consumption and variation of extracellular 3-HP (3-HPx) over time; (B) Glycerol (GLYx) consumption and variation of 3-HPx over time; (C) Variation of intracellular dihydroxyacetone (DHA) concentration over time when using glycerol.
Fig 5.
Simulation results for acrylic acid (AA) production via the malonyl-CoA pathway.
(A) Glucose (GLC) consumption and variation of extracellular AA (AAx) over time; (B) Variation of 3-hydroxypropionate (3-HP) concentration over time when using glucose as carbon source; (C) Glycerol (GLYx) consumption and variation of extracellular AAx over time; (D) Variation of 3-HP concentration over time when using glycerol as carbon source.
Table 2.
Literature review on 3-hydroxypropionate (3-HP) and acrylic acid (AA) production yields by the malonyl-CoA pathway in metabolically engineered Escherichia coli, and comparison with the yields predicted by the dynamic models using the same initial carbon concentration.
Fig 6.
Simulation results for 3-hydroxypropionate (3-HP) production via the β-alanine pathway.
(A) Glucose (GLCx) consumption and variation of extracellular 3-HP (3-HPx) over time; (B) Glycerol (GLYx) consumption and variation of 3-HPx over time.
Fig 7.
Simulation results for acrylic acid (AA) production via the β-alanine pathway.
(A) Glucose (GLC) consumption and variation of extracellular AA (AAx) over time; (B) Variation of 3-hydroxypropionate (3-HP) concentration over time when using glucose as carbon source; (C) Glycerol (GLYx) consumption and variation of extracellular AAx over time; (D)—Variation of 3-HP concentration over time when using glycerol as carbon source.
Table 3.
Literature review on 3-hydroxypropionate (3-HP) production yields by the β-alanine pathway in metabolically engineered Escherichia coli, and comparison with the yields predicted by the dynamic models using the same initial carbon concentration.
Fig 8.
Flux Control Coefficients (FCC) results for acrylic acid formation, where the reaction with the most impact in the yield is highlighted in red.
(A) Results for the glycerol pathway. According to the coefficients, the reaction with the most impact is the glycerol-3-phosphate dehydrogenase (G3pD), which due to its positive FCC is a potential target for overexpression; (B) Results for the malonyl-CoA pathway. The results showed that the acetyl-CoA carboxylase (AccC) is a potential bottleneck in the pathway due to the positive FCC; hence, another target for overexpression; (C) Results for the β-alanine pathway. The highest FCC was for the aspartate aminotransferase (AspAT) which appears to be an ideal target for an overexpression.
Fig 9.
Comparison between the original acrylic acid (AA) production with the results obtained for the mutants developed with the optimisation strategies identified.
(A) AA production using glycerol pathway. Mutant 0 represents the model with the heterologous pathway, and Mutant 1 the same model with a 45-fold increase in the Vmax of the glycerol-3-phosphate dehydrogenase (G3pD) reaction; (B) AA production using malonyl-CoA pathway. Mutant 0 represents the model with the heterologous pathway, and Mutant 1 the same model with a 2.5-fold increase in the Vmax of the acetyl-CoA carboxylase (AccC); (C) AA production for the β-alanine pathway. Mutant 0 represents the model with the heterologous pathway, and Mutant 1 the same model with a 50-fold increase in the Vmax of the aspartate aminotransferase (AspAT).
Table 4.
Summarised results of acrylic acid production for the mutant strains developed for the glycerol, malonyl-CoA, and β-alanine models, using 10 g/L of glucose as substrate.
Fig 10.
Representation of the central carbon metabolism of Escherichia coli and the reactions added to the kinetic model.
The reactions depicted by the blue, orange, green and yellow arrows represent, respectively, the glycolysis, pentose-phosphate pathway, tricarboxylic acid cycle and the glyoxylate shunt, which are all present in the original model. The black arrows represent the nine reactions that were added to the model. Finally, red arrows depict the Synth reactions added to account for the presence of the newly added metabolites in other pathways.
Table 5.
Rate Law (RL) equations, kinetic parameters and the respective references for each reaction that belong to the native metabolism of Escherichia coli.
Table 6.
Rate Law (RL) equations, kinetic parameters and the respective references for each reaction of the three heterologous pathways (glycerol, malonyl-CoA and β-alanine) required to produce acrylic acid.