In Vivo Validation of In Silico Predicted Metabolic Engineering Strategies in Yeast: Disruption of α-Ketoglutarate Dehydrogenase and Expression of ATP-Citrate Lyase for Terpenoid Production.

BACKGROUND: Engineering of the central carbon metabolism of Saccharomyces cerevisiae to redirect metabolic flux towards cytosolic acetyl-CoA has become a central topic in yeast biotechnology. A cell factory with increased flux into acetyl-CoA can be used for heterologous production of terpenoids for pharmaceuticals, biofuels, fragrances, or other acetyl-CoA derived compounds. In a previous study, we identified promising metabolic engineering targets in S. cerevisiae using an in silico stoichiometric metabolic network analysis. Here, we validate selected in silico strategies in vivo. RESULTS: Patchoulol was produced by yeast via a heterologous patchoulol synthase of Pogostemon cablin. To increase the metabolic flux from acetyl-CoA towards patchoulol, a truncated HMG-CoA reductase was overexpressed and farnesyl diphosphate synthase was fused with patchoulol synthase. The highest increase in production could be achieved by modifying the carbon source; sesquiterpenoid titer increased from glucose to ethanol by a factor of 8.4. Two strategies predicted in silico were chosen for validation in this work. Disruption of α-ketoglutarate dehydrogenase gene (KGD1) was predicted to redirect the metabolic flux via the pyruvate dehydrogenase bypass towards acetyl-CoA. The metabolic flux was redirected as predicted, however, the effect was dependent on cultivation conditions and the flux was interrupted at the level of acetate. High amounts of acetate were produced. As an alternative pathway to synthesize cytosolic acetyl-CoA, ATP-citrate lyase was expressed as a polycistronic construct, however, in vivo performance of the enzyme needs to be optimized to increase terpenoid production. CONCLUSIONS: Stoichiometric metabolic network analysis can be used successfully as a metabolic prediction tool. However, this study highlights that kinetics, regulation and cultivation conditions may interfere, resulting in poor in vivo performance. Main sites of regulation need to be released and improved enzymes are essential to meet the required activities for an increased product formation in vivo.

In silico profiling of Escherichia coli and Saccharomyces cerevisiae as terpenoid factories.

BACKGROUND: Heterologous microbial production of rare plant terpenoids of medicinal or industrial interest is attracting more and more attention but terpenoid yields are still low. Escherichia coli and Saccharomyces cerevisiae are the most widely used heterologous hosts; a direct comparison of both hosts based on experimental data is difficult though. Hence, the terpenoid pathways of E. coli (via 1-deoxy-D-xylulose 5-phosphate, DXP) and S. cerevisiae (via mevalonate, MVA), the impact of the respective hosts metabolism as well as the impact of different carbon sources were compared in silico by means of elementary mode analysis. The focus was set on the yield of isopentenyl diphosphate (IPP), the general terpenoid precursor, to identify new metabolic engineering strategies for an enhanced terpenoid yield. RESULTS: Starting from the respective precursor metabolites of the terpenoid pathways (pyruvate and glyceraldehyde-3-phosphate for the DXP pathway and acetyl-CoA for the MVA pathway) and considering only carbon stoichiometry, the two terpenoid pathways are identical with respect to carbon yield. However, with glucose as substrate, the MVA pathway has a lower potential to supply terpenoids in high yields than the DXP pathway if the formation of the required precursors is taken into account, due to the carbon loss in the formation of acetyl-CoA. This maximum yield is further reduced in both hosts when the required energy and reduction equivalents are considered. Moreover, the choice of carbon source (glucose, xylose, ethanol or glycerol) has an effect on terpenoid yield with non-fermentable carbon sources being more promising. Both hosts have deficiencies in energy and redox equivalents for high yield terpenoid production leading to new overexpression strategies (heterologous enzymes/pathways) for an enhanced terpenoid yield. Finally, several knockout strategies are identified using constrained minimal cut sets enforcing a coupling of growth to a terpenoid yield which is higher than any yield published in scientific literature so far. CONCLUSIONS: This study provides for the first time a comprehensive and detailed in silico comparison of the most prominent heterologous hosts E. coli and S. cerevisiae as terpenoid factories giving an overview on several promising metabolic engineering strategies paving the way for an enhanced terpenoid yield.