AUTHOR=Misra Ashish , Conway Matthew F., Johnnie Joseph , Qureshi Tabish M., Derrick Anne M., Agbo Eddy C., Sriram Ganesh 

TITLE=Metabolic analyses elucidate non-trivial gene targets for amplifying dihydroartemisinic acid production in yeast

JOURNAL=Frontiers in Microbiology

VOLUME=4

YEAR=2013

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2013.00200

DOI=10.3389/fmicb.2013.00200

ISSN=1664-302X

ABSTRACT=<p>Synthetic biology enables metabolic engineering of industrial microbes to synthesize value-added molecules. In this, a major challenge is the efficient redirection of carbon to the desired metabolic pathways. Pinpointing strategies toward this goal requires an in-depth investigation of the metabolic landscape of the organism, particularly primary metabolism, to identify precursor and cofactor availability for the target compound. The potent antimalarial therapeutic artemisinin and its precursors are promising candidate molecules for production in microbial hosts. Recent advances have demonstrated the production of artemisinin precursors in engineered yeast strains as an alternative to extraction from plants. We report the application of <italic>in silico</italic> and <italic>in vivo</italic> metabolic pathway analyses to identify metabolic engineering targets to improve the yield of the direct artemisinin precursor dihydroartemisinic acid (DHA) in yeast. First, <italic>in silico</italic> extreme pathway (ExPa) analysis identified NADPH-malic enzyme and the oxidative pentose phosphate pathway (PPP) as mechanisms to meet NADPH demand for DHA synthesis. Next, we compared key DHA-synthesizing ExPas to the metabolic flux distributions obtained from <italic>in vivo</italic><sup>13</sup>C metabolic flux analysis of a DHA-synthesizing strain. This comparison revealed that knocking out ethanol synthesis and overexpressing glucose-6-phosphate dehydrogenase in the oxidative PPP (gene <italic>YNL241C</italic>) or the NADPH-malic enzyme ME2 (<italic>YKL029C</italic>) are vital steps toward overproducing DHA. Finally, we employed <italic>in silico</italic> flux balance analysis and minimization of metabolic adjustment on a yeast genome-scale model to identify gene knockouts for improving DHA yields. The best strategy involved knockout of an oxaloacetate transporter (<italic>YKL120W</italic>) and an aspartate aminotransferase (<italic>YKL106W</italic>), and was predicted to improve DHA yields by 70-fold. Collectively, our work elucidates multiple non-trivial metabolic engineering strategies for improving DHA yield in yeast.</p>